quality worklife indicators for nursing practice -

Linda McGillis Hall, RN, PhDDiane Doran, RN, PhD Linda O’Brien Pallas, PhD Joan Tranmer, RN, PhD Deborah Tregunno, RN, PhD Ellen Rukholm, RN, PhD Donna Thomson, RN, MBA Leah Pink, RN, MNJessica Peterson, RN, PhD StudentErin Johnston, RN, MN StudentAmy Palma, RN, BScN

Funded by The Ontario Ministry of Health & Long-Term Care

MARCH 2006

Quality Worklife Indicators for NursingPractice Environments in OntarioDetermining the Feasibility of Collecting Indicator Data

Linda McGillis Hall, RN, PhD

Associate Professor, Faculty of Nursing & CIHR New

Investigator & Co-investigator, Nursing Health Services

Research Unit, University of Toronto

Diane Doran, RN, PhD, Faculty of Nursing,

University of Toronto

Linda O’Brien Pallas, PhD, Faculty of Nursing,


Joan Tranmer, RN, PhD, Queen’s University/

Kingston General Hospital

Deborah Tregunno, RN, PhD, Faculty of Nursing,

York University

Ellen Rukholm, RN, PhD, School of Nursing,

Laurentian University

Donna Thomson, RN, MBA, St. Peter’s Hospital

Leah Pink, RN, MN, Faculty of Nursing,


Jessica Peterson, RN, PhD Candidate, Faculty

of Nursing, University of Toronto

Erin Johnston, RN, MN Student, Faculty of Nursing,


Amy Palma, RN, BScN, Faculty of Nursing,


Funded by The Ontario Ministryof Health & Long-Term Care

MARCH 2006


Acknowledgements

We gratefully acknowledge the Ontario Ministry of Health and Long-term Care, Dr. Dorothy Pringle – Executive Lead, and Peggy White of the Health Outcomes for Better Information and Care initiative for

their support of this research. The findings reported herein are those of the authors. No endorsement by the Ontario Ministry of Health

and Long-term Care is intended or should be inferred.

We would also like to acknowledge the contribution of DavidMontgomery for his assistance with the statistical analysis.

Finally, we would like to thank the hospital nursing personnel, unitmanagers, nurse executives, and chief executive officers, of the

participating sites who gave their time and energy to support this study.

Toronto Ontario Region:University Health Network – Toronto General Hospital site

Shalom Village (Hamilton)Chelsey Park Mississauga

Toronto Salvation Army GraceSpectrum Health Care (Toronto)

Southwestern Ontario Region:Huron Perth Healthcare Alliance – Stratford General Hospital

St. Joseph’s Health Centre (London)St. Peter’s Health System (Hamilton)

ParaMed Home Health Care (London)

Eastern Ontario Region:Kingston General Hospital

Peter D. Clark Long-Term Care Centre (Nepean)Perley & Rideau Veteran’s Health Centre (Ottawa)

St. Mary’s of the Lake Hospital (Kingston)All-Care Health Services (Kingston)

Northern Ontario Region:Manitoulin Health Centre-Little Current and Mindemoya sites

Bethammi Nursing Home (Thunder Bay)Pioneer Manor (Sudbury)

St. Joseph’s Care Group (Thunder Bay)Bayshore Home Health (Thunder Bay)

Cover photograph provided by University of Toronto, Public Affairs

Quality Worklife Indicators for Nursing Practice Environments in Ontario: Determining

the Feasibility of Collecting Indicator Data

ISBN 0-7727-3610-3Copyright © 2006

Correspondence regarding this report can be directed toLinda McGillis Hall, RN, PhD

Associate Professor, Faculty of Nursing New Investigator, Canadian Institutes of Health Research

Co-investigator, Nursing Health Services Research UnitUniversity of Toronto, Toronto, Ontario CANADA

T 416 978-2869F 416 978-8222

email: [email protected]: www.nursing.utoronto.ca/l.mcgillishall/

EXECUTIVE SUMMARY

The Quality Worklife Indicators in Nursing Practice Environments in Ontario study was a province-

wide research project that was designed to assess the feasibility, quality, and utility of collecting

data on nursing worklife indicators for acute care, long-term care, complex continuing care, and

homecare settings. The study also explored the feasibility of linkage of these data to data

collected in similar settings as part of the Health Outcomes for Better Information and Care

initiative (formerly the Nursing and Health Outcomes Project). The study was conducted at

20 health care facilities (5 acute care, 7 long-term care, 4 complex continuing care, 4 homecare)

across Ontario and included questionnaires, interviews, focus groups, and data from selected

administrative databases. Approximately 451 nursing personnel and 53 unit managers

participated in the study.

Data Quality – Reliability and Completion of Nursing Worklife Data

Two instruments were used to measure the quality of nurses’ worklife – the Work Quality Index

(WQI) and the Nursing Work Index – Revised (NWI-R). Both instruments were highly reliable with

no reliability differences noted between work groups or health care sectors. The NWI-R had lower

alpha reliability scores than the WQI for the majority of subscales across the health care sectors,

with homecare attaining the lowest alpha values. Overall, the completion rate was best for the

WQI, with registered nurses (RNs) having the highest completion rates, followed by registered

practical nurses (RPNs) and unregulated health workers (URWs). Homecare participants had the

lowest completion rates for both instruments.

Feasibility of Collecting Nursing Worklife Data – Receptivity and Burden

Nursing personnel and unit managers were receptive to collecting these data. Nursing personnel

found the surveys to be straightforward although work environment supports to enable nurses

to complete the survey were important considerations. Unit managers identified substantial

challenges related to having ready access to the data needed to assess nurses’ worklife. These

managers went to inordinate lengths to obtain the data for this study, a burden that could not be

maintained on an ongoing basis. Efforts should be made to ensure unit-based managers have

access to nursing worklife data to enable them to make linkages between nurse staffing, the

work environment, and clinical outcomes.

Utility of Nursing Worklife Data – Comprehensiveness and Relevance

From the perspective of nursing personnel, the data collected in the nursing surveys was

considered to be appropriate. However, the challenges encountered by unit managers in accessing

accurate unit-based information on key data elements such as percentage of baccalaureate nurses,

years of experience, nurse-to-patient ratios, use of casual staff, number of voluntary resignations,

orientation and educational programs, absenteeism, and agency use, highlight the importance of

having comprehensive and relevant data available for decision-makers. Currently, access to these

data is sporadic and inconsistent, depending on sector and site.

Potential Data Repositories

A number of existing groups with varied experience in gathering, maintaining, and storing data

provided information on important considerations for a large data set designed to link nurse

staffing, nurses’ worklife, and clinical outcomes. No specific group could be identified as the

ideal repository, given the complexity of this process.

Determining the Feasibility of Collecting Indicator Data 3

Data Linkage

Challenges were encountered when considering linking this data with other sources, such as

Management Information System (MIS) data collected as part of the Ontario Hospital Reporting

System (OHRS). The first relates the level of analysis the data are available for, while the second

relates to the limited scope of available data in terms of health care sectors. The data available

from the OHRS is available only at the aggregate level of functional centre, which can include

several patient care units. At the current time, there is no method for clearly breaking out the

aggregate functional centre data from the OHRS dataset to the level of the patient care unit to

link to the clinical outcomes. As well, these linking data are only available in acute care and

some complex continuing care facilities in Ontario. Further expansion to other sectors is needed

to enable data linkage. This is a concern that needs to be addressed in the future to enable these

data to be useful to health care leaders, decision-makers, policy makers, and researchers.

Despite this, data obtained from unit managers provided some important information about the

consistency and relevance of several of the nursing worklife indicators examined in this study.

Specifically, several of the study variables of interest that had emerged from the original review

of the literature were found to be related to the nursing work environment measures across

sectors. These include span of control of the unit manager, absenteeism, nurse-to-patient ratios,

experience, and education. As well, in long-term care, the percentage of RN staffing was also

identified.

Summary

This study demonstrated that the collection of worklife date is feasible and useful, and the quality

of the data collected is good, although there were challenges with data collection in some sectors.

There does not seem to be overwhelming evidence to suggest that one instrument is superior

to the other for collecting nursing worklife data. Both appear to be fairly reliable and consistent,

although some specific sectors (i.e., homecare) and nursing personnel groups (i.e., URWs)

experienced difficulties relating to some of the questions. Thus, consideration should be given to

adapting the language of these measures to specific health care sectors (i.e., homecare, long-term

care) to accurately capture their unique work environments in future work.

4 Quality Worklife Indicators for Nursing Practice Environments in Ontario


TABLE OF CONTENTS

9 Chapter One: Overview

10 Introduction

10 Goals

10 Purpose

11 Study Objectives

13 Chapter Two: Methods

14 Research Methodology

14 Design

14 Phase 1

14 Phase 2

15 Phase 3

15 Setting

16 Sample

17 Sample Size

18 Recruitment

18 Study Variables

18 Unit Manager Survey

18 Secondary Data

18 Nursing Worklife Survey

19 1) Nursing Work Index – Revised (NWI-R)

19 2) Work Quality Index (WQI)

19 Focus Groups

20 Stakeholder Interviews

20 Data Management

20 Data Preparation

20 Data Entry Error and Missing Data

20 Computing Total Scale Scores

21 Chapter Three: Study Participants

22 Description of the Study Sample

22 Settings

22 Nurse Surveys

22 Nursing Personnel

23 Age of Nursing Personnel Participants

24 Educational Preparation of Nursing Personnel

24 Experience of Nursing Personnel

25 Employment Status of Nurse Participants

26 Unit Manager Surveys

26 Staff Mix

26 Percentage of RNs

27 Absenteeism

27 Employment Status

28 Experience

29 Unit Manager Span of Control

30 Nurse-to-Patient Ratios

30 Summary

TABLE OF CONTENTS

31 Chapter Four: Quality of Nursing Worklife Indicators

32 Introduction

32 Instrument Reliability

32 Overall Sample

32 Nursing Personnel Group Reliability and Completion Rate Comparisons

32 Worklife Scale Reliabilities: RN, RPN, and URW

34 Work Quality Index (WQI)

35 Nursing Work Index – Revised (NWI-R)

36 Comparison of Worklife Scales: RN, RPN, and URW

36 Sector Reliability and Completion Rate Comparisons

36 Worklife Scale Reliabilities: Acute Care, Long-term Care, Complex Continuing Care, and Homecare

37 Work Quality Index (WQI)

38 Nursing Work Index – Revised (NWI-R)

39 Comparison of Worklife Scales: Acute Care, Long-term Care, Complex Continuing Care, and Homecare

39 Missing Data

40 Summary

41 Chapter Five: Feasibility and Utility of Collecting Nursing Worklife Indicator Data

42 Introduction

42 Assessing the Feasibility and Utility of Nursing Worklife Indicator Data Collection

43 Receptivity and Burden of Nursing Worklife Indicator Data Collection for Nursing Personnel

44 Comprehensiveness and Relevance of Nursing Worklife Indicator Data Collection for Nursing Personnel

46 Receptivity and Burden of Nursing Worklife Indicator Data Collection for Unit Managers

46 Comprehensiveness and Relevance of Nursing Worklife Indicator Data Collection for Unit Managers

50 Summary

51 Chapter Six: Collection and Storage of Nursing Worklife Indicator Data

52 Introduction

52 Feasibility of Collecting and Maintaining Nursing Worklife Indicator Data

52 1) College of Nurses of Ontario (CNO) Perspective

52 Challenges for Collecting Nursing Worklife Indicator Data

54 Facilitators for Collecting Nursing Worklife Indicator Data

54 Frequency of Collecting Nursing Worklife Indicator Data

55 Data Collection Process for Nursing Worklife Indicator Data

55 Data Storage and Accessibility

55 Costs Associated with Data Collection and Storage

56 2) Canadian Coucil on Health Services Accreditation (CCHSA) Perspective



57 Frequency of Collection of Nursing Worklife Indicator Data






TABLE OF CONTENTS

58 3) Canadian Institute for Health Information (CIHI) Perspective



60 Frequency for Collection of Nursing Worklife Indicator Data




61 Summary

61 Nurses’ Perspectives of Nursing Worklife Indicator Data Collection (Focus Groups)

62 Managers’ Perspectives of Nursing Worklife Indicator Data Collection (Focus Groups)

63 Summary

65 Chapter Seven: Nursing Worklife in Ontario

66 Introduction

66 Mean Scale Scores for Work Quality Index (WQI) by Nursing Personnel Group

69 Mean Scale Scores for Nursing Work Index (NWI-R) by Nursing Personnel Group

70 Summary

70 Work Quality Index

71 Nursing Work Index – Revised

71 Mean Scale Scores for Work Quality Index (WQI) by Health Care Sector

74 Mean Scale Scores for Nursing Work Index (NWI-R) by Health Care Sector

77 Conclusions

77 Nursing Personnel Groups

77 Health Care Sectors

79 Chapter Eight: Abstracting and Linking Nursing Worklife Indicator Data

80 Introduction

80 Unit-Manager Data

80 Acute Care

81 Complex Continuing Care

81 Long-term Care

82 Home Care

82 Overall

82 Summary

85 Chapter Nine: Discussion and Conclusions

86 Introduction

86 Quality of Nursing Worklife Indicator Data

86 Reliability of Data Collected

86 Completion Rate

87 Receptivity and Burden of Nursing Worklife Indicator Data Collection

87 Comprehensiveness and Relevance Nursing Worklife Indicator Data

87 Collection, Storage and Management of Nursing Worklife Indicator Data

88 Linking Nursing Worklife Indicator Data to Clinical Outcomes

89 A Snapshot of Nursing Worklife in Ontario

89 Conclusions

90 Appendix A: Semi-structured Interview Participants

91 References

LIST OF TABLES

16 Table 1 Setting Selection by Region of the Province

17 Table 2 Nursing Personnel Sample

17 Table 3 Unit Manager Sample

23 Table 4 Participation Rates of Nursing Personnel by Occupational Title and by Sector

23 Table 5 Age of Nursing Personnel by Sector

24 Table 6 Educational Preparation of Nursing Personnel by Sector

24 Table 7 Experience of Nursing Personnel by Sector

25 Table 8 Employment Status of Nursing Personnel by Sector

25 Table 9 Choice of Employment Status of Nursing Personnel by Sector

25 Table 10 Preferred Change in Employment Status of Nursing Personnel by Sector

26 Table 11 Hours Worked Weekly by Study Nurse Participants by Health Care Sector

26 Table 12 Unit Staffing Model by Sector

27 Table 13 Mean Percentage of RNs on Study Units

27 Table 14 Average Number of Days Absent Annually

27 Table 15 Percentage of Employment by Occupational Status

28 Table 16 Percentage Experience of Nursing Personnel

29 Table 17 Span of Control of Unit Managers on Study Units

29 Table 18 Mean Scope of Responsibility

30 Table 19 Mean Nurse-to-Patient Ratios by Shift

32 Table 20 Reliability of Nursing Worklife Measures

33 Table 21 Reliability of Nursing Worklife Measures by Individual Nursing Personnel Group (RN, RPN, and URW)

36 Table 22 Reliability of Nursing Worklife Measures by Health Care Sectors

40 Table 23 Missing Data for Nursing Worklife Measures by Individual Nursing Personnel Group (RN, RPN, and URW) and by Health Care Sectors

66 Table 24 Mean Score for Worklife Indicators for Nursing Personnel Groups (RN, RPN, URW) and Health Care Sectors

68 Table 25 Work Quality Index Mean Score Differences Between Nursing Personnel Groups (RN, RPN, URW)

70 Table 26 Nursing Work Index Mean Score Differences Between Nursing Personnel Groups (RN, RPN, URW)

72 Table 27 Work Quality Index Mean Score Differences Between Health Care Sectors

75 Table 28 Nursing Work Index Mean Score Differences Between Health Care Sectors

83 Table 29 Correlations for Unit-Level Nursing and Unit Structural Variables


on

e Chapter One: Overview

Introduction

Goals

Purpose

Study Objectives

9

INTRODUCTION

A number of recent U.S. and Canadian studies have demonstrated that linkages exist between

nurse staffing models and patient outcomes. Little or no work has been conducted that explores

variables in the work environment beyond nurse staffing that may also have an impact on

patient outcomes. Evidence exists in the literature that the quality of a patient’s health care

experience can be influenced by nurses’ job satisfaction. While it is widely recognized that

factors in the nursing work environment and the work organization may have an impact on

nurses’ worklife and job satisfaction, indicators for measuring these specific worklife factors

have not been identified and validated. This research addresses the need for a description and

evaluation of key quality of nursing worklife indicators that can be linked to patient outcomes.

GOALS

The goals of this overall research study were: (a) to conduct a critical review and analysis of the

literature on input or structural variables in work settings that could be considered indicators

of the quality of nurses’ worklife in health care settings in Ontario, Canada, and (b) to conduct

a pilot study to determine the feasibility of collecting data related to these indicators. Phase one

of this research involved completion of a critical review and analysis of the literature on

variables that could be considered indicators of the quality of nurses’ worklife in health care

settings, which was subsequently published as a book, Quality Work Environments for Nurse and

Patient Safety (McGillis Hall, 2005). The indicators that emerged from the literature review

included: staff mix proportions for registered nurses; percentages of full-time, part-time, and

casual nursing staff; educational background of nursing staff; experience of nursing staff; use

of overtime hours; use of agency staff; absenteeism hours; level of autonomy and decision-

making experienced by nurses; professional development opportunities; span of control of the

unit manager; team functioning; organizational climate and culture; job satisfaction; and

workload/productivity. Following this determination of key indicators of importance for

measuring the nursing work environment, a feasibility study was undertaken to provide sound

information related to the availability, feasibility, and utility of measuring many of these nursing

worklife variables. Ultimately this research will inform decisions and recommendations regarding

the complementary data required to link to the clinical outcome database being developed

and implemented by the Ontario Ministry of Health and Long-term Care (MOHLTC) as part of the

Health Outcomes for Better Information and Care (HOBIC) initiative (Ministry of Health and

Long-term Care, 2005).

PURPOSE

The primary purpose of this study was to evaluate the feasibility, quality, and utility of

instituting data collection for nursing worklife indicators in acute care, long-term care, complex

continuing care, and homecare settings in Ontario, Canada. A second purpose was to examine

the potential for linkage of these data to the clinical outcomes data collected in similar settings

as part of the Health Outcomes for Better Information and Care initiative (formerly the Nursing

and Health Outcomes Study). A third purpose was to make recommendations regarding

potential sources for where these data can be housed in a database in the future. In order to

address the primary purpose and sub-purposes, several study objectives and research questions

were identified.


STUDY OBJECTIVES

The first study objective examines the quality of nursing worklife indicator data collected by

nurses and managers in everyday practice settings in acute care, complex continuing care,

long-term care, and homecare settings in Ontario, Canada. The specific research questions

were: (1) What is the reliability of data collected by nurses and managers? and (2) What is the

completion rate of the nursing worklife measures collected by nurses and managers?

The second study objective was to examine the feasibility of collecting nursing worklife indicator

data in everyday practice settings in acute care, complex continuing care, long-term care, and

homecare settings in Ontario, Canada. The specific research questions were: (1) What is the

receptivity to nursing worklife indicator data collection by nurses and managers? and

(2) What is the burden of collecting nursing worklife indicator data for nurses and managers?

The third study objective examines the utility of nursing worklife indicator data for nurses

and managers in acute care, complex continuing care, long-term care and homecare settings

in Ontario, Canada. The specific research questions were: (1) To what extent are the nursing

worklife indicator data comprehensive, as perceived by nurses and managers? and (2) How

relevant and useful are the nursing worklife indicator data in assisting nurses and managers

in decision-making for the organization?

The fourth study objective examines the potential sources for where these data can be housed

in a database in the future. The specific research questions were: (1) What is the feasibility of

collecting nursing worklife indicator data as part of the data collected by the College of Nurses

of Ontario (CNO), the Canadian Institute for Health Information (CIHI), the Canadian Council on

Health Services Accreditation (CCHSA)? and (2) What is the feasibility of housing nursing worklife

indicator data with the CNO, CIHI, and CCHSA?

The fifth study objective examines the feasibility of abstracting and linking nursing worklife

indicator data to other datasets (e.g., outcomes). The specific research questions were: (1) What

is the feasibility of abstracting nursing worklife indicator data? and (2) What are the issues

associated with abstracting and linking nursing worklife indicator data to data from different

databases, such as Management Information Systems (MIS), CIHI, and across settings?


Tw

o Chapter Two: Methods

Research Methodology

Study Variables

Data Management

13

RESEARCH METHODOLOGY

Design

A cross-sectional survey research design was used to address the study objectives including

nurse and manager surveys, focus groups and interviews. The survey data collection took place

over a 9 month period from August 2004 to May 2005. The study was designed to provide

in-depth examination of the feasibility of instituting nursing worklife indicator data collection in

acute care, complex continuing care, long-term care, and homecare settings in Ontario.

The research was conducted in each type of practice setting, ensuring province wide

representation, and purposively sampling different types of organizations that typify the range

of service providers.

Phase One

Health care unit managers in a sample of acute care, complex continuing care, long-term care,

and homecare settings in Ontario were surveyed to obtain data on 8 nurse structural variables –

percentage of RNs in staff mix; percentage of full-time, part-time, and casual nursing staff;

educational background of nursing staff; experience of nursing staff employed on the study

units in the study sites; span of control of the unit manager; and unit absenteeism rates. This

survey, an adaptation of one used by the principal investigator in a previous study, has been

validated in earlier studies to ensure the relevance of the data items (McGillis Hall et al., 2001).

Secondary data related to 5 unit structural variables – nursing hours per weighted case/RUG

weighted patient day; nursing overtime hours; agency staff hours; absenteeism hours; and

workload/productivity (i.e., direct patient care) was also sought from the organization’s

management information system database, the Ontario Hospital Reporting System (OHRS) at one

point in time for fiscal year 2004/2005, for the acute care and complex continuing care sites in

this study. Data were not sought for the long-term care and home-care sectors as no consistent

data were collected and available from these sectors at the time of this study.

Phase Two

In phase two, nurses working on selected units in a sample of acute care, complex continuing

care, long-term care, and homecare settings in Ontario were surveyed to obtain data on 8 nursing

worklife variables – level of autonomy and decision-making experienced by nursing staff; team

functioning and professional work relationships; work environment; role enactment; work worth;

organizational support; education; and experience in nursing. For each participating unit, the

study research coordinator met with eligible nursing staff, i.e., registered nurses (RNs),

registered practical nurses (RPNs), and unregulated workers (URWs), to explain the study and the

sampling procedure with the assistance of the unit manager or her designate. The research

coordinator individually ascertained their interest in participation. A survey questionnaire

package along with a letter of explanation and a pre-stamped return envelope was given to all

nurses who consented to participate. As part of the returned survey questionnaire package,

nursing staff were asked to indicate their interest in participating in a focus group follow-up

meeting to be held at a later point in the study aimed at obtaining their input regarding the

utility of the worklife data collection.



Phase 3

Following completion of phases one and two, the final qualitative component of this study was

carried out. The qualitative component was comprised of separate focus groups with the nurses

and their managers, and semi-structured interviews with stakeholders involved with the study.

Two focus group interviews were held with representatives from each of the four regions involved

in the study to obtain input regarding the feasibility and utility of collecting nursing worklife data.

The first focus group included nursing staff from acute care, complex continuing care, long-term

care, and homecare settings involved in the study. The second focus group involved unit managers

from the same settings.

As well, semi-structured interviews were conducted individually with relevant stakeholders (i.e.,

CNO, CCHSA, CIHI) to determine the feasibility for collection and maintenance of these data in the

future. Participants in these interviews were asked to discuss the feasibility of collecting and

maintaining these data in their organization, and to identify any barriers and facilitators to nursing

worklife indicator data collection from their perspective. The frequency that these data should be

collected was also discussed.

Setting

The settings for this feasibility study were acute care, complex continuing care, long-term care,

and homecare organizations in Ontario, Canada. Health care organizations were purposively

selected for participation in the study based on their involvement in the complementary study

project – The Nursing and Health Outcomes Study. In cases where the original sites were not

accessible, alternate settings were selected. These settings were selected using a stratified

random sampling approach based on a set of criteria developed with input from stakeholders

(see Table 1). These included: (1) geographic location from the four MOHLTC regions of the

province; (2) availability of two medical and two surgical care units in each setting; (3)

representation of teaching, community, and small rural facilities; (4) long-term care settings

including a for-profit and not-for-profit home (Metro Homes and Charitable Homes for the Aged),

a new home (schedule A) and an established home (schedule C), a facility with case mix index

(CMI) >110, a small independent facility, and also one facility that is part of a large corporation;

(5) complex continuing care settings could be either freestanding or attached to an acute care

site; and (6) homecare settings including at least one close to a teaching hospital and one rurally

located. Therefore, this feasibility study was conducted in a total of 20 health care facilities, of

which 5 were acute care, 7 were long-term care, 4 were complex continuing care, and 4 were

homecare settings across the province. A total of 65 patient care units were included in the study;

16 from acute care, 30 from long-term care, and 15 from complex continuing care settings.

Table 1. Setting Selection by Region of the Province

Region 1 Region 2 Region 3 Region 4

Setting Central Southwestern Eastern Northern Total

Acute care 4 units/1 site: 4 units/1 site: 6 units/1 site: 2 units/2 sites: 16 units/

University Health Huron Perth Kingston Manitoulin Health 5 sites

Network – Healthcare General Centre – Little

Toronto General Alliance – Hospital Current and

Hospital site Stratford General Mindemoya

Hospital site sites

Long-term 6 units/2 sites: 10 units/1 site: 9 units/2 sites: 5 units/2 sites: 30 units/

care Shalom Village St. Joseph’s Peter D. Clark Bethammi Nursing 7 sites

(Hamilton)*+; HealthCentre Long-term Care Home (Thunder

Chelsey Park – (London)*+/† Centre (Nepean)*+; Bay)*; Pioneer

Mississauga**†^ Perley & Rideau Veteran’s Health Manor (Sudbury)*+

Centre (Ottawa)*+

Complex 4 units/1 site: 4 units/1 site: 4 units/1 site: 3 units/1 site: 15 units/

continuing Toronto Salvation St. Peter’s St. Mary’s of the St. Joseph’s 4 sites

care Army Grace Health System Lake Hospital Care Group

(Hamilton) (Kingston) (Thunder Bay)

Community 1 site: 1 site: 1 site: 1 site: 4 sites

care access Spectrum Health ParaMed Home All-Care Health Bayshore Home

centres Care (Toronto) Health Care Services Health (Thunder

(London) (Kingston) Bay)

Total 15 units/ 19 units/ 20 units/ 11 units/ 65 units/

5 sites 4 sites 5 sites 6 sites 20 sites

* Not-for-profit** For-profit+ New home (Schedule A)† Established home (Schedule C)^ Case Mix Index >110

Sample

The sample for the study included (1) nursing personnel caring for patients/residents admitted to

acute care, complex continuing care, long-term care, and homecare settings in Ontario; (2) unit

managers from units participating in this study; and (3) potential key stakeholders for future data

collection and housing of the database. All full-time, part-time, and casual nursing personnel

(i.e., RNs, RPNs, URWs) associated with the study units were recruited to participate in the study.

Nurses caring for medical-surgical patients were recruited from acute care hospitals, long-term

care, and complex continuing care facilities, as well as nurses working within homecare settings.

All unit managers associated with the study units were recruited to participate in the study.

Organizations currently involved with the collection of data related to nursing in the province

were recruited to participate in the study (i.e., CNO, CIHI, CCHSA).


Sample Size

Sample size determination was based on the data analytic needs. Data analysis to address the

questions for feasibility, data quality, and utility were conducted separately for each sector. A

minimum of 10 subjects for each variable were included in the analysis for construct validity. Based

on this consideration, the desired sample size was 450 nurses, which included a 30% increase for

subject refusal and attrition. Table 2 demonstrates that the sample requirements were met for the

study overall, with approximately 30% of responses coming from acute care, 29% from long-term

care, 23% from complex continuing care, and 18% from homecare nursing staff. Some challenges

were encountered achieving the sample within specific sectors and regions (i.e., complex continuing

care in the southwest region; long-term care in central and southwest regions; acute care in the

north). Reasons for this included heavy workload on the units, which made attending the data

collection meetings difficult for some nurses. As well, facility and unit size resulted in lower nursing

staff numbers than anticipated. Finally, in some facilities (i.e., long-term care), the numbers of

registered nursing staff working at one time were very low. Given these issues, oversampling was

undertaken in the other regions of the province to ensure the overall sampling requirements were

met (i.e., complex continuing care in eastern region; long-term and acute care in the eastern region).

As a result, approximately 40% of the sample came from the eastern region of the province, while

25% came from central Ontario, 18% from the north, and 17% from southwestern Ontario.

Table 2. Nursing Personnel Sample

Region 1 Region 2 Region 3 Region 4 Minimum

Central Southwestern Eastern Northern Total sample

(attained/ (attained/ (attained/ (attained/ (attained/Setting sample/%) sample/%) sample/%) sample/%) sample/%)

Acute care 31/30 38/30 53/30 16/30 138/120 (30)

Long-term care 15/30 17/30 73/30 27/30 132/120 (29)

Complex continuing care 19/30 7/30 47/30 29/30 102/120 (23)

Homecare 48/23 16/22 8/23 7/22 79/90 (18)

Total 113/113 (25) 78/112 (17) 181/113 (40) 79/112 (18) 451/450 (100)

Table 3 demonstrates that all 53 unit managers on the study units participated in the study, for a

100% response rate.

Table 3. Unit Manager Sample

Region 1 Region 2 Region 3 Region 4 Minimum

Central Southwestern Eastern Northern Total sample

(attained/ (attained/ (attained/ (attained/ (attained/Setting sample/%) sample/%) sample/%) sample/%) sample/%)

Acute care 4/4 4/4 6/6 2/2 16/16 (30)

Long-term care 6/6 2/2 5/5 5/5 18/18 (34)

Complex continuing care 4/4 4/4 4/4 3/3 15/15 (28)

Homecare 1/1 1/1 1/1 1/1 4/4 (8)

Total 15/15 (28) 11/11 (21) 16/16 (30) 11/11 (21) 53/53 (100)


Recruitment

Participants in the study were recruited from the settings listed in Table 1. Following ethics

approval from the Research Ethics Board of each of the universities affiliated with the 4

university teaching hospitals as well as each of the 20 individual study sites, the study

coordinator contacted the managers of each unit involved in the study. At this time the unit

managers were recruited to complete the study questionnaire. The study coordinator also

arranged to meet with nursing staff (i.e., RNs, RPNs, and URWs) with the help of the unit

managers to complete a nursing worklife questionnaire. The ethics review process proved to be

quite lengthy for this study, due to the number of university and individual research ethics

boards that required study approval and the length of the individual ethics review processes.

Approximately 7 months elapsed from the time of the first ethics submission until final approval

at the last study site.

STUDY VARIABLES

Unit Manager Survey

Unit managers provided information through a questionnaire about the nurse structural

variables – percentage of registered nurses in staff mix; percentage of full-time, part-time, and

casual nursing staff; educational background of nursing staff; experience of nursing staff

employed on the study units in the study sites; span of control of the unit manager; and unit

absenteeism rates.

Secondary Data

Data on the unit structural variables (nursing hours per weighted case/RUG weighted patient

day; nursing overtime hours; agency staff hours; absenteeism hours; and workload/productivity

(i.e., direct patient care) was obtained from the organization’s management information system

database, the Ontario Hospital Reporting System (OHRS) at one point in time for fiscal year

2004/2005, for the acute care and complex continuing care sites in this study.

Nursing Worklife Survey

Nursing staff (i.e., RNs, RPNs, and URWs) provided information through a questionnaire about the

nursing worklife variables – level of autonomy and decision-making experienced by nursing staff;

team functioning and professional work relationships; work environment; role enactment; work

worth; organizational support; education; and experience in nursing. Instruments with

demonstrated reliability and validity were used to collect data on these nursing worklife

indicators. The nurses’ perceptions of the quality of their work environment were measured with

two scales; the Nursing Work Index-Revised and the Work Quality Index. The two instruments

were used for the following reasons: (1) they captured aspects of the nursing work environment

identified as important constructs to measure in the critical appraisal of the literature conducted

prior to the development of this study (e.g., autonomy and decision-making, team functioning,

organizational climate and culture, job satisfaction); and (2) each has been identified as having

acceptable evidence of their psychometric properties. Thus, using both measures in this study

enabled a comprehensive assessment of environmental factors affecting nurses’ work, and

enhanced the validity of measurement.


1) Nursing Work Index-Revised – A measure of nurses’ reports of the presence or absence

of a series of organizational factors: autonomy, control over the work environment, and

relationships with physicians. The traits of a hospital or a unit within a hospital were obtained

using the Nursing Work Index-Revised (NWI-R; Aiken & Patrician, 2000). This scale contains 57

Likert-like items with four response categories: “strongly agree”, “somewhat agree”, “somewhat

disagree”, and “strongly disagree”. The scale items are coded such that a 1 is equal to “strongly

agree” and a 4 is equal to “strongly disagree”. Multiple nurses’ responses on a single item are

summed to create a measure of an organizational trait. The organizational trait is an average of

that particular item of the NWI-R across a unit or a hospital (Aiken & Patrician). Cronbach’s alpha

was reported as .96 for the overall scale by the instrument developers. When the data were

aggregated to the unit level, Cronbach’s alpha for each of the subscales were reported as .80 for

autonomy, .91 for control, .84 for relationships with physicians, and .84 for organizational

support (Aiken & Patrician). Content, construct, and criterion-related validity were also

demonstrated (Aiken & Patrician).

2) Work Quality Index – A measure of nurses’ satisfaction with the quality of their work and

their work environment using 6 subscales for job properties: professional work environment,

autonomy, work worth, professional relationships, role enactment, and benefits was obtained

using the Work Quality Index (WQI; Whitley & Putzier, 1994). This scale contains 38 Likert-like

items with seven response categories ranging from “not satisfied” to “satisfied”. The scale items

are coded such that a 1 is equal to “not satisfied” and a 7 is equal to “satisfied”. A high score on

this scale indicates a higher degree of job satisfaction. Cronbach’s alpha was reported by the

instrument developers as .94 for the overall scale, .87 for the work environment scale, .84 for

the autonomy scale, .79 for the work worth scale, .80 for the relationships scale, .72 for the role

enactment scale, and .79 for the benefits scale. Construct validity was also demonstrated

(Whitley & Putzier).

Focus Groups

Nursing staff and managers who indicated a willingness to participate in focus groups were

randomly selected and invited to a focus group meeting. In order to assess the feasibility of

collecting nursing data in practice settings, information was obtained in focus groups on the

amount of time it takes for a nurse and manager to complete the worklife indicators survey. in

Focus group participants were asked to identify the time involved in survey completion, and to

identify any barriers and facilitators to nursing worklife indicator data collection. In addition,

information was collected from nurses on their perceived ease of collecting the nursing worklife

indicator data, ease of interpreting the nursing worklife indicator data, and perceptions of the

frequency with which it should be collected. Nurses were asked to comment on their receptivity

to incorporating a standardized approach to nursing worklife indicators assessment. Another

aspect of feasibility is whether it is possible to collect the nursing worklife indicator data in a

timely manner. Data was collected on the time required for data collection to be completed,

completeness of data collection, and reasons for failure to complete data collection. Work

environment factors may contribute to the receptivity of nurses towards the completion of the

data collection. Data was collected from nurses and managers on their perception of the work

environment factors that influence nurses’ receptivity to the data collection. Unit managers were

also invited to participate in a focus group concerning their perceptions of the value and/or

utility of nursing worklife indicator assessments for management decision-making.


Stakeholder Interviews

The stakeholders from the CNO, CCHSA, and CIHI were invited to participate in semi-structured

interviews to determine the feasibility for collection and maintenance of these data in the future.

DATA MANAGEMENT

Data Preparation

Prior to conducting statistical analyses on the data set, several preliminary steps were taken.

The purpose of these preliminary steps was to ensure accuracy of the data obtained from nurses

and unit managers from the 20 participating health care organizations across Ontario, Canada.

Specifically, issues related to missing data, coding, and measurement error were addressed.

The preliminary steps are presented in sequential order.

Data Entry Error and Missing Data

Data entry error and missing data occurred for several reasons, such as unclear responses

(e.g., circling two response options for the same item). Since data entry errors and missing data

can adversely affect the accuracy of the data set, each item in every survey was reviewed three

times to increase the validity of the study conclusions. Decision rules were established related

to data entry error and missing data by the principal investigator. As well, unit managers were

contacted by telephone to clarify any unclear responses on the unit manager surveys.

Missing data (i.e., cases with incomplete data or responses) can be problematic in multivariate

analyses, particularly when different subgroups of cases have incomplete data on different

subsets of variables. This causes the number of cases available for analysis to be reduced, which

decreases the statistical power to detect significant effects or correlations; which, in turn,

potentially leads to type II error (Ward & Clark, 1991).

Computing Total Scale Scores

Total scale and subscale scores were computed to quantify the variables of interest. The total

scores were calculated based on the scores of the individual items comprising each scale or

subscale, as recommended by the tool developer. The subscales represented the different

domains of the concept being measured. The formulae for computing the total scores were those

provided by the instrument developers, and usually consisted of taking either the sum or the

mean of the items.


TH

re

e Chapter Three: Study Participants

Description of the Study Sample

Nurse Surveys

Unit Manager Surveys

Summary

21


DESCRIPTION OF THE STUDY SAMPLE

Settings

The sample consisted of registered nurses (RNs), registered practical nurses (RPNs), unregulated

health workers (URWs), and unit managers employed in a sample of acute care, complex

continuing care, long-term care, and homecare organizations in Ontario, Canada. Five acute care

settings were involved in the study, comprising 16 medical and surgical units in total (see

Table 1). In long-term care, seven facilities were included in this study, comprising 30 resident

care units. The long-term care facilities included two larger settings that ranged from 216 to 394

beds between them, and four smaller nursing homes that ranged in bed size from 110 to 124.

Four complex continuing care settings were included in this study, involving 15 patient care

units. Finally, four homecare settings were involved in the study. These settings were

representative of all regions of the province with 5 sites comprised of 15 units coming from

central Ontario, 4 sites comprised of 19 units from southwestern Ontario, 5 sites comprised of

20 units from eastern Ontario, and 6 sites consisting of 11 units from northern Ontario. Thus,

the sample can be considered geographically representative of health care settings in Ontario, as

well as representative of the different sectors of interest to this study (i.e., acute care, complex

continuing care, long-term care, and homecare).

NURSE SURVEYS

Nursing Personnel

A total of 451 nursing staff questionnaires were completed and returned in the study (see

Table 4). The sampling requirements for the study were met and the sample was representative

of all sites in the study. Approximately 57% of respondents were RNs, 31% were RPNs, and 10%

URWs. Close to half of the RN respondents (n=117) were employed in acute care, while fewer

came from homecare, complex continuing care, and long-term care. In contrast, the majority

of RPNs were employed in complex continuing care, followed by long-term care, homecare, and

the fewest in the acute care sector. The majority of unregulated workers in this study were

employed in long-term care settings, while few came from homecare, complex continuing care,

or acute care.

The employment profiles reported by RNs in the sample are comparable to profiles of RNs

working in both Canada and Ontario. In 2004, over 60% of RNs reported working in hospitals

including rehabilitation and convalescent centres and approximately 13% of RNs worked in

community health (CIHI, 2005a). Additionally, 7.9% of RNs in Ontario and 10.5% of RNs in Canada

worked in nursing homes or long-term care facilities (CIHI, 2005a). The places of employment

reflected by the RPNs in the sample are less similar to provincial and national profiles, which

reported that the majority of RPNs (referred to as Licensed Practical Nurses [LPN] in the database)

work in hospitals, followed by long-term care and community health (CIHI, 2005b). This may be

partly explained by the fact that the national and provincial databases include convalescent

facilities with acute care hospitals. Comparisons of unregulated workers are not possible due to

lack of data (CIHI 2005a, 2005b).

23

Table 4. Participation Rates of Nursing Personnel by Occupational Title and by Sector

ComplexAcute care Long-term care continuing care Homecare Overall care

N (%) N (%) N (%) N (%) N (%)

RN 117 (84.8) 42 (31.8) 44 (43.1) 55 (69.6) 258 (57.2)

RPN 17 (12.3) 47 (35.6) 54 (52.9) 22 (27.8) 140 (31.0)

URW 3 (2.2) 42 (31.8) 2 (2.0) 0 (0) 47 (10.4)

No response 1 (0.7) 1 (0.8) 2 (2.0) 2 (2.5) 6 (1.3)

Total 138 (100.0) 132 (100.0) 102 (100.0) 79 (100.0) 451 (100.0)

Age of Nursing Personnel Participants

Demographic data included general biographical data and data pertaining to educational

preparation and work arrangements. Overall 420 (93%) participants were female and 24 (5%) were

male. As Table 5 demonstrates, the age range of study participants varied by health care sector.

For example, in acute care, the age range in this study was fairly balanced. Similarly, the age of

nurses was fairly consistent in homecare settings, with the exception of new nurses. In contrast,

fewer young nurses were employed in long-term care and complex continuing care settings,

where the majority of nurse participants were over the age of 40.

The information available in the national database separates RNs from RPNs in the reports of

ages and therefore are not directly comparable to the study sample which combines RNs, RPNs

and URWs. In Ontario, the largest percentages of both RNs and RPNs in all health care sectors are

found in the over 50 years of age category. This is most evident in nursing homes or long-term

care settings, where almost 50% of RNs and 32.5% of RPNs are over 50 years of age (CIHI, 2005c).

Provincially, in all sectors, nurses under the age of 30 make up the smallest percentage of the

workforce (CIHI, 2005c).

Table 5. Age of Nursing Personnel by Sector


N (%) N (%) N (%) N (%) N (%)

20-29 years 30 (21.7) 11 (8.3) 7 (6.9) 11 (13.9) 59 (13.1)

30-39 years 32 (23.2) 29 (22.0) 19 (18.6) 19 (24.0) 99 (22.0)

40-49 years 40 (29.0) 35 (26.5) 42 (41.2) 17 (21.5) 134 (29.7)

> 50 years 30 (21.7) 41 (31.1) 23 (22.5) 19 (24.0) 113 (25.1)

No response 6 (4.3) 16 (12.1) 11 (10.8) 13 (16.5) 46 (10.2)

Totals 138 (100.0) 132 (100.0) 102 (100.0) 79 (100.0) 451 (100.0)


Educational Preparation of Nursing Personnel

Table 6 demonstrates that on average the majority of RN, RPN and URW participants (n=285,

63%) in this study were prepared at the level of diploma education, 91 (20%) had hospital-based

certificates, while 65 (14%) were baccalaureate prepared, and 2 (0.4%) held a Masters degree.

In comparison, in 2004, the data indicating highest education in nursing of RNs in Canada

showed that almost 68% of the RN workforce had a diploma education, 29.8 % had a

baccalaureate degree, and another 2.3% were Masters or Doctorate prepared (CIHI, 2005a). In

Ontario, almost 80% of RNs were diploma-prepared, while 22.8% of the RN workforce held a

baccalaureate degree and 2.2% had a Masters or Doctorate degree (CIHI, 2005a). Over 92% of

RPNs in each province in Canada were diploma prepared (CIHI, 2005b).

Table 6. Educational Preparation of Nursing Personnel by Sector


Education N (%) N (%) N (%) N (%) N (%)

Diploma 102 (73.9) 71 (53.8) 63 (61.8) 49 (62.0) 285 (63.2)

Hospital-based certificate 9 (6.5) 44 (33.3) 26 (25.5) 12 (15.2) 91 (20.2)

Baccalaureate 27 (19.6) 13 (9.8) 10 (9.8) 15 (19.0) 65 (14.4)

Masters 0 (0) 1 (0.8) 1 (1.0) 0 2 (0.4)

No response 0 (0) 3 (2.3) 2 (2.0) 3 (3.8) 8 (1.8)

Totals 138 (100.0) 132 (100.0) 102 (100.0) 79 (100.0) 451 (100.0)

Experience of Nursing Personnel

Table 7 indicates that 19% of the RN, RPN and URW study respondents (n=85) have less than 5

years of experience. The range of experience is more evenly distributed for each 5 year interval

from 5 to 34 years. Few participants in this study had over 35 years of experience. Acute care

settings employed the greatest number of new, less experienced nurses.

Table 7. Experience of Nursing Personnel by Sector


Years N (%) N (%) N (%) N (%) N (%)

< 5 years 36 (26.0) 19 (14.4) 13 (12.7) 17 (21.5) 85 (18.9)

5-9 years 14 (10.1) 24 (18.2) 10 (9.8) 10 (12.6) 58 (12.9)

10-14 years 15 (10.9) 16 (12.1) 11 (10.8) 9 (11.4) 51 (11.3)

15-19 years 17 (12.3) 20 (15.1) 16 (15.7) 9 (11.4) 62 (13.7)

20-24 years 16 (11.6) 15 (11.4) 25 (24.5) 9 (11.4) 65 (14.4)

25-29 years 18 (13.0) 18 (13.6) 13 (12.7) 8 (10.1) 57 (12.6)

30-34 years 17 (12.3) 12 (9.1) 9 (8.8) 8 (10.1) 46 (10.2)

35-39 years 3 (2.2) 2 (1.5) 2 (2.0) 5 (6.3) 12 (2.7)

40-44 years 1 (0.7) 1 (0.8) 0 (0) 1 (1.3) 3 (0.7)

45-50 years 0 (0) 0 (0) 0 (0) 1 (1.3) 1 (0.2)

No response 1 (0.7) 5 (3.8) 3 (2.9) 2 (2.5) 11 (2.4)

Totals 138 (100.0) 132 (100.0) 102 (100.0) 79 (100.0) 451 (100.0)


Employment Status of Nurse Participants

Table 8 indicates that the majority of nurses participating in this study (n=275, 61%) wereemployed full-time, while less than one-third (n=133, 30%) were employed part-time, and 6%(n=28) held casual positions. Some nurses indicated that they worked a combination of thesealternatives (3%), (n=12). These patterns of employment remained consistent across all sectors.

In comparison, the employment status of the sample is reflective of the averages found inOntario, in which 50.4% of regulated nursing workers in 2004 were employed full-time, 28.9%were employed part-time, and 7.6% were employed casually (CIHI, 2005a). This is slightlydifferent than the national averages, which showed that 48.8% of all regulated nursing personnelworked full-time, 32.2% part-time, and 10.8% casual (CIHI, 2005a).

Table 8. Employment Status of Nursing Personnel by Sector


Employment status N (%) N (%) N (%) N (%) N (%)

Full-time 91 (65.9) 83 (62.9) 62 (60.8) 39 (49.4) 275 (61.0)

Part-time 42 (30.4) 35 (26.5) 33 (32.4) 23 (29.1) 133 (29.5)

Casual 2 (1.4) 10 (7.6) 4 (3.9) 12 (15.2) 28 (6.2)

Other combinations 3 (2.2) 3 (2.3) 2 (2.0) 4 (5.1) 12 (2.7)

No response 0 (0) 1 (0.8) 1 (1.0) 1 (1.3) 3 (0.6)

Totals 138 (100.0) 132 (100.0) 102 (100.0) 79 (100.0) 451 (100.0)

The majority of respondents (n=383, 85%) indicated that their employment status had beenchosen by them (see Table 9). These response patterns remained consistent across all sectors.

Table 9. Choice of Employment Status of Nursing Personnel by Sector


Work status N (%) N (%) N (%) N (%) N (%)

My choice 118 (85.5) 116 (87.9) 85 (83.3) 64 (81.0) 383 (84.9)

Not my choice 19 (13.8) 13 (9.8) 16 (15.7) 13 (16.5) 61 (13.5)

No response 1 (0.7) 3 (2.3) 1 (1.0) 2 (2.5) 7 (1.6)

Totals 138 (100.0) 132 (100.0) 102 (100.0) 79 (100.0) 451 (100.0)

Participants were asked what types of changes they would like to have made to their employmentstatus. Over half (n=248, 55%) identified that they wanted their work hours to remain unchanged,while one-quarter (n=107, 24%) indicated that they wanted to work more, and 87 (19%) indicatedthat they wanted to work less (see Table 10).

Table 10. Preferred Change in Employment Status of Nursing Personnel by Sector

ComplexWork status Acute care Long-term care continuing care Homecare Overall care

preference N (%) N (%) N (%) N (%) N (%)

Same 83 (60.1) 75 (56.8) 49 (48.0) 41 (51.9) 248 (55.0)

More hours 21 (15.2) 28 (21.2) 29 (28.4) 29 (36.7) 107 (23.7)

Less hours 34 (24.6) 26 (19.7) 20 (19.6) 7 (8.9) 87 (19.3)

No response 0 (0) 3 (2.3) 4 (3.9) 2 (2.5) 9 (2.0)

Totals 138 (100.0) 132 (100.0) 102 (100.0) 79 (100.0) 451 (100.0)


Table 11 shows that two-thirds of the participants (n=300, 67%) indicated that they worked

up to 40 hours a week. Over one-quarter (n=119, 27%) identified that they worked over 40 hours

per week.

Table 11. Hours Worked Weekly by Study Nurse Participants by Health Care Sector


Hours N (%) N (%) N (%) N (%) N (%)

< 40 hrs/wk 86 (62.3) 96 (72.7) 73 (71.5) 45 (57.0) 300 (66.5)

> 40 hrs/wk 45 (32.6) 23 (17.4) 23 (22.5) 28 (35.4) 119 (26.4)

No response 7 (5.1) 13 (9.8) 6 (5.9) 6 (7.6) 32 (7.1)

Totals 138 (100.0) 132 (100.0) 102 (100.0) 79 (100.0) 451 (100.0)

UNIT MANAGER SURVEYS

Staff Mix

Nurse staffing models varied by sector in this study (see Table 12). The majority of all-RN

staffing models were evidenced in acute care settings (21%), while fewer were seen in complex

continuing care (8%), homecare (5%), and long-term care (1%). A regulated professional nursing

staff mix model comprised of RNs and RPNs was most prevalent in complex continuing care

settings in this study (71%) and homecare (48%), with fewer (33%) in acute care, and long-term

care (7%). Nurse staffing models comprised of RNs, RPNs, and URWs were most visible in long-

term care settings (83%), followed by homecare (41%), complex continuing care (13%), and acute

care (13%). RN/URW models are most often seen in acute care (33%), with fewer evident in

homecare (6%), long-term care (6%), and complex continuing care (1%). Finally, RPN/URW models

are not common, but when they do occur, they are seen in complex continuing care (6%) and

long-term care settings (3%).

Table 12. Unit Staffing Model by Sector


N (%) N (%) N (%) N (%) N (%)

RN only 34 (21.4) 2 (1.4) 8 (7.9) 5 (4.9) 49 (9.7)

RNs & RPNs 53 (33.3) 10 (6.9) 72 (71.3) 50 (48.5) 185 (36.5)

RNs, RPNs, & URWs 20 (12.6) 119 (82.6) 13 (12.9) 42 (40.8) 194 (38.3)

RNs & URWs 52 (32.7) 8 (5.6) 1 (1.0) 6 (5.8) 67 (13.2)

RPNs & URWs 0 (0.0) 4 (2.8) 6 (5.9) 0 (0.0) 10 (2.0)

Missing 0 (0.0) 1 (0.7) 1 (1.0) 0 (0.0) 2 (0.4)

Totals 159 (100.0) 144 (100.0) 101 (100.0) 103 (100.0) 507 (100.0)

Percentage of RNs

The average number of RNs on the study units also varied as identified in Table 13. Acute care

study units had a mean percentage of RNs of 75%, followed by complex continuing care study

units with 41%, and long-term care units with 25%. Although homecare settings do not provide

unit-based care, they have a mean percentage of 70% RNs in their settings.


Table 13. Mean Percentage of RNs on Study UnitsComplex

Acute care Long-term care continuing care Homecare Overall care

x̄ (SD) x̄ (SD) x̄ (SD) x̄ (SD) x̄ (SD)

RNs 74.9 (20.02) 24.6 (29.57) 41.2 (5.52) 70.0 (8.16) 48.4 (29.42)

Absenteeism

Average rates of absenteeism were highest in long-term care and complex continuing care in thisstudy (see Table 14). Unregulated workers had the highest absenteeism with their average numberof days absent in long-term care (x̄=61), followed by acute care (x̄=20), and complex continuingcare (x̄=5). For RNs, the highest average number of days absent occurred in long-term care(x̄=22), followed by complex continuing care (x̄=9), acute care (x̄=8), and homecare (x̄=4). Thesepatterns were similar for RPNs with the highest average number of days absent being in long-termcare (x̄=27), followed by complex continuing care (x̄=11), acute care (x̄=7), and homecare (x̄=4).

Table 14. Average Number of Days Absent AnnuallyComplex


Employee Group x̄ (SD) x̄ (SD) x̄ (SD) x̄ (SD) x̄ (SD)

RN 8.4 (2.99) 22.3 (28.48) 8.5 (5.77) 3.7 (2.54) 11.5 (15.13)

RPN 6.6 (3.11) 27.0 (42.92) 10.6 (5.47) 3.7 (2.54) 15.1 (25.75)

URW 19.7 (26.27) 60.6 (100.05) 4.9 (1.90) N/A 42.4 (81.87)

Employment Status

Overall, unit managers in this study indicated that 43% of RNs were employed full-time, while33% were employed part-time, and 25% in casual positions (see Table 15). In contrast, 38% ofRPNs were employed full-time, with close to 35% part-time, and 27% in casual positions. Finally,39% of URWs worked full-time, 27% part-time, and 34% casually.

Table 15. Percentage of Employment by Occupational Status Complex


Status N (%) N (%) N (%) N (%) N (%)

RN

Full-time 370.0 (56.8) 50.5 (38.8) 98.0 (34.0) 10.0 (6.1) 528.5 (42.8)

Part-time 205.0 (31.5) 49.5 (38.1) 149.0 (51.7) 0.0 (0.0) 403.5 (32.7)

Casual 76.0 (11.7) 30.0 (23.1) 41.0 (14.2) 155.0 (93.9) 302.0 (24.5)

Total 651.0 (100.0) 130.0 (100.0) 288.0 (100.0) 165.0 (100.0) 1234.0 (100.0)

RPN

Full-time 29.0 (39.7) 79.0 (39.9) 157.0 (44.0) 2.0 (2.5) 267.0 (37.8)

Part-time 31.0 (42.5) 66.0 (33.3) 151.0 (42.3) 0.0 (0.0) 248.0 (35.1)

Casual 13.0 (17.8) 53.0 (26.8) 49.0 (13.7) 77.0 (97.5) 192.0 (27.2)

Total 73.0 (100.0) 198.0 (100.0) 357.0 (100.0) 79.0 (100.0) 707.0 (100.0)

URW

Full-time 52.0 (68.0) 309.0 (40.5) 9.0 (33.3) 0.0 (0.0) 370.0 (39.2)

Part-time 23.5 (30.7) 221.0 (28.9) 7.0 (25.9) 0.0 (0.0) 251.5 (26.6)

Casual 1.0 (1.3) 233.5 (30.6) 11.0 (40.7) 78.0 (100.0)+ 323.5 (34.2)

Total 76.5 (100.0) 763.5 (100.0) 27.0 (100.0) 78.0 (100.0) 945.0 (100.0)

+ single site


Differences in employment status were noted by sector, where 57% of acute care RN staff

members were employed full-time, while 39% of long-term care RNs, 34% of complex continuing

care RNs, and only 6% of homecare RNs were employed full-time. In contrast, the complex

continuing care sector employed the highest percentage of full-time RPNs (44%), while 40% of

both acute care and long-term care RPNs, and less than 3% of homecare RPNs were employed

full-time. Finally, the acute care sector employed the highest percentage of full-time URWs (68%),

while 40% of long-term care URWs and 33% of complex continuing care URWs were employed

full-time. No URWs working in the homecare sector were employed full-time.

For part-time staff members, complex continuing care employed the highest percentage of part-

time RNs (52%), while 38% of long-term care RNs and 32% of acute care RNs were employed part-

time. In both the acute care and complex continuing care sectors, 42% of RPNs were employed

part-time, while 33% of RPNs in the long-term care sector were employed part-time. Similar

findings were seen for the percentage of URWs employed part-time in the acute care, long-term

care, and complex continuing care sectors; where 31%, 29%, and 26% of URWs in each respective

sector were employed part-time. None of the sites in the study sample of homecare sites

employed nursing staff part-time.

For casual employment, 94% of homecare RNs were employed casually, while 23% of long-term

care RNs, 14% of complex continuing care RNs, and 12% of acute care RNs were employed

casually. Similarly, within the homecare sector, 98% of RPNs were employed casually, while 27%

of long-term care RPNs, 18% of acute care RPNs, and 14% of complex continuing care RPNs

worked as casual employees. Finally, 100% of URWs working in the homecare sector were

employed casually, while 41% of complex continuing care URWs, 31% of long-term care URWs,

and less than 2% of acute care URWs were employed as casual staff.

Experience

Table 16 demonstrates that the majority of nurses in this study had over 10 years of

experience. Some differences were noted by sector, with complex continuing care settings having

the highest percentage of nurses with greater than 10 years of experience (n=303, 64%), acute

care with 42% (n=264), long-term care with 50% (n=139), and homecare with 20% (n=40). In

contrast, acute care settings in this study had the highest percentage of nurses with less than

2 years of experience.

Table 16. Percentage Experience of Nursing Personnel


Years N (%) N (%) N (%) N (%) N (%)

< 1 year 45 (7.2) 20 (7.1) 23 (4.9) 5 (2.5) 93 (5.9)

1-2 years 70 (11.2) 29 (10.4) 22 (4.6) 28 (13.9) 149 (9.4)

2-5 years 116 (18.6) 39 (13.9) 44 (9.3) 44 (21.8) 243 (15.4)

5-10 years 130 (20.8) 53 (18.9) 81 (17.1) 85 (42.1) 349 (22.1)

> 10 years 264 (42.2) 139 (49.6) 303 (64.1) 40 (19.8) 746 (47.2)

Totals 625 (100.0) 280 (100.0) 473 (100.0) 202 (100.0) 1580 (100.0)


Unit Manager Span of Control

The span of control of unit managers in this study also varied (see Table 17). For the most part,

acute care unit managers had between 40 and 59 staff reporting to them, while complex

continuing care unit managers had between 30 and 59. The number of staff reporting to unit

managers in long-term care settings in this study varied more than any of the sectors in

this study.

Table 17. Span of Control of Unit Managers on Study Units


Staff N (%) N (%) N (%) N (%) N (%)

< 10 staff 0 (0.0) 2 (11.1) 0 (0.0) 1 (25.0) 3 (5.7)

10-19 0 (0.0) 3 (16.7) 0 (0.0) 0 (0.0) 3 (5.7)

20-29 1 (6.3) 0 (0.0) 0 (0.0) 1 (25.0) 2 (3.8)

30-39 0 (0.0) 1 (5.6) 4 (26.7) 0 (0.0) 5 (9.4)

40-49 4 (25.0) 2 (11.1) 4 (26.7) 0 (0.0) 10 (18.9)

50-59 9 (56.2) 1 (5.6) 5 (33.3) 0 (0.0) 15 (28.3)

60-69 1 (6.3) 0 (0.0) 0 (0.0) 0 (0.0) 1 (1.9)

70-79 0 (0.0) 2 (11.1) 0 (0.0) 1 (25.0) 3 (5.7)

80-89 0 (0.0) 2 (11.1) 0 (0.0) 0 (0.0) 2 (3.8)

90-99 0 (0.0) 0 (0.0) 1 (6.7) 0 (0.0) 1 (1.9)

> 100 1 (6.3) 2 (11.1) 1 (6.7) 1 (25.0) 5 (9.4)

Missing 0 (0.0) 3 (16.7) 0 (0.0) 0 (0.0) 3 (5.7)

Totals 16 (100.0) 18 (100.0) 15 (100.0) 4 (100.0) 53 (100.0)

With the exception of homecare, the majority of managers (n=40, 76%) in this study were

managing multiple units, regardless of sector (see Table 18).

Table 18. Mean Scope of Responsibility


Scope (Units) N (%) N (%) N (%) N (%) N (%)

Managing One 1 (6.3) 5 (27.8) 5 (33.3) 2 (50.0) 13 (24.5)

Managing Multiple 15 (93.8) 13 (72.2) 10 (66.7) 2 (50.0) 40 (75.5)

16 (100.0) 18 (100.0) 15 (100.0) 4 (100.0) 53 (100.0)


Nurse-to-Patient Ratios

Nurse-to-patient ratios varied by shift and sector in this study (see Table 19). On acute care

study units, the nurse-to-patient ratio was 1:5 on days and evenings, and 1:7 on night shifts.

Complex continuing care study units had a nurse-to-patient ratio of 1:4 on day shifts, 1:7 on

evenings, and 1:13 on nights. In long-term care, these ratios were higher, averaging 1:17 on days,

1:22 on evenings and 1:46 on night shifts. Homecare settings had a standard ratio of 1:8.

Table 19. Mean Nurse-to-Patient Ratios by Shift


Shift x̄ (SD) x̄ (SD) x̄ (SD) x̄ (SD) x̄ (SD)

Days 1 : 5.1 (0.72) 1 : 16.6 (14.91) 1 : 4.3 (0.90) 1 : 8.0 + (0.00) 1 : 9.1 (10.51)

Evenings 1 : 5.4 (0.83) 1 : 21.8 (27.22) 1 : 6.8 (1.61) 1 : 8.0 + (0.00) 1 : 11.7 (17.62)

Nights 1 : 6.9 (1.44) 1 : 46.1 (48.59) 1 : 12.7 (3.58) N/A 1 : 23.1 (34.06)

+Note only one site, therefore no SD

SUMMARY

Nurse-to-patient ratios varied by shift and sector in this study (see Table 19). On acute care

study units, the nurse-to-patient ratio was 1:5 on days and evenings, and 1:7 on night shifts.

Complex continuing care study units had a nurse-to-patient ratio of 1:4 on day shifts, 1:7 on

evenings, and 1:13 on nights. In long-term care, these ratios were higher, averaging 1:17 on days,

1:22 on evenings and 1:46 on night shifts. Homecare settings had a standard ratio of 1:8.


Fo

ur Chapter Four:

Quality of Nursing Worklife Indicators

Introduction

Instrument Reliability

Nursing Personnel Group Reliability

and Completion Rate Comparisons

Sector Reliability and Completion Rate

Comparisons

Missing Data

Summary

31

INTRODUCTION

The first study objective examines the quality of nursing worklife indicator data collected by

nurses and managers in everyday practice settings in acute care, complex continuing care,

long-term care and homecare settings in Ontario, Canada. The specific research questions were:

(1) What is the reliability of data collected by nurses and managers? and (2) What is the

completion rate of the nursing worklife measures collected by nurses and managers? The results

of these questions are presented overall, as well as according to nursing personnel groups (i.e.,

RNs, RPNs, and URWs) and health care sectors examined in this study (i.e., acute care, long-term

care, complex continuing care, and homecare).

INSTRUMENT RELIABILITY

Overall Sample

The Cronbach’s alpha measure for scale reliability was very high for both the Work Quality Index

(WQI; α= .95) and the Nursing Work Index-Revised (NWI-R; α= .95) implying that there was high

inter-item correlation in the questions being asked in these surveys (see Table 20 below).

Completion of the questions by study respondents was slightly better with the WQI instrument

(n=310) as compared to the NWI-R instrument (n=297) when completing all possible questions.

Table 20. Reliability of Nursing Worklife Measures

N µ SD α

Work Quality Index (WQI) 310 4.314 .7609 .95

Nursing Work Index-R (NWI-R) 297 2.298 .2898 .95

NURSING PERSONNEL GROUP RELIABILITY

AND COMPLETION RATE COMPARISONS

Worklife Scale Reliabilities: RN, RPN and URW

There were no appreciable differences between RNs, RPNs, or URWs with respect to either the

WQI Cronbach’s alpha scores (α= .95, .95, .96) or the NWI-R Cronbach’s alpha scores (α= .95, .96,

.93) for the overall scales (see Table 21). Thus, the reliability of both instruments is relatively

consistent across the different nursing work groups that participated in this study.


Table 21. Reliability of Nursing Worklife Measures by Individual Nursing Personnel Group (RN, RPN, and URW)

RN only RPN only URW only All staff

N, µ, SD, α N, µ, SD, α N, µ, SD, α N, µ, SD, α

WQI

Professional work environment 237 116 32 3903.819 3.686 3.520 3.745.5958 .6173 .7503 .6033.866 .877 .905 .873

Autonomy of practice 247 128 37 4175.155 4.830 4.243 4.967.2881 .3435 .3449 .2828.855 .882 .856 .869

Work worth to self and others 230 116 31 3805.030 4.922 5.073 4.996.3975 .3949 .3647 .3194.778 .792 .709 .765

Professional relationships 241 114 25 3844.735 4.565 3.845 4.619.6826 .8025 .9055 .7225.862 .854 .892 .865

Professional role enactment 250 130 33 4184.434 4.355 3.933 4.3641.1845 .9487 1.048 1.082.782 .784 .750 .777

Benefits 236 128 33 4003.988 3.758 3.932 3.901.4989 .4817 .7817 .4806.823 .836 .846 .830

Overall scale 195 91 22 3104.392 4.237 4.008 4.314.7906 .7556 .8654 .7609.950 .950 .956 .950

NWI-R

Autonomy 243 132 39 4152.192 2.270 2.385 2.238.1095 .1789 .1000 .1265.755 .768 .541 .746

Control over practice setting 237 130 35 4052.426 2.432 2.306 2.416.3391 .2387 .3493 .2828.716 .732 .671 .710

Nurse-physician relationship 253 133 32 4222.153 2.110 2.021 2.132.1517 .0548 .1265 .1095.778 .611 .662 .719

Organizational support 242 128 29 4022.287 2.240 2.307 2.275.2627 .1924 .2646 .2258.800 .760 .697 .778

Overall scale 183 88 23 2972.314 2.251 2.304 2.298.3114 .2702 .3421 .2898.949 .959 .927 .950


α=

Work Quality Index (WQI)

An assessment of the WQI instrument by study participants revealed that the Cronbach alpha’s

were relatively consistent across each of the six subscales – professional work environment,

autonomy of practice, work worth to self and others, professional relationships, professional role

enactment, and benefits (see Table 21). The alpha range was from .71 to .91 with the subscales

containing the greater number of items having the largest alpha score. For example, the 8-item

“Professional Work Environment” subscale achieved the highest alpha scores in general, while the

4-item “Work Worth to Self and Others” subscale scored the lowest alpha ratings.

Completion of the subscale questions was lowest for the “Work Worth to Self and Others” subscale

for the RN group. There were only 230 RNs that fully completed that section, as compared to

236 to 250 for the other subscales. This subscale explores the nurses’ contribution to the

hospital, profession, the overall sense of achievement they get from work, and whether or not

the work associated with their position provides the opportunity for them to use a full range of

skills. It is possible that some RNs were unable to answer these questions because they generally

receive inadequate feedback about their contributions to patient care. As well, nurses may have

chosen not to answer questions rather than to provide negative answers. A general lack of

recognition of the work of nurses within the institution, media, and within the general public

often leads nurses to undervalue their own contribution. Increased patient loads and higher

patient acuity make work environments stressful, leaving nurses with insufficient time to do the

job the way they intended, and there may also be a disconnect between how much autonomy

nurses actually have and how much they should have or want to have.

For RPNs, completion of the subscale questions was lowest for the “Professional Relationships”

subscale. There were 114 RPNs that fully completed that section, as compared to 116 to 130 for

the other subscales. The professional relationships subscale examines support received from

physicians and peers for nursing care decisions, support for work from nurses on other shifts,

whether good work relations exist with physicians, peers, and supervisors, and whether

adequate praise for work well done is received from hospital physicians and peers. It is possible

that the nature of the work of RPNs involves less exposure to disciplines outside of nursing.

RPNs may work closely with an RN, but may have difficulty answering questions about their

relationships with other categories of health care providers. Some RPNs may feel their skills are

underutilized or they may not be satisfied with their level of involvement in decision-making

and formulating plans of care in the interdisciplinary team and may therefore have chosen not to

respond to these questions rather than give an answer that reflects these feelings.

Similarly, completion of the subscale questions was lowest for the “Professional Relationships”

subscale for the URW group. There were 25 URWs that fully completed that section, as compared

to 31 to 37 for the other subscales. Reasons for low completion on this subsection may have

been similar to RPNs. While the level of involvement with health care professionals may be even

more limited for URWs than RPNs, this may be mediated by a lower expectation of involvement

since these workers are not a part of a regulated health care profession.


Nursing Work Index – Revised (NWI-R)

For the NWI-R instrument, the Cronbach’s alphas were relatively consistent across all four

subscales – autonomy, control over practice, nurse-physician relationship, and organizational

support. They appeared to be less specific than the WQI subscale ratings, in general, ranging

from .54 to .80. The subscales with the greater number of items had the largest alphas. For

example, the 5-item “Autonomy” subscale scored the lowest alpha ratings, whereas, the 10-item

“Organizational Support” subscale scored the highest, in general.

Completion of the subscale questions was lowest for the “Control over the Practice Setting”

subscale for the RN group. There were only 237 registered nurses that fully completed that

section, as compared to 242 to 253 for the other subscales. This subscale examines support

services in place to allow nurses to spend time with patients, adequacy of time and opportunity

to discuss patient care problems with other nurses, adequacy of nurse staffing to provide quality

patient care and get work done, effectiveness of nurse manager as a manager and leader,

opportunity to work on a highly specialized unit, and patient assignments that foster continuity

of care. Control over their practice setting may be impacted by a shortage of nursing staff,

increased patient loads, and higher patient acuity. All of these factors may create a challenge for

RNs as they try to respond to this scale. Substantial evidence exists on the Canadian nursing

work environment that suggests that RNs are interested in having greater control over their

practice settings (Advisory Committee on Health Human Resources, 2000; 2002). The low

completion rates may indicate that RNs have chosen not to answer the question rather than

provide negative answers.

For RPNs, completion of the subscale questions was lowest for the “Organizational Support”

subscale. There were 128 RPNs that fully completed that section, as compared to 130 to 133 for

the other subscales. This subscale explores support services in place to allow nurses to spend

time with patients, whether physicians and nurses have good working relationships, nursing’s

control over its own practice, adequacy of time and opportunity to discuss patient care problems

with other nurses, adequacy of nurse staffing to provide quality patient care and get work done,

effectiveness of the nurse manager as a manager and leader, freedom to make important patient

care and work decisions, not being placed in a position of having to do things that are against

their nursing judgment, teamwork between nurses and doctors, and patient assignments that

foster continuity of care. The items on this subscale may not adequately represent RPN practice.

It is possible that those who work in organizations where there are few targeted supports in

place for RPNs may have difficulty completing this subscale.

Similarly, completion of the subscale questions was lowest for the “Organizational Support”

subscale for the URW group. There were 29 URWs that fully completed that section, as compared

to 32 to 39 for the other subscales. Again, reasons for low completion on this subsection may

have been similar to RPNs. URWs are employed as unregulated support workers. There are few

components of this subscale that would be applicable to this group of employees, which might

explain the lower rate of completion.


Comparison of Worklife Scales: RN, RPN, and URW

In general, the completion was slightly better for the NWI-R subscales (n=415, 405, 422, and

402) than the WQI subscales (n=390, 417, 380, 384, 418, and 400). However, if you look at

completeness of records for the overall scales, the WQI seemed to fare better (n=310) than the

NWI-R (n=297) instrument. For RNs, 195 study participants completed every question of the WQI

scale, while 183 participants completed every question of the NWI-R scale. The number of RPNs

who completed every scale question was 91 for the WQI and 88 for the NWI-R. Finally, the

number of URWs who completed every scale question was very similar for both the WQI (n=22)

and the NWI-R (n=23). These findings are not surprising as the instruments were both originally

developed for use with RN populations. It is plausible that the instruments may be tapping

facets of nursing practice that are not central to the RPN or URW role, or perhaps are of less

interest to nursing personnel in those roles.

SECTOR RELIABILITY AND COMPLETION RATE COMPARISONS

Worklife Scale Reliabilities: Acute Care, Long-term Care,

Complex Continuing Care, and Homecare

There were no appreciable differences between acute care, long-term care, complex continuing

care, and homecare with respect to either the WQI Cronbach’s alpha scores (α =.94, .96, .96, .93)

or the NWI-R Cronbach’s alpha scores (α =.92, .96, .96, .95) for the overall scales (see Table 22).

Thus, the reliability of both instruments is relatively consistent across the different health care

sectors that participated in this study.

Table 22. Reliability of Nursing Worklife Measures by Health Care Sectors

Long-term ComplexAcute care care continuing care Homecare Overall care

N, µ, SD, α N, µ, SD, α N, µ, SD, α N, µ, SD, α N, µ, SD, α

WQI

Professional work environment 130 106 94 59 3903.475 4.013 3.511 4.261 3.745.5339 .5167 .6885 1.0252 .6033.858 .915 .876 .778 .873

Autonomy of practice 132 120 93 71 4174.921 4.758 4.748 5.713 4.967.2387 .3049 .3755 .3163 .2828.853 .861 .897 .823 .869

Work worth to self and others 130 105 91 53 3804.960 5.002 4.920 5.208 4.996.4086 .2881 .2214 1.156 .3194.810 .778 .862 .648 .765

Professional relationships 135 100 91 57 3844.480 4.599 4.588 5.081 4.619.7937 .6610 .7987 .6481 .7225.893 .845 .843 .845 .865

Professional role enactment 135 114 95 73 4184.173 4.158 4.027 5.499 4.3641.347 1.088 1.089 .6978 1.082.665 .765 .782 .697 .777


Continued

Long-term ComplexAcute care care continuing care Homecare Overall care

N, µ, SD, α N, µ, SD, α N, µ, SD, α N, µ, SD, α N, µ, SD, α

Benefits 126 110 95 68 4003.756 4.139 3.961 3.732 3.901.4074 .6767 .5273 .6481 .4806.780 .872 .825 .839 .830

Overall scale 115 81 79 34 3104.163 4.440 4.215 4.809 4.314.8538 .6550 .8081 1.059 .7609.944 .956 .958 .925 .950

NWI-R

Autonomy 130 118 97 72 4152.374 2.254 2.330 1.850 2.238.1732 .1378 .1871 .0949 .1265.667 .709 .785 .751 .746

Control over practice 133 115 96 61 4052.516 2.437 2.571 1.916 2.416.3435 .3873 .2408 .2949 .2828.669 .713 .680 .590 .710

Nurse-physician relationship 136 113 98 74 4222.262 1.959 2.221 2.045 2.132.1612 .1000 .1581 .0447 .1095.801 .721 .663 .589 .719

Organizational support 132 108 95 66 4022.405 2.239 2.355 1.962 2.275.2569 .3225 .2280 .2214 .2258.779 .758 .744 .773 .778

Overall scale 108 77 70 42 2972.435 2.283 2.346 1.893 2.298.3420 .3271 .3449 .2775 .2898.922 .957 .945 .951 .950

Work Quality Index (WQI)

An assessment of completion of the WQI instrument by different sectors revealed that the

Cronbach alpha’s were relatively consistent across each of the six subscales – professional work

environment, autonomy of practice, work worth to self and others, professional relationships,

professional role enactment, and benefits (see Table 22). The alpha range was from .77 to .87.

Homecare had the smallest number of completed instruments (n=34) and the lowest alpha

(α =.93), while acute care had the highest number of completed instruments (n=115). The largest

alpha (α =.96) was recorded in complex continuing care.

Completion of the subscale questions was lowest for the “Work Worth to Self and Others” subscale

for the homecare group. There were only 53 RNs that fully completed that section, as compared

to 57 to 73 for the other subscales. This subscale explores the nurses’ contribution to the


hospital, the profession, the overall sense of achievement they get from work, and whether or

not the work associated with their position provides the opportunity for them to use a full range

of skills. For complex continuing care, completion of the subscale questions was also lowest for

the “Work Worth to Self and Others” subscale. There were 91 complex continuing care

respondents that fully completed that section and the “Professional Relationships” subscale, as

compared to 93 to 95 for the other subscales.

For long-term care, completion of the subscale questions was lowest for the “Professional

Relationships” subscale. There were 100 respondents that fully completed that section, as

compared to 105 to 120 for the other subscales. The professional relationships subscale

examines support received from physicians and peers for nursing care decisions, support for

work from nurses on other shifts, whether good work relations exist with physicians, peers, and

supervisors, and whether adequate praise for work well done is received from hospital

physicians and peers.

For acute care, completion of the subscale questions was lowest for the “Benefits” subscale. There

were 126 respondents that fully completed that section, as compared to 130 to 135 for the other

subscales. The benefits subscale examines opportunities for professional growth, salary and

other financial benefits, funding adequacy for health care premiums, work hour patterns,

vacation, sick leave, and inservice opportunities.

Nursing Work Index – Revised (NWI-R)

Similarly, the overall Cronbach’s alpha reliability measure for the NWI-R instrument varied

from .92 to .96 for the different health care sectors. Again, homecare had the smallest number

of completed instruments (n=42), while acute care had the largest number of completed

instruments (n=108) along with the lowest alpha (α =.92). With the NWI-R scale, long-term care

(α =.96) recorded the highest alpha.

For the NWI-R instrument the Cronbach’s alphas were relatively consistent across all four

subscales – autonomy, control over practice, nurse physician relationship, and organizational

support. They appeared to be much lower than the WQI subscale ratings, in general, the range

being from .71 to .78. The subscales with a greater number of items had the largest alphas.

For example, the 10-item “Organizational Support” subscale scored the highest, in general.

Completion of the subscale questions was lowest for the “Control over the Practice Setting”

subscale for the homecare group. There were only 61 registered nurses that fully completed that

section, as compared to 66 to 74 for the other subscales. This subscale examines support services

in place to allow nurses to spend time with patients, adequacy of time and opportunity to discuss

patient care problems with other nurses, adequacy of nurse staffing to provide quality patient

care and get work done, effectiveness of nurse manager as a manager and leader, opportunity to

work on a highly specialized unit, and patient assignments that foster continuity of care.

For complex continuing care and long-term care, completion of the subscale questions was lowest

for the “Organizational Support” subscale. There were 95 and 108 respondents respectively that

fully completed that section, as compared to 98 to 118 for the other subscales. This subscale

explores support services in place to allow nurses to spend time with patients, whether


physicians and nurses have good working relationships, nursing’s control over its own practice,

adequacy of time and opportunity to discuss patient care problems with other nurses, adequacy

of nurse staffing to provide quality patient care and get work done, effectiveness of nurse

manager as a manager and leader, freedom to make important patient care and work decisions,

not being placed in a position of having to do things that are against their nursing judgment,

teamwork between nurses and doctors, and patient assignments that foster continuity of care.

Completion of the subscale questions was lowest for the “Autonomy” subscale for the acute care

sector. There were 130 respondents that fully completed that section, as compared to 132 to 136

for the other subscales.

Comparison of Worklife Scales: Acute Care, Long-term Care,

Complex Continuing Care, and Homecare

As noted earlier, the completion was slightly better for the NWI-R subscales than the WQI

subscales. When examined by sector, for acute care participants, 115 study participants

completed every question of the WQI scale, while 108 participants completed every question of

the NWI-R scale. The number of long-term care participants who completed every scale question

was 81 for the WQI and 77 for the NWI-R. For complex continuing care, 79 participants

completed every WQI scale question, while 70 completed the NWI-R. Finally, for home care, the

number of participants who completed every scale question was much lower overall, for the WQI

(n=34) and the NWI-R (n=42). These findings are not surprising as the instruments were both

originally developed for use with acute-care or hospital settings, and may not be representative

of home care practice.

MISSING DATA

Overall, for all of the nursing worklife data, every hospital sector and nursing personnel group

included, there are no significant differences between the percent of missing values for the WQI

questions and the percent of missing values for the NWI-R (see Table 23). Homecare had the

highest percentage of missing data on both instruments, followed by long-term care, complex

continuing care, and acute care. This corresponds to the findings reported in the focus groups,

where homecare and long-term care nursing personnel suggested the instruments were reflective

of acute care nursing work environments.

For one particular sector and one particular staff group, there were some significant differences

between the instruments, with the WQI questions having a few more missing values than the

NWI-R questions. Specifically, in the long-term care sector, the WQI questions had an average

of 7.79% missing values, whereas the NWI-R questions had an average of 6.17% missing values.

These means are judged to be statistically significantly different (t=1.809; 84 df; p<.10),

indicating that in long-term care missing data was significantly greater than that of other

sectors. As well, for the URW group of staff, WQI questions had an average of 16.07% missing

values, whereas the NWI-R questions had an average of 11.50% missing values. These means

are also statistically significantly different (t=3.115; 78 df; p<.05), indicating that URWs had a

higher proportion of missing data than other care providers in this study.


Table 23. Missing Data for Nursing Worklife Measures by Individual Nursing Personnel Group (RN, RPN, and URW) and by Health Care Sectors

Overall Acute Long-term Complex Home RN RPN URWnurses care care care care only only only

N=451 N=138 N=132 N=102 N=79 N=259 N=140 N=47Mean Mean Mean Mean Mean Mean Mean Mean(SD) (SD) (SD) (SD) (SD) (SD) (SD) (SD)

WQI Average 4.98% 1.60% 7.79% 3.12% 8.56% 3.17% 4.61% 16.07%

percent missing (3.03) (1.56) (4.20) (2.45) (9.91) (2.46) (3.86) (7.15)

NWI-R Average 4.58% 1.48% 6.17% 3.04% 9.55% 3.96% 3.40% 11.50%

percent missing (3.36) (1.61) (4.43) (1.88) (12.6) (3.77) (3.35) (6.79)

t-test Average 0.605 0.384 1.809* 0.166 0.427 1.216 1.575 3.115**

percent missing 86 df 83 df 84 df 67 df 92 df 95 df 73 df 78 df

* p < 0.10** p < 0.05

SUMMARY

These results imply that overall, there were no substantial differences between the WQI and

NWI-R scale reliabilities. However, the NWI-R instrument tended to have lower alpha scores than

the WQI instrument for the majority of the subscales, within all health care sectors. As well,

within the NWI-R subscales, the homecare sector appears to have lower alpha values than the

other sectors, for three out of four NWI-R subscales.

The completion rate for the scales showed some differences with the WQI subscales achieving

a better completion rate by respondents in this study. While there does not seem to be over-

whelming evidence to suggest that one instrument is superior to the other, this study suggests

that the WQI may be a more stable measure of nursing work environments. Both appear to be

fairly reliable and consistent, although some specific sectors (i.e., long-term care) and nursing

personnel groups (i.e., URWs) experienced difficulties relating to some of the questions. Thus,

consideration should be given to adapting the language of these measures to specific health care

sectors (i.e., long-term care, homecare) to accurately capture their unique work environments.


FIv

e Chapter Five: Feasibility and Utility of Collecting Nursing Worklife Indicator Data

Introduction

Assessing the Feasibility

and Utility of Nursing Worklife

Indicator Data Collection

Summary

41

INTRODUCTION

The second study objective was to examine the feasibility of collecting nursing worklife indicator

data in everyday practice settings in acute care, complex continuing care, long-term care, and

homecare settings in Ontario, Canada. The specific research questions were: (1) What is the

receptivity to nursing worklife indicator data collection by nurses and managers? and

(2) What is the burden of collecting nursing worklife indicator data for nurses and managers?

The third study objective examines the utility of nursing worklife indicator data for nurses and

managers in acute care, complex continuing care, long-term care and homecare settings in

Ontario, Canada. The specific research questions were: (1) To what extent are the nursing

worklife indicator data comprehensive, as perceived by nurses and managers? and (2) How

relevant and useful are the nursing worklife indicator data in assisting nurses and managers in

decision-making for the organization?

ASSESSING THE FEASIBILITY AND UTILITY

OF NURSING WORKLIFE INDICATOR DATA COLLECTION

Focus groups were held with nursing personnel and unit managers to explore the feasibility and

utility issues related to nursing worklife data collection. Nursing staff participants worked in

either a surgical or a medical unit in an acute care, long-term care, complex continuing care, or

homecare setting. Most of the participants were registered nurses, although there were RPNs and

URWs as well. All participants were actively involved in the discussion and validated the points

raised. Focus group interviews were conducted with 14 nursing staff (i.e., RN, RPN and URW) and

10 manager representatives from each of the four regions in Ontario where the study was being

conducted. Nursing staff participants consisted of one person from Region 1 (Central Ontario),

six from Region 2 (Southwestern Ontario), three from Region 3 (Eastern Ontario), and four from

Region 4 (Northern Ontario). Managers included two from Region 1 (Central Ontario), one from

Region 2 (Southwestern Ontario), five from Region 3 (Eastern Ontario), and two from Region 4

(Northern Ontario).

In order to assess the feasibility of collecting nursing data in practice settings, information was

obtained in focus groups on the amount of time it takes for a nurse and manager to complete the

worklife indicator survey. Participants in focus groups were asked to identify the time involved

in survey completion, and to identify any barriers and facilitators to nursing worklife indicator

data collection. In addition, data was collected from nurses on their perceived ease of collecting

the nursing worklife indicator data, ease of interpreting the nursing worklife indicator data, and

perceptions of the frequency that it should be collected. Nurses were consulted on their

receptivity to incorporating a standardized approach to nursing worklife indicators assessment.

Another aspect of feasibility is whether it is possible to collect the nursing worklife indicator

data in a timely manner. Information was gathered about the time required for data collection

to be completed, completeness of data collection, and reasons for failure to complete the survey.

Data was collected from nurses and managers on their perceptions of the factors in the work

environment that influence nurses’ receptivity to completing the survey.


Receptivity and Burden of Nursing Worklife Data Collection

for Nursing Personnel

The nurse surveys contained two instruments that measure aspects of the nursing work

environment, the Nursing Work Index – Revised and the Work Quality Index, as well as a number

of demographic questions. Nursing personnel in this study identified that it took between 15 to

30 minutes to complete the nursing worklife indicators survey, and identified that it was

relatively straightforward. Nurses’ receptivity towards nursing worklife data collection and

assessments of the burden associated with it can be characterized by exploring their perceptions

of the barriers and facilitators to the process of this data collection. Most of these relate to the

organization of nursing work and the work environment. While a few nurses denied any barriers

to this data collection existed, a number of impediments were identified by others that related to

time available to complete the worklife indicators survey. Getting away from the unit and then

returning later to “a mess of things that went wrong” was a problem for one nurse. In addition to

returning to the unit to face a number of problems, nurses also had to cope with colleagues who

were frustrated that they had to cover for them when they were gone. “Trying to make do with

fewer nurses” was identified as a challenge. Another nurse felt that the timing of the survey was

an obstacle to participation. In this case, the data collection took place at a point in the day

when the workload was heavy. Some nurses ended up staying late to complete the survey while

others completed the survey on their own personal time. While some expressed aggravation at

taking their own time to complete the survey, others talked about the importance of

participating despite the additional time required.

“…I did it at the end of shift and I was very, very frustrated.”

“...it causes resentment when it’s imposed upon my time to say you’re to do this but you’ll do

it on your own time.”

“I specifically had to arrange my day so that I could take time to come and do it. And I just believe

that it’s important so it was something that I wanted to do.”

“You really do have to create time if you want to do these things.”

“I guess I looked at it from the standpoint that yes, I did it on my coffee break but I wanted

to get my opinion in so I didn’t mind,”

There was some concern among nurses that management would “catch wind” of the data they

reported in the survey.

“I was kind of rallying my colleagues to fill it in. They were a little bit intimidated to think

that this might be something that might reflect on them badly should they sit down and

take the time to do it.”

“I found people when they filled it out they were asking each other back and forth, you know,

is it okay to put this type deal because they didn’t want to be reprimanded for it.”


“I specifically had to arrange my day so that I could take time to come and do it. And I just believe that it’s important so it was something that I wanted to do.”

Participants identified a number of factors that facilitated their participation. Several people

talked about being given a room where they could sit, along with a treat to have while they filled

out the surveys (i.e., cookies).

“…cookies helped because we were able to sit down, have a snack.”

“If I’m not mistaken, it was the only break I had that day which was nice.”

Support from managers to participate was also identified as a facilitator.

“We were very well prepared and our manager actually pulled us … pulled us from the

floor and said don’t worry.”

“Our manager was very supportive because a group of us were isolated up in a room and

said here’s a half an hour to fill out this survey. She was very supportive and encouraged

us to do that.”

“We had a nice experience. Our nurse manager mentioned it at a staff meeting and then supplied

a nice quiet room for us to go to and had cookies so it was a good experience.”

A couple of nurses talked about how having the data collector explain confidentiality facilitated

their willingness to participate.

“[The data collector] who did come to our facility did stress that this was completely anonymous.”

“They were very good at reassuring us that this was anonymous and was research and not

punitive based.”

Despite the need to use personal time, one nurse suggested it helped that the survey was

dropped off in the morning and picked up later, giving her time to “ponder” her responses over

coffee and lunch breaks. The opportunity to “debrief” facilitated participation for some of the

nurses.

“I really found I actually enjoyed doing the survey because I think as nurses we don’t often

have the opportunity to sit down and meet with each other and talk.”

“It was really nice just to sit down for even half an hour with my peers and just say, you

know, maybe this place isn’t such a bad place to work and I really enjoyed it.”

Comprehensiveness and Relevance of Nursing Worklife Indicator Data Collection

for Nursing Personnel

Most nursing staff participants reported that the survey was comprehensive, “detailed”, and

“really did get to the heart of the matter”. However, there were some difficulties identified by

homecare nurses who were completing the survey, compared to nurses working in long-term

care, complex continuing care, and acute care sectors. One nurse explained,

“There were a lot of questions that didn’t apply to them [homecare nurses] and they weren’t sure

what to answer.”


“We had a nice experience. Our nurse manager mentioned it at a staff meeting and then supplied a nice quiet room for us to go to and had cookies so it was a good experience.”

Participants further highlighted the unique environment in which homecare nurses work.

They discussed a variety of services they provide to patients that normally fall outside of

nursing (e.g., social work, occupational therapy, and physiotherapy).

“There are definitely things that the homecare nurses face that you wouldn’t necessarily face

in a facility.”

One nurse pointed out that the survey refers to interactions and relationships with other

staff on the ‘unit’, such as physicians. These questions do not capture the quality of the work

of homecare nurses (e.g., isolation) because they are tailored to the acute care rather than the

community setting. In response to these problems, one nurse suggested that a future survey

elicit feedback specifically from homecare nurses.

One participant referred to “trick questions”, where items on the surveys were unclear or

difficult to understand. Participants were asked about a number of specific areas of the survey

that had been identified in preliminary data analysis as not being consistently answered.

Some nurses had difficulty with questions that referred to a Chief Nursing Officer, Clinical Nurse

Specialist, or support staff because there were no such positions in their organizations. While

there may have been at one point in time, the question was not applicable to the organization’s

current status at the time of data collection.

“…when I put ‘not applicable’ it’s because really they don’t exist and you should have an

explanation as to why it’s not applicable.”

There was also some confusion over the question on the survey pertaining to nursing care

delivery models. Focus group participants indicated that the model used in practice can often be

ambiguous.

“…years ago they converted us from team nursing to total patient care and yet in fact the ways

things went … it started out that way but we’ve gone back to team nursing because you cannot do

total patient care anymore because things are so hectic and stressed and rushed so you absolutely

depend on the team.”

One nurse referred to the model of care as a “method of survival”. Another nurse denied that

there was any official model of care delivery, rather “it’s just what we need to do to get the

work done.”

When nurse participants in the focus group talked about preceptorship there was a sense that

additional clarity for survey questions around preceptorship would be helpful.

“…preceptor program, does that mean an orientation program for new staff?”

“…what is the definition of that preceptorship?”


“There were a lot of questions that didn’t apply to them [homecare nurses] and they weren’t sure what to answer.”

Another question on the survey asked about opportunities to participate in hospital committees.

One participant said that there were no formal committees in their organizations, therefore the

question did not apply to them. Others had a problem answering this question because, while

committees exist within their organizations, there were either no openings for new members or

the nurses had no time to spare.

Nurses also talked about the beneficial aspects of the survey in terms of how they view this

process as giving them a voice.

“…I think we want a voice and what I’m hearing is that we don’t have one.”

However, the motive and outcome of the research was questioned by a nurse who contemplated

whether their opinions were really valued or if interest in their feedback was just, “lip service.”

Another nurse wondered,

“…who’s really doing anything about this because over the years you receive so many of these

surveys and you fill them out with good intentions but we still go to work and we’re still short-

staffed and nobody listens to us.”

Receptivity and Burden of Nursing Worklife Indicator Data Collection

for Unit Managers

Unit managers were asked to provide information on the unit-related information in a survey

that related to the percentage of RNs in staff mix; percentage of full-time, part-time, and casual

nursing staff; educational background of nursing staff; experience of nursing staff employed on

the study units in the study sites; span of control of the unit manager; and unit absenteeism

rates. Managers identified that it took them between 45 minutes to 2 hours to complete. Survey

completion took longer for those managers responsible for multiple nursing units.

Similar to the nursing staff, unit managers also found the institutional-focus of the survey a

barrier for those in a homecare setting. One manager commented that the survey did not seem

applicable to all health care sectors, and expected that the community sector would have filled

out a different survey.

Comprehensiveness and Relevance of Nursing Worklife Indicator Data Collection

for Unit Managers

A few participants suggested that there was a need to look at advanced practice nurses (APN) and

how they were utilized on the unit, although there was concern that it might be difficult to

capture an APNs mandate on a survey.

“…depending on whether they have a regional mandate versus just an organizational mandate

makes a difference to their availability on the patient care areas.”

With respect to the usefulness of the information, managers felt that knowledge of the

percentage of baccalaureate nurses, use of casual staff, and breakdown of full- and part-time

staff was useful. Gathering those kinds of data made the managers more aware of their numbers.

“I think knowing how many degree nurses I have was important.”

“And it also made me look at my ratio because I’ve always strived for 70% full-time and 30% part-

time so in that sense it made me re-look at my complement, my ratio.”


Managers found some survey questions difficult to complete because the requested information

was not readily available. Some problematic areas included the percentage of baccalaureate

nurses, years of experience, nurse to patient ratios, use of casual staff, and the number of

voluntary resignations.

“I had to go to Human Resources and to our nursing staffing office to help with the years

of experience.”

“To determine the casual staff over a year in each category is…I don’t know I’d collect it all.

We don’t keep it. We don’t keep that kind of data in categories and by unit.”

Unit managers discussed some of the problems they faced in completing the survey. Several

participants described having to gather information from different computer programs to fill out

the survey.

“…one of the biggest challenges for myself in doing the questionnaire was having to go from one

program electronically to another to access some of the information.”

Other participants had to physically search for the needed information in different departments.

As one manager noted,

“I think some of us had to physically run from one building to the other to Human Resources and

to Finance to find some of the data that we needed.”

Overall, questions about part-time and casual employment numbers as well as voluntary

resignations, and number of beds was a source of difficulties for several participants.

“I also found that the last page, there was a lot of answers I had…I couldn’t get.”

In general, the survey was less challenging to fill out for those with smaller units and was more

problematic for larger units with more staff.

“It depends on how many staff you do have because it means HR has to look up the file on each

of those people.”

“My unit’s small with 20 registered staff so the information was right there. I didn’t have the

same challenges that the larger units had.”

There were four areas with inconsistent answers that needed clarification, which included data

pertaining to the length of orientation programs and educational programs offered, absenteeism

data, and information on the use of agency staff. When asked to clarify their responses around

orientation programs, most respondents stated that orientation was provided in their facilities,

and the length of orientation was based on need.

“…if the staff nurse comes and say that they need more we will give more orientation.”

“We really do try to individualize it to meet the needs.”


“And it also made me look at my ratio because I’ve always strived for 70% full-time and 30% part-time so in that sense it made me re-look at my complement, my ratio.”

Most agreed that new graduates received more orientation than experienced nurses.

“…we give a week for an RN but if they require more we give more and for new grads we’ve

done a mentorship program for about a month.”

“Also new grads are given more orientation.”

Managers were also asked about keeping track of educational programs for nurses as well as

funding for education. Most units kept track of mandatory education classes attended, such as

WHMIS and Advanced Cardiac Life Support courses.

“It’s tracked through our staff education department and it’s tracked on-line…which courses

they’ve attended because they have mandatory…WHMIS, all that are mandatory.”

“We have a binder on the unit that the nurses sort of keep track on their own unless it’s something

that’s mandatory education and then the clinical educator keeps track of that but we haven’t

gotten to the on-line part yet.”

With respect to educational funding, there was a mix of responses with some managers

commenting that course and conference registration fees were paid for, and others stating that

registration fees were not paid for.

“Registration fees are given.”

“We pay for the course cost.”

“…we were getting reimbursement from RNAO, submitting like a group of nurses’ registration fees

for the year type thing but we’re not doing that this year, they’re not doing that.”

One manager commented that time off was given for courses, however, several participants

referred to a lack of paid education days.

“We’ll accommodate their time off.”

“…but we don’t have paid education days per se.”

“We don’t have education…paid education in the budget.”

“…but they don’t get paid for their day of work so…”

To determine who had access to educational opportunities, one unit manager stated,

“If there’s a course that let’s say, for example, 10 nurses wanted to go [to] then we might draw

names out of a hat.”


“If there’s a course that let’s say, for example, 10 nurses wanted to go [to] then we might draw names out of a hat.”

Many commented that educational funding is limited as the educational budget for the unit

is divided per nurse. Managers spoke of having to divide funds allotted for education

among nurses.

“Programs have a certain amount of money budgeted, however, it’s watered down significantly

per nurse.”

“The education line budget is held with the Director and the Director has more than one program

or one area so it’s hard to even know what we have available but I know it’s not a lot and it’s

probably getting less.”

Managers were also asked to clarify their responses about the absenteeism. Several participants

stated absenteeism data was easily available and many kept track of nurse absenteeism with

attendance management programs.

“We’re very aware because of our new attendance management program that’s been

implemented.”

“It’s available on the staffing program…and it’ll break down stats-leave of absence, sick

time, WSIB, whatever.”

“And we’ve also implemented an attendance management program so the managers are

very well aware of absenteeism.”

“We have an attendance management program in [facility name] as well and that’s how we’re

keeping track of, you know, the frequent offenders.”

“…it does have an attendance awareness program on-line, which is tracked to the information that

our Occupational Health Services department provides us quarterly information so we follow up.”

Unit managers participating in the focus groups also clarified their responses around use and

tracking of agency staff. Some hospitals did not use agency nurses, while others had an in-

hospital resource pool or used casual nurses for staffing.

“[Name of organization] does not use agency nurses.”

“[Name of organization] has no agencies like that.”

“…internally we have a resource pool and that’s how we manage our staffing vacancies.”

Some units did use agency staff and agency use was tracked and accessible for managers. One

manager commented that when benefits for full-time staff were considered, the cost for agency

staff was roughly the same as for regular staff.

“[Name of organization] does use agency nurses and we can track that on our financial reports.”

“When you factor in the benefits that the full-time staff get, 14%, or what part-time staff would get

the dollar figure is approximately the same as with agency replacement.”


SUMMARY

The focus groups examined nursing personnel and unit managers’ perceptions of the data

collection process and provided a better understanding of the feasibility of gathering these data.

Specifically, focus groups provided information about the experience of completing the surveys,

comprehensiveness, feasibility, utility, and barriers and facilitators to participation. As well,

areas identified as problematic during preliminary analysis were explored in more detail.

Nurses and managers reported that while the surveys were mostly comprehensive, they were

institutionally-focused and therefore, at times, not applicable to the homecare setting. In

addition, one manager suggested that the manager survey look more specifically at the presence

and utilization of APNs. Several barriers and facilitators for completing the nurse surveys were

identified, a number of which were related to problems with physically leaving the unit. A heavy

workload, leaving colleagues to cover their patients, fewer nurses left on the unit, and having

to stay late were among the challenges discussed. The institutional focus of both the nurse and

unit manager surveys was identified as a barrier. There was also intimidation around

management having access to nurses’ responses.

Conversely, one of the facilitators identified by nurses was having a data collector who

thoroughly explained how confidentiality would be protected. Support from managers, time and

space to complete the survey, and providing refreshments were also identified as facilitators.

A number of problematic sections of the surveys were identified and explored during the focus

groups. In the nursing surveys, questions referring to nursing administrative and support staff

were not always answered because they did not exist in some organizations at the time of data

collection. Similarly, questions around opportunity for committee involvement may not have

been answered because there were either no committees in the facility, or there were no

openings on committees. Finally, the question that referred to model of care delivery was not

always answered because the model in practice was unclear in some settings.

Problematic sections in the unit manager surveys were also explored. For the most part this

related to their lack of access to key data on their units such as percentage of baccalaureate

nurses, years of experience, nurse to patient ratios, use of casual staff, and number of voluntary

resignations. There were also some areas with inconsistencies requiring clarification, including

orientation and educational programs, absenteeism, and agency use. Concern with government

access to worklife data was raised in the manager focus group, specifically related to disparity

between two sources of the same data: reports to the government and the survey data.


SIx

Chapter Six: Collection and Storage of Nursing WorklifeIndicator Data

Introduction

Feasibility of Collecting and Maintaining

Nursing Worklife Indicator Data

Summary

Nurses’ Perspectives of Nursing Worklife

Indicator Data Collection (Focus Groups)

Managers’ Perspectives of Nursing Worklife

Indicator Data Collection (Focus Groups)

Summary

51

INTRODUCTION

The fourth study objective examines the potential sources for where these data can be housed in

a database in the future. The specific research questions were: (1) What is the feasibility of

collecting nursing worklife indicator data as part of the data collected by the College of Nurses

of Ontario (CNO), the Canadian Institute for Health Information (CIHI), and the Canadian Council

on Health Services Accreditation (CCHSA), and (2) What is the feasibility of housing nursing

worklife indicator data with the CNO, CIHI, and CCHSA.

These interviews were held between July 19, 2005 and July 26, 2005. Representatives from the

CNO, CCHSA, and CIHI were interviewed separately to determine their positions on the feasibility

of their involvement in collecting, maintaining, and storing nursing worklife data. These

interviews were led by the Principal Investigator and were taped and transcribed to allow for

analysis and integration of responses. As well, information obtained from nurses and managers

during the focus groups that relates to these study objectives are also presented.

FEASIBILITY OF COLLECTING AND

MAINTAINING NURSING WORKLIFE INDICATOR DATA

(1) College of Nurses of Ontario (CNO) Perspective

The CNO is the governing body for the 140,000 RNs and RPNs in Ontario, Canada. The CNO

regulates nursing to protect the public interest and sets requirements to enter the profession,

establishes and enforces standards of nursing practice, and assures the quality of practice of the

profession and the continuing competence of nurses (CNO, 2005).

The CNO is in the process of reviewing all of the data currently collected on their annual

membership renewal form, and at the moment CNO is not considering collecting data on nursing

worklife in Ontario. There are a number of reasons for the current review of their data. First, it is

reviewed regularly, with the impetus of enhancing the accuracy of the data that is collected as

there is heavy reliance externally on CNO data. It is self-report data and thus the CNO encounters

obvious problems with individual nurses not completing the form, which leads to gaps in the

data, particularly around employment status. Second, the review is examining why and how CNO

can make the tool more user-friendly, while retaining the compulsory elements needed from a

regulatory perspective.

Challenges for Collecting Nursing Worklife Indicator Data

A number of challenges for the CNO to collect nursing worklife data were identified. When

considering the CNO strategic plan, which in part discusses bridging the practice realities for

nurses, you could make an argument for how it “fits” with the idea of collecting data on nursing

worklife in Ontario. On the other hand, the CNO’s current requirement for data and the approach

taken is to try to enhance the trust that individual nurses have in the regulator’s role. The CNO

has been actively working at meeting health human resource data planning needs in Ontario.

Moving into collecting data on nursing worklife would be an entirely new agenda for them to

consider. The CNO would have to strategically think about how or if they could meet another

data collection need. One of the challenges to be considered would be how CNO could merge

these two perspectives – nursing health human resources and worklife data collection. CNO


would need to give serious consideration to whether or not it is appropriate for them to collect

data on nursing worklife. Of particular importance is the mandate of the college, as well as

nurses’ perception of the role of the college.

A determination of whether the data being collected related to nursing worklife were mandatory

would be required. The focus of current CNO data collection as part of the renewal form is

mandatory data, not voluntary reporting of select items. If these new data elements were not

compulsory, it could lead to confusion for nurses completing the form. The rationale for

collecting these data needs to be clearly articulated. Nurses want to know what is going

to happen as a result of these data being collected and how quickly they are going to see the

difference. Otherwise, they will question the point of collecting these data. As well, this is

a very costly exercise, not just financially, but in the goodwill and the general interest that

nurses have in ensuring quality care. If the effort, time, and resources of nurses are being put

towards mandatory collection of these data, we need to ensure that it really has an impact on

quality of care.

On the contrary, if these data were compulsory, a number of new challenges would emerge.

First, a by-law change would be required. The CNO would have to look at their legislation and

determine whether regulatory bodies have the authority to make this information mandatory. It

is likely that both a regulation change as well as a by-law change would be required, as the

information currently collected by CNO is specified in the by-law. It will be important to consider

the length of time and the process that is required for legislative and by-law changes. If the

MOHLTC is convinced that there is a role within regulatory colleges to collect worklife data, it

should be explored sooner rather than later, because the Health Professions’ Regulatory Advisory

Council’s (HPRAC) consultation regarding potential changes to the Regulated Health Profession’s

Act is going on at this time. The report to the Minister is due by the end of March, 2006. It is

timely to be looking at expanding it while the legislation is opened. The minister’s current plan

is to bring legislation forward in the fall of 2006. If a legislative change is to happen after that

time, it will take substantially longer, perhaps 2009 at the earliest.

The terminology used on the CNO renewal form can also pose challenges. The CNO would have

to create definitions to ensure that everyone completing the forms understands what is meant

when they use a term. That will require substantial education for nurses prior to beginning to

collect the data, as well as re-formatting of the existing renewal form.

It is also important to consider the implicit assumptions that underpin data collection by the

CNO. It is possible that a skewed response would occur if the regulator is collecting information

about nurses’ worklife. Nurses may underrate the quality of their work environment when

reporting to the regulatory body. For example, a nurse may know that their obligation as a member

of a self-regulated profession is to meet the standards of practice. For whatever reason, they may

find themselves having difficulty meeting the standards of practice. The environment might be a

factor, but the individual nurse is then deciding how much of a factor the environment is.

From a more philosophical perspective, it is quite likely that people would challenge nursing

worklife data being collected by the CNO, even if a legislated change were made for it to become

the regulator’s role, particularly if there is any intention of linking these data to the individual


nurse and patient outcomes. A substantial barrier is the link to a unique identifier – the link to

individual nurses. This raises questions about what the data are going to be used for. For the

CNO, this concern could compromise their quality assurance program. The CNO would need to

look at the impact this would have on the College’s mandate in relation to ongoing competence.

If it were to move forward, it would be a huge initiative that would require a great deal of

planning, consultation, and external stakeholder support. The CNO could envision it as a

possibility down the road far more easily if it were aggregate data for settings, rather than data

linked to individual nurses.

Facilitators for Collecting Nursing Worklife Indicator Data

The most obvious reason for the CNO to collect data on nursing worklife is that a mechanism

already exists for them to obtain information from Ontario’s nurses on an annual basis.

Advantages can be seen in linking this data collection with registration and annual renewal.

The primary advantage is that registration is mandatory annually, and if the regulator collects

these data, it reinforces the importance of completing the data forms for nurses. If the intent

is not to have mandatory data collection for the nursing worklife data, then it probably does

not make sense to have the CNO collect these data. This does not mean that the college might

not have a role in collecting the data, but maybe it would be at a different time of the year.

As well, the CNO strategic plan serves as a facilitator with strategies aimed at bridging nurses’

practice realities and supports for nurses and employers in providing quality care in practice

settings. This linkage would be evident to the CNO College Council. This leads to some reasons

why CNO may be interested in having access to these data, even if the data were available at an

aggregate level. Whether the nursing worklife data are collected by CNO or another body, CNO

might have an interest in looking at the relationships between nursing worklife data and data it

collects through its regulatory processes, such as kinds of calls they get to their practice line in

relation to care in a particular sector, the incidence and type of complaints from the public, and

reports of termination of nurses.

If the nursing worklife data were collected and reported at a higher level of analysis than the

individual nurse, it would be easier to achieve compliance with data collection. Collecting non-

aggregate data begs the question of what is the real purpose of linking the data to the individual

nurse. The obvious conclusion for a CNO member would be that it will be used to challenge

nurses’ individual competencies. It therefore seems like the logical place to start would be at the

organization- or unit-level, to get nurses to accurately report in a manner that they feel that they

will not be incriminating themselves.

If collection of worklife data were mandatory for all regulated health professions, that would be

a facilitator. As well, support and buy-in by unions would also be a facilitator.

Frequency of Collection of Nursing Worklife Data

The CNO representatives felt that the collection of data on nurses’ worklife should definitely not

be conducted any more frequently than annually. Based on their expertise, the CNO suggested

that it would be hard to go to nurses and ask them to report on this more frequently than once a

year. While decision-makers may wish to have data on nurses’ worklife more frequently, it is not

practical. It takes considerable time to collect these data, review what is being collected, ensure


that the data being collected are the right data, and ensuring that good quality data are being

collected in an accurate manner.

Data Collection Process for Nursing Worklife Indicator Data

One of the concerns that have been identified by the advisory committee to the Hospital Report

Research Collaborative (HRRC) is the number of different data collection activities that are going

on within the province related to worklife. Institutions are saturated with these activities, and

that means that individuals are saturated too. The more data collection that we can link, the

better. Also, people would be able to see a logical connection among the data that they are

providing. The HRRC collect their data annually, so it would make sense to have some of these

new initiatives linked. Perhaps the nursing worklife indicator data could be collected through

that process.

Data Storage and Accessibility

A number of locations for data storage and access were identified by the CNO respondents.

Possible locations included the Canadian Institute for Health Information (CIHI), the Ontario

Ministry of Health and Long-term Care (MOHLTC), the HRRC, and the CNO if legislated. CIHI was

identified as an option, particularly if the data being collected involved more than just nursing

and were national, rather than just provincial data. Another option is the information

management infrastructure within the MOHLTC – the Health Results Team for Information

Management. The HRRC collaborative was previously identified as they collect annual hospital-

level data from hospitals across Ontario. Finally, the CNO could be contemplated given all of the

considerations outlined in this interview. The CNO stressed the importance of standardization of

the data collection process for these data.

The CNO suggested that there should be means and ways of having the data accessible to

researchers and decision-makers. Such systems are currently in place at the CNO and they are

exploring new ones to enhance accessibility. There are safeguards that need to be in place to

ensure privacy, a clear understanding of why the information is being obtained, what it is going

to be used for, and who it is released to. Currently the college publishes annual membership

statistics reports that are posted on the website. The CNO also handles complex research

requests regarding information not available through the report. This involves a separate request

that is submitted and processed. When data are released, it is aggregate data that cannot link

back to the individual nurse.

Costs Associated with Data Collection and Storage

A number of costs are associated with the collection of data of this nature. Many of these are

difficult to estimate. If these data were to be collected by CNO, it may be layered on to the

existing renewal forms, or it may need to be done separately. The current renewal process is a

smooth, but complicated process. There would be an additional cost involved in collecting and

processing the data because it is quite a lengthy process of reviewing and cleaning the annual

renewal form. Costs associated with collecting nursing worklife data could be based somewhat

on the annual renewal process costs, as well as this parallel process required to collect the new

worklife data. It would be that cost plus the extra burden in the first few years for data cleaning,

set up of the database, and testing. As well, it may be necessary to house the data offsite

because of space challenges, thus leading to additional costs.


(2) Canadian Council on Health Services Accreditation (CCHSA) Perspective

The mission of the CCHSA is to drive quality in health services through accreditation. To achieve

its mission, CCHSA provides health services organizations with an accreditation program based

on national standards and knowledge exchange. CCHSA has a demonstrated interest and proven

experience in data collection related to work life indicators. In March 2004, CCHSA convened a

national meeting to share information and knowledge regarding recent work in the area of work

life indicators in Canada. A significant number of meeting participants represented professional

nursing bodies from across Canada. In 2004, CCHSA and the Ontario Hospital Association (OHA)

formed a partnership to collaborate on a worklife indicators research project. The objective was

to develop and test a pulse-type survey tool that would enable health service organizations to

monitor key work life indicators.


CCHSA representatives have noted that a number of different data collection initiatives targeting

the health care workplace and worklife issues are currently underway, both nationally and

provincially. If a review of the data/information that is being collected from each of the tools

was conducted, collaboration on data collection may be possible. For example, CCHSA could

identify the information that it requires for their accreditation process. Then, once the tools

required to measure nursing worklife were identified, they may complement the accreditation

process, and CCHSA could explore whether there is a way to either synchronize or tie together

the data collection tools. As a national organization, it is important to CCHSA that any tool

developed and resulting data collected are applied nationally so that all health care

organizations benefit. Consequently if work in this area is Ontario-based, it is important for

CCHSA to be able to apply it on a broader scale so that all can benefit. While data collection on

nursing work life is profession-specific and provides vital information, worklife quality is a

concern of leaders in health care organizations across all employment and professional groups.

CCHSA has noted that it is important to pursue a measurement tool that provides a worklife

pulse relevant to multiple professions and employees.


CCHSA would be interested in nursing worklife data, regardless of which organization collects

the data. As the accreditation program evolves, CCHSA will be collecting and monitoring

organizational data on a continual basis, to provide surveyors with information about the

environment in which they will survey. This will identify specific areas upon which the surveyors

might focus. CCHSA is therefore looking at a number of priority areas and associated data

elements that would help to scope out and identify these survey target areas.

The identification of elements that need to be measured in the nursing work environment would

be important information that CCHSA would benefit from. Based on CCHSA’s leadership position

in accreditation, the Council may be well-positioned to collect nursing work environment-related

data. CCHSA’s involvement would facilitate recognition of the importance that the nursing work

environment must be attended to, and that it is an essential component of measuring quality

within health care organizations.

CCHSA recently completed a pilot test of the worklife Pulse survey, in conjunction with the

Ontario Hospital Association. The Pulse survey includes measures related to the work


environment (e.g., communication, supervision, job control); individual outcomes (e.g., perceived

job stress, self-rated overall health, job satisfaction); and organizational outcomes (e.g.,

absenteeism, presenteeism, organizational satisfaction). CCHSA is currently investigating

whether to incorporate this tool into the accreditation program. The Pulse survey would then be

available to any of its client organizations. In addition to providing the organizations’ leadership

with important information, as mentioned above, these data elements would also help CCHSA

identify target areas within organizations upon which the surveyors might focus.

Frequency of Collection of Nursing Worklife Indicator Data

From CCHSA’s perspective, it is important to collect data in a timely manner to support the

accreditation process. As a result, the timing of data collection as well as data utilization are

important issues for CCHSA to consider. Ideally, the timing for data collection should correspond

to and support the accreditation timeline and the critical issues (priority focus areas) that face

the organization. In addition, ultimately, the data must be accessible in a timely way and meet

the accreditation process requirements.

By way of example, CCHSA discussed the worklife Pulse tool and the frequency of data

collection. The Pulse survey is a simple tool that can be administered by an organization at

almost any time. At the direction of the organization’s leadership, staff could complete the

online survey from a computer within the organization or externally. To optimize its value, the

Pulse survey should be completed relatively frequently – a minimum of twice a year. This

minimum takes into consideration the rapid changes in the health care environment, and the

related issues and stressors faced by care and service providers. As improvement initiatives are

implemented, the online survey can provide “a pulse” as to the results or impact. Are initiatives

and strategies which have been implemented, having the desired impact on worklife? The tool

can therefore provide relatively rapid insight into key worklife indicators being monitored and

inform decision-making.

The simplicity of data collection may also be an important factor to consider when attempting

to identify an appropriate measurement instrument related to nursing worklife. The CCHSA-OHA

Pulse tool includes 20 measures that would inform planning and action within health care

organizations. The Pulse survey should be considered as complementary to a more comprehen-

sive employee survey. At indicated, the Pulse survey would be administered at regular intervals,

complementing a more intensive employee survey currently used annually or biannually by

health care organizations. The complementary model approach may also enable organizations to

add a limited number of specific measures (questions) to the Pulse tool in order to gather data

on a particular issue or concern that the organization is facing at that time.


As discussed above, CCHSA is supportive of an online data collection process for a worklife

survey. Nurses would be able to complete the survey from their homes or work. While access to

computers and computer knowledge can both be challenging issues, strategies can be

implemented to manage them successfully. CCHSA’s experience is that a Pulse survey

team/champion within each organization is required to facilitate and coordinate the online

survey process. It is important to communicate the objectives of the survey clearly and

consistently, and to take action based on survey results.



Collecting the nursing worklife data and maintaining it in a database is something that CCHSA

would consider. Factors such as the size of the survey, and the scope of the data collection

anticipated for the future would be important considerations. The current survey data that CCHSA

collects, not including the worklife Pulse data, is accessible to members in aggregate form. CCHSA

also produces a national health accreditation report which is released on an annual basis. This

aggregate report is widely distributed across the country, and available on the CCHSA website.

Individual client organizations can also access their own organization-specific confidential data.

Given the significant database built on survey data, CCHSA has the potential to compare sectors

across the country and produce provincial roll-up reports, as long as individual organization data

confidentiality is maintained. Similarly, CCHSA has processes and systems in place to share data

with researchers and decision-makers while protecting client confidentiality.

CCHSA suggests that a national organization is best suited to manage the worklife data collection

and storage. This would ensure consistency in data collection and storage, and would support

integrity of the overall objective. CCHSA has no concern if these data were to be collected and

housed by another national organization, provided that CCHSA has timely access to the data for

accreditation-related purposes. Data collection and storage by provincial regulatory colleges

would likely lead to data inconsistencies between the provinces, as well as challenges when

trying to aggregate the data nationally.


If CCHSA were to lead the data collection and storage processes, the associated costs would have

to be identified and long-term funding obtained. Sustainable funding would be required to

support long-term data collection and analysis so that worklife trends and patterns can be

identified and addressed across the country. The costs of collecting, analyzing, maintaining, and

storing data are important questions for any national organization considering this challenging

and exciting endeavor.

(3) Canadian Institute for Health Information (CIHI) Perspective

CIHI is an independent, pan-Canadian, not-for-profit organization working to improve the health

of Canadians and the health care system by providing quality, reliable and timely health

information (CIHI, 2005d). CIHI develops and maintains a number of health databases and

registries related to health care, including health care services, health human resources, and

health spending. This includes identifying national health indicators and conducting special

studies and analyses on key areas of interest.

CIHI has led the development of a standardized database on nursing health human resources in

Canada, and publishes nursing workforce reports annually based on these data. Most recently,

CIHI has partnered with Statistics Canada and Health Canada in undertaking a National Survey of

the Work and Health of Nurses. The survey is being administered by Statistics Canada to a

sample of registered nurses (RNs), licensed practical nurses (LPNs), and registered psychiatric

nurses from across Canada and will help to identify relationships between selected health

outcomes, the work environment, and worklife experiences. Specific topic areas include: work

history, job satisfaction, hours of work, absences from work, perception of the quality of care,

respect and support, general health, chronic conditions and work limitations, and work stress.


The one-time survey will produce a comprehensive national data set that will provide

information on the health and working conditions of nurses across Canada (CIHI, 2005d).


CIHI typically does not do primary data collection, although because of their level of existing

involvement in nursing data collection in Canada, CIHI may consider the possibility of collecting

this nursing worklife data. CIHI’s role would likely be that of the data warehouse, therefore

somebody else would need to collect the data and file it in an electronic format that is consistent

with CIHI standards.

At CIHI there is a transfer of ownership or partnership that needs to be established for the

maintenance of data. Typically, there would be an agreement between the owner and CIHI to

create a partnership that would establish the frequency of data collection, that privacy is being

respected, and how the data can be used and accessed. The time involved with this process may

be considered a challenge for data collection.

Data being collected also have to fit within the CIHI mandate, and the use and relevancy for

CIHI to house and maintain this type of database must be considered. Currently the mandate of

CIHI may be broad enough to reflect data collection on nursing worklife indicators, but this

request would need to be considered by the Board of Directors and the Chief Executive Officer

to determine if CIHI can play a role with these data. It is important to consider how these

data can be considered an important component of health information in Canada to fit with

CIHI’s mandate.

CIHI is a nationally based institute, but they do not reject data collection because it takes place

in a single province. CIHI would normally be interested in promoting it if other provinces wanted

to use the tool and provide the data back to CIHI for the development of larger reports.


The key facilitator for CIHI is that it has longstanding experience in collecting data related to

nursing human resources in Canada. Currently CIHI is also collaborating on data being collected

by Statistics Canada on the National Survey of the Work and Health of Nurses. The areas covered

in that survey are similar to those identified as key worklife indicators for nursing. Thus, CIHI is

uniquely positioned both experientially and as a data institute to manage these data and has the

system in place and the technology for such data collection. It would be necessary to adapt their

technology according to the fields and the number of records that would need to be maintained.

CIHI also has a data quality framework that is applied to all data. They have experience with

developing data quality processes for large datasets to ensure the accuracy of the information.

Essentially, when CIHI receives a file, it would go through some edit checks electronically as well

as an edit check visually. Often there is a need to go back to the owner or the sender with a few

questions, and then once the process is done and the data is considered clean, it goes into the

database where it could be queried for analytical output. After that, the data goes through CIHI’s

data quality framework where every piece of information is documented (e.g., number of surveys

sent out, response rates, changes to survey, number of questions removed or added, etc.). This

data framework guides CIHI’s interpretation of the data in any reports generated from it.


Frequency for Collection of Nursing Worklife Indicator Data

One of the key factors to consider with data collection of this nature is who the target audience

is. For decision-makers, planners, or health care professionals, they tend to want to see the

results of the data collection and have time to develop strategies around the findings. In some

cases it can take up to three years for an institution to respond. Therefore by repeating the

survey too quickly, you would not see the results expected from the application of a new policy,

new guidelines, or new procedure as a result of the previous findings. It can take four to five

years to see a change. Decision-makers always indicate the need to generate a response to the

data and to give that change time to occur. Some policies can be applied quickly, while others

take time.

In contrast, if you are looking for trends only, data collection could be conducted yearly. Caution

should be taken with annual trends data to ensure that they are not used in a negative or punitive

manner towards the institution. Annual data collection could be used more for monitoring of

worklife. This can be particularly useful at times of changes in government funding or new policy

directions that are out of the control of the institution. In these cases the yearly data collection

could give some good information – timely information. You could get the reaction to a SARS

event, for example, things that the employer cannot control.

CIHI works with a lot of stakeholders, and one of the challenges they hear is that if the tool is

changed too frequently, you lose comparability. Comparability is a key element to be considered

in order to see trends and enable accurate comparisons.


From CIHI’s perspective individual-level data collection is always better. With gathering

individual-level nursing worklife data at the place of employment there may be a sense that the

administration will have ownership of the data. If data collection were to be conducted by the

MOHLTC, responses may be reflective of government policies (i.e., cutbacks to funding), rather

than the issue being addressed in the survey. The regulatory bodies or Colleges may be most

feasible as they already have the mechanisms and processes for surveying nurses annually.


CIHI, as the premier health information data warehouse in Canada, have systems and processes

in place for data storage and access. These systems include mechanisms to ensure data

consistency and accuracy, as well as processes for accessing data by researchers and decision-

makers. This process includes preparing a statement of the project purpose or research

question, determining the data holdings from which data are needed, reviewing the relevant data

quality and privacy information, developing a list of the scope of data and data elements

required to achieve the study purpose – including a rationale for each variable requested, prior

to having initial discussion with the CIHI data contact person, and completion of a data request

and confidentiality form. CIHI provides cost estimates for these data requests.


CIHI costs related to data management would include an initial cost for the system, and then

smaller costs associated with maintenance of the system on an ongoing basis. As well, human

resources costs for data maintenance would need to be determined.


SUMMARY

All three of the stakeholder groups provide some considerations for who could be a potential

source to house the nursing worklife data in the future. Each has specific challenges that bear

deliberation. It is plausible that data collection and storage will need to be considered separately.

For example, while CIHI may be seen as a repository for storage and maintenance of these data,

they are not in the habit of conducting primary data collection. In contrast, the CNO has a

mechanism in place to survey nurses annually, yet to do so would require a change in their

mandate. Finally, CCHSA has identified an existing short Pulse tool that they are currently

testing, and suggest it could serve as a marker for when a more focused nursing worklife survey

is needed. As well, CCHSA may able to accommodate this nursing worklife survey as part of their

accreditation process.

Nurses’ Perspectives of Nursing Worklife Indicator Data Collection

(Focus Groups)

When asked about preferred methods of data collection, nurses in the focus groups discussed a

variety of options, weighing the pros and cons of completing the survey along with their nursing

registration, on-line, at home, and at work. Several nurses preferred the idea of having the data

collected along with annual renewal of their College of Nursing registration.

“If you’re already in the frame of mind of having to fill out a survey and what’s another couple of

pages when you’re already sitting down and dedicating that block of time to doing something.”

It was also suggested that the response rate would be higher if the data was collected along with

CNO registration. However, there was a concern expressed regarding anonymity.

“…if you want to reach more nurses and have everybody have a chance to do it then send it with

the registration as long as they can send it back in a separate envelope and be anonymous.”

There were also nurses who disagreed with the notion of collecting the data along with the CNO

registration. One nurse suggested that it would cause problems for nurses who tended to

procrastinate with renewing registration.

An alternative to collecting data with renewal of registration was an on-line survey. Other focus

group participants resisted on-line data collection.

“I dislike the computer.”

“I don’t get on-line often enough because my kids are always on-line.”

One nurse suggested that they be given the choice between completing the survey on-line or

with registration.


“If you’re already in the frame of mind of having to fill out a survey and what’s another couple of pages when you’re already sitting down and dedicating that block of time to doing something.”

Another debate centred on whether it was best to complete the survey at home or at work. While

some completed their nursing worklife study survey at home out of necessity (e.g., sick leave),

others chose to complete it at home because they found it “more relaxing.” Nurses talked about

how completing it at work made them feel rushed. Some questioned the accuracy of either

approach to data collection. One nurse was concerned that they may not have paid as much

attention to the survey at work as they might have if they had done it at home.

“I really felt that if we had the opportunity to take it home some of my answers would have been

maybe a bit different because I would have had more time to consider the right response.”

Another indicated that it was possible that by completing the survey at home, there would be a

failure to capture the emotions aroused in the work environment.

“…if you do it at work you’re getting an honest opinion at the time of the irritations, of the things

you like, things you don’t like. If you come home you sort of cool off and you think well maybe it

wasn’t this bad but then you go back the next day and it was that bad.”

Focus group participants were asked how often they thought the nursing worklife indicator data

should be collected. The vast majority thought that in order to fully capture changes in the

workplace, the data should be collected approximately every six months.

“… because in our society now everything is changing so fast. You can go into work one week, be

off three weeks, go back and they’ve decided to change something already. And I mean there’s just

so much change going on in our world and with our patients.”

“…my answers I would have sent in last fall would be totally different from how I would answer

the questionnaire today.”

“…depending on which provincial party’s in or if there’s a change of rules that comes down the

pipeline, you know, you can be stressed at one time of year and then things resolve and you’re less

stressed at another time of year and things happen frequently.”

“There’s a little bit more volatility in the workplace because of the changing government and

budgets and the downfall from, you know, top down kind of perspective but I think definitely

needing it at least twice a year because of that change and we need to reflect that.”

Managers’ Perspectives of Nursing Worklife Indicator Data Collection

(Focus Groups)

Managers were also asked about their preferred method of collecting nursing worklife data. Many

were happy to submit the data on-line and most preferred to be able to update changes instead

of re-entering data from the start.

“If this was somehow on-line and I could just go in and amend the data when something changed.”

“I get impatient with having to provide the same information, I would rather update information.”

“…then if we could do it and then send it back and just make any changes that would be

one option.”


“I get impatient with having to provide the same information, I would rather update information.”

Others would prefer that the survey be sent out electronically or that a central website be

created where the information would be located, only requiring periodic updates. Some

managers wanted an integrated way of collecting nursing worklife data, but there were no

specific suggestions on how to achieve this.

“…it sounds good to have an integrated way of doing it.”

Participants discussed access to the nursing worklife data, and some expressed concern over the

MOHLTC having access to the information, especially if there were inconsistencies between the

data submitted from the nursing worklife survey and information from other reports and sources.

“I guess we would have to make sure that the numbers that we were submitting to this were

consistent with what the hospital was submitting to the Ministry…numbers coming in from two

different sources don’t always match up for very, very innocent reasons…that kind of thing I found

in my experience is a bit of an alert to the Ministry where there doesn’t really need to be one.”

“We have to report that to the Ministry anyway so it’s not like they’re unaware of what our

numbers are. It might perhaps be overly emphasizing a point that some of us would rather not be

overly emphasized.”

Others were concerned about submitting data that could be misinterpreted if information was

collected at a time when the unit was in the process of reorganization or change.

“They [the Ministry] wouldn’t have any idea of the changes that were going on within an

organization that could impact our responses from one six month period or annually.”

“…in how this information was going to be used in the sense that if you were in an environment

that was evolving or changing, programs, units, or increasing the number of staff based on the

opening of beds, that would make a different flavour to answer those questions on an annual or

every six month basis for some and so it could be misleading in some way…”

SUMMARY

In terms of frequency, focus group participants recommended that nursing data should be

collected every six months to keep up with the dynamic health care environment. Nurses

discussed different methods of data collection, such as collecting data along with annual College

of Nursing registration and on-line. There was a suggestion that nurses be given a choice

between the two methods of data collection as there was some resistance to both. Managers also

expressed a preference for a system in which data could be entered one time only, and then

updated.


“…it sounds good to have an integrated way of doing it.”

se

ve

n Chapter Seven: Nursing Worklife in Ontario

Introduction

Mean Scale Scores for Work Quality Index

(WQI) by Nursing Personnel Group

Summary

Mean Scale Scores for Work Quality Index

(WQI) by Health Care Sector

Mean Scale Scores for Nursing Work Index

(NWI-R) by Health Care Sector

Conclusions

65

INTRODUCTION

Further analysis of the nursing worklife survey data was conducted to obtain an assessment

of nursing worklife in Ontario. First, the mean scores for each of the scales and subscales were

assessed. Next, differences in the mean scores for each of the nursing personnel groups and

health care sectors were explored.

MEAN SCALE SCORES FOR WORK QUALITY INDEX (WQI)

BY NURSING PERSONNEL GROUP

The WQI has seven response options ranging from “not satisfied” to “satisfied”. Overall, the mean

score for all of the nursing staff grouped together was 4.314 indicating that study participants

were neither satisfied nor dissatisfied with the quality of their work environment (see Table 24).

Table 24. Mean Score for Worklife Indicators for Nursing Personnel Groups (RN, RPN, URW) and Health Care Sectors

Long-RN RPN URW All Acute term Complex Home Overallonly only only staff care care care care care

WQI

Professional work

environment 3.819 3.686 3.520 3.745 3.475 4.013 3.511 4.261 3.745

Autonomy

of practice 5.155 4.830 4.243 4.967 4.921 4.758 4.748 5.713 4.967

Work worth to

self and others 5.030 4.922 5.073 4.996 4.960 5.002 4.920 5.208 4.996

Professional

relationships 4.735 4.565 3.845 4.619 4.480 4.599 4.588 5.081 4.619

Professional role

enactment 4.434 4.355 3.933 4.364 4.173 4.158 4.027 5.499 4.364

Benefits 3.988 3.758 3.932 3.901 3.756 4.139 3.961 3.732 3.901

Overall scale 4.392 4.237 4.008 4.314 4.163 4.440 4.215 4.809 4.314

NWI-R

Autonomy 2.192 2.270 2.385 2.238 2.374 2.254 2.330 1.850 2.238

Control over

practice setting 2.426 2.432 2.306 2.416 2.516 2.437 2.571 1.916 2.416

Nurse-physician

relationship 2.153 2.110 2.021 2.132 2.262 1.959 2.221 2.045 2.132

Organizational

support 2.287 2.240 2.307 2.275 2.405 2.239 2.355 1.962 2.275

Overall scale 2.314 2.251 2.304 2.298 2.435 2.283 2.346 1.893 2.298


Further analysis of the responses for each of the nursing personnel groups was conducted by

exploring the mean scores on the WQI overall. Table 26 demonstrates that registered nurses

had a significantly higher overall mean WQI score (x̄=4.392) than did the unregulated workers

(x̄=4.008) [t=1.989, 26 df, p <.05 one tailed] in this study. Mean scores for registered practical

nurses (x̄=4.237) were not significantly different from either the RNs or the URWs.

Some variation in the mean scores could be seen for the individual subscales (see Table 25).

The overall mean scores were highest for the “work worth to self and others” (x̄=4.996) and

“autonomy of practice” (x̄=4.967) subscales, and lowest for the “professional work environment”

(x̄=3.745) and “benefits” (x̄=3.901) subscales. RNs scored highest on all but one of the subscales

with the exception of “work worth to self and others”. In turn, RPNs scored higher than URWs on

all of the subscales with the exception of “work worth to self and others” and “benefits”. Some of

these differences in mean scores were found to be significant (see Table 26). Specifically, RNs had

a significantly higher mean score for the “professional work environment” (x̄=3.819) than URWs

(x̄=3.520) [t=2.164, 37 df, p <.05 two tailed]. In contrast, RPN mean scores were not significantly

different from either the RNs or the URWs for the “professional work environment” subscale.

RNs also had a significantly higher mean score for “autonomy of practice” (x̄=5.155) than did

the URWs in this study (x̄=4.243) [t=15.30, 44 df, p <.05 two tailed] (see Table 26). As well RNs

had a significantly higher mean score for “autonomy of practice” (x̄=5.155) than did the RPNs

(x̄=4.243) [t=9.16, 222 df, p <.05 two tailed]. Similarly, RPNs had a significantly higher mean

score for “autonomy of practice” (x̄=4.830) than did the URWs (x̄=4.243) [t=9.126, 59 df, p <.05

two tailed].

In contrast, URWs had a significantly higher mean score for “work worth to self and others”

(x̄=5.073) than did RPNs (x̄=4.922) [t=2.011, 52 df, p <.05 two tailed] (see Table 26). Also, RNs

had a significantly higher mean score for “work worth to self and others” (x̄=5.030) than did

RPNs (x̄=4.922) [t=2.396, 233 df, p-value <.05 two tailed. Mean scores for RNs and URWs were

not significantly different for the “work worth to self and others” subscale.

RNs also had a significantly higher mean score for “professional relationships” (x̄=4.735)

than did URWs (x̄=3.845) [t=4.776, 27 df, p <.05 two tailed] (see Table 26). As well, RPNs had

a significantly higher mean score for “professional relationships” (x̄=4.565) than did URWs

(x̄=3.845) [t=3.672, 33 df, p-value <.05 two tailed]. Mean scores for RNs and RPNs were not

significantly different for the “professional relationships” subscale.

RNs also had a significantly higher mean score for “professional role enactment” (x̄=4.434) than

URWs (x̄=3.933) [t=2.54, 44 df, p <.05 two tailed] (see Table 26). As well, RPNs had a significantly

higher mean score for “professional role enactment” (x̄=4.355) than URWs (x̄=3.933) [t=2.105,

47 df, p-value <.06 two tailed]. Mean scores for RNs and RPNs were not significantly different for

the “professional role enactment” subscale.

RNs had significantly higher mean scores for “benefits” (x̄=3.988) than RPNs (x̄=3.758) [t=4.29,

270 df, p <.05 two tailed] (see Table 25). Mean scores between RPNs and URWs as well as RNs and

URWs were not significantly different for the “benefits” subscale.


Table 25. Work Quality Index Mean Score Differences Between Nursing Personnel Groups (RN, RPN, and URW)

WQI x̄ SD N

Professional work environment RN 3.819 .60 237

URW 3.520 .75 32

t = 2.164*, df = 1,37

Autonomy of practice RN 5.155 .29 247

URW 4.243 .34 37

t = 15.30*, df = 1,44

RN 5.155 .28 247

RPN 4.830 .34 128

t = 9.16*, df = 1,222

RPN 4.830 .34 128

URW 4.243 .34 37

t = 9.126*, df = 1,59

Work worth to self and others RN 5.030 .39 230

RPN 4.922 .34 128

t = 2.396*, df = 1,233

URW 5.073 .36 31

RPN 4.922 .34 128

t = 2.011*, df = 1,52

Professional relationships RN 4.735 .68 241

URW 3.845 .90 25

t = 4.776*, df = 1,27

RPN 4.565 .80 114

URW 3.845 .90 25

t = 3.672*, df = 1,33

Professional role enactment RN 4.434 1.18 250

URW 3.933 1.04 33

t = 2.54*, df = 1,44

RPN 4.355 .94 130

URW 3.933 1.04 33

t = 2.105*, df = 1,47

Benefits RN 3.988 .49 236

RPN 3.758 .48 128

t = 4.29*, df = 1,270

Overall RN 4.392 .79 195

URW 4.008 .86 22

t = 1.989*, df = 1,27

*P <0.05


Mean Scale Scores for the Nursing Work Index (NWI-R)

by Nursing Personnel Group

The NWI-R has four response options ranging from “strongly agree” to “strongly disagree”.

Table 25 demonstrates that overall, the mean score for all of the nursing staff grouped together

was 2.298 indicating that study participants reported some presence of the key work

environment factors in their work settings (i.e., autonomy, control over practice setting, nurse-

physician relationships and organizational support). Further analysis of the responses for each

of the nursing personnel groups was conducted by exploring the mean scores on the NWI-R

overall. No significant differences were found between the overall mean scores for RNs

(x̄=2.314), RPNs (x̄=2.251) and URWs (x̄=2.304; see Table 25).

RNs had a significantly lower mean score on the “autonomy” subscale (x̄=2.192) than URWs

(x̄=2.385) [t=11.038, 55 df, p <.05 two tailed] (see Table 27). RNs also had a significantly lower

mean score on the “autonomy” subscale (x̄=2.192) than RPNs (x̄=2.270) [t=4.567, 186 df, p <.05

two tailed]. As well, RPNs had a significantly lower mean score for “autonomy” (x̄=2.270) than

did the URWs (x̄=2.385) [t=5149, 117 df, p <.05 two tailed].

There were no significant differences in mean scores for the “control over practice” subscale

between the three nursing personnel groups in this study.

RNs had a significantly higher mean score on the “nurse-physician relationship” subscale

(x̄=2.153) than RPNs (x̄=2.110) [t=4.035, 352 df, p <.05 two tailed] (see Table 27). RNs also had

a significantly higher mean score on the “nurse-physician relationship” subscale (x̄=2.153) than

did the URWs (x̄=2.021) [t=5.429, 44 df, p <.05 two tailed]. Finally, RPNs had a significantly

higher mean score on the “nurse-physician relationship” subscale (x̄=2.110) than URWs (x̄=2.021)

[t=3.893, 34 df, p <.05 two tailed].

RNs had a significantly higher mean score for “organizational support” (x̄=2.287) than RPNs

(x̄=2.240) [t=1.961, 334 df, p <.05 two tailed] (see Table 26). Mean scores between RNs and

URWs and between RPNs and URWs were not significantly different for the “organizational

support” subscale.


Table 26. Nursing Work Index Mean Score Differences Between Nursing Personnel Groups (RN, RPN, and URW)

NWI-R x̄ SD N

Autonomy RN 2.192 .11 243

URW 2.385 .10 39

t = 11.038*, df = 1,55

RN 2.192 .11 243

RPN 2.270 .18 132

t = 4.567*, df = 1,186

RPN 2.270 .18 132

URW 2.385 .10 39

t = 5.149*, df = 1,117

Nurse-physician relationship RN 2.153 .15 253

RPN 2.110 .05 133

t = 4.035*, df = 1,352

RN 2.153 .15 253

URW 2.021 .13 32

t = 5.429*, df = 1,44

RPN 2.110 .05 133

URW 2.021 .13 32

t = 3.893*, df = 1,34

Organizational support RN 2.287 .26 242

RPN 2.240 .19 128

t = 1.961*, df = 1,334

*P <0.05

SUMMARY

Work Quality Index

RNs in this study had significantly higher overall perceptions of the quality of their work and

work environment than URWs. Specifically, RNs held higher perceptions of the professional work

environment, autonomy of practice, professional relationships and professional role enactment

than URWs. As well, RNs had higher perceptions of autonomy of practice, work worth to self and

others, and benefits than RPNs in this study.

RPNs in this study had higher perceptions of autonomy of practice, professional relationships,

and professional role enactment than URWs. In contrast, URWs held a higher perception of their

work worth to self and others than RPNs in this study.


Nursing Work Index-Revised

No substantial differences between the nursing personnel groups were noted overall for the NWI-R.

RNs had lower scale scores for autonomy, which indicates that they have higher perceptions of

autonomy than URWs or RPNs. As well, RNs had higher perceptions of the nurse-physician role

than either RPNs or URWs, and higher perceptions of organizational support than RPNs.

RPNs had lower scale scores for autonomy than URWs, indicating that they have higher levels

of autonomy. As well, RPNs identified higher perceptions of the nurse-physician relationship

than URWs.

MEAN SCALE SCORES FOR WORK QUALITY INDEX (WQI)

BY HEALTH CARE SECTOR

Table 27 demonstrates that homecare nurses had a significantly higher overall mean WQI score

(x̄=4.809) than acute care nurses (4.163) [t=3.258, 47 df, p <.05] and complex continuing care

nurses (x̄=4.215) [t=2.925, 51 df, p <.05]. As well, long-term care nurses had a significantly

higher overall mean WQI score (x̄=4.440) than acute care nurses (x̄=4.163) [t=2.568, 194 df,

p-value <.05].

Homecare nurses had significantly higher mean scores on the “professional work environment”

subscale (x̄=4.261) than acute care nurses in this study (x̄=3.475) [t=5.557, 73 df, p <.05] as well

as complex continuing care nurses (x̄=3.511) [t=4.961, 92 df, p <.05] (see Table 28). Long-term

care nurses had significantly higher mean scores on the “professional work environment”

subscale (x̄=4.013) than complex continuing care nurses (x̄=3.511) [t=5.773, 173 df, p <.05] and

acute care nurses (x̄=3.475) [t=7.838, 229 df, p <.05].

Homecare nurses had significantly higher mean scores on the “autonomy of practice” subscale

(x̄=5.713) than acute care nurses in this study (x̄=4.921) [t=18.459, 115 df, p <.05], as well as

complex continuing care nurses (4.748) [t=17.842, 162 df, p <.05), and long-term care nursing

staff (x̄=4.758) [t=20.436, 145 df, p <.05]. In contrast, acute care nurses had significantly higher

mean scores on the “autonomy of practice” subscale (x̄=4.921) than complex continuing care

nurses (x̄=4.748) [t=3.919, 144 df, p <.05] and long-term care nursing staff (x̄=4.758) [t=5.548,

264 df, p <.05].

Long-term care nurses had significantly higher mean scores on “work worth to self and others”

(x̄=5.002) than complex continuing care nursing staff (x̄=4.92) [t=2.249, 193 df, p <.05].


Table 27. Work Quality Index Mean Score Differences Between Health Care Sectors

WQI x̄ SD N

Professional work environment Home 4.261 1.02 59

Acute 3.475 .53 130

t = 5.557*, df = 1,73

Home 4.261 1.02 59

Complex 3.511 .69 94

t = 4.961*, df = 1,92

Long-term 4.013 .52 106

Complex 3.511 .69 94

t = 5.773*, df = 1,173

Long-term 4.013 .52 106

Acute 3.475 .53 130

t = 7.838*, df = 1,229

Autonomy of practice Home 5.713 .32 71

Acute 4.921 .24 132

t = 18.459*, df = 1,115

Home 5.713 .32 71

Complex 4.748 .38 93

t = 17.842*, df = 1,162

Home 5.713 .32 71

Long-term 4.758 .30 120

t = 20.436*, df = 1,145

Acute 4.921 .24 132

Complex 4.748 .38 93

t = 3.919*, df = 1,144

Acute 4.921 .24 132

Long-term 4.758 .30 120

t = 5.548*, df = 1,264

Work worth to self and others Long-term 5.002 .29 105

Complex 4.92 .22 91

t = 2.249*, df = 1,193

Professional relationships Home 5.081 .65 57

Acute 4.480 .79 135

t = 6.389*, df = 1,130

Home 5.081 .65 57

Complex 4.588 .80 91

t = 4.111*, df = 1,139

Home 5.081 .65 57

Long-term 4.599 .66 100

t = 4.449*, df = 1,120


Continued

WQI x̄ SD N

Professional role enactment Home 5.499 .70 73

Acute 4.173 1.34 135

t = 9.349*, df = 1,208

Home 5.499 .70 73

Complex 4.027 1.09 95

t = 10.633*, df = 1,163

Home 5.499 .70 73

Long-term 4.158 1.09 114

t = 10.268*, df = 1,187

Benefits Complex 3.961 .53 95

Home 3.732 .65 68

t = 2.400* df = 1,127

Long-term 4.139 .68 110

Home 3.732 .65 68

t = 4.003*, df = 1,149

Long-term 4.139 .68 110

Complex 3.961 .53 95

t = 2.114*, df = 1,203

Complex 3.961 .53 95

Acute 3.756 .41 126

t = 3.147*, df = 1,173

Long-term 4.139 .68 110

Acute 3.756 .41 126

t = 5.174*, df = 1,175

Overall Home 4.809 1.00 34

Acute 4.163 .85 115

t = 3.258*, df = 1,47

Home 4.809 1.00 34

Complex 4.215 .81 79

t = 2.925*, df = 1,51

Long-term 4.440 .66 81

Acute 4.163 .85 115

t = 2.568*, df = 1,194

*P <0.05

Homecare nurses had significantly higher mean scores on the “professional relationships”

subscale (x̄=5.081) than acute care nurses in this study (x̄=4.480) [t=6.389, 130 df, p <.05] as

well as complex continuing care nurses (x̄=4.588) [t=4.111, 139 df, p <.05], and long-term care

nurses (x̄=4.599) [t=4.449, 120 df, p <.05].


Homecare nurses had significantly higher mean scores on the “professional role enactment”

subscale (x̄=5.499) than acute care nurses in this study (x̄=4.173) [t=9.349, 208 df, p <.05] as

well as complex continuing care nurses (x̄=4.027) [t=10.63, 163 df, p <.05], and long-term care

nurses (x̄=4.158) [t=10.26, 187 df, p <.05].

Complex continuing care nurses had significantly higher mean scores on the “benefits” subscale

(x̄=3.961) than homecare nurses (x̄=3.732) [t=2.400, 127 df, p <.05] and acute care nurses

(x̄=3.756) [t=3.147, 173 df, p <.05]. As well, long-term care nurses had significantly higher mean

scores on the “benefits” scale (x̄=4.139) than homecare nurses (x̄=3.732) [t=4.003, 149 df,

p <.05], complex continuing care nurses (x̄=3.961) [t=2.114, 203 df, p <.05], and acute care

nursing staff (x̄=3.756) [t=5.174, 175 df, p <.05].

MEAN SCALE SCORES FOR NURSING WORK INDEX (NWI-R)

BY HEALTH CARE SECTOR

Table 28 demonstrates that homecare nurses had a significantly lower overall mean NWI-R score

(x̄=1.89) than acute care nurses (x̄=2.44) [t=10.036, 94 df, p <.05], complex continuing care

nurses (x̄=2.34) [t=7.621, 103 df, p <.05] and long-term care nurses (x̄=2.28) [t=6.869, 99 df,

p-value <.05]. As well, long-term care nurses had a significantly lower overall mean NWI-R

score(x̄=2.28) than acute care nurses (x̄=2.43) [t=3.057, 170 df, p <.05].

For the specific subscales, home care nurses also had significantly lower mean scores on the

“autonomy” subscale (x̄=1.85) than acute care nurses (x̄=2.37) [t=27.778, 202 df, p <.05], complex

continuing care nurses (x̄=2.33) [t=21.774, 151 df, p <.05], and long-term care nurses (x̄=2.257)

[t=23.889, 187 df, p <.05] (see Table 28). As well, long-term care nurses had significantly lower

mean scores on the “autonomy” subscale (x̄=2.25) than complex continuing care nurses (x̄=2.33)

[t=3.327, 174 df, p <.05] and acute care nurses (x̄=2.37) [t=6.063, 244 df, p <.05].

Home care nurses also had significantly lower mean scores on the “control over practice”

subscale (x̄=1.92) than acute care nurses (x̄=2.52) [t=12.476, 136 df, p <.05], complex continuing

care nurses (x̄=2.57) [t=14.539, 111 df, p <.05], and long-term care nurses (x̄=2.437) [t=9.971,

155 df, p <.05] (see Table 29). As well, long-term care nurses had significantly lower mean scores

on the “control over practice” subscale (x̄=2.44) than complex continuing care nurses (x̄=2.57)

[t=3.067, 196 df, p <.05].

Home care nurses also had significantly lower mean scores on the “nurse-physician relationship”


care nurses (x̄=2.22) [t=10.479, 117 df, p <.05], and significantly higher than long-term care

nurses (x̄=1.96) [t=8.001, 168 df, p <.05] (see Table 29). As well, complex continuing care nurses

had significantly higher mean scores on the “nurse-physician relationship” subscale (x̄=2.04)

than long-term care nurses (x̄=1.96) [t=14.135, 161 df, p <.05]. Finally, acute care nurses had

significantly higher mean scores on the “nurse-physician relationship” subscale (x̄=2.26) than

long-term care nurses (x̄=1.96) [t=18.122, 231 df, p <.05].


Home care nurses also had significantly lower mean scores on the “organizational support”


care nurses (x̄=2.36) [t=10.943, 145 df, p <.05], and long-term care nurses (x̄=2.24) [t=6.707,

172 df, p <.05] (see Table 29). As well, complex continuing care nurses had significantly higher

mean scores on the “organizational support” subscale (x̄=2.36) than long-term care nurses

(x̄=2.24) [t=2.985, 194 df, p <.05]. Finally, acute care nurses had significantly higher mean

scores on the “organizational support” subscale (x̄=2.41) than long-term care nurses (x̄=2.24)

[t=4.340, 204 df, p <.05].

Table 28. Nursing Work Index Mean Score Differences Between Health Care Sectors

NWI-R x̄ SD N

Autonomy Home 1.85 .09 72

Acute 2.37 .17 130

t = 27.778*, df = 1,202

Home 1.85 .09 72

Complex 2.33 .19 97

t = 21.774*, df = 1,151

Home 1.85 .09 72

Long-term 2.25 .14 118

t = 23.889*, df = 1,187

Long-term 2.25 .14 118

Complex 2.33 .19 97

t = 3.327*, df = 174

Long-term 2.25 .14 118

Acute 2.37 .17 130

t = 6.063*, df = 1,244

Control over practice Home 1.92 .29 61

Acute 2.52 .34 133

t = 12.476*, df = 1,136

Home 1.92 .29 61

Complex 2.57 .24 96

t = 14.539*, df = 1,111

Home 1.92 .29 61

Long-term 2.44 .39 115

t = 9.971*, df = 1,155

Long-term 2.44 .39 115

Complex 2.57 .24 96

t = 3.067*, df = 1,196


Continued

NWI-R x̄ SD N

Nurse-physician relationship Home 2.04 .04 74

Acute 2.26 .16 136

t = 14.694*, df = 1,170

Home 2.04 .04 74

Complex 2.22 .16 98

t = 10.479*, df = 1,117

Home 2.04 .04 74

Long-term 1.96 .10 113

t = 8.001*, df = 1,168

Complex 2.22 .16 98

Long-term 1.96 .10 113

t = 14.135*, df = 1,161

Acute 2.26 .16 136

Long-term 1.96 .10 113

t = 18.122*, df = 1,231

Organizational support Home 1.96 .22 66

Acute 2.40 .26 132

t = 12.567*, df = 1,151

Home 1.96 .22 66

Complex 2.36 .23 95

t = 10.943*, df = 1,145

Home 1.96 .22 66

Long-term 2.24 .32 108

t = 6.707*, df = 1,172

Complex 2.36 .23 95

Long-term 2.24 .32 108

t = 2.985*, df = 1,194

Acute 2.40 .27 132

Long-term 2.24 .32 108

t = 4.340*, df = 1,204

Overall Home 1.89 .28 42

Acute 2.44 .34 108

t = 10.036*, df = 1.94

Home 1.89 .28 42

Complex 2.35 .34 70

t = 7.621*, df = 1,103

Home 1.89 .28 42

Long-term 2.28 .33 77

t = 6.869*, df = 1,99

Long-term 2.28 .33 77

Acute 2.44 .34 108

t = 3.057*, df = 1,170

*P <0.05


CONCLUSIONS

Nursing Personnel Groups

From the perspective of individual nursing personnel groups, the WQI appears to tap moredimensions of the nursing work environment that are relevant to different care provider groupsthan the NWI-R in this study. Overall, the NWI-R appeared to discriminate less between theprovider groups in this study.

Health Care Sectors

From the perspective of the different health care sectors, both instruments appear todiscriminate between the sector groups well. Home care nurses had higher perceptions of thework environment overall and on most of the subscales for both instruments.


eIG

HT

Chapter Eight: Abstracting and Linking Nursing WorklifeIndicator DataIntroduction

Unit-Manager Data

Summary

79

INTRODUCTION

The fifth study objective examines the feasibility of abstracting and linking nursing worklife

indicator data to other datasets (e.g., outcomes). The specific research questions were: (1) What

is the feasibility of abstracting nursing worklife indicator data? and (2) What are the issues

associated with abstracting and linking nursing worklife indicator data to data from different

databases, such as Management Information Systems (MIS), Canadian Institute for Health

Information (CIHI), and across settings?

Data were collected using two mechanisms to test these linkages. First, unit managers for each of

the study units were asked to provide unit-level data on the nurse structural variables –

percentage of registered nurses in staff mix; percentage of full-time, part-time, and casual nursing

staff; educational background of nursing staff; experience of nursing staff employed on the study

units in the study sites; span of control of the unit manager; unit absenteeism rates; nursing

overtime hours; and agency staff hours. These data elements were used in a unit-level analysis of

the data. As well, secondary data on the secondary data structural variables – nursing hours per

weighted case/RUG weighted patient day; nursing overtime hours; agency staff hours;

absenteeism hours; and workload/productivity (i.e., direct patient care) was also sought from the

organization’s management information system database, the Ontario Hospital Reporting System

(OHRS) at one point in time for fiscal year 2004/2005, for the acute care and complex continuing

care sites in this study. However, data provided for this secondary analysis were not available at

the level of the patient care unit rather they are provided only at the aggregate level of functional

centre, which is comprised of a grouping of units in a program. Thus, the data analysis using

secondary analysis could not be conducted, as the units of measurement were not consistent.

The results presented for the linkage are based on primary data obtained from unit managers.

Unit-Manager Data

The unit manager data were analyzed to determine if relationships existed between any of the

unit-level nursing structural variables and the overall WQI and NWI-R scores for each of the

health care sectors in this study.

Acute Care

A statistically significant positive relationship was found between overall NWI-R scores and span

of control (rho=.25, p=.00*) in acute care (see Table 29). This indicates that the higher the span

of control of the unit manager, the higher unit staff nurses responses on the overall NWI-R.

Higher scores on the NWI-R indicate that nurses are not satisfied with the level or presence of

specific factors in their work environment including autonomy, control over the work

environment, relationships with physicians and organizational supports. As well, a statistically

significant positive relationship was noted between the overall NWI-R and RN absenteeism rates

(rho=.51, p=.08**), suggesting that the higher RN absenteeism, the greater dissatisfaction with

the quality of the nursing work environment. Finally, a statistically significant positive

relationship was found between the nurse-to-patient ratio on the day (rho=.48, p=.06**) and

night shifts (rho=.47, p=.07**) and overall NWI-R scores, suggesting that nurses on units where

the nurse-to-patient ratio was highest on these shifts, reported higher dissatisfaction with the

quality of the work environment.


Similarly, a statistically significant relationship was noted between overall WQI scores and span

of control (rho = -.19, p = .03*) in acute care. This suggests that the lower the span control of the

unit manager the higher the level of satisfaction reported by unit nurses with the quality of their

work and work environment. High scores on the WQI indicate greater satisfaction with the

professional work environment, autonomy, work worth, professional relationships, role

enactment and benefits.

Complex Continuing Care

A statistically significant positive relationship was noted between the overall NWI-R scores and

overall nursing experience (rho=.25, p=.01*) and experience in the present role (rho=.25, p=.01*),

suggesting that nurses with more years of experience indicated greater dissatisfaction with the

quality of the nursing work environment. As well, a statistically significant positive relationship

was noted between the overall NWI-R scores and RPN absenteeism rates (rho=.49, p=.09**),

suggesting that the higher RPN absenteeism, the greater unit nurses dissatisfaction with the

quality of the nursing work environment. Finally, a statistically significant positive relationship

was found between the nurse-to-patient ratio on the day (rho=.46, p=.10**) and evening shift

(rho=.49, p=.08**) and overall NWI-R scores, suggesting that nurses reported higher dissatisfaction

with the quality of the work environment on units with higher nurse-to-patient ratios.

A statistically significant positive relationship was noted between the overall WQI scores and

nursing education (rho=.25, p=.01*), indicating that the higher the level of education of nurses

on the unit, the higher the level of satisfaction reported with the quality of their work and work

environment. As well, a statistically significant negative relationship was noted between the

overall WQI scores and overall nursing experience (rho=-.24, p=.02*) and experience in the

present role (rho=-.26, p=.01*), suggesting that less experienced nurses reported the highest

level of satisfaction with the quality of the nursing work environment. Finally, a statistically

significant negative relationship was noted between the nurse-to-patient ratio on the day

(rho=-.48, p=.08**) and night shifts (rho=-.59, p=.03*) suggesting that the higher the nurse-to-

patient ratio on these shifts, the lower nurses satisfaction with the work and work environment.

Long-term Care

A statistically significant positive relationship was found between overall NWI-R scores and span

of control (rho=.22, p=.01*) in long-term care, indicating that the higher the span of control of

the unit manager, the greater the dissatisfaction with the quality of the nursing work environment.

A statistically significant positive relationship was noted between the overall WQI scores and the

percentage of RNs employed on the unit (rho=.55, p=.03*), indicating that the higher the

percentage of RNs on the unit, the higher the level of satisfaction reported by unit nurses with

the quality of their work and work environment. As well, a statistically significant positive

relationship was noted between the overall WQI scores and nursing education (rho=.18, p=.04*),

indicating that the higher the level of education of nurses on the unit, the higher the level of

satisfaction reported with the quality of their work and work environment. A statistically

significant negative relationship was noted between the overall WQI scores and experience in the

present role (rho=-.15, p=.10*), suggesting that less experienced nurses reported the highest

level of satisfaction with the quality of the nursing work environment.


Home Care


nursing education (rho=.28, p=.02*) suggesting that home care nurses with the highest level of

education indicated greater dissatisfaction with the quality of the nursing work environment.

Overall


nurses experience in the present role (rho=.17, p=.00*), suggesting that nurses with the largest

amount of experience indicated greater dissatisfaction with the quality of the nursing work

environment. A statistically significant positive relationship was found between overall NWI-R

scores and span of control (rho=.26, p=.00*), indicating that the higher the span of control of

the unit manager the greater overall nurses dissatisfaction with the quality of the nursing work

environment. Finally, a statistically significant positive relationship was noted between the

overall NWI-R scores and the number of hours nurses worked per week (rho=.09, p=.06**),

suggesting that the more nurses work each week the greater their dissatisfaction with the quality

of their work and work environment.

A statistically significant positive relationship was noted between the overall WQI scores and

nursing education (rho=.14, p=.01*) indicating that the higher the level of education of nurses

on the study units, the higher the level of satisfaction reported with the quality of their work

and work environment. A statistically significant negative relationship was noted between the

overall WQI scores and experience in the present role (rho=-.13, p=.01*), suggesting that overall

in this study, less experienced nurses reported the highest level of satisfaction with the quality

of the nursing work environment.

SUMMARY

The results from the unit-level analysis are fairly consistent across both of the nursing work

environment instruments. Several of the study variables of interest that had emerged from the

original review of the literature were found to be related to the nursing work environment

measures across sectors. These include span of control of the unit manager, absenteeism, nurse-

to-patient ratios, experience, and education. As well, in long-term care, the percentage of RN

staffing was also identified.



Table 29: Correlations for Unit-Level Nursing and Unit Structural Variables

Complex

Acute care continuing care Home care Long-term care Overall care

NWI-R WQI NWI-R WQI NWI-R WQI NWI-R WQI NWI-R WQI

rho(p) rho(p) rho(p) rho(p) rho(p) rho(p) rho(p) rho(p) rho(p) rho(p)

Nurse Structural Variables

Percent Registered

Nurse -.31(.24) -.21(.44) -.21(.46) .44(.12) -.22(.78) .89(.11) -.34(.20) .55(.03)* -.02(.92) .23(.12)

Percent Full Time -.05(.86) -.38(.21) -.20(.56) -.15(.67) -.19(.81) .50(.50) -.25(.41) -.07(.82) -.10(.54) -08(.61)

Percent Part Time -.12(.71) .43(.14) -.35(.29) .45(.17) -.19(.81) .49(.51) -.27(.37) -.47(.11) -.14(.39) -.08(.62)

Percent Casual .13(.67) -.43(.15) .48(.13) -.26(.44) .19(.81) -.50(.50) .33(.28) .37(.22) .14(.38) .10(.55)

Education .01(.96) .05(.57) -.16(.11) .25(.01)* .28(.02)* -.10(.38) .07(.45) .18(.04)* .05(.28) .14(.01)*

Experience

Years employed

in nursing -.01(.87) .08(.38) .25(.01)* -.24(.02)* .08(.47) -.03(.83) .08(.36) .05(.62) .08(.11) -.01(.79)

Years employed

in present role .02(.84) .07(.42) .25(.01)* -.26(.01)* .05(.70) -.04(.75) .05(.55) -.15(.10)• .17(.00)* -.13(.01)*

Span of Control .25(.00)* -.19(.03)* .09(.40) .09(.37) -.01(.96) .05(.68) .22(.01)* -.07(.47) .26(.00)* -.08(.10)

Absenteeism

RN .51(.08)• .24(.43) .44(.14) -.23(.45) + + -.45(.27) .06(.88) -.12(.49) .13(.45)

RPN .01(.99) -.53(.47) .49(.09)† -.30(.32) + + -.04(.93) -.07(.87) -.04(.85) -.11(.57)

URW .79(.42) -.46(.70) .50(.67) .08(.95) + + -.24(.54) .13(.75) -.20(.47) .12(.67)

Unit Structural Variables

Nursing hours

worked per week .07(.42) .07(.42) .15(.16) -.07(.53) -.12(.33) .00(.99) .08(.40) -.05(.57) .09(.06)• -.02(.62)

OT -.06(.68) .12(.42) .20(.36) -.20(.37) .22(.26) -.32(.10) -.28(.18) .24(.28) -.04(.67) -.01(.93)

Agency

RN + + .11(.84) -.09(.87) + + -.21(.62) .32(.45) -.01(.97) .01(.96)

RPN + + -.47(.35) .59(.21) + + -.42(.30) -.23(.58) -.27(.35) .00(1.00)

URW + + -.24(.84) -.35(.77) + + .31(.42) -.09(.82) .05(.87) .03(.92)

Workload/productivity: Nurse-Patient Ratio:

Day .48(.06)• .29(.28) .46(.10)• .-48(.08)• + + -.12(.65) .27(.30) .04(.77) .21(.15)

Evening .08(.77) .17(.53) .49(.08)• .43(.13) + + .16(.53) -.22(.40) .10(.50) -.04(.77)

Night .47(.07)• .42(.11) .45(.11) -.59(.03)* + + -.12(.66) .06(.82) -.17(.26) .12(.42)

nIn

e Chapter Nine: Discussion andConclusions Introduction

Quality of Nursing Worklife Indicator Data

A Snapshot of Nursing Worklife in Ontario

Conclusions

85

INTRODUCTION

The primary purpose of this study was to evaluate the feasibility, quality, and utility of

instituting data collection for nursing worklife indicators in acute care, long-term care, complex

continuing care, and homecare settings in Ontario, Canada. A second purpose was to examine

the potential for linkage of these data to the clinical outcomes data collected in similar settings

as part of the Health Outcomes for Better Information and Care initiative (formerly the Nursing

and Health Outcomes Study). A third purpose was to make recommendations regarding potential

sources for where these data can be housed in a database in the future.

The study was conducted in a total of 65 patient care units in 20 health care facilities, of which 5

were acute care, 7 were long-term care, 4 were complex continuing care, and 4 were homecare

settings across the province. The sample comprised a total of 451 nursing personnel (i.e., RNs,

RPNs, and URWs) in these facilities, with approximately 30% of responses coming from acute

care, 29% from long-term care, 23% from complex continuing care, and 18% from homecare

nursing staff. Approximately 57% of respondents were RNs, 31% were RPNs, and 10% were URWs.

All 53 unit managers on the study units participated in the study.

QUALITY OF NURSING WORKLIFE INDICATOR DATA

Reliability of Data Collected

The Cronbach’s alpha measure for scale reliability was very high for both the Work Quality Index

and the Nursing Work Index-Revised indicating that both instruments are stable, and the

questions being asked in these surveys elicit consistent and reliable responses. There were no

appreciable differences between the scale reliabilities for RNs, RPNs, or URWs with respect to

either the WQI or the NWI-R overall scales. There were also no notable differences between acute

care, long-term care, complex continuing care, and homecare with respect to either the WQI or

the NWI-R Cronbach’s alpha scores. Thus, the reliability of both instruments is relatively

consistent across the different nursing work groups and health care sectors that participated in

this study. These results imply that overall, there were no substantial differences between the

WQI and NWI-R scale reliabilities. However, the NWI-R instrument tended to have lower alpha

scores than the WQI instrument for the majority of the subscales, within all health care sectors.

As well, within the NWI-R subscales, the homecare sector appears to have lower alpha values

than the other sectors, for three out of four NWI-R subscales.

Completion Rate

In general, the WQI seemed to fare better than the NWI-R instrument in terms of completion rate.

RNs appeared to have the most ease of completion, followed by RPNs and URWs. These findings

are not surprising as the instruments were both originally developed for use with RN populations.

It is plausible that the instruments may be tapping facets of nursing practice that are not central

to the RPN or URW role, or perhaps are of less interest to nursing personnel in those roles. When

examined by sector, the number of homecare participants who completed every scale question

was much lower than the other sectors for both instruments, suggesting that the instruments are

best suited for hospital settings, and may not be feasible for homecare practice. This corresponds


to the findings reported in the focus groups, where homecare and long-term care nursing

personnel suggested the instruments were reflective of acute care nursing work environments.

There does not seem to be overwhelming evidence to suggest that one instrument is superior

to the other. Both appear to be fairly reliable and consistent, although some specific sectors

(i.e., homecare) and nursing personnel groups (i.e., URWs) experienced difficulties relating to

some of the questions. Thus, consideration should be given to adapting the language of these

measures to specific health care sectors (i.e., long-term care, homecare) to accurately capture

their unique work environments.

Receptivity and Burden of Nursing Worklife Indicator Data Collection

Focus groups were held with nursing personnel (i.e., RN, RPN, and URW) and unit managers to

explore the feasibility and utility issues related to nursing worklife data collection from across

the different health care sectors. Nursing personnel in this study identified that it took between

15 to 30 minutes to complete the nursing worklife indicators survey, and identified that it was

relatively straightforward. Nurses’ receptivity towards nursing worklife data collection and

assessments of the burden associated with it related primarily to whether there were supports

in place to permit them to complete the survey in their work environment. While a few nurses

denied any barriers to this data collection existed, a number identified that time available to

complete the worklife indicators survey was a potential impediment. Participants identified a

number of factors that facilitated their participation.

Comprehensiveness and Relevance of Nursing Worklife Indicator Data

Some challenges were encountered with obtaining accurate and comparable data from the unit

managers in this study. For example, managers were asked to provide data on the average

number of days annually that they used agency nursing staff as replacement staff. These data

were not available by managers from all settings, and the data quality when provided was

questionable. Most nursing staff participants reported that the survey was comprehensive,

although there were some difficulties identified by homecare nurses who were completing the

survey. The relevance of specific items for homecare nursing practice was questioned. As well,

some participants identified concern with the relevance of the questions to their practice

settings. Managers identified that it took them between 45 minutes to 2 hours to complete the

unit manager survey, particularly for those managers responsible for multiple nursing units.

One of the concerns identified by managers was the lack of necessary data to complete the

questionnaire. Problematic sections in the unit manager surveys were also identified. For the

most part this related to their lack of access to key data on their units such as percentage of

baccalaureate nurses, years of experience, nurse-to-patient ratios, use of casual staff, and

number of voluntary resignations. There were also some areas with inconsistencies requiring

clarification, including orientation and educational programs, absenteeism, and agency use.

Collection, Storage, and Management of Nursing Worklife Data

Representatives from the College of Nurses of Ontario, CCHSA, and CIHI were interviewed to

determine the feasibility of their involvement in collecting, maintaining, and storing nursing

worklife data. As well, this information was also sought from nurses and managers during the

focus groups. All three of the stakeholder groups provided some considerations for who could


be a potential source to house the nursing worklife data in the future. Each has specific

challenges that bear consideration. It is plausible that data collection and storage will need to be

considered separately. For example, while CIHI may be seen as a repository for storage and

maintenance of these data, they are not in the habit of conducting primary data collection.

Despite this, they have considerable experience in the management of large administrative

datasets, and the systems and processes necessary to determine data reliability and consistency.

In contrast, the CNO has a mailing mechanism in place to contact Ontario regulated nursing

personnel annually, yet to add on a worklife survey would require a change in their mandate.

While there may be a “fit” with their strategic plan, the CNO would need to consider their role as

a regulatory body prior to making this decision. Finally, CCHSA has identified an existing short

Pulse tool that they are currently testing, and suggest it could serve as a marker for when a more

focused nursing worklife survey is needed. Thus, they have an identified interest and are leading

some work in this area across the country. CCHSA may be able to accommodate this nursing

worklife survey as part of their accreditation process in the future, although the frequency of

administration of this survey would need to be assessed. All three groups have mechanisms in

place to provide access to such data in an anonymized ethical manner. Further work is required

prior to a decision being made on the location and storage of these data in the future.

Linking Nursing Worklife Data to Clinical Outcomes

The feasibility of abstracting and linking nursing worklife indicator data to other datasets and

the issues associated with this abstraction and linkage were examined in this study. Data for the

nursing worklife indicators were obtained at the nursing unit level in this study. Complementary

data from study units were obtained from the Management Information System (MIS) as part of

the Ontario Hospital Reporting System (OHRS) for the acute care and complex continuing care

settings in this study. These are the only sectors where data currently exist that could be used

for data linkage. However, the data available from the OHRS is available only at the level of the

functional centre, which can include several patient care units in the aggregate data. At the

current time, there is no method for clearly breaking out the aggregate functional centre data

from the OHRS dataset to the level of the patient care unit, thus this analysis could not be

conducted in this study. This is a concern that needs to be addressed in the future to enable

these data to be useful to health care leaders, decision-makers, policy makers, and researchers.

Similar data elements were also obtained from unit managers in the study in an effort to explore

these linkages. As noted earlier, this process was quite burdensome and time-intensive for unit

managers, requiring them to seek out data sources that were not readily accessible to them. It is

evident that this process is not a viable approach to use in the future. Despite this, the data

obtained from unit managers provided some important information about the consistency and

relevance of several of the nursing worklife indicators examined in this study. Specifically, several

of the study variables of interest that had emerged from the original review of the literature were

found to be related to the nursing work environment measures across sectors. These include span

of control of the unit manager, absenteeism, nurse-to-patient ratios, experience, and education.

As well, in long-term care, the percentage of RN staffing was also linked to higher work

environment perceptions.


A SNAPSHOT OF NURSING WORKLIFE IN ONTARIO

When considering the Work Quality Index, RNs in this study had significantly higher overall

perceptions of the quality of their work and work environment than URWs – higher perceptions

of the professional work environment, autonomy of practice, professional relationships, and

professional role enactment; and higher perceptions of autonomy of practice, work worth to self

and others, and benefits than RPNs in this study. RPNs in this study had higher perceptions of

autonomy of practice, professional relationships, and professional role enactment than URWs.

In contrast, URWs held a higher perception of their work worth to self and others than RPNs in

this study.

No substantial differences between the nursing personnel groups were noted overall for the NWI-R.

RNs had lower scale scores for autonomy, which indicates that they have higher perceptions of

autonomy than URWs or RPNs. As well, RNs had higher perceptions of the nurse-physician role

than either RPNs or URWs, and higher perceptions of organizational support than RPNs. RPNs had

lower scale scores for autonomy than URWs, indicating that they have higher levels of autonomy.

As well, RPNs identified higher perceptions of the nurse-physician relationship than URWs.

CONCLUSIONS

From the perspective of individual nursing personnel groups, the WQI appears to tap more

dimensions of the nursing work environment that are relevant to different care provider groups

than the NWI-R in this study. Overall, the NWI-R appeared to discriminate less between the

provider groups in this study. From the perspective of the different health care sectors, both

instruments appear to discriminate between the sector groups well. Homecare nurses had

higher perceptions of the work environment overall and on most of the subscales of both of

the instruments.


Appendix A

SEMI-STRUCTURED INTERVIEW PARTICIPANTS

SSI # 1

July 19, 2005

College of Nurses of Ontario

Anne Coghlan, Executive Director

Margaret Poon, Manager, Information Management

SSI # 2

July 21, 2005

Francine Anne Roy

SSI # 3

July 26, 2005

Wendy Nicklin


References Advisory Committee on Health Human Resources. The Nursing Strategy for Canada, Report of

the Advisory Committee on Health Human Resources, Retrieved from the WWW on April 14, 2003,

(http://www.hc-sc.gc.ca/english/pdf/nursing.pdf), 2000.

Advisory Committee on Health Human Resources. Our Health, Our Future – Creating Quality

Workplaces for Canadian Nurses, Final Report of the Canadian Nursing Advisory Committee,

Retrieved from the WWW on April 14, 2003, (http://www.hc-sc.gc.ca/english/for_you/nursing/

cnac_report/index.html), 2002.

Aiken, L. H., & Patrician, P. A. (2000). Measuring organizational traits of hospitals: The revised

nursing work index. Nursing Research, 49(3), 146-153.

Canadian Council on Health Services Accreditation (CCHSA). (2004). Worklife Indicators Research

Project. Ottawa, ON: Health Canada.

Canadian Institute for Health Information (CIHI; 2005a). Workforce Trends of Registered Nurses

in Canada, 2004. Retrieved on October 26, 2005 from http://secure.cihi.ca/cihiweb/products/

Workforce_RN_2004_e.pdf

Canadian Institute for Health Information (CIHI; 2005b). Workforce Trends of Licensed Practical

Nurses in Canada, 2004. Retrieved on October 29, 2005 from http://secure.cihi.ca/cihiweb/

products/Workforce_LPN_2004_e.pdf

Canadian Institute for Health Information (CIHI; 2005c). Workforce Trends of Regulated Nurses

in Canada, 2004. (CD-ROM ISBN # 1-55392-711-7). Ottawa, ON: Author.

Canadian Institute for Health Information (CIHI). (2005d, August 29). CIHI – Taking health

information further. Retrieved November 26, 2005, from http://secure.cihi.ca/cihiweb/

dispPage.jsp?cw_page=profile_e

College of Nurses of Ontario. (2005, January 25). CNO’s Mission and Vision. Retrieved November

26, 2005, from http://www.cno.org/about/mission.html

McGillis Hall, L., Irvine, D., Baker, G.R., Pink, G., Sidani, S., O’Brien Pallas, L., & Donner, G. (2001).

A Study of the Impact of Nursing Staff Mix Models & Organizational Change Strategies on Patient,

System & Caregiver Outcomes. Final report submitted to Canadian Health Services Research

Foundation, February, 2001.

McGillis Hall, L. (2005). Quality Work Environments for Nurse and Patient Safety. Sudbury, MA:

Jones and Bartlett Publications.


Ministry of Health and Long-term Care. (n.d.). 2005 Nursing Health Outcomes Project: Project

background. Retrieved August 4, 2005, from http://www.health.gov.on.ca/english/providers/

project/nursing/background.html

Ward, T. J. & Clark, H. T. (1991). A reexamination of public versus private school achievement:

the case for missing data. Journal of Educational Research, 84 (3), 153-163.

Whitley, MP., & Putzier, D. ( 1994) Measuring nurses’ satisfaction with the quality of their work

and work environment. Journal of Nursing Care Quality, 8(3), 43-51.


Faculty of NursingUniversity of Toronto155 College StreetToronto, Ontario M5T 1P8

www.nursing.utoronto.ca

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Linda McGillis Hall, RN, PhDDiane Doran, RN, PhD Linda O’Brien Pallas, PhD Joan Tranmer, RN, PhD Deborah Tregunno, RN, PhD Ellen Rukholm, RN, PhD Donna Thomson, RN, MBA Leah Pink, RN, MNJessica Peterson, RN, PhD StudentErin Johnston, RN, MN StudentAmy Palma, RN, BScN

Funded by The Ontario Ministry of Health & Long-Term Care

MARCH 2006


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