Empowering Educators to be Innovators

706.721.7839 EII@gru.edu

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Jefferson Scale of Lifelong Learning-Health Professions Version (JeffSLL-HSP)

Malorie Kosht Novak, PT, Ph.D., DPT, Christie Lancaster Palladino, MD, MSc,

Brittany Layne Ange, MS, Deborah South Richardson, Ph.D.

Department of Physical Therapy and Educational Innovation Institute

Georgia Regents University, Augusta, Georgia

DESCRIPTION

DEVELOPMENT

THE JEFFSLL-HPS APPLICATION

CONCLUSIONS

REFERENCES

The Jefferson Scale of Lifelong Learning-Health

Professions Students Version (JeffSLL-HPS), an

adaptation of the Jefferson Scale of Lifelong

Learning-Medical Students Version (JeffSPLL-MS)1

is an instrument that measures health professions

students‟ (HPS) orientation toward lifelong learning

(LLL). It has 14 items with response options

presented along a 4-point Likert scale (1= strongly

disagree; 4 = strongly agree). Higher JeffSLL-HPS

scores indicate a greater orientation toward lifelong

learning. The instrument may be administered

electronically or on paper.

The JeffSPLL-MS1 was modified for use with HPS

across different disciplines. Cognitive interviews

were used to assess content validity. 180 senior

students in dental hygiene, dental medicine,

medicine, nursing, occupational therapy, physician

assistant, physical therapy, and respiratory therapy

completed the JeffSLL-HPS (out of 502 students

approached). Confirmatory factor analysis (CFA)

revealed a three-factor solution consistent with that

of the JeffSPLL-MS.1 The factors are named

“learning beliefs and motivation,” “skills in seeking

information,” and “attention to learning

opportunities.”1 Internal consistency for scores on

each of the three factors ranged from .62 -.78. CFA

of the subgroup of medical students yielded results

similar to those reported above, suggesting that the

JeffSLL-HPS may be appropriate to use with this

group. Students answered using the full range of

responses for each item on the JeffSLL-HPS,

suggesting that social desirability was not a major

factor in item response. We received IRB approval

for this study.

JeffSPLL-MS Compared to JeffSLL-HPS

Statistic JeffSPLL-MS1

(N = 652)

JeffSLL-HPS

(N = 180)

Total Mean Score 43.52 43.06

Standard

Deviation 4.65 5.50

Range 27 - 56 26 – 56

Cronbach's Alpha .77 .85

Our work with the JeffSLL-HPS demonstrates an

internal structure consistent with that of the

JeffSPLL-MS1 and suggests that the JeffSLL-HPS

may be used as a reliable assessment of orientation

toward LLL in students from multiple healthcare

disciplines. We are conducting longitudinal research

with the instrument to study whether students‟

orientation toward LLL changes over time. Future

research should investigate additional forms of

validity evidence for scores on the JeffSLL-HPS and

whether scores on self-report measures of LLL

translate into behavior change and educational

outcomes. Additional research could also explore

whether the JeffSLL-HPS could be used to assess

the effectiveness of specific activities implemented

in a curriculum geared toward facilitating LLL.

ACKNOWLEDEGEMENT

Jefferson Scale of Lifelong Learning (JeffSLL- Health Professions Student Version)

Instructions: Please indicate the extent of your agreement with each of

the following statements by circling the appropriate number.

1. Searching for the answer to a question is, in and by itself, rewarding. ............................ 1 2 3 4 2. Lifelong learning is a professional responsibility of all healthcare providers .................... 1 2 3 4 3. I enjoy reading articles in which issues of healthcare/medicine are discussed ................ 1 2 3 4 4. I routinely attend student study groups. .......................................................................... 1 2 3 4 5. I read healthcare/medical literature in journals, websites or textbooks at least once every week............................................................................................................. 1 2 3 4 6. I routinely search electronic resources to find out about new developments in healthcare/medicine. ...................................................................................................... 1 2 3 4 7. I believe that I would fall behind if I stopped learning about new developments in healthcare/medicine. ................................................................................................... 1 2 3 4 8. One of the important goals of health professions‟ education is to develop students‟ lifelong learning skills ...................................................................................................... 1 2 3 4 9. Rapid changes in health science/medicine require constant updating of knowledge and development of new professional skills. ................................................................... 1 2 3 4 10. I always make time for learning on my own, even when I have a busy class schedule and other obligations. ...................................................................................... 1 2 3 4 11. I recognize my need to constantly acquire new professional knowledge. ........................ 1 2 3 4 12. I routinely attend optional sessions, such as professional meetings, guest lectures, or clinics where I can volunteer to improve my knowledge and clinical skills ....................... 1 2 3 4 13. I take every opportunity to gain new knowledge/skills that are important to my discipline. .................................................................................................................. 1 2 3 4 14. My preferred approach in finding an answer to a question is to consult a credible resource such as a textbook or electronic resource. ....................................................... 1 2 3 4

© 2007 Jefferson Medical College. All rights reserved. Adapted with permission for administration to health professions students at Georgia Regents University.

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We wish to thank Mohammadreza Hojat, Ph.D. of

Jefferson Medical College for his consultation and

permission to adapt the JeffSPLL-MS.

1. Wetzel AP, Mazmanian PE, Hojat M, et al. Measuring medical

students„ orientation toward lifelong learning: a psychometric

evaluation. Acad Med. 2012;85(10):S41-S44.

2. Slavin MD. Teaching evidence-based practice in physical

therapy: critical competencies and necessary conditions. JOPTE

2004;18(3):4-11.

We confirmed that in our sample, the JeffSLL-HPS

replicated the structure of the JeffSPLL-MS.1 This

tool may be valuable for faculty and administrators in

health professions programs to assess their goal of

meeting accreditation standards, the effects of

curricular design and teaching strategies on LLL,2

and student attitudes toward LLL.2

Assessing Health Professions Students’ Orientation Toward Lifelong Learning

Malorie Kosht Novak, PT, Ph.D., DPT, Christie Lancaster Palladino, MD, MSc,

Brittany Layne Ange, MS, Deborah South Richardson, Ph.D.

Department of Physical Therapy and Educational Innovation Institute

Georgia Regents University, Augusta, Georgia

REFERENCE

INTRODUCTION

PURPOSE

METHODS

RESULTS DISCUSSION

CONCLUSION

REFERENCES

Lifelong learning is considered an

element of professionalism in many

disciplines,1 and accreditation

standards for healthcare

professions education require an

emphasis on lifelong learning

(LLL). However,

tools to assess LLL in healthcare

professions students (HPS) are

lacking,2 thus making it difficult to

assess whether these standards

have been met.

Health Professions Students’ Orientation

Toward Lifelong Learning

To examine the psychometric

properties of an adaptation of the

Jefferson Scale of Physician

Lifelong Learning- Medical

Students Version (JeffSPLL-MS)3

that was designed to assess LLL in

HPS (JeffSLL-HPS)

The JeffSPLL-MS was modified for

use with HPS across different

disciplines and administered to

students in their last year of study.

180/502 (35.9%) students

representing all programs

responded with useable surveys.

We received IRB approval for this

study.

1. Arnold L. Assessing professional behavior: yesterday, today, and

tomorrow. Acad Med. 2002;77:502-515.

2. Slavin MD. Teaching evidence-based practice in physical therapy:

critical competencies and necessary conditions. JOPTE.

2004,18(3):4-11.

3. Wetzel AP, Mazmanian PE, Hojat M, et al. Measuring medical

students' orientation toward lifelong learning: a psychometric evaluation. Acad Med. 2012;85(10):S41-S44.

College Program N/Total (%) Completed*

Allied Health

Sciences

Dental Hygiene 6/23 (26%)

Occupational

Therapy 11/39 (28%)

Physician Assistant 18/37 (49%)

Physical Therapy 24/33 (73%)

Respiratory Therapy 6/22 (9%)

Dental Medicine Dental Medicine 14/67 (21%)

Medical College of

Georgia Medicine 80/201 (40%)

Nursing Nursing 18/80 (23%)

*Three survey respondents did not indicate their program; we included their data in the

analyses.

JeffSPLL-MS3 Compared to JeffSLL-HPS

Statistic JeffSPLL-MS

(N = 652)3

JeffSLL-HPS

(N = 180)

Total Mean Score 43.52 43.06

Standard

Deviation 4.65 5.50

Range 27 - 56 26 – 56

Cronbach's Alpha .77 .85

Confirmatory factor analysis revealed a

three-factor structure for the JeffSPLL-HPS

that was consistent with the JeffSPLL-MS.3

The factors are named “learning beliefs and

motivation,” “skills in seeking information,”

and “attention to learning opportunities.”3

The JeffSLL-HPS may be valuable

to

use in healthcare professions

programs to assess compliance

with

accreditation criteria regarding LLL,

effects of curricular design and

teaching strategies on LLL,2 and

student attitudes toward LLL.2

The internal structure of responses

of the JeffSLL-HPS is consistent

with the JeffSPLL-MS. As

healthcare professions education

becomes more interdisciplinary, it

is important to have tools to assess

elements of professionalism, such

as LLL, across disciplines. The

JeffSLL-HPS is currently being

used in a longitudinal study to

assess changes in orientation

toward LLL in Doctor of Physical

Therapy students from

matriculation to graduation.

How Do Engineering Majors Perform in the Pre-Clinical Years of Medical School Compared to Their Peers?

Brittany Ange, MS; Andria Thomas, PhD; and Paul Wallach, MD Medical College of Georgia at Georgia Regents University

Evaluation Services

• An Analysis of Covariance (ANCOVA) was calculated to determine the effect of undergraduate major on pre-clinical grade point average (GPA) after adjusting for undergraduate GPA.

• Similarly, ANCOVAs were performed to determine the effect of undergraduate major on Year 1 GPA and Year 2 GPA separately after adjusting for undergraduate GPA.

• Students matriculate into medical school with varying undergraduate degrees and diverse backgrounds.

• An increasing number of students have degrees other than the traditional basic sciences.

• The curriculum of an undergraduate degree is designed with an emphasis on problem solving skills development. Thus, anecdotal evidence suggest that medical students with engineering degrees may struggle in the pre-clinical curriculum (first two years) of medical school.

• The purpose of this study was to examine how medical students with an undergraduate engineering degree perform in the first two years of medical school compared to their peers.

• ANCOVA results showed that the overall F-test was significant (p<.0001) indicating that either undergraduate GPA, major, or both had an effect on pre-clinical GPA.

• The p-value for major was not statistically significant (p=0.622) and the p-value for undergraduate GPA was statistically significant (p<.0001).

• Hence, after adjusting for undergraduate GPA, there was not a statistically significant difference among pre-clinical GPA across the categories of majors used in this study.

• Secondary analyses assessing year 1 and year 2 GPA separately yielded similar results. There was not a statistically significant difference among Year 1 GPA (p=0.348) or Year 2 GPA (p=0.395) across majors after adjusting for undergraduate GPA.

• These results suggest that engineering majors do not perform differently from non-engineering majors in their pre-clinical performance in total.

• This study also revealed that, overall, engineering majors do not perform differently from their peers during the first or second year of medical school.

• This information is useful for: • Medical school admissions offices as they seek to determine the best performance indicators of medical school. • Undergraduate engineering programs as they advocate for the usefulness and applicability of their programs for future medical students.

• Future research will seek to examine if these results hold during the clinical component of their medical education.

Major Category MCAT Mean (SD)

UGPA Mean (SD)

Year 1 GPA Mean (SD)

Year 2 GPA Mean (SD)

Pre-Clinical GPA Mean (SD)

Engineering 31.3 (2.5) 3.6 (0.2) 3.4 (0.4) 3.5 (0.4) 3.4 (0.4)

Non-Eng. Science 30.4 (3.0) 3.7 (0.2) 3.3 (0.5) 3.5 (0.5) 3.4 (0.4)

Other 30.2 (3.1) 3.7 (0.2) 3.4 (0.4) 3.5 (0.4) 3.4 (0.4)

• Students in the Classes of 2011 – 2014 (n=721) were included.

• Undergraduate major was categorized as follows: engineering (n=56), non-engineering science (n=538), and other (n=127).

PROCESS ORIENTED GUIDED INQUIRY LEARNING: A NATURAL FIT FOR OCCUPATIONAL THERAPY EDUCATION

Evidence based practice (EBP) is the use of research, experience, and client/student

factors in the provision of health care and education. Learning and employing EBP

requires critical thinking and evaluation skills. Students learn best when they are actively

engaged in learning cycles of exploration, concept invention, and application.

David Hanson and colleagues, funded by the National Science Foundation, developed

Process-Oriented Guided-Inquiry Learning (POGIL) to enhance science education and

address the observed weaknesses of both lecture-based and problem-based learning.

Specifically, lecture-based learning is passive, solitary, and limits responsibility for learning.

Problem based learning has the weaknesses of 1) expecting content to be learned by

novices who may not recognize important content and 2) requiring extensive facilitation to

ensure that the problem-solving progresses effectively to desired outcomes (Gallow;

Problem-Based Learning).

POGILs were developed to facilitate the skills of information processing, critical and

analytical thinking, problem solving, communication, teamwork, management, and

assessment (Hanson, 2006). This strategy has been adapted in a variety of non-core

science areas, such as marketing, healthcare, and humanities (Hale & Mullen, 2009).

Evidence Based Practice was taught in the first semester of the Occupational Therapy Program for

6 years using a traditional lecture-based format. During that time both instructors and students were

dissatisfied with the course. To address this dissatisfaction and to increase active learning, we

implemented POGIL strategies in the Fall of 2010 (1x/week for 3 hours) and continued in Fall 2011

and 2012 (2x/week for 1 ½ hours). We developed 12 modules on topics including: an introduction to

evidence based practice, asking clinical questions, searching for evidence, the structure and use of

scientific writing, APA formatting, levels of evidence, and appraising evidence from descriptive,

quasi-experimental, RCTs, systematic reviews, and qualitative studies.

Each class had pre-assigned readings. In 2010 new groups were established weekly at the

beginning of each class; in 2011 and 2012 students remained in the same group throughout the

semester. POGIL sessions would begin with the distribution of the packets. Students were expected

to work through the instructions, moving from the basic content to the applied experiences by the

end of the session.

Over the course of the semesters, faculty‟s belief that the use of POGIL was an effective teaching

strategy was reinforced through observation of the active engagement and written reflections from

the students. Implementation in the second and third years was enhanced due to better structuring

of the activities; a clear introduction of the benefits of the process on the first day of class; and

clearer grading guidelines than during the first year.

The summary points listed in the next column would assist other faculty in using this method.

Gallow, D. What is Problem-based Learning? Problem-based Learning Faculty

Institute, University of California, Irvine. Retrieved 3/21/13 from

http://www.pbl.uci.edu/whatispbl.html

Hale, D., & Mullen, L.G. (2009). Designing process-oriented guided-inquiry activities:

A new innovation for marketing class.

Hanson, D.M. (2006). Instructor‟s guide to process-oriented guided-inquiry learning.

Lisle, IL: Pacific Crest

Problem-based learning. Learning Theories.com retrieved 3/21/13 from

http://www.learning-theories.com/problem-based-learning-pbl.html

Preparing, Planning & Developing It is important to experience and study the POGIL method before implementing

Faculty need to be creative and write clear task instructions

Development requires appreciable initial time and familiarity with format Foster identification of essential elements of learning through graphics

Introducing benefits of this learning method to promote student buy-in is critical

Challenges

Student‟s inexperience with critique and reflection

Student‟s perception of teaching/learning: “I feel like I have to teach myself. I pay you to

teach me.”

Environment not consistently conducive to small group work

Process is multifactorial, thus difficult to draw causal relationships.

Examining effectiveness of teaching strategy requires additional measures Advantages Some students preferred this format to “Death by PowerPoint”

Format appealed to adult preferences for active learning

Self-assessment of knowledge trended higher across the semester

Suggested group size is 3-5 students with specific roles assigned to each member per

session:

Manager: Manages the group; time-keeper; ensures participation in roles; interfaces with

facilitator

Recorder: Records names/roles of group; note-taker

Presenter: Presents concise oral reports to class

Reflector: Observes/comments on the group‟s performance

Additional roles might include Technician, Encourager, Fact Checker.

POGILs can be employed as an adjunct or supplement to lectures, or as the primary method

of teaching/learning with some supplemental mini-lectures. Written materials guide the

process of the session, with in-class facilitation available. Presentations of group work and

discussion clarify content. Sessions end with shared critical thinking questions.

POGIL activities are done in structured, collaborative small groups. They

follow a defined Learning Cycle:

Lynn Jaffe, ScD, OTR/L; Robert Gibson, PhD, MSOTR/L; Mariana D’Amico, EdD, OTR/L, BCP

College of Allied Health Sciences at Georgia Regents University, Augusta, Georgia

POGIL FORMAT DESCRIPTION

OBJECTIVES 1. Describe POGIL, the collaborative learning format used in the Evidence-Based

Practice class

2. Discuss pros and cons of using POGIL format with graduate students

Overall, an increase in course satisfaction was evident between 2010 and 2011, but

remained static in 2012. Comments and ratings revealed there is still room for improvement.

Some students suggested having more explicit directions for the assignments and more

mini-lectures before doing the active learning.

Student self-reports on knowledge and skill development were comparable both years,

showing statistically significant improvement across the semester.

Student comments were more positive in 2011 & 2012 than in 2010. Examples:

“I think the POGILS were a good way of helping us to retain the information.” 2010

“It was interesting that when it came to the tests I felt like I knew the information well

because we had worked with the information so much in class.” 2011

“Prepared us to be better researchers. Group activities allowed us to work on collaboration

and team work.” 2011

“Having groups in class to work on assignments was a strength because it helped students

learn more by seeing other student's thought processes.” 2011

“…It also helped with teaching me how to operate effectively within a group.” 2011 “All of the hands on work was useful in learning the material.” 2012

BACKGROUND COURSE DESCRIPTION

SELECTED REFERENCES

CLASS OUTCOMES

SUMMARY POINTS

The IPE Journal at GRU Lori Anderson, Michael Brands, Miriam Cortez-Cooper, Matthew Diamond, Mahmood Mozaffari, Barbara Russell

.

Student Explanations for Declining Participation in an Educational Survey: A Qualitative Analysis

Lara Stepleman, Abbey Valvano, & Lauren Penwell-Waines

Educational Innovation Institute (EII), Georgia Regents University (GRU), Augusta, GA

Online administration of educational surveys is a common method for collecting critical health professions student data; yet, poor response rates frequently limit the utility and generalizability of findings.

Although numerous studies have explored approaches to increasing survey response, we know less about the motivations of students choosing not to participate.

Objective: To thematically describe anonymous, optional written feedback from health professions students declining participation in an online survey study about sexual health competencies.

Participants: 178 health professions students providing a written explanation for opting-out of an online survey regarding training issues in sexual health

Approximately 1600 health professions students

received survey

683 acknowledged receipt of survey

496 at least partially completed

187 requested to opt-out

178 provided written explanations

Explanations were independently analyzed by three raters using tenets of grounded theory. Our iterative analysis yielded six themes.

Background

Methods

Conclusions

This study contributes to our knowledge about the contextual factors related to health professions students’ decisions to decline participation in educational survey research, especially around a topic perceived to be sensitive.

Both survey characteristics and the characteristics of those completing the survey should be considered when optimizing the instrument and survey procedures for maximum response.

Opt out responses are unique, informative data that researchers may consider collecting when feasible to provide additional context to their results.

Limitations: Demographics for the opt-out sample are unknown, precluding additional analyses regarding characteristics of those who provided opt-out feedback.

Results

Table 1. Themes of opt-out explanations

We would like to acknowledge the GRU EII for their financial support toward the completion of this project.

MAJOR THEMES EXEMPLAR QUOTES n (%)

Survey Structure Length, unsure how to answer item as worded

“Too long”

“Some of the questions are impossible to answer accurately.”

45 (25)

Time “MCG raised my tuition, I have to work to make an extra 1000 per semester. No time for surveys.”

33 (18)

Content Relevancy Not seen as relevant, important, interesting or applicable

“As a dental student, we rarely deal with sexual health.”

“It doesn’t apply to me.”

28 (15)

Content Sensitivity Disclosure concerns, discomfort

“I do not wish to share this kind of information freely, even if anonymous.”

“I do not feel comfortable taking a survey on this

topic.”

20 (11)

Personal Competency Not enough experience with sexual health topics, perceived competence in sexual health training

“I do not feel I am adequately educated about sexual health”

“I feel comfortable discussing sexual health with my patients and feel like I approach it in a non-

threatening and non-judgmental way.”

19 (10)

Personal Attributes Religion, marital status, sexual activity

“Personal” “Not sexually active” “Religious reasons”

“I am married”

10 (5)

Figure 1. Model of opt-out response themes

N = 182 total codes (16 responses were given more than 1 code)

28 responses did not contribute to a meaningful theme or were too vague (e.g., “Choose not to respond”) and were included in an “Other” category.

10 nonsensical responses were excluded from thematic analyses.