administration and scoring manual for the k-state problem identification rating scales: k-pirs...
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K-PIRS 1
ADMINISTRATION AND SCORING MANUAL FOR
THE K-STATE PROBLEM IDENTIFICATION RATING SCALES:
K-PIRS™ & K-PIRS FORM B™
John M. Robertson
with contributions from
Fred B. Newton, Eunhee Kim, Stephen L. Benton,
Ronald G. Downey, Sheryl A. Benton, and Patricia A. Marsh
The K-PIRS is a self-report intake screening instrument that provides information on four
types of client variables: demographics, clinical symptoms, readiness to change, and degree of
interference with academic and social functioning.
K-PIRS Form B is an outcome instrument that tracks symptom change across time. It
measures changes in goal achievement, symptom reduction, decision-making, problem-solving,
overall health and well-being, stress management, and relationship functioning.
K-PIRS
2
2006 Edition
Copyright 2006 by Kansas State University Research Foundation
Used under license and published by Kansas State University Comprehensive Assessment Tools
(K-CAT™), a virtual non-profit corporation, Kansas State University, Manhattan, Kansas.
All rights reserved. No part of this publication may be reproduced or transmitted in any form or
by any means, electronic or mechanical, including photocopy, recording, or any information
storage and retrieval system, without permission from the publisher.
Kansas State University Comprehensive Assessment Tools (K-CAT™) is a registered trademark
of Kansas State University, Manhattan, Kansas.
Published in the United States of America
K-PIRS
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Acknowledgments
The author of this manual acknowledges the assistance of those who contributed to the
development of the K-PIRS: the investigators who contributed materially to the set of studies
that produced this instrument (see Robertson, Benton, Newton, Downey, Marsh, Benton, Tseng,
& Shin, 2006); the 21 mental health professionals and pre-doctoral interns who provided both
clinical expertise and technical assistance; the college students who participated in focus groups;
the staff who provided clerical support; and the experimenters who collected data for the cross-
validation study. Of particular help during the item development stage were William Arck, Jr.,
Lia Boedman, Aaron H. Carlstrom, Alexander B. Cohen, Dorothy M. Farrand, Ann L. Johnson,
Dorinda J. Lambert, Jeana L. Magyar-Moe, Barbara A. Pearson, Art Rathbun, Mary Todd, Dan
Wilcox, and Joyce A. Woodford.
Correspondence concerning this manual should be sent to Fred B. Newton, Director,
Counseling Services, 232 ECS Building, Kansas State University, Manhattan, KS 66506. E-mail:
K-PIRS
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Contents
Chapter 1 Development .............................................................................................8
Purpose...................................................................................................8
Overview................................................................................................8
Item Development..................................................................................9
Data Collection Procedures..................................................................12
Chapter 2 Administration and Scoring.................................................................13
Appropriate Uses .................................................................................13
User Qualifications ..............................................................................13
Testing Conditions ...............................................................................14
Scoring Procedures ..............................................................................14
Chapter 3 Interpretation of Results .......................................................................17
Clinical Information.............................................................................17
Form B: Client Outcome Measure.......................................................19
Cluster Analysis ...................................................................................21
Chapter 4 Psychometric Information ....................................................................24
Samples ................................................................................................24
Exploratory Factor Analysis ................................................................28
Confirmatory Factor Analysis..............................................................30
Reliability.............................................................................................31
Internal Consistency.............................................................................32
Temporal Stability ..............................................................................33
K-PIRS
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Content Validity...................................................................................34
Construct Validity................................................................................35
Discriminant Validity...........................................................................39
Convergent Validity.............................................................................40
Chapter 5 Conclusions.............................................................................................41
Summary ..............................................................................................41
Future Research ...................................................................................41
Limitations ...........................................................................................43
References ..............................................................................................................45
Tables ..............................................................................................................50
Figures ..............................................................................................................76
Appendixes ..............................................................................................................87
K-PIRS
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Tables
Table 1 Means and Standard Deviations for the K-PIRS Clinical Scales, Global Concern
Scale, and Interference Items for the Normative Sample of College
Undergraduates (N = 1,716)
Table 2 T-Score Conversion Table for the K-PIRS Normative Sample of College
Undergraduates (N = 1,716)
Table 3 Means and Standard Deviations for SOS Items (Significant Other Situations) in
the K-PIRS Normative Sample of College Undergraduates (N = 1,716)
Table 4 Reduction in Clinical Symptoms between Intake and Session Three, as Measured
by the K-PIRS Form B
Table 5 Cluster Analysis for the K-PIRS: Means and Standard Deviations for Factor
Scores across Clusters
Table 6 Promax Rotated Pattern Matrix of Exploratory Factor Analysis of the K-PIRS
Table 7 K-PIRS Component Factor Correlation Matrix for the Oblique Solution
Table 8 Overall Fit Indices for the Seven Components of the K-PIRS
Table 9 Means, Standard Deviations, Standard Errors of Measurement, and Cronbach
Alpha Reliabilities With 95% Confidence Intervals for K-PIRS Symptom Variable
Raw Scores in a Normative Sample of College Students (N = 1,716)
Table 10 Means, Standard Deviations, Standard Errors of Measurement, and Cronbach
Alpha Reliabilities With 95% Confidence Intervals for K-PIRS Symptom Variable
Raw Scores in an Active Client Sample of College Students (N = 917)
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Table 11 Means, Standard Deviations, Standard Errors of Measurement, and Cronbach
Alpha Reliabilities With 95% Confidence Intervals for K-PIRS Symptom Variable
Raw Scores in a Non-Client Sample of College Students (N = 932)
Table 12 Standard Errors of Measurement (SEM) and Test-Retest Reliabilities with 95%
Confidence Intervals for K-PIRS Symptom Variable Raw Scores in a Sample of
Active Clients
Table 13 Correlations between K-PIRS Scales and Seven Validation Instruments (N = 234)
Table 14 Convergent Validity of the K-PIRS: Correlations between Client Scores and
Counselor Assessments on the Seven Scales at Intake
Figures
Figure 1. K-PIRS Profile Charts and clinical interview information for six clients
Figure 2. K-PIRS Form B Profile Charts and clinical information for two clients, showing
symptom change over time
Appendixes
Appendix A Printable version of K-PIRS, Form B
Appendix B K-PIRS Means and Standard Deviations for an Active Client Sample (N = 917) of
Undergraduate and Graduate Students at Assessment
Appendix C T-Score Conversion Table for an Active Client Sample (N = 917) of
Undergraduate and Graduate Students at Assessment
Appendix D K-PIRS Means and Standard Deviations for a Non-Client Sample of
Undergraduates (N = 932)
Appendix E T-Score Conversion Table for a Non-Client Sample of Undergraduates (N = 932)
K-PIRS
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Chapter 1: Development
Purpose
The K-State Problem Identification Rating Scales (K-PIRS) are designed for use in
college counseling centers at intake. As a screening instrument, it alerts counselors to problem
areas that may need a more extensive examination during the clinical interview or through the
use of standardized tests to assess specific symptom patterns.
The K-PIRS:
• Can be completed in 10-15 minutes, either in the clinical setting or on-line
• Gathers demographic data on up to 30 variables
• Provides reliable and valid data on both academic concerns and clinical problems
• Calculates T-Scores on seven clinical scales
• Assesses level of interference with academic and social life
• Evaluates readiness to engage in therapy
• Uses rating scales rather than a dichotomous checklist in order to increase sensitivity
• Presents items as descriptive phrases rather than individual words
Counselors will find the K-PIRS useful in identifying clinical leads, making case
disposition decisions, and developing treatment plans. Form B of the instrument develops
actuarial evidence of client change over time, or in generating research related to client outcomes.
Overview
Three studies contributed to the initial development of the K-PIRS instruments
(Robertson, Benton, Newton, Downey, Marsh, Benton, Tseng, & Shin, 2006). First, an
K-PIRS
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exploratory factor analysis (EFA) was performed on a large derivation sample of university
students who were active clients. Seven factors were revealed and named as follows:
• Mood Difficulties
• Learning Problems
• Food Concerns
• Interpersonal Conflicts
• Career Uncertainties
• Self-Harm Indicators
• Substance/Addiction Issues
Second, a confirmatory factor analysis (CFA) was conducted on a replication sample of
active clients. Strong support for the factor structure was provided. Third, a cross-validation
study completed on a Non-Client sample of university students explored levels of relationship
between the seven factors and other standardized instruments measuring the same constructs.
Additional studies included a cluster analysis (Benton, 2003) using the CFA sample, and
the development of normative scores using an entirely new sample of college students (Marsh,
Newton, & Kim, 2006).
Item Development
The research team first considered a universe of several hundred possible symptoms
derived from a review of four types of sources: published summaries of college student problems
(Archer & Cooper, 1998; Grayson & Cauley, 1989), available checklists and inventories (e.g.,
Anton & Reed, 1991; Derogatis, 1983, 1993; Heppner, Kivlighan, Good, Roehlke, Hills, & Ashby,
1994; Heppner, Cooper, Mulholland, & Wei, 2001; Lambert, Hansen, Umphress, Lunnen, Okiishi,
K-PIRS 10
Burlingame, & Reisinger, 1996; Mooney & Gordon, 1950; Zalaquett, 1996; & Zalaquett &
McManus, 1996), unpublished checklists collected from other college counseling centers, and the
clinical experiences of the mental health professionals on our staff. This information was discussed
weekly over the course of several months (see Content Validity section for details).
The result was a decision to develop a screening instrument that would provide data on
four types of variables: (a) demographic data, (b) presenting symptoms, (c) interference with
functioning, and (c) readiness to change.
Demographic Data. Over the course of 25 years, the counseling center staff at Kansas
State University developed and revised a list of up to 30 demographic variables that begin to
introduce the client to the counselor. In addition to contact and identifying information, variables
include ethnic identity, hometown population, marital status, type of housing, children, transfer
student status, year in school, hours enrolled, academic major and college within the university,
overall GPA, physical disabilities, medications, previous counseling or therapy, referral source,
employment status, hours of work per week, and a written summary of the reasons for seeking
assistance. However, each college or university using the K-PIRS may elect to identify
demographic variables that are of particular interest in their region or on their campus. As a set
of core variables, the K-PIRS includes the following dozen items: gender, date of birth, race,
ethnicity, citizenship, student status (full-time or part-time), residence type, health insurance,
work (yes/no) hours, previous mental health treatment, current psychiatric medications, and type
of service desired.
Presenting Symptoms. A search of available literature led to an initial list of 85 phrases
that addressed a broad range of factors that affect student functioning. Included were items that
K-PIRS 11
addressed all the areas covered by the team’s review of the literature: clinical symptoms,
situational concerns, personal development issues, social problems, and concerns with academic
performance and career aspirations. No specific problem area noted in the literature cited above
was omitted. The items were presented to 16 college counseling center therapists for their review,
comment, and discussion. By consensus, four items were regarded as either too broad or
redundant. The reduced list of 81 items was then given to four focus groups of undergraduate
and graduate students, who were asked to review the items individually before meeting as a
group. They were asked to evaluate the items with regard to comprehensibility, word choice, and
repetitiousness. This step eliminated eleven more items because the groups agreed that the items
met the exclusionary criteria.
The team then examined the remaining 70 presenting symptoms, and hypothesized that
they might fall into 12 categories: acting out issues (anger, legal issues, substance abuse), anxiety,
attention deficit problems, career concerns, depression, eating problems, health behavior,
learning disabilities, relational difficulties, self-concept issues, self-harm behavior, and
situational concerns (housing, finances, resources, etc.).
The symptom items were worded as phrases rather than individual words in order to
provide more detail to both client and counselor. Participants were given a 4-point rating scale
estimating how much “concern” they had about each item in the list. In this way, the instrument
also provided a global score for clinical symptom endorsement.
Interference with Functioning. To assess the severity with which the presenting
symptoms were interfering with their ability to function, clients were asked to use a 4-point scale
K-PIRS 12
in estimating the degree of interference their problems were creating with both academic and
social functioning.
Readiness to Change. The team developed items to measure readiness, based on the
literature on change assessment (McConnaughy, Prochaska, & Velicer, 1983; Prochaska &
DeClemente, 1982; 1992). Participants were given a list of options that explored how they felt
about their situations, and why they were coming to counseling at the present time. These items
provided nominal data useful not only to counselors, but also to researchers who may wish to test
various hypotheses about relationships among readiness, symptom severity, symptom change
over time, or outcomes.
Together, these four sections of the K-PIRS provide therapists with a quick overview of a
wide range of both situational information and selected clinical symptoms associated with
common disorders found in the Diagnostic and Statistical Manual of Mental Disorders (DSM-
IV-TR) (American Psychiatric Association, 2000).
Data Collection Procedures
Participants in the two factor analytic studies completed the K-PIRS at the counseling
center at the time of their intake, or on-line. No significant differences in scores were found
between paper and on-line submissions. Data for the validation study were collected at one
sitting, and temporal stability data for the K-PIRS were obtained at a second sitting, one week
later (with an attrition rate of 2.6%). The studies were approved by the Committee for Research
Involving Human Subjects under the University Research Compliance Office at Kansas State
University. Normative data was collected from active clients and from students in academic
classes over the course of a year.
K-PIRS 13
Chapter 2 Administration and Scoring
Appropriate Uses
The K-PIRS was developed from a large population of university students seeking
clinical services at a campus counseling center. It is appropriate to use the K-PIRS for student
populations at community colleges, four-year institutions, professional schools and graduate
institutions in North America. It should be used with caution with other clinical populations,
such as inpatients, young adults not attending college, or high school students. This caution is
offered because the reliability and validity of the K-PIRS has not been tested on other clinical
populations, and because some items specifically address college student issues (e.g., concerns
about selecting an academic major). Its utility for non-student groups is doubtful.
User Qualifications
The K-PIRS can be scored electronically or by clerical staff covered by the National
Standards to Protect the Privacy of Personal Health Information. This set of standards is
promulgated by the United States Department of Health and Human Services, which has been
entrusted with administering the Heath Insurance Portability and Accountability Act of 1996
(HIPAA). More information can be found online, at http://www.hhs.gov/ocr/hipaa/.
After the scoring is completed, the interpretation and use of the profiles should be
restricted to professionals who have academic training in mental health, who have completed
supervised experience in clinical assessment and treatment, and who hold current state licenses
to offer psychological services to the public. Graduate students in mental health fields can
analyze results under the direction of their supervisors. Guidelines are spelled out in Standards
for Educational and Psychological Testing, approved jointly by the American Educational
K-PIRS 14
Research Association, the American Psychological Association, and the National Council on
Measurement in Education (American Educational Research Association, 1999).
Testing Conditions
Clients can complete the K-PIRS in a private space in the clinic, using either a pencil and
paper format, or a keyboard and screen. The instrument may completed by each client at the time
of intake for clinical purposes, in groups for larger screening purposes, or in groups for research
purposes. No statistically significant differences have been found in profiles developed from
these various testing conditions.
Scoring Procedures
Participants may answer the questions on-line, and submit them electronically for scoring
and profile calculation. Or written forms can be entered into the on-line computer scoring
program by clerical staff. On-line scoring for the K-PIRS is administered through the Kansas
State Comprehensive Assessment Tools Corporation (K-CAT), a state of Kansas not-for-profit
corporation. The website for K-CAT corporation is http://www.k-cat.org.
On the seven clinical scales, each individual item contributes equally to the total score for
that scale. Theory and research long ago indicated that for an instrument of this type, differential
weighting systems are not more informative than unit weighting systems (Downey, 1979;
Gulliksen, 1950). More elaborate weighting systems may be used when the purpose is to create
either orthogonal (non-correlated) or oblique (minimally correlated) scores. The K-PIRS is given
to persons who tend to have problems in related areas; for example, it is possible to imagine the
same person scoring high on Mood Difficulties, Food Concerns, and Self-Harm Indicators. Note
that items left blank are given a weight of a zero score so would not contribute to either scale
K-PIRS 15
scores or the global score. No response on items may be cause to consider the resulting profile
as invalid.
An individual client’s mean raw score for each clinical scale is compared with average
scale scores generated by a large normative sample, and T-Scores are calculated for each of the
seven clinical scales.
Table 1 reports the means and standard deviations for a large sample of university
students. This normative sample is weighted to include representative proportions of both active
clients in the counseling center and enrolled students from the general university population. It is
also weighted to reflect academic standing. Scores are provided for each of the seven clinical
scales, a global concern scale, and the academic and social interference items. Table 2 presents
the Conversion Table for the normative sample, transforming mean raw scores for each scale
into T-Scores. Additionally, Appendixes A and B provide the same information for a sample of
students who were active clients, and Appendixes C and D for a sample of students who were not
clients.
Individual profiles can be displayed for counselors or clients on a single sheet or a
computer screen. To illustrate, Figure 1 shows Profile Charts for six clients at the time of their
intakes. It is important to note that a K-PIRS profile does not provide a DSM IV-TR diagnosis.
Instead, it is a screening tool that indicates levels of self-reported concerns on the seven clinical
scales. Scale scores in the sample profiles have been transformed from mean raw scores, and are
shown as T-Scores with a Mean of 50 and a Standard Deviation of 10.
The profiles in Figure 1 also include a brief synopsis of case intake material to provide an
illustration of how scales correlate with other case data. This information demonstrates how
K-PIRS 16
Profile Charts highlight areas for further discussion during the clinical interview, contribute to
triage decision-making, and assess levels of client functioning.
K-PIRS 17
Chapter 3 Interpretation of Results
Clinical Information
Each of the four sections of the K-PIRS can be used to gather clues that can be used in
developing initial clinical impressions.
Demographic Variables. The demographic section identifies factors that may contribute
to a student’s experience of clinical symptoms. Consider the implications, for example, of a first-
year student who comes from a rural community with a population of 300, works 30 hours a
week, is enrolled in 18 credit hours, is living off campus, and is reporting a hidden disability. It
should be noted, however, that demographic variables are heuristic in nature, and not valid
predictors of any symptom profile.
Presenting Symptoms. Scores on the seven clinical scales provide a direct measure of
symptomology. Scales are scored independently, so that any combination of high and low scores
is theoretically possible. A average of the seven scales is called the Global Score. Mean scores
for each scale are transformed into T-Scores, and are displayed on Profile Charts. See Figure 1
for six examples.
T-Scores are interpreted using a Mean of 50 and a Standard Deviation of 10.
• 68% of the normative sample falls between T = 40 and T = 60
• 96% of the normative sample falls between T = 30 and T = 70
• 99% falls between T = 20 and T = 80.
To illustrate, a T-Score of 60 is one standard deviation above the mean, and higher than
84% of the normative sample, while a T-Score of 70 would be higher than 98% of the normative
sample. It would be relatively safe to conclude that any T-Score above 60 does not represent a
K-PIRS 18
random outcome, but rather indicates a significant level of concern warranting further clinical
evaluation. It must be noted, however, that no T-Score should be used in isolation to make a hard
DSM-IV-TR diagnosis.
In addition to scores on the seven clinical scales and the global scale, the K-PIRS also
presents a series of independent items designed to alert counselors to areas that may need further
exploration during the clinical interview. These items were deemed important in the screening
process by our team of clinician researchers, even though they are not a part of any single scale.
The items were labeled “SOS Items” (Significant Other Situations) because they represent
serious situations that are often awkward for clients to initiate orally at an intake.
• Concerned about my safety
• Memories of past sexual abuse/assault
• Recent sexual assault
• Questions related to pregnancy
• Dealing with grief or loss
• Taking risks or chances
• My sexual identity or orientation
• Facing legal issues
Our experience as clinicians has demonstrated that clients often find it easier to mark
these items on an intake form than to initiate a conversation about them. Means and standard
deviations for these SOS items are found in Table 3, and are derived from the normative sample
of college undergraduates.
K-PIRS 19
Interference with Functioning. Questions about the severity with which symptoms are
perceived to be interfering with client functioning can be used in several ways: (a) as an
indication of where the distress lies (in social functioning, but not academic functioning, for
example); (b) as part of a larger profile that includes scores on the clinical scales; (c) or as an
overall measure of the impact symptoms may be having on the ability to function.
Readiness to Change. The readiness questions provide nominal data that can be used in
understanding a client’s initial approach to the clinical interview and treatment. Using the model
developed by Prochaska and DeClemente (1992), the K-PIRS gives clients choices that reflect
the five stages of change presented in the model: pre-contemplation, contemplation, planning,
action, and maintenance. The readiness questions might also be used to test various research
hypotheses about possible associations between readiness and a variety of variables, such as
symptom severity at intake, symptom change over time, or outcome.
Form B: Client Outcome Measure
The K-PIRS package also features the ability to measure changes in client symptoms
over the course of psychotherapy. The K-PIRS follow-up instrument, called Form B (Kim,
Marsh, & Newton, 2006), can be used repeatedly to monitor any changes in the seven clinical
scales, the global scale, or the interference items. It also measures several other important
outcomes: progress on reaching counseling goals; self-reported reduction of symptoms;
movement toward making decisions; success in coping with problems; improvement in academic
performance; and any changes experienced regarding health and wellbeing, stress management,
and interactions with significant others.
K-PIRS 20
Form B is also a useful tool to track group outcomes and demonstrate the efficacy of
counseling interventions. Data may be analyzed by problem category, by number of sessions, by
random follow-up sampling, or by any combination of variables deemed appropriate by an
agency. Changes can be tracked for the seven clinical scales, the global scale (the mean score for
rating all items), and the items that investigate interference in social and academic functioning.
Table 4 shows results from a study indicating significant and positive changes occurring on all
scales between the intake and the third session.
Figure 2 shows graphically how the Profile Charts of two clients changed over time. Each
chart shows three profiles, including scores at intake, after the 3rd session, and after the 6th
session. Some counselors may want to use these follow-up charts as part of their treatment
process to discuss further any changes in symptoms that may have occurred over the course of
psychotherapy. Given the current climate on many universities in North America, demonstrating
the effectiveness of counseling and the possibility of a related increase in retention rates may
represent one of the more important benefits of the K-PIRS.
Additional information about the availability of Form B can be found on-line from
Kansas State Comprehensive Assessment Tools: http://www.k-cat.org/web/index.html.
Appendix A shows a printable version. Also available are tools counselors can use during the
intake process, such as a Case Descriptors form (allowing counseling centers to track counselor
identified problems at intake over time), and a Counselor Intake Evaluation form (providing
estimates of problem severity, client functioning, DSM information, and recommendations for
types of additional assessment or treatment). A printable copy of the Counselor forms can also be
found at the K-CAT website cited above.
K-PIRS 21
Cluster Analysis
For clinical reasons, the research team was interested in seeing whether various response
patterns might provide additional useful information. If the intake data from the derivation and
replication samples could be organized so that groups of clients could be identified based on
characteristics they had in common, then clinicians would have information that could be used in
developing initial conceptualizations and treatment approaches. A cluster analysis is a
multivariate analysis technique that seeks to organize information about variables so that
relatively homogeneous groups, or "clusters," can be formed.
Observations were clustered by their scores on the seven clinical scales. The Ward
method of cluster analysis (SPSS, 2001) was performed on data from the derivation sample,
using the squared Euclidean distance. Ward’s method creates clusters that limit the loss of
information from adjacent groups (Johnson & Wichern, 2002) by minimizing within-group
variation and maximizing between-group variation. The SPSS program automatically
standardizes all variables by transforming them to z-scores. Six cases were eliminated because of
missing data.
The dendogram indicated a six-cluster solution. Table 5 presents means, standard
deviations, and ANOVA results for the seven factor scores across the six clusters. All F values
were significant at p < .0001. The Tukey HSD procedure, using the harmonic mean of the
sample sizes, was employed to make all post-hoc comparisons. Using a Bonferroni adjustment
(.05 divided by seven scales), each comparison was performed using an approximate alpha level
of .007.
K-PIRS 22
Cluster 1: Low Distress. The clients in Cluster 1 (171 women and 123 men) scored
significantly lower than clients in other clusters on mood difficulties, learning problems, and
food concerns. They were also descriptively lower than other clients with respect to interpersonal
conflicts, career uncertainties, self-harm indicators, and substance/addiction issues.
Cluster 2: Interpersonal Conflicts. These individuals (55 women and 43 men) had the
next lowest scores on mood difficulties, food concerns, and career uncertainties; however, they
scored significantly higher than all other clients in interpersonal conflicts. These first two client
groups represented approximately 39% of the total sample.
Cluster 3: Addiction Issues. Clients in Cluster 3 (39 women and 28 men) were
significantly higher than all other clients in substance/addiction issues. They also reported
relatively high levels of problems with mood difficulties, career uncertainties, and self-harm
indicators. All other scales were relatively moderate in magnitude.
Cluster 4: Learning Problems. The clients in Cluster 4 (136 women and 77 men)
indicated relatively high levels of concern with learning problems, but scored moderately or low
on all other scales. Their lowest scores were on interpersonal conflicts and substance/addiction
issues.
Cluster 5: Food Concerns. Clients in Cluster 5 (86 women and 13 men) reported their
greatest difficulties with food concerns. All other factor scores were relatively low to moderate
for this group.
Cluster 6: High Distress. Finally, Cluster 6 clients (72 women and 23 men) reported
significantly more problems than any other clients with mood difficulties, learning problems, and
K-PIRS 23
career uncertainties. Clients in this cluster also scored high on food concerns, interpersonal
conflicts, self-harm indicators, and substance/addiction issues.
Comparisons between clusters were conducted on several demographic variables. No
significant differences were observed for ethnicity or housing; however, differences were found
for student age, F(5, 857) = 3.38, p < .005, Me = 104.69, ω2 = .014; and overall grade-point
average (GPA), F(5, 823) = 6.71, p < .001, Me = 10.58, ω2 = .033. The Tukey HSD procedure,
using the harmonic mean of the sample sizes, revealed that clients in Clusters 1 (M = 23.44) and
6 (M = 23.20) were significantly older than those in Cluster 2 (M = 21.07). The rankings for
client GPAs were Cluster 5 (M = 4.05), Cluster 1 (M = 3.83), and Cluster 2 (M = 3.71) >
Cluster 4 (M = 3.47) > Clusters 3 (M = 3.29) and 6 (M = 3.27). Differences were also found
for gender, χ2(5, N = 866) = 36.30, p < .001, with the largest contributors to the overall chi-
square coming from Clusters 1 and 5. A greater number of men were found in Cluster 1 than in
any other cluster, and the proportion of clients in Cluster 5 who were women (86%) exceeded
that of any other cluster. In addition, clusters differed by the students’ year in school, χ2(25, N =
847) = 72.50, p < .001. Graduate students were more likely to be found in Cluster 1 than in all
other clusters; juniors were more common in Cluster 6 than all other clients; and sophomores
comprised the majority of clients in Cluster 2.
K-PIRS 24
Chapter 4 Psychometric Information
Samples
Four samples of university students were used in developing the K-PIRS: a derivation
sample of active clients for an exploratory factor analysis (EFA), a replication sample of active
clients for a confirmatory factor analysis (CFA), a non-client sample for a cross-validation study,
and a weighted sample of both active clients and non-clients to develop normative profiles.
Derivation Sample. Participants for the EFA were university students (N = 872) who
sought counseling or psychological services at a university counseling center in a large public
university (enrollment greater than 20,000 students) in the Midwest. The center serves an
average of approximately 1,000 clinical clients each year. All clients were invited to complete
the K-PIRS at the time of their intakes. The average age was representative of college and
university students generally (M = 22.90, SD = 5.78), with an age range of 16 to 64 years. About
two thirds of the students were women (N = 560, 64.2%). Graduate students made up 12.3% of
the sample. Undergraduates were weighted toward seniors (29.3% of the total sample), followed
by juniors (21.8%), sophomores (20.6%), first-year students (15.1%) and special students (.9%).
Slightly more than half of the participants (52.5%) had a Grade Point Average (GPA) of 3.0 or
higher. Most participants described their ethnicity as White/Non-Hispanic (82.9%); other
ethnicities represented included Black/African American (3.3%), Hispanic/Mexican American
(3.1%), Asian or Pacific Islander (2.5%), Multi-racial (2.4%), Native American (1.2%), and
Other ethnic heritages (1.7%). A few students (2.9%) did not answer the question about ethnicity.
Replication Sample. Participants for the CFA were university students (N = 879) who
sought clinical services at the same university during a subsequent academic year. In this sample,
K-PIRS 25
65.1% were women (N = 572), ranging in ages from 17 to 57 years, with a mean of 22.9 (SD =
5.59). With regard to class standing, 13.7% were graduate students, 28.3% were seniors, 24.2%
were juniors, 18.6% were sophomores, and 15.2% were first year students. More than half the
participants (55.6%) reported GPA’s of 3.0 or higher. Ethnically, 85.3% reported that they were
White/Non-Hispanic, 3.0% were Black/African American, 2.2% were Hispanic/Mexican
American, 2.2% were Asian or Pacific Islander, 2.0% checked Multi-racial, .8% were Native
American, 1.2% were “other,” and the rest (3.4%) chose not to respond.
Group comparisons were made between the two samples of clients. In addition to the
above variables, the groups were compared on marital status, campus or community housing,
approximate hometown size, referral source, and academic major grouped by college.
Participants were also compared on employment status, student status (transfer, full-time,
international), and whether or not the participant had previous counseling experience. No
significant differences on any of these variables were found between the derivation and
replication samples (p < .01).
Validation Sample. Participants in the cross-validation study were 234 university students
enrolled in classes that offered credit for participating in research. The sample was viewed as
non-clients, in that only 1.7% indicated that they were seeking psychological services at the time
they completed the research questionnaire. The mean client age for this normative sample was
20.08 (SD = 2.60). More women (54.7%) than men participated in this study. A few (2.1%) were
international students. Most (90.2%) reported their ethnicity as White/Non-Hispanic. The rest
indicated that they were Hispanic/Mexican American (3.0%), Black/African American (2.6%),
Asian or Pacific Islander (1.7%), Native American (1.7%), or Multi-Racial (.4%); the remainder
K-PIRS 26
chose not to respond to the ethnicity question. In addition to other demographic variables,
participants reported their enrollment by colleges: Agriculture (4.8%), Architecture (1.3%), Arts
and Sciences (37.6%), Business Administration (13.7%), Education (20.5%), Engineering (3.9%),
Human Ecology (11.8%), Veterinarian Medicine (.4%), and other majors (5.7%). About half
were employed (48%).
Participants in the validation study differed from active client participants in the
exploratory and confirmatory studies on several demographic variables. Participants in the
validation sample were younger than those in the exploratory, t(1104) = 7.27, p < .001, and
confirmatory, t(1111) = 7.58, p < .001, samples. The validation sample also included more men
than in the exploratory, χ2(1) = 7.11, p < .001, and confirmatory, χ2(1) = 8.52, p < .001, samples.
The validation sample was exclusively undergraduate students, and it contained proportionately
more freshmen and proportionately fewer seniors than the exploratory, χ2(3) = 112.51, p < .001,
and confirmatory, χ2(3) = 112.62, p < .001, samples. Because of the power generated by sample
size, the significance of these differences is more statistical than meaningful. For example, more
women were in the active client samples because more women seek counseling than men. And
the validation sample was younger because the psychology pool of younger students was used.
The larger point is that all the samples consisted of college students, the population for which the
instrument was designed to be used.
Normative Sample. Data were collected over the course of a year from active clients in a
university counseling center, and from enrolled college students who were not clients. Means
and standard deviations on this large sample (N = 1,716) were calculated for each clinical scale
and for the items that measured interference with academic and social functioning. The sample
K-PIRS 27
was weighted to reflect overall proportions in the student population with respect to class
standing and client/non-client identity. Participants in the normative sample (N = 1,716) included
both active clients (N = 784, 45.7%) and non-client students (N = 932, 54.3%). Table 1 shows
descriptive statistics for this sample. The normative sample was mostly female (60.7%). By year
of study, 41.2% were first-year students, 20.7% were sophomores, 17.1% were juniors, and
20.9% were seniors. Reported overall Grade Point Averages (GPA) covered the full spectrum:
3.5 and above (22.2%), 3.0 to 3.4 (26.1%), 2.5 to 2.9 (26.7%), 2.0 to 2.4 (3.5%), and below 2.0
(6.1%). The rest did not select a GPA bracket.
Ethnicity was selected from seven categories: White/Non-Hispanic (85.8%), Black/
African American, (4.7%), Multi-Racial (1.8%), Mexican/Mexican American (1.6%), Hispanic,
Spanish, Latin American (1.5%), Asian, Pacific Islander (1.2%), American Indian, Alaskan
Native (.5%). The rest chose Other (.6%), or did not respond (2.3%).
Participants came from eight colleges in the university: Agriculture (7.2%), Architecture
and Design (3.1%), Arts and Sciences (46.4%), Business Administration (13.6%), Education
(6.3%), Engineering (9.0%), Human Ecology (14.0%), and Veterinary Medicine (.3%).
Given the possibility that some users of the K-PIRS might want to compare their own
findings to larger samples comprised exclusively of clients or non-clients, descriptive statistics
on these two groups were calculated. Means and standard deviations for an active client sample
of undergraduate and graduate students (N = 917) are shown in Appendix B, with a
corresponding Conversion Table in Appendix C. Means and standard deviations for a non-client
sample of undergraduate students (N = 932) are shown in Appendix D and the Conversion Table
in Appendix E.
K-PIRS 28
Exploratory Factor Analysis
Given that co-morbidity often exists among various problems presented to counselors in a
clinical setting, an oblique solution was conducted in order to account for these hypothesized
relationships. A principal components extraction with promax (oblique) rotation was performed
using the correlation matrix from derivation data (N = 872) of the 70 presenting items of the K-
PIRS. The initial extraction used eigenvalues greater than 1. In determining the final number of
factors to extract, we used two criteria: (a) a pattern matrix coefficient of at least .40, and (b) a
minimum of three items per factor. Using these criteria, we adopted an instrument comprised of
seven factors and 42 items; this solution accounted for 57 percent of the total variance. Since an
oblique rotation method was used, the percent of variance for each factor cannot be calculated.
Pattern matrix coefficients and final communality estimates are shown in Table 6. Variables are
ordered and grouped by size of coefficients to facilitate interpretation. Table 7 presents the
component correlation matrix.
We labeled the seven factors as follows: (1) Mood Difficulties; (2) Learning Problems; (3)
Food Concerns; (4) Interpersonal Conflicts; (5) Career Uncertainties; (6) Self-Harm Indicators;
and (7) Substance/Addiction Issues.
All seven of these factors appeared in our original list of 12 hypothesized categories
noted above. No new factors emerged. Items originally hypothesized as attention deficit or
learning disabilities items merged into the Learning Problems factor. The anxiety and depression
categories merged into the Mood Difficulties factor. Situational concerns disappeared as a
category (legal, financial, prejudice and housing problems were unrelated). For apparently
similar reasons, the self-concept category dissolved (e.g., sexual orientation, self-esteem,
K-PIRS 29
spirituality, problematic cognition, weight), as did the health concerns category (e.g., stress, pain,
disability, nutrition). Some of the “acting out” items went to the Substance/Addiction Issues
factor, whereas others moved to the Interpersonal Conflicts factor. Some of the items from the
categories of self-concept and physical health behavior became part of the Mood Difficulties
factor.
Factor 1 (Mood Difficulties) had 15 items with pattern coefficients between .50 and .88.
Factor 1 also was positively correlated with the two severity measures: .34 with academic
functioning and .52 with social functioning (see Table 6). This suggests that as mood difficulties
increased, interference with both academic and social life became more severe.
Factor 2 (Learning Problems) had 8 items with pattern coefficients between .54 and .87.
Factor 2 also showed significant and positive correlations with the two interference scales, but it
indicated different patterns in terms of strength. As would be expected, learning problems
interfered more with academic functioning (.56) than with social functioning (.15). Factor 3
(Food Concerns) contained 5 items with coefficients ranging from .63 to .92. Endorsement of
items relating to food concerns was positively correlated with interference in both academic life
(.12) and social life (.25). Factor 4 (Interpersonal Conflicts) was composed of 5 items with
pattern coefficients ranging from .45 to .83. As might be expected, Interpersonal Conflicts were
associated more strongly with interference in social functioning (.40) than with academic
functioning (.11). Factor 5 (Career Uncertainties) contained 3 items with pattern coefficients
ranging from .72 to .87. With regard to the interference variables, Factor 5 was positively
correlated only with academic functioning (.24), indicating that as career uncertainty increases,
problems with academic functioning also increase. However, having career uncertainties does
K-PIRS 30
not appear to affect adversely students’ social lives. Factor 6 (Self-Harm Indicators) consisted of
3 items with coefficients ranging from .49 to .89, and was positively associated with interference
in both academic (.17) and social functioning (.23). Finally, Factor 7 (Substance/Addiction
Issues) contained 3 items with pattern coefficients ranging from .49 to .91. The presence of
problems with substance abuse or addiction behavior had low but significant and positive
correlations with interference in both academic and social functioning.
One additional decision was made about some of the items from the original list that did
not load on any of the seven factors. Our group of clinician-researchers decided that the clinical
utility of eight of these items warranted their inclusion as a separate part of the instrument. The
items were labeled “SOS items” (Significant Other Situations) because of their value in alerting
counselors to the presence of a situation that might need to be addressed early in therapy.
Included were items identifying sensitive topics often awkward for clients to introduce, such as
concerns about safety, sexual abuse or assault, pregnancy, loss, taking risks, and sexual identity.
Confirmatory Factor Analysis
A series of confirmatory factor analyses were performed on data collected in a replication
sample (N = 879) during the next academic year. The purpose of this study was to see if the
seven factor structure that emerged from the derivation sample adequately applied to the
replication sample.
Using LISREL 8 (Joreskog & Sorbom, 1993), seven fit indices were used to determine
the data fit of the hypothesized model: (a) chi-square (χ2), (b) Normed Fit Index (NFI ), (c)
Goodness-of-Fit Index, (d) Adjusted Goodness-of-Fit Index (AGFI), (e) Root Mean Square
Residual (RMR), (f) Root Mean Square Error of Approximation Residual (RMSEA), and (g)
K-PIRS 31
Comparative Fit Index (CFI). Three separate Confirmatory Factor Analyses (CFA’s) were
conducted (see fit indices in Table 8). The first analysis (Model 1 in the Table) employed
maximum likelihood estimation, most commonly used when the data are multivariate and
normally distributed. As indicated in Table 8, the fit indices for the hypothesized model using
maximum likelihood estimation were not adequate. The second approach to the CFA applied
unweighted least squares estimates, which also assumes multivariate normal distributions. This
analysis resulted in a generally good fit, with the exception that RMSR and RMR were a bit high.
A third approach (Model 3) used unweighted least squares estimates and correlated errors within
scales because it was assumed that some elements of the measurement error might have been
systematic and overlapping. That is to say, highly distressed students likely responded high on
items across the scales, thereby contributing to correlated errors. This approach resulted in a
good fit across all six indices. A fourth CFA employing maximum likelihood and correlated
errors within scales failed to converge after 300 iterations.
Reliability
Reliability analyses were conducted on the EFA sample (N = 872), the CFA sample (N =
879), and on the normative samples (N = 1,716).
The major sources of error on the K-PIRS were hypothesized to stem from the expected
instability of some of the traits measured (especially mood difficulties and self-harm indicators),
respondent fatigue and boredom, differences in testing times (e.g., near midterm exams, finals
week), and individual differences among students.
To control for error due to trait instability, reliability estimates included measures of
internal consistency. In addition, two stability estimates of the attributes were conducted within a
K-PIRS 32
short time period (one week and two weeks). Because the K-PIRS is a screening instrument and
students are not placed into categories, estimates of classification consistency would be
inappropriate.
The normative sample included both active clients and non-client enrolled students.
Because of the number of tests conducted and the relatively large sample sizes, Type I error rate
was set at α = .01. There were proportionately more female clients (67.1%) than female non-
clients (55.3%), χ2 (1) = 24.69, p < .001. This proportion is consistent with the fact that women
typically seek therapy in higher proportions than do men. A greater proportion of non-clients
(60.9%) than clients (17.7%) were first-year students, χ2 (3) = 353.94, p < .001. This is not
surprising because many non-clients were selected from the pool of psychology students required
to participate in research. Consequently, non-clients were significantly younger (M = 19.48, SD
= 2.13) than clients (M = 21.57, SD = 3.45), t (1234.44) = 14.68, p < .001. Non-clients were also
less diverse in age, F (771, 930) =100.67, p < .001. There were no differences between the two
samples in student ethnicity.
Internal Consistency. Cronbach alphas for the exploratory and confirmatory studies were
similar: Factor 1 (.91 and .90), Factor 2 (.87 and .86), Factor 3 (.87 and .87), Factor 4 (.77
and .75), Factor 5 (.72 and .67), Factor 6 (.75 and .81), and Factor 7 (.68 and .81). Because these
reliabilities were high, no additional re-specification studies of the factors were conducted. This
decision was based in part on the fact that our analysis met a series of recommendations by Kline
(1998): each factor had a minimum of three items; all of the pattern coefficients were high,
making it unreasonable to consider any hypothesis that some variables might load on different
factors in a re-specification; and the inter-correlations among the factors were relatively low,
K-PIRS 33
with the highest correlations found between Mood Difficulties and other factors that would be
expected to be related clinically to mood (problems with learning, relationships, eating, and self-
harm).
Additional internal consistency examinations were made on three separate samples
collected for the normative studies—a normative sample (N = 1,716) that included weighted
proportions of active clients and non-client students (Table 9), a sample (N = 917) using only
active clients (Table 10), and a sample (N = 932) with only non-client students (Table 11). Each
table provides means and standard deviations for the scales, the standard errors of measurement,
and the Cronbach alpha reliabilities with 95% confidence intervals.
In addition, standardized item alphas for the symptom variable raw scores were
calculated for the three samples noted in the previous paragraph. They are here reported in this
order: the normative sample, an active client sample, and a non-client sample. The results: Mood
Difficulties (.9010, .8794, and .9089); Learning Problems (.8789, .8034, .8417); Food Concerns
(.8909, .6937, .8081); Interpersonal Conflicts (.7956, .7244, .7922); Career Uncertainties
(.6864, .5053, .6015); Self-Harm (.7621, .8040, .7892); and Substances/Addiction Issues
(.7233, .4688, .5848).
Temporal stability. A test-retest (one week) examination of the instrument’s stability was
conducted on the CFA sample of college students who were active clients (N = 879).
Correlations were statistically significant (p < .001) for all seven scales: Mood Difficulties (.77),
Learning Problems (.69), Food Concerns (.67), Interpersonal Conflicts (.60), Career
Uncertainties (.70), Self-Harm Indicators (.40), and Substance/Addiction Issues (.51).
Correlations were statistically significant (p < .001) for all seven scales. The relatively lower
K-PIRS 34
stability of scores for Self-Harm Indicators should not be especially surprising, and is consistent
with other measures of these constructs (e.g., the one week test-retest reliability for the Beck
Scale for Suicide Ideation was .54) (Beck & Steer, 1991). For a long time (Guildford, 1954), it
has been apparent that when a test measures psychological functions that are known to vary,
lower test-retest reliabilities are to be expected. In such cases, the more appropriate measure of
instrument reliability is internal consistency. The Cronbach alpha reliabilities reported above
were equal to or higher than the test-retest figures for all the scales.
One other test-retest examination was conducted using a separate sample (N = 135) of
active clients. This particular sample was part of a study measuring changes in self-reported
symptom severity between the intake session and the third session. Time gaps between the two
measures were generally two to three weeks. Reliabilities are reported in Table 12, and ranged
between .45 and .78. The test-retest reliabilities are somewhat lower for this sample than for the
CFA sample noted in the previous paragraph. This is to be expected, given that clinical
interventions had occurred over two to three weeks for this second sample, producing reduced
scores at the time of the third session. Nevertheless, test-retest reliabilities were significant at the
p < .01 level.
Content Validity
Although the content of the K-PIRS was not developed solely on the basis of any widely
known theoretical model of student development (e.g., Chickering, McDowell, & Campagna
1969; Kohlberg, 1969; Perry, 1970), information from these models was reviewed and discussed
by the research team. The theoretical development was also informed by available taxonomies of
student problems (e.g., Archer and Cooper, 1998; Grayson and Cauley, 1989), as well as the
K-PIRS 35
sizable body of research on how the college experience affects the cognitive, psychosocial,
attitudinal, and educational development of college students (cf., Pascarella & Terenzini, 1991,
2005). From these sources, an inclusive set of possible problem areas for college students was
identified. Listed alphabetically, this set included autonomy and individuation, career concerns,
cognitive development, depression and anxiety, eating disorders, educational attainment,
existential and meaning concerns, ethnic and cultural awareness, date rape, developmental
transitions, family issues, fear of failure, feelings of inadequacy, gender issues, interpersonal
relationships, learning disabilities, personality disorders, sexually transmitted diseases, substance
abuse, sexual problems, sexual identity questions, stress, suicidal ideation, and trauma. Also
examined were the scope and impact of some relatively new stressors facing college students in
the early years of the new century: the information revolution, technological impermanence, new
social grouping patterns, political correctness, and more (Newton, 1998, 2002).
A series of discussions among research team members (eight licensed psychologists and
four masters-level counselors) transformed this set of problem areas and developmental
transitions into a model that included four variable types. Together, these four categories were
thought to cover the major factors counselors examine at intake: Demographic Variables,
Clinical Presenting Symptoms, Problem Interference with Academic and Social life, and
Readiness for Change. Procedures that transformed this information into a set of items are
described in Item Development section.
Construct Validity
K-PIRS 36
The degree to which the seven scales measure what they were intended to measure was
tested on a non-client sample of 234 university students. Correlations between the validation
instruments and the K-PIRS scales are shown in Table 13.
Mood Difficulties. Factor 1 was correlated with the Beck Depression Inventory-II (BDI-II)
(Beck, Steer, & Brown, 1996), a widely used instrument for assessing depression in clinical
populations. The BDI-II consists of items developed to assist in the assessment of depression
disorders as defined by the DSM-IV (American Psychiatric Association, 1994).
The Mood Difficulties scale of the K-PIRS correlated positively with the BDI-II (r = .76,
p < .001), providing evidence that the scale is a valid measure of depression.
Learning Problems. No published learning disability (LD) screening inventories with
validity and reliability data were available. One unpublished instrument that presents such data is
The Adult Learning Disabilities Screening (ALDS) (Mellard, Lancaster, & Leubbers, 1998;
Mellard & Lancaster, 2000). In developing the ALDS, the authors used a sample population that
was defined by using published protocols from the Wechsler Adult Intelligence Scale-III (WAIS-
III) (Wechsler, 1997) and The Woodcock-Johnson Psycho-Educational Battery-Revised (WJ-R)
(Woodcock & Johnson, 1989, 1990).
The K-PIRS Learning Problems scale showed a positive association with the ADLS,
which examines several factors associated with learning disabilities (r = .48, p < .001), including
self-attributions common to learning problems (r = .56, p < .001), poor planning and time
management skills (r = .40, p < .001), and problems with spelling and reading (r = .24, p > .001,
and r = .27, p < .001, respectively). Not associated with the K-PIRS Learning Problems scale
were the ALDS scales measuring social skills and a perceived sense of direction.
K-PIRS 37
Food Concerns. The Eating Attitudes Test (EAT-26) (Garner & Garfinkel, 1979; Garner,
Olmsted, Bohr, & Garfinkel, 1982) was constructed to measure symptoms of eating disorders in
North America. Scores are reported for clinical samples of college-aged females being treated for
anorexia nervosa, and for a comparison sample of non-client females attending college. The
correlation between EAT-26 scores and diagnosed membership in the eating disordered group as
measured by the DSM-IV was r = .79. Nelson, Hughes, Katz, and Searight (1999) have shown
that the EAT-26 also detects men with eating disorders.
The association between the K-PIRS Food Concerns scale and the total score for the
EAT-26 was significant (r = .63, p < .001), and showed a correlation with both dieting (r = .61,
p < .001) and bulimia (r = .67, p < .001) issues.
Interpersonal Conflicts. The Aggression Questionnaire (AG) (Buss & Perry, 1992)
contains four subcales addressing physical aggression, verbal aggression, anger, and hostility.
Psychometric data were compiled on more than 1,200 college students. Cross-validation
correlations were positive for several other traits hypothesized to be related to aggression, such
as impulsivity (r = .46), assertiveness (r = .43), and competitiveness (r = .46).
The K-PIRS Interpersonal Conflicts scale showed a significant correlation (p < .001) with
the AQ total score (r = .45), and with all four of the AQ’s subscales: physical aggression (r
= .24), verbal aggression (r = .22), anger (r = .39), and hostility (r = .61). Because the
Interpersonal Conflicts scale does not address overtly aggressive behavior, correlations with the
two AQ aggression scales were understandably lower.
Career Uncertainties. The Career Decision Profile (CDP) (Jones, 1989) was developed
on a sample of undergraduate college students. Scores are reported for three scales: decidedness,
K-PIRS 38
comfort, and reasons. Symptomatic scores on the Reasons scale indicate problems with self-
clarity, decisiveness, career choice importance, and knowledge about occupations.
Support for the K-PIRS Career Uncertainty factor was provided by a positive correlation
with the CDP (r = .51, p < .001). Correlations between the K-PIRS and the various CDP
subscales were positive and significant (p < .001): comfort with making a choice (r = .52), self-
appraisal of the ability to make decisions (r = .45), self-clarity regarding interests and abilities
(.41), career decidedness (r = .37, and the perceived importance of making a career decision (r
= .36). Less significant (p < .01) was knowledge about occupations and training (r = .19).
Self-Harm Indicators. The Beck Scale for Suicide Ideation (BSS) (Beck & Steer, 1991) is
a self-report instrument designed to measure suicidal risk. Scores were calculated on both
inpatients and outpatients. The Self-Harm Indicators scale on the K-PIRS showed positive
correlations (p < .001) with the outpatient population with suicidal ideation (r = .42), as well as
with the BDI-II (r = .33).
Substance/Addiction Issues. Developed on a sample of more than 500 college students
who self-reported as regular drinkers, the Questionnaire for Problem Drinkers (QPD) (Heck,
1991) consists of five items that discriminate between “normal drinkers” and “problem
drinkers.” Using a problem-based definition of problem drinking that combined
quantity/frequency of drinking with a range of negative consequences, the QPD was able to
make useful predictions into groups already defined as problem drinkers or normal drinkers.
Sensitivity (correctly identifying problem drinkers) was 88%, and Specificity (correctly
identifying normal drinkers) was 87%.
K-PIRS 39
The K-PIRS Substance/Addiction Issues scale showed a positive association with the
QPD (r = .40, p < .001).
Discriminant Validity
Well-Being. In order to test the discriminant validity of the K-PIRS, we used the
Satisfaction With Life Scale (SWLS) (Diener, Emmons, Larsen, & Griffin, 1985), which
measures subjective well-being, or satisfaction with life. Developed on a sample of
undergraduate students, SWLS provides respondents with five statements, and asks for a level of
agreement. Higher scores on the SWLS reveal higher levels of life satisfaction, while higher
scores on the K-PIRS reveal higher levels of distress. Correlational results were negative for all
seven K-PIRS scales (p < .001): Mood Difficulties (r = -.48), Learning Problems (r = -.29), Food
Concerns (r = -.23), Interpersonal Conflict (r = -.42), Career Uncertainty (r = -.24),
Substance/Addiction Issues (r = -.18), and Self-Harm Indicators (r = -.23).
Social Desirability. In order to check for the possibility that the K-PIRS items elicit
socially desirable responses, participants were given a shorter version of the Marlowe-Crowne
Social Desirability Scale (Crowne & Marlowe, 1960, Marlowe & Crowne, 1961). For the present
study, the 10-item version abbreviated as MC 2(10) was used. When correlated with the longer
version, reliability for scores from this shortened version was .75 for university women (N = 130)
and .62 for university men (N = 64) (Strahan & Gerbasis, 1972).
No K-PIRS scale correlation with the MC2(10) was positive. Further, test-retest
reliability on the MC 2(10) for our sample was r = .63, p < .001. This result was similar to
published reliability coefficients of .62 for university men and .75 for university women (Strahan
& Gerbasi, 1972).
K-PIRS 40
Convergent validity
To explore convergent validity, we compared K-PIRS scores on two samples—a group of
counselors and a group of clients. This was done in two ways. First, we randomly selected seven
Intake Summaries from the agency’s clinical files, and asked a set of clinicians unfamiliar with
these cases to read each Intake Summary, and then endorse all K-PIRS items that seemed to
apply to the case. The only information used was the narrative summary written by the original
counselor. Eleven full-time clinicians (six women and five men) read the same set of seven cases.
The average number of years employed in a college clinical setting for this group was 21.
For each of the seven cases, the scores of the eleven counselors were collapsed into a
single score. This score was then compared with the client’s actual score, calculated at the time
of intake. Kendall’s Coefficient of Concordance was positive and significant (p < .001) for all
seven estimations. Kendall’s W values ranged between .60 and .80, indicating that counselors
and clients were interpreting the items in ways highly similar ways.
Second, counselors were asked to use the K-PIRS in making an assessment of each new
client’s symptoms immediately following the intake session. Because the clients also completed
the K-PIRS at this same time, we were able to compare the counselor assessment scores with
client scores on all seven scales. The Pearson correlations in Table 14 show that the associations
were positive and significant for each of the seven scales.
K-PIRS 41
Chapter 5 Conclusions
Summary
Two realities in the university milieu provided impetus for the development of the K-
PIRS. One was an earlier finding by our research team (Benton, Robertson, Tseng, Newton, &
Benton, 2003) that there has been an increase in the frequency with which severe issues are
being brought to our counseling center (e.g., depression, sexual assault, and thoughts of suicide).
The other is the interest among some university administrators that various medical and mental
health services may be better provided by “out-sourcing” them. These realities underline the
value of using a screening instrument that assesses client intake problems quickly and efficiently.
If K-PIRS Form B continues to prove useful in following client progress across time or in
demonstrating significant outcomes, then the instrument may provide central university
administrators with meaningful data.
In sum, the K-PIRS offers significant advantages to counseling centers needing a valid
and reliable screening instrument. First, it can identify important treatment factors that go
beyond the presenting symptoms, including a client-reported level of interference with social and
academic functioning, and an indication of client readiness to make changes. Second, the
instrument can be scored quickly, and is therefore suitable for routine use for every incoming
client. Counselors can use the profiles to determine urgency (e.g., overall level of distress score
and the self-harm factor), and to mark issues to examine in more detail during the clinical
interview.
Future Research
K-PIRS 42
The K-PIRS can be used as a research instrument to examine questions relevant to
college counseling center functioning. For example, as data is collected from around the country,
both normative profiles and predictive patterns may emerge regarding a variety of clinical
questions. Additional norms can be compiled by region, gender, ethnicity, and other identifiable
characteristics. Profiles can be formed based on such variables as specific presenting problems,
client demographic variables, or readiness estimates.
Studies may also examine hypotheses about possible correlations between clinical
profiles and other variables, such as persistence with treatment, selection of treatment approaches,
the prediction of a need for more intensive services, or factors that predict successful outcomes.
Some early studies at Kansas State University along these lines suggest patterns that
warrant further research:
• Students with moderate to severe scores on Academic Interference score high on the
Mood Difficulties, Learning Problems, Food Concerns, Interpersonal Conflicts, and
Career Uncertainty scales.
• Students with moderate to severe scores on Social Interference scored high on all
scales except Learning Problems.
• Females report significantly higher scores than males on the Mood Difficulties,
Learning Problems, Food Concerns, and Interpersonal Conflicts scales. Males score
significantly higher on the Substance/Addition scale.
• Students with lower GPAs score significantly higher on the Learning Problems,
Career Uncertainty, and Substance/Addictions scales.
K-PIRS 43
• Seniors and graduate students express significantly less concern about Learning
problems, and graduate students have less concern than undergraduates about
Substance/Addictions Issues
Other studies are beginning to show the utility of the K-PIRS for measuring outcome.
Over the course of therapy, clients have reported drops in their levels of interference with both
academic functioning (from 2.78 to 2.09 on a 4-point scale from 0-3), and social functioning
(from 2.74 to 2.33).
These patterns need further study from other counseling centers around the country.
Limitations
Several cautions must be noted in the use of the K-PIRS.
• Scores on the K-PIRS are not adequate for confirming diagnostic formulations found
in the DSM-IV-TR. Rather, K-PIRS profile scores identify areas that may need
additional information from the clinical interview, or from the selective use of
standardized instruments that examine questions raised by the K-PIRS.
• The K-PIRS is a self-report instrument, and is not designed to detect response
patterns that are deliberately false or random. Thus, the K-PIRS should not be used as
the only source of clinical information at intake.
• The use of the K-PIRS for populations other than university counseling centers is not
recommended, unless additional research suggests otherwise.
• Manual norms and profiles have been developed on a normative sample that includes
weighted proportions of clients and non-clients, an undergraduate and graduate
sample of active clients and a sample of undergraduate non-clients from one setting.
K-PIRS 44
As additional research is generated from other regions, these norms may adjust
slightly.
K-PIRS 45
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K-PIRS 50
Table 1
Means and Standard Deviations for the K-PIRS Clinical Scales, Global Concern Scale, and Interference Items for the Normative
Sample of College Undergraduates (N = 1,716)
____________________________________________________________________________________________________________
Year in School
________________________________________________________________________
K-PIRS Scales First Year Sophomore Junior Senior Total
____________________________________________________________________________________________________________
1. Mood Difficulties Mean 1.57 1.71 1.72 1.72 1.68
SD .52 .60 .62 .63 .60
2. Learning Problems Mean 2.18 2.23 2.19 2.08 2.16
SD .62 .67 .68 .70 .67
3. Food Concerns Mean 1.61 1.65 1.75 1.71 1.68
SD .59 .66 .74 .93 .76
4. Interpersonal Conflicts Mean 1.58 1.65 1.69 1.66 1.65
K-PIRS 51
SD .54 .60 .68 .66 .63
5. Career Uncertainties Mean 2.14 2.12 1.97 1.84 2.00
SD .60 .62 .67 .69 .66
6. Self-Harm Indicators Mean 1.12 1.14 1.10 1.15 1.13
SD .39 .39 .32 .46 .40
7. Substance/Addictions Mean 1.46 1.41 1.42 1.38 1.41
SD .51 .53 .56 .58 .55
Global Concern Score Mean 1.69 1.77 1.76 1.72 1.73
SD .39 .45 .47 .49 .46
Academic Interference Mean 1.91 2.15 2.21 2.30 2.16
SD .82 .90 .88 .95 .91
Social Interference Mean 1.85 1.98 2.12 2.09 2.02
SD .85 .87 .90 .92 .90
____________________________________________________________________________________________________________
Note. First Year n = 400, Sophomore n = 369, Junior n = 383, Senior n = 564. Means and standard deviations are weighted
by Active Client ratios in the larger university population (.10 for Active Client sample and .90 for Non-Client sample), and by
K-PIRS 52
class level proportions (.233 for First Year, .215 for Sophomore, .233 for Junior, and .329 for Senior).
K-PIRS 53
Table 2 T-Score Conversion Table for the K-PIRS Normative Sample of College Undergraduates (N = 1,716)
K-PIRS 54
Note. The client mean score is calculated by summing the total raw score for all the items on a scale and dividing by the number of
items in the scale.
K-PIRS 55
Table 3
Means and Standard Deviations for SOS Items (Significant Other Situations) in the K-PIRS Normative Sample of College
Undergraduates (N = 1,716)
____________________________________________________________________________________________________________
Year in School
________________________________________________________________________
K-PIRS Scales First Year Sophomore Junior Senior Total
____________________________________________________________________________________________________________
Concerned about my safety Mean 1.64 1.67 1.46 1.47 1.55
SD .84 .93 .73 .78 .82
Memories of past sexual abuse/assault Mean 1.14 1.18 1.19 1.14 1.16
SD .50 .59 .60 .50 .55
Recent sexual assault Mean 1.05 1.08 1.04 1.03 1.05
SD .33 .38 .24 .20 .29
Questions related to pregnancy Mean 1.17 1.17 1.05 1.07 1.11
SD .50 .80 .24 .35 .50
K-PIRS 56
Dealing with grief or loss Mean 1.36 1.39 1.45 1.39 1.40
SD .71 .76 .82 .80 .78
Taking risks or chances Mean 1.65 1.67 1.59 1.50 1.59
SD .82 .88 .75 .79 .81
My sexual identity or orientation Mean 1.10 1.15 1.15 1.07 1.11
SD .43 .54 .50 .31 .44
Facing legal issues Mean 1.13 1.20 1.19 1.13 1.16
SD .49 .65 .59 .44 .54
____________________________________________________________________________________________________________
Note. First Year n = 400, Sophomore n = 369, Junior n = 383, Senior n = 564. Scores were weighted by proportions of clients and non-
clients in the larger university population (.10 for clinical sample and .90 for non-clinical sample), and by proportion of class levels
(.233 for First Year Students, .215 for Sophomores, .233 for Juniors, and .329 for Seniors).
K-PIRS 57
Table 4 Reduction in Clinical Symptoms between Intake and Session Three, as Measured by the K-PIRS Form B
____________________________________________________________________________________________________________
K-PIRS Scales Mean, SD Intake Session Three Significance
____________________________________________________________________________________________________________
1. Mood Difficulties Mean 2.33 1.91 **
SD .71 .61
2. Learning Problems Mean 2.22 1.98 **
SD .81 .72
3. Food Concerns Mean 1.84 1.52 **
SD .92 .75
4. Interpersonal Conflicts Mean 2.04 1.76 **
SD .84 .63
5. Career Uncertainties Mean 1.63 1.45 **
SD .66 .55
K-PIRS 58
6. Self-Harm Indicators Mean 1.33 1.13 **
SD .53 .36
7. Substance/Addiction Issues Mean 1.40 1.31 *
SD .71 .64
Global Concern Score Mean 2.03 1.74 **
SD .45 .45
Academic Interference Mean 2.75 2.25 **
SD .98 .82
Social Interference Mean 2.87 2.57 *
SD .91 1.22
____________________________________________________________________________________________________________
Note. N = 135
* p < .05, ** p < .01. Paired samples t-tests for mean differences
K-PIRS 59
Table 5
Cluster Analysis for the K-PIRS: Means and Standard Deviations for Factor Scores across Clusters
____________________________________________________________________________________________________________
Clusters
1 2 3 4 5 6 (n = 294) (n = 98) (n = 67) (n = 213) (n = 99) (n = 95)
F(5,860)/R2 M SD M SD M SD M SD M SD M SD
Factor Scores Mood Difficulties 153.08/.47 1.56 .45 1.91 .56 2.73 .59 2.33 .59 2.36 .64 3.05 .48 Learning Problems 189.00/.52 1.43 .41 2.12 .66 2.53 .60 2.59 .61 2.08 .70 3.13 .50 Food Concerns 313.54/.65 1.16 .28 1.39 .47 2.10 .74 1.40 .38 3.13 .56 2.34 .79 Relationship Conflicts 287.55/.63 1.28 .38 3.11 .52 1.68 .59 1.49 .45 1.49 .52 2.73 .75 Career Uncertainties 70.63/.29 1.29 .36 1.30 .33 1.94 .57 1.56 .49 1.57 .50 2.18 .59 Self-harm Indicators 25.79/.13 1.55 .66 1.56 .62 2.22 .74 1.63 .62 1.68 .64 2.26 .77 Substance/Addiction Issues 185.02/.52 1.17 .39 1.35 .53 2.92 .64 1.21 .37 1.28 .40 1.49 .51 ____________________________________________________________________________________________________________
K-PIRS 60
Table 6
Promax Rotated Pattern Matrix of Exploratory Factor Analysis of the K-PIRS ____________________________________________________________________________________________________________ Pattern Matrix Coefficients ____________________________________________________________ Factor Labels and Individual Items 1 2 3 4 5 6 7 h2
____________________________________________________________________________________________________________ Factor 1: Mood Difficulties
Depressed mood .88 -.14 .01 -.09 -.05 .10 .01 .69
Excessive worry .76 .04 -.12 -.02 .02 -.18 -.04 .48
Bored or unhappy with life .75 -.18 -.08 -.04 .14 .11 .09 .57
Lost interest in activities .74 -.01 .01 -.09 .10 -.04 .08 .54
Loss of energy, fatigued .73 .03 .06 -.01 -.02 -.05 -.06 .53
Changes in sleep patterns .71 .08 .06 -.16 -.10 -.02 .09 .51
No close personal friendships .67 -.17 -.02 .04 .03 .12 -.06 .45
Anxiety attacks .65 .16 .02 -.13 -.10 -.05 -.09 .43
Lost hope that life will improve .64 .08 -.07 .10 .09 .24 -.01 .55
K-PIRS 61
Feel shy or timid .59 -.03 .01 .08 .12 .03 .08 .38
Feeling agitated or restless .59 .11 .05 .17 -.07 -.14 -.06 .51
Excessive tearfulness or crying .57 -.09 .03 .16 -.02 .11 -.14 .44
Low self-esteem .52 -.03 .15 .12 .10 .10 -.01 .49
Mood swings .50 -.03 .10 .27 -.05 -.04 .05 .50
Feel out of place on this campus .50 .02 -.04 .11 .19 .05 -.03 .42
Factor 2: Learning Problems
Trouble memorizing -.13 .87 -.01 .08 -.04 .08 -.05 .66
Working hard, but getting poor grades -.26 .84 -.05 .03 .10 .11 -.06 .59
Test anxiety -.17 .79 .09 -.04 -.02 .13 -.04 .55
Making careless mistakes in math and writing -.07 .70 .03 -.07 .03 .05 -.07 .46
Focusing or paying attention .35 .63 -.03 -.03 -.10 -.14 -.01 .65
Difficulty concentrating .39 .63 -.04 -.05 -.11 -.10 .03 .67
Though smart in many ways, at times I feel stupid .20 .56 -.07 .05 .06 .04 .08 .52
Time management .10 .54 .01 .07 .16 -.10 .08 .49
Factor 3: Food Concerns
K-PIRS 62
Food controls my life -.09 -.04 .92 .03 .03 .02 -.07 .76
My weight interferes with my daily life -.04 -.02 .90 -.03 .03 .09 -.04 .78
My eating habits .10 .02 .84 -.03 .02 -.05 .07 .79
Nutrition or exercise habits .05 .05 .75 .07 .06 -.11 .08 .62
Recent significant weight change .10 .07 .63 -.05 -.07 -.09 .09 .47
Factor 4: Interpersonal Conflicts
My anger or arguing -.02 -.03 -.04 .83 -.04 -.08 .03 .67
Unsolved conflicts with others -.07 -.04 -.02 .79 -.05 -.07 -.03 .52
Difficulty controlling angry thoughts and actions -.01 .05 -.04 .72 .03 .09 .04 .59
Feel misunderstood or mistreated .20 .02 .08 .55 -.05 .03 .06 .47
Difficulty trusting other people .28 .04 .01 .45 -.09 .07 -.02 .47
Factor 5: Career Uncertainties
Unsatisfied with my current major .08 -.01 -.01 -.05 .87 -.05 -.02 .76
Pressured by others to choose the right major -.03 .02 .06 .08 .80 .03 -.05 .65
Choosing the right major/career .07 .09 -.04 -.04 .72 -.05 .02 .57
Factor 6: Self-Harm Indicators
K-PIRS 63
Intentions of suicide .09 .10 -.01 -.08 -.04 .89 .01 .82
Recent thoughts of suicide .21 .04 -.05 -.08 -.04 .85 -.01 .82
Hurting myself (i.e., cutting, burning, bruising) -.10 .07 .06 .20 .02 .49 .06 .34
Factor 7: Substance/Addiction Issues
My use of alcohol/drugs -.02 -.04 -.02 -.04 .02 -.02 .91 .79
Others worry about my use of alcohol and/or drugs -.10 -.05 -.04 .02 -.06 .05 .89 .76
Addiction concerns -.08 .09 .15 .06 -.02 .11 .49 .35
_________________________________________________________________________________________________________
Note. N = 872. The solution accounted for 57 percent of the total variance. Since an oblique rotation method was used, the percent of
variance for each factor cannot be calculated. h2 = final communality estimates. Highest value for an item is in bold type. Structure
matrix is available upon request.
K-PIRS 64
Table 7
K-PIRS Component Factor Correlation Matrix for the Oblique Solution
____________________________________________________________________________________________________________
Factor 1 2 3 4 5 6 7
1 .47 .40 .51 .18 .37 .25
2 .26 .22 .23 .02 .18
3 .24 .12 .14 .18
4 .13 .31 .26
5 .13 .16
6 .23
Note. Coefficients > .12 significant at the p < .01 level.
K-PIRS 65
Table 8
Overall Fit Indices for the Seven Components of the K-PIRS
____________________________________________________________________________________________________________ Model Chi-Square df NFI GFI AGFI RMR RMSEA CFI ____________________________________________________________________________________________________________ Independence Model 16,324.71** 861 Model 1 4,362.38** 798 .78 .79 .77 .07 .08 .82 Independence Model 48,840.95** 861 Model 2 4,170.22** 798 .95 .96 .96 .06 .07 .97 Model 3 1,381.37** 636 .97 .98 .97 .04 .04 .99 ____________________________________________________________________________________________________________ Note. df = degrees of freedom; NFI = Normed Fit Index; GFI = Goodness of Fit Index; AGFI = Adjusted Goodness of Fit Index; RMR
= Root Mean Square Residual; RMSEA = Root Mean Square Error of Approximation Residual; CFI = Comparative Fit Index.Model 1:
maximum likelihood estimation; Model 2: unweighted least squares; Model 3: unweighted least squares and correlated errors within
scales.
**p < .001
K-PIRS 66
Table 9
Means, Standard Deviations, Standard Errors of Measurement, and Cronbach Alpha Reliabilities With 95% Confidence Intervals for
K-PIRS Symptom Variable Raw Scores in a Normative Sample of College Students (N = 1,716)
____________________________________________________________________________________________________________
Variables Items M SD SEM 1 2 3 4 5 6 7
____________________________________________________________________________________________________________
Symptom Scales
1 Mood Difficulties 15 27.77 10.33 3.10 (.9078a)(.9077, .9078)
2 Learning Problems 8 17.71 5.84 2.34 (.8417a) (.8417, .8418)
3 Food Concerns 5 8.38 3.75 1.67 (.8019a) (.8018, .8020)
4 Interpersonal Conflicts 5 8.77 3.52 1.61 (.7893a) (.7893, .7895)
5 Career Uncertainties 3 5.84 2.10 1.37 (.5725) (.5724, .5728)
6 Self-Harm Indicators 3 3.59 1.43 0.65 (.7938a) (.7938, .7940)
7 Substance/Addiction 3 4.17 1.64 1.08 (.5629) (.5628, .5632)
____________________________________________________________________________________________________________
K-PIRS 67
Note. Cronbach alpha reliabilities for the scales, along with 95% confidence intervals are reported in the parentheses in the diagonals.
aReliability coefficient significantly greater than hypothesized value of .70, p < .001. Normative sample includes both Active Clients
and Non-Clients in weighted proportions that represent the general university population.
K-PIRS 68
Table 10
Means, Standard Deviations, Standard Errors of Measurement, and Cronbach Alpha Reliabilities With 95% Confidence Intervals for
K-PIRS Symptom Variable Raw Scores in Active Client Sample of College Students (N = 917)
________________________________________________________________________________________________________
Variables Items M SD SEM 1 2 3 4 5 6 7
________________________________________________________________________________________________________
Symptom Scales
1 Mood Difficulties 15 32.61 10.89 3.43 (.9011a)(.9011, .9013)
2 Learning Problems 8 17.72 6.71 2.33 (.8791a) (.8791, .8793)
3 Food Concerns 5 8.47 4.22 1.39 (.8914a) (.8914, .8916)
4 Interpersonal Conflicts 5 9.84 4.02 1.82 (.7947a) (.7947, .7950)
5 Career Uncertainties 3 5.13 2.22 1.30 (.6564) (.6563, .6567)
6 Self-Harm Indicators 3 3.86 1.60 0.77 (.7679a) (.7678, .7682)
7 Substance/Addiction 3 3.95 1.68 0.92 (.7016) (.7015, .7019)
________________________________________________________________________________________________________
K-PIRS 69
Note. Cronbach alpha reliabilities for scales, along with 95% confidence intervals are reported in the parentheses in the diagonals.
aReliability coefficient significantly greater than hypothesized value of .70, p < .001.
K-PIRS 70
Table 11
Means, Standard Deviations, Standard Errors of Measurement, and Cronbach Alpha Reliabilities With 95% Confidence Intervals for
K-PIRS Symptom Variable Raw Scores in Non-Client Sample of College Students (N = 932)
________________________________________________________________________________________________________
Variables Items M SD SEM 1 2 3 4 5 6 7
________________________________________________________________________________________________________
Symptom Scales
1 Mood Difficulties 15 23.59 7.64 2.77 (.8684a)(.8684, .8686)
2 Learning Problems 8 17.35 4.96 2.22 (.7997 a) (.7997, .8000)
3 Food Concerns 5 8.20 3.25 1.85 (.6746) (.6746, .6750)
4 Interpersonal Conflicts 5 7.89 2.17 1.45 (.7143a) (.7143. .7146)
5 Career Uncertainties 3 6.34 1.83 1.30 (.4939) (.4937, .4944)
6 Self-Harm Indicators 3 3.32 1.00 0.49 (.8052a) (.8052, .8054)
7 Substance/Addiction 3 4.33 1.56 1.17 (.4340) (.4338, .4346)
________________________________________________________________________________________________________
K-PIRS 71
Note. Cronbach alpha reliabilities for scales, along with 95% confidence intervals are reported in the parentheses in the diagonals.
aReliability coefficient significantly greater than hypothesized value of .70, p < .001.
K-PIRS 72
Table 12
Standard Errors of Measurement (SEM) and Test-Retest Reliabilities With 95% Confidence Intervals for K-PIRS Symptom Variable
Raw Scores in a Sample of Active Clients
________________________________________________________________________________________________________
Variables Items N SEM 1 2 3 4 5 6 7
________________________________________________________________________________________________________
Symptom Scales
1 Mood Difficulties 15 135 5.90 (.64) (.53, .73)
2 Learning Problems 8 135 3.39 (.69 ) (.59, .77)
3 Food Concerns 5 135 1.93 (.78) (.70, .84)
4 Interpersonal Conflicts 5 136 2.21 (.64 ) (.53, .73)
5 Career Uncertainties 3 135 1.04 (.67 ) (.57, .76)
6 Self-Harm Indicators 3 134 0.99 (.45) (.33, .58)
7 Substance/Addiction 3 121 0.94 (.78) (.70, .84)
________________________________________________________________________________________________________
K-PIRS 73
Note. Test-retest reliabilities for scales, along with 95% confidence intervals are reported in the parentheses in the diagonals. All
scales were significant at p < .01.
K-PIRS 74
Table 13
Correlations between K-PIRS Scales and Seven Validation Instruments (N = 234)
____________________________________________________________________________________________________
K-PIRS Scale Validation Instrument Pearson r Contingency Coefficient ____________________________________________________________________________________________________ Mood Difficulties Beck Depression Inventory-II .76*** Learning Problems Adult Learning Disability Screening .48*** Food Concerns Eating Attitudes Test-26 .63*** Interpersonal Conflicts Aggression Questionnaire .45*** Career Uncertainties Career Decision Profil e .51*** Self-Harm Indicators aBeck Scale for Suicide Ideation .42*** Beck Depression Inventory-II .33*** Substances/Addictions Questionnaire for Problem Drinkers .40*** ______________________________________________________________________________________________________ Note. aDifferences in scale scoring procedures between the BSSI and Self-Harm Indicators resulted in a decision to conduct a chi-
square test for independence, which produced a contingency coefficient that can be interpreted similarly to a Pearson correlation.
*** p < .001.
K-PIRS 75
Table 14 Convergent Validity of the K-PIRS: Correlations between Client Scores and Counselor Assessments on the Seven Scales at Intake
_________________________________________________________________________________________________________
Factor Name Pearson r Sample Size
_________________________________________________________________________________________________________
Mood Difficulties .53* 570
Learning Problems .67* 564
Food Concerns .71* 566
Interpersonal Conflicts .61* 568
Career Indecision .46* 565
Self-Harm Indicators .54* 561
Substance/Addiction Issues .74* 560
_________________________________________________________________________________________________________
Note. The significance tests were 2-tailed. In the full correlation matrix, the diagonals always showed the highest correlations;
therefore, only the diagonals are shown here. Correlations were calculated on raw scores.
*p <.001
K-PIRS 76
Figure 1. K-PIRS Profile Charts and clinical interview information for six clients
Client #1001 shows elevations (T-Scores higher than 60) on three Scales: Mood Difficulties,
Interpersonal Concerns, and Self-Harm Indicators. Also elevated, although not as highly, were
concerns with academic and social functioning. This client was an adult graduate student with an
international background who presented multiple concerns to her therapist: depressive and
anxiety symptoms, low self esteem, a conflicted relationship, and developmental issues.
Consistent with her high score on Scale 6, she reported that she had been cutting on her body,
and that she had been having thoughts of suicide as a wish for release, but that she had no plan or
intent to harm herself. She had been taking medication for sleep. She was given a GAF score of
55.
K-PIRS 77
The Profile Chart for Client #1002 shows T-Scores above 60 on both Learning Problems and
Career Uncertainties. He also scored high on the Academic Interference scale. In the clinical
interview, this client reported feeling unmotivated to do academic work: he was missing classes,
earning poor grades, feeling distracted from study, finding it difficult to manage his time,
struggling with concentration, and feeling generally lethargic about his academic role. He
commented that his current major of engineering matched his father’s career. When questioned
further, he indicated that his motivation to take engineering classes was more external (his
parents’ wishes) than internal (his own desires, needs, and experiences). Consistent with his low
score on Scale 4, he reported strong relationship and social support. Note also the relatively high
score on Self-Harm Indicators, focusing attention on a question that might sometimes be
overlooked when conducting an intake with a student who presents only with academic and
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career questions. In this case, the initial counseling focus was on client safety concerns, and then
moved to examine the possibility of learning disabilities, given his high score on Scale 2. Finally,
career issues were addressed in the context of family dynamics.
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Client #1003 scored very high on Food Concerns (T = 80), and also scored high (above T = 60)
on Mood Difficulties, Self-Harm, and Addictions/Substance Issues. These concerns clearly were
having an impact on both Academic Functioning and Social Functioning. During the clinical
interview, the client requested an evaluation for his mood concerns, and also admitted that he
would often overeat and follow high food consumption with periods of fasting. The client
described himself as socially “more of a loner”. These patterns led the counselor to recommend
that the client take a personality inventory (in this case, the Millon™ Clinical Multiaxial
Inventory-III) to assess for possible personality disorders. He showed few clinically elevated
scales but deflected feelings of isolation and boredom with comfort eating and somewhat masked
depressive symptoms.
K-PIRS 80
Example #1004 shows very high scores on Mood Difficulties and Interpersonal Conflicts, both
about three standard deviations above the mean. The interference with Social Functioning is
significantly above the mean, with some corresponding elevation on Academic Functioning. In
the interview, the client reported that she had recently made a significant geographical move and
was starting in a professional program. She was feeling very anxious about the adjustment to the
new setting, and was having difficulty with a now long distance relationship. These factors led to
some short term goals: monitoring her mood and any thoughts of self-harm, finding social
support in her new environment, and making decisions about her relationship.
K-PIRS 81
Client Profile Chart #1005 reflects a very high score for Career Uncertainties, with additional
elevations for Learning Problems and Eating Concerns. Both of the Interference with
Functioning scores were high, as well. This client presented with multiple concerns about her
inability to concentrate, manage her daily tasks, and perform well in her major. She had joined a
career decisions group but did not find the group helpful. A referral to the counseling center was
made by the facilitator of the career group. The high score on Learning Problems led to a
discussion of attention difficulties, and an ADHD assessment was positive. A medication
regimen was started. At this point, with an increased ability to focus, the client was able to
address her career concerns with more clarity, and her eating concerns faded.
K-PIRS 82
Client #1006 reflects a very high concern with Substances or Addictions, and a high concern for
Self-Harm. Factor 1 (Mood Difficulties) is also elevated. Combined, these concerns were
interfering with both Academic and Social Functioning for this student. At the time of the
clinical interview, the counselor gave a Global Assessment Functioning score of 55 (Axis V on
the DSM-IV-TR). The client was asked to come to the counseling center by a family member.
The interview provided the story that had elevated the scores. He was facing numerous problems
from the abuse of multiple substances—possession of illegal drugs, recovery from an accident, a
history of substance abuse treatment, current use of marijuana and the overuse of prescription
pain medication obtained without a prescription. Not surprisingly, he also reported that he was
missing classes. Motivation to seek counseling initially was attributed to mother’s continued
support. These issues led to an agreement to begin counseling by addressing his use of illegal
substances.
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Figure 2. K-PIRS Form B Profile Charts and clinical information for two clients, showing
symptom change over time
Client #8 is a 20-year old woman who transferred from a community college. She had sought
counseling previously to address childhood abuse issues, excessive alcohol use, and relationship
conflicts. The presenting problems at this intake included maintaining some stability in a dating
relationship, dealing with a lingering concern about alcohol use (blackouts had occurred), and
managing the stress of her academic challenges while working 30 hours per week. She had found
her previous counseling to be helpful in working through her family of origin issues, and she
hoped for similar help in addressing her current issues. Her intake K-PIRS profile is shown in
red, and reveals significant elevations on six different scales, as well as the Academic and Social
functioning items. Counseling began, and she was given the K-PIRS again after the 3rd
K-PIRS 84
counseling session. Notice that her profile chart shows reduced scores on all seven scales, within
a single standard deviation of the mean on all scales except for Career Uncertainty. At this point
the client completed a career assessment and made a decision to change majors. After her 6th
session, a second follow-up evaluation was conducted. This time, all scores fell within the one
standard deviation of the mean. She no longer reported that her problems were interfering with
either her academic or social situation. At termination, the client reported that she was satisfied
with her new major, had a good peer support system, and was feeling more in control of her life.
Her counselor gave her a GAF of 80.
K-PIRS 85
Client #9 was a 5th year senior in majoring in education. He presented with concerns about both
anxiety and depression. Yet the K-PIRS profile reflected what would look like a flat or
suppressed reporting of symptoms, except for a high elevation on the Self-Harm scale. The
clinical interview revealed that the client was feeling insecure and shy, and was worried about
being a senior without a significant dating relationship. This led to a series of questions that
highlighted the mood disorder, revealing significant vegetative symptoms (an especially
common presentation of depression among men). The Self-Harm score led to questions that
allowed him to admit that his discouragement was related to thoughts about the worth and value
of his life. But he had no suicidal plans, and had not made any gestures. After the 3rd session, the
client reported more distance from his problems, noting that he seemed to be looking at his life
from the outside. He acknowledged that previously, he had acted passively and with a fear of
failure. Counseling then moved to an existential examination of his lack of personal meaning
when he was only “reflecting and not acting.” This perspective left him feeling considerable
K-PIRS 86
angst. Form B after the third session reflected this angst on the Self-Harm scale. At this point, the
counselor challenged him to initiate social contact, deal with fears of rejection, and utilize a
behavior change strategy that focused on engagement rather than reflection. His Self-Harm score
dropped. The client noted at termination that he felt better at focusing on “what he does have,”
and was acting to make progress socially. He also reported no significant interference with his
academic or social functioning.
K-PIRS 87
Appendix A
Printable version of K-PIRS Form B
______________________________________________________________________________________________
Student ID# For Office Use Only:
Session # Doctor #
Institution # ____________________________
CLIENT EVALUATION OF COUNSELING
Please respond to this questionnaire as honestly and accurately as you can. Your responses will help evaluate counseling progress and outcomes. All information will remain confidential; no identifying
information will be released.
I. Please estimate how much your problems are presently affecting the following areas of your life: Academic Social1 No interference 1 No interference 2 Mild 2 Mild 3 Moderate 3 Moderate 4 Severe 4 Severe
II. Overall, counseling has been helpful to me.
1 Strongly Disagree 2 Somewhat Disagree 3 Somewhat Agree 4 Strongly Agree
N/A Not Applicable
Rate your level of functioning in the following areas since beginning counseling: 1 No Improvement 2 Slight Improvement 3 Moderate Improvement 4 Substantial Improvement Making important decisions Relating to significant people in my life Achieving goals I have set Coping with problem situations
1 1 1 1
2 2 2 2
3 3 3 3
4 4 4 4
Maintaining health and well-being Progress on therapy goals Symptoms/concerns that brought you to counseling Academic performance
1 1 1 1
2 2 2 2
3 3 3 3
4 4 4 4
Please rate how much each item concerns you now.
1 No Concern 2 Little Concern 3 Moderate Concern 4 Significant Concern
1. Choosing the right major/career 1 2 3 4 26.Feel shy or timid 1 2 3 42. My use of alcohol/drugs 1 2 3 4 27.Excessive worry 1 2 3 43. Working hard, but getting poor grades 1 2 3 4 28.Questions related to pregnancy 1 2 3 44. Test anxiety 1 2 3 4 29.Nutrition or exercise habits 1 2 3 45. Excessive tearfulness or crying 1 2 3 4 30.Dealing with grief or loss 1 2 3 46. Feel misunderstood or mistreated 1 2 3 4 31.Making careless mistakes in math or writing 1 2 3 47. Intentions of suicide 1 2 3 4 32.Low self-esteem 1 2 3 4
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88
8. Recent thoughts of suicide 1 2 3 4 33.Unsatisfied with my current major 1 2 3 49. Lost hope that life will improve 1 2 3 4 34.Difficulty trusting other people 1 2 3 410.Unresolved conflicts with others 1 2 3 4 35.Lost interest in activities 1 2 3 411.Food controls my life 1 2 3 4 36.Changes in sleep patterns 1 2 3 412.Feeling agitated or restless 1 2 3 4 37.No close personal friends (lonely) 1 2 3 413.My anger or arguing 1 2 3 4 38.Feel out of place on this campus 1 2 3 414.Trouble memorizing 1 2 3 4 39.Time management 1 2 3 415.Others worry about my use of alcohol/drugs 1 2 3 4 40.Mood swings 1 2 3 416.Though smart in many ways, at times I feel stupid 1 2 3 4 41.My eating habits 1 2 3 417.Concerned about my safety 1 2 3 4 42.Taking risks or chances 1 2 3 418.Difficulty concentrating 1 2 3 4 43.My sexual identity or orientation 1 2 3 419.Focusing or paying attention 1 2 3 4 44.Pressured by others to choose the right major 1 2 3 420.Memories of past sexual abuse/assault 1 2 3 4 45.Facing legal issues 1 2 3 421.Recent sexual assault 1 2 3 4 46.Difficulty controlling angry thoughts/actions 1 2 3 422.Hurting myself (e.g., cutting, burning, bruising) 1 2 3 4 47.Anxiety attacks 1 2 3 423.My weight interferes with my daily life 1 2 3 4 48.Recent significant weight change 1 2 3 424.Bored or unhappy with life 1 2 3 4 49.Depressed mood 1 2 3 425.Loss of energy, fatigued 1 2 3 4 50.Addiction concerns__________ 1 2 3 4 (gambling, computer, nicotine, pornography, sex, etc)
K-PIRS 89
Appendix B
K-PIRS Means and Standard Deviations for an Active Client Sample (N = 917) of Undergraduate and Graduate Students at
Assessment
____________________________________________________________________________________________________________
Year in School
________________________________________________________________________
K-PIRS Scales First Year Sophomore Junior Senior Graduate Total
____________________________________________________________________________________________________________
1. Mood Difficulties Mean 2.33 2.10 2.24 2.15 2.09 2.18
SD .75 .76 .73 .68 .72 .73
2. Learning Problems Mean 2.41 2.27 2.37 2.11 1.91 2.21
SD .83 .85 .87 .80 .76 .84
3. Food Concerns Mean 1.70 1.69 1.79 1.70 1.55 1.69
SD .80 .85 .92 .84 .76 .84
K-PIRS 90
4. Interpersonal Conflicts Mean 2.04 1.86 2.08 1.94 1.98 1.98
SD .79 .81 .82 .81 .76 .80
5. Career Uncertainties Mean 1.91 1.81 1.74 1.61 1.51 1.71
SD .78 .80 .76 .67 .65 .74
6. Self-Harm Indicators Mean 1.42 1.30 1.29 1.27 1.17 1.29
SD .67 .52 .54 .53 .32 .54
7. Substance/Addictions Mean 1.36 1.29 1.41 1.29 1.24 1.32
SD .56 .54 .65 .53 .48 .56
Global Concern Score Mean 2.06 1.92 2.04 1.90 1.80 1.94
SD .54 .53 .53 .49 .50 .52
Academic Interference Mean 2.91 2.77 2.93 2.81 2.74 2.83
SD .95 1.01 .97 .96 1.05 .98
Social Interference Mean 2.72 2.66 2.77 2.75 2.70 2.72
SD .89 .95 .86 .87 .93 .90
____________________________________________________________________________________________________________
K-PIRS 91
Note. First Year n = 139. Sophomore n = 192. Junior n = 192. Senior n = 261. Graduate n = 133. Means and standard deviations are
unweighted to reflect the real-world clinical setting in which the results were collected. Demographically, 33% of the sample was
male, 15.2% were first year students, 20.9% were sophomores, 20.9% were juniors, 28.5% seniors, and 14.5% were graduate students.
Ethnically, 81.6% of the sample self-identified as White/Non-Hispanic, 4.9% as Black/Non-Hispanic, 3.1% as Asian/Pacific Islander,
2.1% as Hispanic, 1.5% as Mexican American, 1.3% as Multiracial, and .4% as Native American/Alaskan Native, and 1.0% as Other.
The rest checked Choose not to Respond (3.9%), or did not respond (.2%) to the question about ethnicity.
K-PIRS 92
Appendix C T-Score Conversion Table for an Active Client Sample (N = 917) of Undergraduate and Graduate Students at Assessment
K-PIRS 93
Appendix D
K-PIRS Means and Standard Deviations for a Non-Client Sample of Undergraduates (N = 932)
____________________________________________________________________________________________________________
Year in School
________________________________________________________________________
K-PIRS Scales First Year Sophomore Junior Senior Total
____________________________________________________________________________________________________________
1. Mood Difficulties Mean 1.55 1.64 1.59 1.57 1.59
SD .49 .55 .52 .53 .52
2. Learning Problems Mean 2.17 2.22 2.14 2.08 2.15
SD .61 .64 .61 .67 .64
3. Food Concerns Mean 1.61 1.65 1.75 1.71 1.68
SD .58 .63 .69 .96 .76
4. Interpersonal Conflicts Mean 1.56 1.62 1.60 1.56 1.58
SD .52 .55 .61 .57 .57
K-PIRS 94
5. Career Uncertainties Mean 2.15 2.17 2.02 1.92 2.05
SD .59 .57 .64 .68 .64
6. Self-Harm Indicators Mean 1.11 1.11 1.06 1.11 1.10
SD .38 .37 .22 .42 .36
7. Substance/Addictions Mean 1.46 1.43 1.42 1.40 1.42
SD .50 .52 .54 .59 .54
Global Concern Score Mean 1.68 1.74 1.69 1.67 1.69
SD .38 .43 .43 .48 .44
Academic Interference Mean 1.88 2.04 2.03 2.13 2.03
SD .79 .83 .76 .88 .83
Social Interference Mean 1.82 1.87 1.95 1.86 1.87
SD .83 .81 .84 .83 .83
____________________________________________________________________________________________________________
Note. First Year n = 217, Sophomore n = 200, Junior n = 208, Senior n = 307. Means and Standard Deviations are weighted by class
level proportion in the larger university population from which the sample was drawn: First Year (.233), Sophomore (.215), Junior
(.233), Senior (.329). Demographically, this sample was 44.7% male, 60.9% first year students, 17.6% sophomores, 10.9% juniors,
K-PIRS 95
and 10.6%% seniors. Ethnically, this sample was 87.3% White/Non-Hispanic, 4.5% Black/Non-Hispanic, 1.5% Asian/Pacific Islands,
1.5% Multiracial, 1.2% Mexican American, .9% Hispanic, .3% Native American/Alaskan Native, and 1.2% Other. The rest did not
respond to the ethnicity question.
K-PIRS
96
Appendix E
T-Score Conversion Table for a Non-Client Sample of Undergraduates (N = 932)