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Running Head: PERSONALITY ASSESSMENT TRAINING

Trends in Training and Trainee Competence in Personality Assessment across Health Service

Psychology Doctoral Students: A Pilot Study

Paul B. Ingram, PhD1 Matthew R. Cribbet, PhD2 Adam T. Schmidt1, PhD

Texas Tech University1

University of Alabama2

Author Notes. Portions of this paper were presented at the 2018 MMPI-2-RF/MMPI-2/MMPI-A-

RF/MMPI-A Research Symposium. Paul Ingram receives research funding from Pearson, the

distributor of several assessment instruments reported on within this paper. Correspondence

concerning this article should be addressed to Paul B. Ingram, PhD., Texas Tech University,

2810 18th Street, Lubbock, TX 79423. Email: [email protected] Phone: (806) 834-3354

© 2019, American Psychological Association. This paper is not the copy of record and

may not exactly replicate the final, authoritative version of the article. Please do not copy

or cite without authors' permission. This article is in press with Training and Education in

Professional Psychology. The final article will be available, upon publication, via its DOI:

10.1037/tep0000249

mailto:[email protected]

PERSONALITY ASSESSMENT TRAINING 2

Abstract

This investigation surveyed students (n = 91) from 16 American Psychological Association

accredited doctoral programs in Clinical and Counseling Psychology about knowledge and

training in personality assessment. We report self-perceived competency on specific instruments

as well as training trends in coursework and instrument exposure in clinical settings. We also

evaluate skill at interpretation on a popular personality instrument using two tasks, a narrative

interpretation where trainees estimate an originating score profile using a standardized

interpretive report and a symptom probability task where trainees predict the likelihood of

symptoms based on a score profile. The Minnesota Multiphasic Personality Inventory-2 and

Personality Assessment Inventory were the most frequently trained and utilized and had the

highest self-perceived competence. When given interpretation tasks to evaluate assessment skills

using the MMPI-2-RF, trainee performance was variable and discrepant from a comparison

expert panel given the same tasks. Overall, our results suggest that there is a need for further, and

more comprehensive, study on competence and training according to the experience of trainees.

We note that there is variability across instruction on instrument use, exposure to instruments in

practice, and practical skill level. We highlight our findings across four conceptual areas and

discuss the implications for the observed trends: frequency of instrument exposure, trainee

beliefs of competence, trainee interpretation skills, and reporting of testing interpretation.

Public Significance Statement: This pilot study provide the first evaluation of assessment

training patterns as reported by health service psychology trainees. Results indicate that, in

general, trainee instrument exposure and use mirror those of practicing psychologists; however,

there is notable variability in how assessment results are reported and in trainee competency.


Additional research evaluating health service psychology training should utilize student

participants so that direct evaluations of competency and outcomes are possible.

Keywords: Personality, Psychological Assessment, Training, Competence


Trends in Training and Trainee Competence in Personality Assessment across Health Service

Psychology Doctoral Students: A Pilot Study

Assessment is an integral and consistent part of a psychologist’s work and professional

identity. It has been identified by the American Psychological Association (APA) as a critical

component of clinical training (Kaslow et al., 2004; Krishnamurthy et al., 2004; Rodolfa et al.,

2005; Rodolfa et al., 2013) and represents a core area needed for program accreditation (APA,

2017). Given its central role during training, it is unsurprising that a recent survey found that a

small majority (58%) of practicing psychologists report performing psychological assessments

(Norcross & Karpiak, 2012). In fact, practicing psychologists spend, on average, 24% of their

time engaged in some form of assessment (Wright et al., 2016).

Given the wide use of assessment in clinical practice and its cornerstone in professional

psychology, even training in specialized assessment has seen an increase (e.g., neuropsychology;

Ready & Veague, 2014) despite a historical tendency towards limited coverage during training

(Krishnamurthy et al., 2004; Pidano & Whitcomb, 2012). An increasing emphasis on training in

assessment has coincided with the development of a set of competencies set forth by the

Psychological assessment work group of the competencies conference (Krishnamurthy et al.,

2004). Personality assessment has been previously recognized as a health service proficiency

within the field and is currently under review for renewal (Commission for Recognitions of

Specialties and Proficiencies in Professional Psychology, 2014). The Society of Personality

Assessment (SPA) (2006) has also identified key domains that should be covered during

assessment training. This includes having two or more courses in graduate education (which

includes coverage of psychometric theory, instrument selection and use, and data integration) as

well as supervised practice. However, training components are vaguely described and primarily


serve to reinforce the role of doctoral training in assessment competence without providing clear

competency benchmarks for such training (SPA, 2006). In turn, assessment training practices,

particularly within personality assessment, need further advancement (Kaslow & Egan, 2017)

and are understudied (Smith, 2017). Accordingly, internship directors view only a minority of

their training candidates as having sufficient experience for the critical assessment practice of

report writing (Ready, Santorelli, Lundquist, & Romano, 2016; Stedman, Hatch, & Schoenfeld,

2001). While general domains for a competence framework have been identified (e.g.,

knowledge, skills, and attitudes about their integration; Kaslow, 2018), little has been done to

evaluate outcomes on the fusion of training program components and those of the field. Domains

of needed competence in assessment exist (APA, 2017; SPA, 2006); however, they are often

vague and describe students needing competency without describing what competency entails.

This vagueness allows for latitude in training and subsequent variability in outcomes.

Presently, personality assessment lacks a framework for evaluating competency (Kaslow,

Finklea, & Chan, 2018) and still needs conceptual frameworks through which skills are taught

and conceptual knowledge is used to inform treatment in a unified manner (Blais & Hopwood,

2017). Accordingly, quality and consistency of personality assessment training is difficult to

evaluate reliably and may be declining relative to other areas of assessment (e.g.,

neuropsychological testing, self-report measures, etc.; Ready & Veague, 2014). Fortunately,

there is some work being done to evaluate assessment training practices. However, that work is

based on reports by training directors about what is typically offered, required, or obtained as

part of the program of study and is not based on trainee responses (e.g., Mihura, Roy, Graceffo,

2017; Ready & Veague, 2014).


While part of the difficulty with promoting assessment competence may relate to

insufficient training exposure (Cook et al., 2017), another issue may be in how test performance

is evaluated and communicated in reports (Cox, Cox, & Caplan, 2013). Some research has been

done to improve and standardize assessment reporting and interpretation; however, this work has

focused almost exclusively on neuropsychological assessment. For example, Guilmette, Hagan,

and Giuliano (2008) noted that when board-certified neuropsychologists were asked to assign

descriptive (qualitative) labels to test scores representing cognitive functioning, there was

substantial variability among individuals. They also found that roughly 33% of

neuropsychological reports excluded any form of explicit score information (i.e., raw item

endorsement, scaled/standardized score, or percentile rank) which made interpretation more

prone to error. Likewise, Schoenberg and Rum (2017) described a pattern of inconsistent use of

qualitative descriptors due to different score interpretation approaches. While some variability is

expected because of the debate between what constitutes pathological and normal functioning

(e.g., Axelrod, & Wall, 2007; Binder, Iverson, & Brooks, 2009), variation in interpretation can

lead to different diagnoses and treatment recommendations (Hagan & Guilmette, 2015). Thus,

despite some efforts to increase awareness of how results are reported and to promote a more

standardized approach, there remains limited work in this area. Moreover, the work that has been

done has focused exclusively on the areas of cognition and memory using samples of

neuropsychologists who have long been in practice.

While work in the interpretation standardization for neuropsychology is helpful to

promoting the assessment proficiency, the guidance offered for that form of testing does not

translate well to the practice of personality measurement. The types of diagnostic labels and

descriptions common to neuropsychological reports (e.g., consistent with IQ, intact, grossly


intact, borderline impaired; Guilmette et al., 2008) vary from how test scores are interpreted in

personality testing, where clinicians are usually attempting to ascertain the likelihood of a given

set of behaviors, sensations, emotions, or perceptions. Thus, not only is it unclear what

constitutes standard training practices for personality assessment, there are no standard

interpretive schemas to guide students as they develop skills in this critical area of practice. Not

having a standardized basis for the interpretation, or even an understanding for what is a typical

skillset for doctoral level trainees, is concerning since most internship training programs

(frequently the final required formal training stop before a psychologist can engage in

independent practice) consider personality assessment as an essential competency for trainees to

develop (Stedman et al., 2017). It is difficult to ensure knowledge is measured reliably: (1) if

standard training practices are unknown, (2) if outcome expectations are inconsistent or poorly

defined, or (3) if outcomes and perceptions of trainees themselves are not assessed.

This pilot study examines assessment training practices and outcomes in a sample of

APA-approved clinical and counseling psychology doctoral programs. Specifically, we assess

exposure to personality instruments during doctoral training, perceptions of competence, testing

data reporting practices, and personality assessment interpretation skill compared to a panel of

expert raters. We also examine what information trainees believe should be included in

psychological reports and how frequently supervisors have directed them to include certain

information (e.g., raw scores, scaled scores, percentile, and qualitative or narrative descriptions).

Such an investigation is warranted because it develops the awareness of current training practices

for personality assessment and thus offers a way to improve educational standards.

Method

Participants


Survey invitations were sent to the directors, as well as associate directors when

available, of clinical training (DCT and ADCT, respectively) at 16 APA-approved doctoral

(Ph.D.) training programs in clinical and counseling psychology (8 = Clinical, 8 = Counseling).

These invitations requested that the DCT/ADCT forward a recruitment e-mail to their students,

requesting that individuals at each of the programs participate in a brief survey on personality

assessment training practices. In exchange for their participation, each graduate student was

awarded a five-dollar gift card to Amazon. Seven programs (2 Counseling and 5 Clinical; 44% of

the sample) DCT/ADCT had prior professional relationships with one of the authors. The

remaining 9 programs were identified based on their similarity in focus (e.g., clinical or

counseling), perspective (e.g., scientist practitioner or clinical science), and training outcomes to

the convenience sample. They were also intentionally targeted in order to increase the

geographic diversity of the programs and trainees sampled (e.g., multiple programs were targeted

for recruitment from the southeast, southwest, northeast, and midwest regions).

In general, the programs targeted were drawn from a variety of geographic regions

(programs in nine states from the east to west coast) and, as of the summer of 2018, represent

approximately 5% of all APA-accredited health service programs and 6.5% of non-combined

type PhD programs. Programs training models were scientist-practitioner (n = 13; 81.3%) and

clinical science training models (n = 3; 18.8%). The programs sampled are also at or above the

national mean on major markers of successful student training (e.g., accredited internship match

rate, Examination of Professional Practice in Psychology [EPPP] pass and licensure rate). Many

were also recognized by outside educational groups as providing particularly strong heath service

psychology training, as noted by program website descriptions. Thus, the programs sampled are

likely representative of training experiences across the country amongst high quality programs in


health service psychology. The final sample of the study included 91 trainee participants (Table

1). Of those who did not complete the entire survey, dropout occurred almost exclusively when

participants were asked to complete assessment interpretation tasks.

Survey and Analysis Plan

The survey contained questions about basic demographic information. The survey also

included questions about the number of formal (i.e., standardized graduate coursework) and

informal (i.e., CE workshops, practicum, internship, etc.) training experiences in assessment. We

also assessed participants’ opportunity to use specific personality measures in clinical practice

during training, exposure to specific personality instruments in both formal and informal

training, number of written reports, and semesters of practicum. Information was also gathered

about how students have been trained to incorporate personality assessments results into reports.

We examined self-assessed competency with instruments on which trainees had exposure.

Competency on specific instruments was rated on a 0-100 scale with the following anchors (0 =

Not at all competent, 50 = Average competency, 100 = Extremely Competent). We also examined

performance-based competency by asking participants to complete several interpretation tasks.

Of personality assessment instruments, the Minnesota Multiphasic Personality Inventory

(MMPI) is the most frequently used in practice (Wright et al., 2017) and is covered in most

graduate training programs (Ready & Veague, 2014). The MMPI has also consistently been

described as inseparable from the process, practice, and history of testing (Benjamin, 2005;

Buchanan, 1994; Craik, 1986). Accordingly, clinicians are also likely to regularly encounter

reports that include the MMPI (Wright et al., 2016). The Restructured Clinical (RC) scales of the

MMPI-2 and MMPI-2-RF were selected because of their simplified interpretive approach,


retention of historic conceptual pathology constructs (Ben-Porath, 2012,) and coverage in major

texts on the MMPI-2 (Ben-Porath & Tellegen, 2018).

Participants were asked to complete interpretation tasks using a score profile and a

qualitative narrative selected from a sample MMPI-2-RF interpretive report on the Pearson

website. They were not instructed to use, or not use, any materials for the task. Trainees were

instructed to assume that the respondent had provided a valid profile and that the elevations and

descriptors were valid indicators of the individual’s personality. Participants were asked to

estimate the probability of twenty-four different symptom and behavioral problems on a five-

point Likert-type scale (Extremely Likely to Extremely Unlikely) using an interpretive profile

composed of only the Higher Order (H-O) and Restructured Clinical (RC) scales (available as

supplemental material). The problem list utilized for this task was generated to reflect an array of

clinical concerns and was drawn from wording used to describe various MMPI-2-RF scales in

various interpretive texts (e.g., Ben-Porath, 2012; Ben-Porath & Tellegen, 2008/2011; Graham,

2016). Participants were also asked to estimate T-scores for the H-O and RC scales based on a

standardized interpretive report of the MMPI-2-RF. Next, a panel of three experts recruited from

the 2018 MMPI research symposium were asked to complete the same two tasks

(symptom/behavior likelihood and T-score estimation). Each expert rater has a lengthy history of

scholarship with the MMPI and are recognized broadly within the field. Trainee T-score

estimates were compared to both expert estimates and to the scale scores included in the sample

interpretive report. Participant estimates of symptom probability were compared to expert rating.

Results

Most participants endorsed needing (n = 57; 62.6%) and wanting (n = 79; 86.8%) more

training than they currently have. Of those who endorsed needing training, most indicated


needing either a substantial (n = 13; 22.8%) or a moderate amount (n =34; 59.6%). A minority

endorsed needing either a great deal (n = 3; 5.3%) or minimal (n = 7; 12.3%) training.

Additionally, participants were asked how likely they were to include personality assessment in

their future career and indicated that they were: extremely likely (n = 17; 18.7%), moderately

likely (n = 29; 31.9%), slightly likely (n =25; 27.5%), slightly unlikely (n =9; 9.9%), moderately

unlikely (n =9; 9.9%), or extremely unlikely (n = 1; 1.1%). Approximately a third (n = 30;

33.0%) of participants had training in the administration and interpretation of projective /

implicit measures of personality. Only a portion (n = 52; 57%) of those who took the survey

completed the interpretive portion while most (87%) completed the survey up to the

interpretation task.

Independent t-tests indicated that no significant differences exist between trainees in

Clinical and Counseling psychology for semesters of clinical practicum or training, t(89) = -1.07,

number of integrative reports authored during training, t(89) = 0.98, number of formal or

informal personality assessment trainings received, t(89) = -0.84, wanting, t(89) = 1.93, or

needing, t(89) = 1.25, additional personality assessment training, or in program year, t(87)=

0.39. Non-significance of these dimensions suggests that assessment training patterns may be

analyzed across disciplines for subsequent analyses. An interclass correlation (ICC) assessing the

absolute agreement of expert raters averaged across measures supported the calculation of a

composite expert rater on the symptom probability task (ICC = .847) and the narrative

interpretation (ICC = .704).

Specific personality instrument training and use (Table 2) suggest that students received

the most training on the MMPI-2 and PAI. These personality inventories are also the most often

utilized instruments within doctoral training programs. The MMPI-2-RF was used slightly less


frequently than the MMPI-2. Despite less frequent use, training on the MMPI-2-RF is received in

slightly more than half of doctoral training experiences. Trainees feel highly variable in their

competence about instrument use, including both those that they are trained in as well as those

they have no exposure to. A large portion of trainees endorsed a self-assessed competency level

below average, with many indicating that despite their training they felt not at all competent with

the instruments.

The survey asked participants about their use of different reporting standards (i.e., what

type of test information is conveyed in a written report) for personality testing results (Table 3).

Participants were most likely to apply qualitative labels during report writing and about half

included some form of normed comparison data; however, for the remaining portion of the

sample, the frequency of including that information varied. This suggests some variability in

reporting standards for personality instruments; however, raw score data were unlikely to have

been reported. These trends also reflect beliefs held by respondents about what is appropriate for

testing result reporting. Approximately a quarter of the sample believed each of the following

about which scales should be reported within a testing report: all scales on a personality measure

(n = 14; 15.4%), only clinically elevated scales (n = 19; 20.9%), relevant scales to the referral

question (n = 31; 34.1%), and only clinically elevated scales relevant to the referral question (n =

25; 27.5%).

When asked to estimate T-scores based on an interpretive report, trainees provided a

widely varied range of estimated scores and often incorrectly estimated if the content represented

in the report indicated a clinical elevation on its associated profile (Table 4). In contrast to

trainee performance, experts predicted T-scores that were generally consistent with the source

profile’s clinical elevations. A similar pattern of discrepancy was noted between both estimated


scale scores and identified symptoms (Table 5) by trainees and experts given the same task.

Notably, there was a substantial rate of survey withdrawal that began during the skill assessment

portion. There we no significant differences in self-rated competence among those who

completed and those who dropped out, t(88) = .821, p = .40. Perceived competence was not

correlated with distance from report or expert scores for any of the estimated MMPI-2-RF scales.

Discussion

This study evaluated doctoral trainee exposure and competence with personality

assessment instruments using a sample of PhD students in Clinical and Counseling psychology.

This investigation was conducted to empirically evaluate the state of assessment as a critical

training component within the practice of health service psychology. Trainee competence in

assessment, particularly personality assessment, is understudied, particularly as it relates to the

use of assessment instruments and training. While previous research has evaluated perception of

trainee competency using training director perception, this study is the first to explore trainee

perceptions of competencies directly. Results indicate four distinct trends which are worthy of

further evaluation and are discussed separately below: frequency and exposure to personality

instruments during doctoral training, perceptions of competence, evidence of learned assessment

skills as measured on performance-based tasks, and implications for test reporting and diagnostic

conceptualizations.

Instrument use frequency

One goal of this study was to identify doctoral training trends for personality assessment

instruments within a sample of health service psychology PhD programs. Importantly, these

training trends appear generally consistent with patterns of use by practicing psychologists and

reports of training directions (e.g. Wright et al., 2017), with only a few exceptions. Such


similarity supports the generalizability of this study on trainee experiences. Trainees receive less

frequent training exposure on the MCMI while students receive more training on the PAI,

relative to professional report of use (Wright et al., 2017). PAI training exposure is high, which

is consistent with rates observed when asking training faculty (Mihura et al., 2017). However,

reported exposure to the Rorschach is less than in use of practicing psychologists (53.6%; Wright

et al., 2016) and by faculty report of required trainee experience (61%; Mihura et al., 2017).

Unlike other personality assessment measures, students demonstrated a strong basis of training

experience on the MMPI, consistent with its reported use (Camara, Nathan, & Puente, 2000;

Mihura et al., 2017; Wright et al., 2016). Even rate of clinical exposure with specific forms of the

MMPI (e.g., MMPI-2, MMPI-2-RF) are relatively consistent with national sales figures (e.g., the

MMPI-2 and MMPI-2-RF account for approximately 60% and 40% of sales, respectively; Ben-

Porath, 2017). Thus, while training experiences and exposure may differ for many instruments,

the MMPI (regardless of version) remains a consistent and central component of personality

assessment training (Benjamin, 2005; Buchanan, 1994; Craik, 1986).

Although results are generally consistent with previous research using training director’s

report, there are some notable variations. The variation in exposure to specific assessment

instruments may function in part because of sampling. For instance, differences in Rorschach

exposure is likely reflective of training program emphasis in either objective or

projective/implicit techniques. In this and other studies of training programs, research has

included only a minority of existing doctoral programs (see Mihura et al., 2017). Given the

general similarity between rates observed here and through faculty report across available

assessment instruments, this study captures a generalized trend of assessment experience. We

believe it is necessary for variability in instruction and training exposure to decline so that there


is a more explicit assessment training standard for all psychologists. Program efforts to meet

more explicit training exposure guidelines are critical if we are to effectively (and universally)

define the knowledge domain for an assessment competency for psychologists (Kaslow & Egan,

2017). Implicitly this often occurs already, as instructors frequently select instruments for

courses which will prepare trainees for the world of work. Efforts to ensure instrument exposure

which mirrors use does not, however, supplant a need for standardized competence assessment

and merely reflects an opportunity to ensure trainees are adequately prepared for what is

commonly utilized in practice.

Attitudes of Trainee Competence

While training and exposure increases self-assessment of competence, there is notable

variation in the level of self-perceived competence. This variability is evident for both those who

are trained with an instrument as well as for those who are not. We are concerned with the large

range of self-assessed competence. These ranges are problematic as they suggest that many of

those with instrument training exposure are not comfortable in their use and that those without

training may, at the same time, see themselves as extremely competent. This is concerning as it

suggests that those without training in an instrument who see themselves as increasingly

competent may be vulnerable to practicing outside their scope of practice. Such impacts of

problematic over-confidence are well-documented, particularly amongst those with less ability,

and lead to a poorer capacity to determine when they are competent (Kruger & Dunning, 1999).

This may lead to trainees without sufficient assessment competence engaging in poorly

standardized, and perhaps even harmful practice / violations of the ethical code of conduct,

without being aware of it. Promoting trainee awareness of the gap between their perceived and


actual performance may help to offset this cognitive bias (Dunning, Johnson, Ehrlinger, &

Kruger, 2003).

Interpretation Skills

In this study we piloted the performance-based competence of common core scales that

are part of the MMPI, the most widely used personality assessment instrument. While training

led to higher perceived competence in general, it did little to attenuate variability in competence

scores. When trainees were asked to demonstrate their assessment competency on that

instrument using skill-based interpretive tasks, there were several patterns suggesting lower skill

levels than desired or expected if perceived competency ratings are believed accurate. As such,

variations in self-assessment of competency mirrored the difficulties observed during the

interpretive tasks. That is, perceptions of competency do not appear to translate well into skill-

based assessment tasks. While this may vary across different assessment instruments, the tasks

presented are drawn from a widely used instrument (Mihura et al., 2017; Wright et al., 2016) and

the scales are a core interpretive component that receives training attention (Ben-Porath &

Tellegen, 2018). In general, trainees displayed variability in the degree to which they interpreted

written narratives and estimated symptom probability. Not only were there large amounts of

variability exceeding what is considered clinically significant differences (Rosenthal, Rosnow, &

Rubin, 2000), indications of clinical severity were frequently incorrectly classified. For example,

estimated t-scores have response ranges which varied wildly when compared to the scale scores

associated with the presented written narrative and to expert ratings of that same written

narrative.

The above-mentioned trends need, of course, to be repeated in a national sample of

training programs and use other common assessment instruments to triangulate the broader state


of assessment competence. However, variability in interpretation skill and participant drop-out

signals to us a potential danger of the current state of how competency is defined. As such, we

believe it is important to promote further study about how curriculum and practicum exposure

translate into generalized practical knowledge. For assessment to emphasize its evidence-based

nature with the greatest impact, interpretation standards should be studied, and this study

emphasizes a need to do so using trainees themselves.

Techniques such as the Q-sort have been described before as providing promise in

training practices (Weed, 2006). It would be beneficial if instructional aids like the Q-sort (e.g.,

those where clear interpretative competency levels that may be set at a national level) were

disseminated and utilized in assessment courses. Such efforts would aid in the standardization of

training outcomes, assist in establishing a consistent basis for skill competency, and promote a

stronger assessment proficiency.

Interpretive Standards

Qualitative labels are the most frequent means of communicating personality testing

results. One need look no further than common training textbooks to see that the field frequently,

and primarily, emphasizes the exclusive use of these labels. Likewise, the panel of experts in this

study also uniformly agreed that quantitative scores should be excluded in lieu of descriptive

labels. Likewise, while some trainees reported supervisors guiding them to include other sources

of data in reports (scaled scores, percentiles, etc.), qualitative labels were the most consistent

way to communicate testing results. This is of curiosity, as such descriptive methods offer

objectively less transparent means of communicating test performance compared to methods

frequently utilized during most other types of testing (e.g., memory, intelligence, aptitude, etc.).

Frequently, the written report (and not the raw data) may be the only information a psychologist


may have about formal testing and they may wish to compare previous psychological

functioning to current test data. Lower transparency about respondent performance in reports has

implications for how effectively we can communicate with other professionals and may explain

some of the variable performance seen on the skill-based competence tasks. Much as language

for describing the qualitative labels is interpreted across a wide range, it is likely that those not

using interpretive report software vary in the language they use – further increasing room for

interpretive mistakes.

We are unaware of any research that offers empirically-based guidance of objective

assessment reporting standards (e.g., probabilistic language recommended for score ranges or

even what type of reporting information to include, such as qualitative summary statements or

standardized T-scores). Aside from interpretive tradition, we are unaware of any studies which

indicate that the reporting of personality instrument results should include clear indications of

respondent scores to reduce the variability surrounding how descriptive language is interpreted

(Cox et al., 2013). Further study is needed to examine how qualitative labels are applied within

personality assessment, as well as the impacts of including standardized reporting data. This is an

area that has already received some attention in intellectual and neuropsychological assessment

(Guilmette et al., 2008).

If there continues to be evidence that qualitative descriptions (i.e., typically thought of

within personality assessment as a summary of empirically-based correlates) alone are associated

with variation in test interpretation, one method to reduce variability that might decrease that

problem is to shift what is traditionally included in testing reports. For instance, the standardized

inclusion of observed scores (T-scores) for scales utilized during personality interpretation

(perhaps in the form of a table within the report, as is frequently done within neuropsychological


testing) may lend itself to less interpretive ambiguity. Such a practice could supplement current

test reports that include only narrative interpretations. While consumers are a frequent recipient

of reports and may be unclear how an assessor goes from a score to an interpretive statement, we

believe that including standardized testing scores (whether in an appendix or in a table within the

main report document) remains beneficial. Such information is also regularly included in other

assessments specialties (e.g., neuropsychology and rehabilitation psychology). While including

standardized interpretive data does not ensure a lack of variation or error in interpretation (see

Cox et al., 2013), such a step may facilitate improved interpretation by other qualified providers

who encounter the report.

As a counter-perspective provided by an anonymous reviewer, the inclusion of

standardized testing data into the report may be problematic because interpretation requires

integration of not only test scores but also contextual and individual variables that may influence

test response. As such, this may lead to a test-based, rather than a client-based assessment,

approach. However, we believe that for a test to be utilized it must be validated on the

populations in which it is used. Comparisons between client scores and context-appropriate

comparison groups should therefore be incorporated as part of the report to help curtail potential

for misrepresentation and labeling. Likewise, adaptations based on contextual and individual

factors should be empirically based and clearly justified within the report. Thus, it is our belief

that more information, rather than less, is likely to reduce inappropriate test and report

interpretations. Studies on the influence of various testing information (including respondent

cultural variables) on interpretation accuracy and bias would be helpful in providing guidance on

what should be included in reports. Likewise, it may also be useful to expand this study to other

reporting trends used within the field (e.g., base rates).


Conclusions and Future Directions

This study builds on existing literature and offers the first evaluation of trainee

experience and performance-based competency within assessment. Results are, in many ways,

consistent with previous studies that have outlined assessment instrument exposure during

training (Mihura et al., 2017) and highlighted ways in which trainees are not as prepared to

perform assessment as they may believe or as might be desired by the field (Ready et al., 2016).

In general, there is variability across instruction on instrument use, exposure to instruments in

practice, and practical skill level for the personality instrument evaluated within this study. This

variability offers both areas in which the assessment competency must grow (e.g., decreased

variability in training instrument exposure, increased consistency in outcomes for training

experiences, etc.) and some ways in which that might occur (e.g., inclusion of standardized

respondent score information).

No study is without limitations, however. For instance, this pilot study does not include a

national sample comprising doctoral students from all programs or program types and that some

program factors (such as program training model which differ on required amount of assessment

courses; Ready & Veague, 2014) were, accordingly, unable to be evaluated. Likewise, this study

does not contain PsyD trainees which represent a growing portion of the training landscape.

Despite these limitations, this study provides a novel, trainee-centered evaluation of competency

that is likely to inform future understanding and study of assessment training and trainee

competence. The programs that were approached, and whose students participated, represent a

variety of different training models across health service psychology (e.g., Clinical and

Counseling as well as Scientist-Practitioner and Clinical Science), with those PsyD programs and

scholar-practitioner programs unrepresented within this sample. Likewise, all programs included


in this study are at or above the national average on indicators of successful training outcomes

(e.g., APA-accredited internship match, EPPP pass and licensure rate, etc.). This, and the diverse

geographic regions from which the schools were recruited, leads us to believe that these results

are likely representative of many doctoral training programs in Clinical and Counseling

psychology and offer the first direct examination of trainee experiences in assessment training.

Therefore, we believe these data offer a reasonable starting point upon which a broader literature

can be developed.

An additional criticism that may be leveled against this study is the way in which

interpretation tasks were utilized to assess competence (e.g., tasks include only one narrative

report, this study assesses the skill of translating narrative description to symptom scores – which

is not trained, etc.). Conversely, it is our position that if clinicians can meaningfully interpret

scores and generate a report (which, we assume, has a purpose of communicating severity of

symptom distress) then that communication (and thus the interpretation of symptom distress)

should be clearest to those training in assessment. This is, in part, why we advocate for more

transparent reporting standards as it is likely to help facilitate communication of symptom levels

and personality testing results. We believe that this is needed as even when scores are displayed

there is notable discrepancy in symptom interpretation (Gilmet & Hagan, 2008). Future research

will, of course, need to expand the number, type, and complexity of interpretation tasks given so

that a fuller picture of competency is established. Such an effort will likely benefit training

programs as they prepare their students for the Enhanced Examination of Professional

Psychology.

Given the pilot nature of this study, findings may be best limited to programs most like

those sampled. In other words, results of this study are likely to be most similar to other


programs which are APA-approved PhD programs in Clinical or Counseling (comprising

approximately 60% of all approved health service psychology programs) that have average (or

above) training outcomes. Accordingly, future research would benefit from a nationally

representative sample. Such an investigation would also benefit from additional performance-

based competency tasks and a wider array of assessment instruments evaluated (e.g., other

domains of assessment such as intellectual assessment). This wider array of instruments would

benefit from including those assessing both clinical and normal variations in personality. A

broader sample would also enable examination of diversity related differences in training

opportunity and outcome.

In general, we hope that this study inspires more conversation about training

standardization across the country as well as efforts to define and promote competency within

assessment. We also hope that such conversations more directly involve trainees and include

performance-based measures of competence. Accordingly, future research would benefit from

use of a larger, more representative and inclusive sample as well as a greater number of

interpretation tasks across additional assessment instruments.


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Table 1.Demographic Information of study sample Program Type

Sample CharacteristicSample (n = 91)

Clinical (n = 50)

Counseling (n = 41)

Age 27. 8 (3.7) 27.7 (4.0) 30.0 (3.4)Ethnicity - - -

Caucasian 73 (80.2%) 42 (84.0%) 31 (75.6%)Hispanic/Latinx 6 (6.6%) 3 (6.0%) 3 (7.3%)Asian American 6 (6.6%) 4 (8.0)% 2 (4.9%)

Native American 2 (2.2%) - 2 (4.9%)Other 4 (4.4%) 1 (2.0%) 3 (7.3%)

%Male 12 (13.2%) 4 (8.0%) 8 (19.5%)Highest Degree - - -

BA/BS 19 (20.9%) 14 (28.0%) 5 (12.2%)MA/MS 72 (79.1%) 36 (72.0%) 36 (87.8%)

Year in Program - - -1st 5 (5.5%) 3 (6.0%) 2 (4.9%)

2nd 14 (15.4%) 8 (16.0%) 6 (14.6%)3rd 23 (25.3%) 13 (26.0%) 10 (24.4%)4th 17 (18.7%) 4 (8.0%) 13 (31.7%)

5th or Beyond 21 (23.1%) 14 (28.0%) 7 (17.1%)Internship 8 (8.8%) 6 (12.0%) 2 (4.9%)

Integrated Reports 11.5 (14.2) 13.0 (13.9) 9.8 (14.5)Semesters of Practicum 6.3 (3.6) 6.0 (4.0) 6.7 (3.1)Completed Assessment Coursework - - -

Objective Personality 89 (97.8%) 49 (98.0%) 40 (97.6%)Projective Personality 10 (11.0%) 2 (4.0%) 8 (19.5%)

Neuropsychological 40 (44.0%) 32 (64.0%) 8 (19.5%)Child/Developmental 37 (40.7%) 29 (58.0%) 8 (19.5%)

School-based Assessment 10 (11.0%) 7 (14.0%) 3 (7.3%)Intellectual 100% 100% 100%

Other Trainings (Practicum, Workshop etc.) - - -Objective Personality 73 (80.2%) 43 (86.0%) 30 (73.2%)

Projective Personality 27 (29.7%) 13 (26.0%) 14 (34.1%)Neuropsychological 46 (50.5%) 32 (64.0%) 14 (34.1%)

Child/Developmental 43 (47.3%) 34 (68.0%) 9 (22.0%)School-based Evaluation 18 (19.8%) 13 (26.0%) 5 (12.2%)

Intellectual 71 (81.3%) 44 (88.0%) 30 (73.2%)


Table 2.Use and Perceived Competency of Specific Personality Assessment Instruments Trained Competence Untrained Competence

Personality Instrument Has TrainingUsed

Clinically M (SD) Range M (SD) RangeMMPI-2 84 (92.3%) 62 (68.1%) 66.1 (18.9) 0 - 98 38.5 (26.9) 0 - 68

MMPI-2-RF 50 (54.9%) 37 (40.7%) 66.2 (19.6) 10 - 100 32.7 (27.2) 0 - 88MMPI-A 34 (37.4%) 24 (26.4%) 60.8 (22.8) 9 - 92 22.7 (23.9) 0 - 85

MMPI-A-RF 10 (11.0%) 8 (8.8%) 50.3 (28.8) 7 - 91 26.0 (25.6) 0 - 91PAI 79 (86.8%) 56 (61.5%) 71.5 (17.5) 18 - 100 18.8 (21.1) 0 - 61

MCMI-III 28 (30.8%) 23 (25.6%) 61.9 (22.9) 0 - 98 11.5 (16.7) 0 - 59MCMI-IV 19 (20.9%) 16 (17.6%) 63.8 (17.7) 18 - 96 16.4 (25.9) 0 - 96

Rorschach (Any System) 17 (18.7%) 13 (14.3%) 41.6 (30.9) 2- 87 6.3 (13.6) 0 - 60Note. Participant dropout resulted in only 85 completing competence questions while all 91 provided information on instrument use and training. All participants were asked to rate their competency on personality measures, regardless of training background. Competency was rated on a 0-100 scale with the following anchors (0 = Not at all competent, 50 = Average competency, 100 = Extremely Competent). Competence was calculated on only those with training in the instrument.

Table 3.Predictors of Perceived Competence Predictor Variables

InstrumentHighest Degree

Doctoral Type

Year in Program

# Integrated Reports

Semesters of Practice

Has Training

Used in Practice Model Result

MMPI-2 t = 1.40 t = -2.01* t = -.85 t = -2.18* t = -.72 t =3.81*** t = -4.16*** F(78, 7) = 6.37***, R = .60MMPI-2-RF t = 0.47 t = -0.93 t = 0.53 t = -0.46 t = -1.30 t =3.37*** t = 1.94 F (78, 7) = 7.42***, R = .63

MMPI-A t = -0.95 t = 1.38 t = -0.65 t = 1.12 t = 0.06 t =4.29*** t = -5.17*** F(75, 7) = 14.44***, R = .76MMPI-A-RF t = -0.65 t = -0.84 t = 0.23 t = -0.05 t = -1.02 t = -1.42 t = -3.14* F (67, 7) = 2.75***, R = .45

PAI t = 0.27 t = -2.15*** t = -0.33 t = 0.62 t = -1.92 t = 7.69*** t = -2.28* F (77, 7) = 19.54***, R = .80MCMI-III t = 0.13 t = 1.86 t = 1.88 t = 0.79 t = -1.25 t = -1.01 t = -7.53*** F (76, 7) = 11.65***, R = .72MCMI-IV t = -0.55 t = 1.33 t = 1.64 t = -0.19 t = -0.66 t = 3.29** t = -4.41*** F (76, 7) = 14.51***, R = .76

Rorschach t = 1.89 t = 1.964* t = -0.39 t = -0.16 t = -0.18 t = -0.17 t = -10.59*** F (76, 7) = 18.73***, R = .80Note. All participants, regardless of training exposure, were included within these analyses. p < .05*, p < .01**, p < .001***


Table 3.Percent of different types of data communicated within testing reports Frequency supervisors have required included in reportsData Type 0% 1-10% 11-25% 26-50% 51-75% 76-100%

Scaled Score / T-score 16 (18.2%) 5 (5.7%) 2 (2.2%) 8 (8.8%) 12 (13.2%) 45 (49.5%)Qualitative Label 1 (1.1%) 1 (1.1%) 2 (2.2%) 2 (2.2%) 8 (8.8%) 74 (81.3%)

Percentile 20 (22.0%) 6 (6.6%) 4 (4.4%) 7 (7.7%) 12 (13.2%) 39 (42.9%)Raw Score 60 (65.9%) 8 (8.8%) 3 (3.3%) 3 (3.3%) 5 (5.5%) 8 (8.8%)

Note. Percentages calculated based on validate percent responding to each question. Include in reports reflects the trainee belief that a type of data should be included as a standard component of a test report about a personality instrument.


Table 4.Certainty of a symptom-positive presentation based on T-scoresT-score Will have or does Is likely to Is unlikely to Will not or does not

45 0 1 (1.2%) 61 (75.3%) 19 (23.5%)50 3 (3.8%) 1 (1.3%) 57 (62.6%) 18 (19.8%)55 5 (6.3%) 9 (11.4%) 42 (53.2%) 21 (26.6%)60 9 (11.4%) 27 (34.2%) 24 (30.4%) 7 (8.9%)65 6 (7.5%) 41 (51.3%) 2 (2.5%) 2 (2.5%)70 9 (9.9%) 43 (47.3%) 1 (1.3%) 075 14 (17.5%) 36 (45.0%) 0 0


Table 5.Interpretation of MMPI-2-RF Narrative Report Distance from Interpretive Report Score Distance from Expert Estimate

Scale M (SD) Range Incorrectly Elevated M (SD) RangeEID 17.8 (11.3) 2 - 42 14 (27.5%) 10.7 (6.6) 1 - 29

THD 8.0 (5.7) 0 - 20 14 (27.5%) 6.1 (5.1) 1 - 21BXD 6.2 (4.3) 2 - 17 11 (21.6%) 5.5 (4.1) 0 - 15RCd 10.0 (8.2) 2 - 28 12 (23.5%) 10.0 (7.6) 1 - 31RC1 23.9 (10.9) 4 - 41 4 (7.7%) 10.7 (6.9) 1 - 36RC2 13.8 (7.9) 2 - 33 13 (25.0%) 11.8 (7.4) 2 - 33RC3 13.3 (8.5) 1 - 31 11 (21.2%) 8.9 (6.5) 0 - 30RC4 8.8 (6.7) 2 - 42 30 (57.7%) 6.8 (8.0) 0 - 48RC6 5.7 (4.7) 0 - 25 15 (28.8%) 6.5 (4.7) 0 - 23RC7 10.7 (6.8) 0 - 30 19 (36.5%) 12.0 (7.4) 2 - 32RC8 9.9 (8.8) 1 - 36 35 (67.3%) 11.3 (6.2) 0 - 25RC9 10.3 (9.5) 0 - 40 13 (25.5%) 6.7 (7.5) 0 - 30

Note. Distance from profile and expert ratings are presented as absolute values of difference scores. Distance from profile was calculated out of available responses, with EID, THD, BXD, RCd, and RC9 estimated out of 51 participants as one left those scores blank (total n = 52). Incorrect elevations indicate the frequency that observed means below are above or the T-score = 65 recommended cut-score (Ben-Porath & Tellegen, 2008/2011) observed on the clinical profile. Self-reported competence for those completing this interpretive task was slightly to that observed for the overall sample (M = 54.9, SD = 27.8) but placed most (70%) at or above an average self-reported level of competence.


Table 6.Prediction of Symptom presentation Trainee Rating Compared to Expert

Symptom, Behavior, or Attitude M SD Range% Incorrect Direction

Mean Expert

Hallucinations 2.1 0.8 1 - 5 16.9% 1Unstable Moods 2.1 1.0 1 - 5 22.0% 1

Nightmares 2.9 0.6 1 - 4 86.4% 3Angry 2.2 0.7 1 - 4 76.3% 2

Defensive 2.3 0.8 1 - 4 74.6% 2Critical 2.7 0.9 1 - 5 52.5% 2

Insecure 3.0 0.9 1 - 5 69.5% 3Anxious 3.0 1.0 1 - 4 64.4% 3

Pessimistic 3.4 1.1 1 - 5 67.8% 3Appetite problems 3.2 0.9 1 - 5 57.6% 3

Suicidal 3.1 1.0 1 - 5 60.3% 3Passive 3.7 0.7 2 - 5 39.7% 3

Somatic issues 3.6 1.0 1 - 5 41.4% 3Delusions 2.0 0.8 1 - 5 13.6% 1

Bizarre behavior 1.9 0.8 1 - 5 11.9% 1Panic episodes 3.1 0.8 1 - 5 64.4% 3

Inattentive / Easily bored 3.1 1.0 1 - 5 71.2% 1Manic/hypo-manic episodes 1.6 1.0 1 - 5 13.6% 1

Euphoric mood 2.1 1.0 1 - 5 27.1% 1Concentration problems 2.4 0.8 1 - 4 44.1% 1

Impulsivity 1.9 0.7 1 - 4 15.3% 1Paranoid 1.7 0.8 1 - 5 6.8% 1

Aggressive 2.2 0.8 1 - 4 28.8% 1Social 3.1 0.9 1 - 5 47.5% 2

Note. Behavioral manifestations of functioning were rated on a 5-point Likert-type scale (1 = Extremely Likely, 2 = Somewhat Likely, 3 = Neither likely nor unlikely, 4 = Somewhat unlikely, and 5 = Extremely unlikely). The percent of answers in the incorrect direction reflects the portion of trainees who endorsed 'Likely', 'Neither Likely or Unlikely', or 'Unlikely' response stems while expert panel selected responses in one of the other three response categories (e.g., the expert panel rated a symptom 'Extremely Likely' or 'Somewhat Likely' and a trainee did not select either of those frequency categories).

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