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Detecting Depression
Running Head: DEPRESSION, RESPONSE TIMES, THE PA1
Detecting Depression and Malingering Using Response Times
on the Personality Assessrnent Inventory
Derick Glen Adam Cyr
M.A Thesis
Lakehead University
November, 2000
Subrnitted in partial fulfillment of the degree of Master of Arts, Clinical Psychology
Supervisor: Dr. D. Mazmanian
Second Reader: Dr. B. O'Connor
Interna1 Examiner: Dr. M Bédard
Extemal Examiner: Dr. R. Holden
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. * Detecting Depression u
Abstract
The detection of individuais who are malingering psychological dyshction has proven
to be a difficult task (Rogers, 1997). This study was conducted to investigate whether
response times on the Personality Assessrnent Inventory could differentiate among
asymptomatic controls (n = 13 , clinically depressed individuals (o = 12), and a group
instructed to malinger depression (I? = 19). Conventional responses and item response
latencies were recorded for the Negative Impression, Positive Impression, Depression -
Affective, Depression - Cognitive, and Depression - Physiologicd scdes. Discriminant
fùnction analyses revealed that conventional scores correctly classined 100% of the
controls, 9 1.7% of the depressed, and 73 -7% of the malingerers. Standardized response
latencies correctly classified 73.3% of controls, 58.3% of depressed, and 84.2% of
malingerers. Classification rates for raw response latencies were 73.394, 50.0%, and
78.9% respectively. Finaily, a new scale composed of items fiom the above subscales
maximally discriminahg malingerers fkom depressed individuals could correctly
classi@ 100% of depressed and 91 -7% of malingerers. These fmdings are consistent
with other research (Fekken & Holden, 1994) suggesting that response latencies might
provide meaningful information.
... Detecting Depression iu
Table of Contents
. . ................................................................................................ Abstract 11
................................................................................... List of Appendices iv ......................................................................................... List of Tables v
Introduction ........................................................................................... 1 .............................................................................. Response Styles 1
.......................................................... Malingering and Test Construction 3 .................................................................................. The MMPI-2 3
.......................................................................... Modem Approaches 4 ..................................................................... The PA1 Validity Scales 7
.......................... The Effectiveness of PA1 Impression Management M e m e s 8 .......................................................................... Response Latencies 11
............................................................... Response Latency Findings 14
............................................................................................... Method 17 .................................................................. Session 1 . Categorization 17
.................................................................................... Participants 17 ..................................................................... Measures 18 ..................................................................................... Procedure 19
............................................................... . Session 2 Experimentation 20 ................................................................................... Participants 20
...................................................................................... Measures 21 ............................................ .................................... Procedure .... 21
............................................................. Treatment of Response Times 23
............................................................................................... Results 28 ........................................................................ Descriptive Statistics 28
....................................................................................... Findings -29
.................................................................................. Discussion ........ 35 .................................................................................... Limitations 40
............................................................................. Fuîure Directions 42
.......................................................................................... References -44
.......................................................................................... Appendices 48
Detecting Depression iv
List of Appendices
Appendix A: Procedure for the recruitment of subjects at the LPH for the study "Detecting
Depression and Malingering Using Response Times on the Personaïty
.......................................................... Assesment Inventory . " 48
...................................................... Appendix B: Debriefing Fom . Session 1 49
..................................................... Appendix C: GWBasic Cornputer Program 50
........................................ Appendix D: Instructions for Malingering Respondents 61 .
....................................................... Appendix E: Debriefing Fom - Session 2 62
Detecting Depression v
List of Tables
...................... Table 1: Means and Standard Deviations for the PA1 Scales of Interest 63
Table 2: Raw Responding T i e Means and Standard Deviations of Items Within a Scale
............................................ ........................... for RTI and RT2 .. 64
................... Table 3: Means and Standard Deviations for the PA1 2-scores of Interest 65
........... Table 4: Tukey Post-hoc Dzerences Between Groups for the PA1 Scale Scores 66
...................... Table 5: Tukey Post-hoc Differences Between Groups for the 2-scores 67
........................................... Table 6: Classification Results Using Scale Scores 68
.............................. Table 7: Classification Results Using Raw Response Latencies 69
................................................. Table 8: Classification Results Ushg 2-scores 70
Table 9: Classification Results Using Scores and Transfomed Response Latencies ....... 71
.................................... Table 10: Classification Results Using NLM Scale Scores 72
......................................... Table 1 1 : Classification Results Using NEM 2-scores 73
Table 12: Classification Results Using NIM Scale Score and NIM Raw Response
...................................................................................... Times 74
................ Table 13 : Classification Results Using NIM Scale Score and NIM 2-scores 75
Table 14: Significant T-test clifferences For 2-Scores Between the Depressed and
.................................................................... Malingering Groups 76
Table 15: Classification Rates Using the Z-scores From 10 Empirically Derived ..................................................................................... Items 77
Detecting Depression 1
Using Response Times to Detect Depression and Malingering With
The Personality Assesment Inventory
Classical test theory assumes that an observed score is the result of an individual's
true score and measurement error (Kaplan & Saccuzzo, 1993). Measurement error in
psychologid testing may be attributed to error inherent in test construction and error
inherent in test administration. Errors in test construction may include irnproper item
selection, item analysis, and test standardkation. Error attributable to test administration
can include the effects of the tedng situation, test administrator characteristics, and test-
taker characteristics (Kaplan & Saccuzzo, 1993). SeEreport tests of personality functioning
are typically concemed with a subject responding in a mamer unrepresentative of their
'%rue" characteristics (Rogers, 1997) - measurement error due to test-taker characteristics.
,4n unrepresentative response style (or adopted response style) minimi;.es, to a greater or
lesser extent, the contribution of tme characteristics to an observed score.
Response Styles
There are a varïety of different response styles, each of which can distort an
individual's score in a p a r t i c h direction. (Some authors have made a distinction between
response set and response style [e.g., Kaplan & Saccuzzo, 19931. Consistent with the
articles reviewed within, the term response style will be used to indicate any responding that
deviates tIom accurate responding.) Examples of response style include acquiescence,
criticalness, extremity bias, and random respondùig. These types of response styles deviate
fiom accurate responding, distorting observed scores due to uncertainty, misunderstanding,
inciifference, or insolence. Another type of response style is dissimulation, or the systematic
exaggeration or minirnization of m e characteristics. This type of responding ranges fiom
Detecîing Depression 2
positive dissimulation (iidividuals tailoring their answers to create a favorable image) to
negative dissimulation (individuals tailoring their answers to create a negative image), with
accurate responding located midway. Positive dissimulation indudes fakiog good and
defensiveness; negative dissimulation includes faking bad, malingering, and exaggeration
(Graham, 1990). Altematively, Rogers (1997) has defined positive and negative
dissimulation as defensiveness and malingering, respectively, and has M e r delineated
each type of dissimulation as severe, moderate, or mild.
The exbernepositive end of the dissimulation response style continuum has been
described as faking good and severe defensiveness (Graham, 1990; Rogers, 1997). Faking
good is the denial of all negative characteristics so that an individual appears to be fiee of al1
psychological problems, however minor, simulating an aimost angelic character. On the
positive end of the dissimulation continuum, but not quite as blatantly removed fiom
accurate responding, is defensiveness (Graham, 1990). Defensive individuals are not as
obvious when presenting themselves in a positive light - they occasionally admit to faults.
Rogers (1 997) defined moderate defensiveness in a similar man.net, and he M e r defined
mild defensiveness as the minïmkation, but not denial, of psychological problems. The
range of possible motives for positive dissimulation is quite broad. Situations in which
positive dissimulation might occur include employment screening, psychiatric evaluations,
parole hearings, and child custody hearings (Holden, 1995; Rogers, 1997).
The extreme negative end of the dissimulation response style continuum has been
described by Graham (1990) as faking bad (also defined by Rogers, 1997, as severe
malingering). Faking bad is the endorsing of unrealistic negative characteristics.
Individuals who are faking bad are so extreme in their fabrication of symptoms that their
Detecting Depression 3
presentation seems fantastic or preposterous. Malùigering, adjacent to faking bad on the
dissimulation continuum, is not as obvious. These individuals actively attempt to accurately
feign psychological disorders by presenting themselves as having either a few critical
symptoms or an array of other symptoms (Graham, 1990; defined as moderate malingering
by Rogers, 1997). Closest to accurate responding on the negative side of the dissimulation
response style continuum is exaggeration. Individuals who exaggerate typically have a
psychological disorder but attempt to exaggerate the levels of their symptoms. Exaggeration
has been defined by Rogers (1997) as "mild malingering" and M e r conceptualized as a
minimal distortion that has little effect upon differential diagnosis. Possible motives for
negative dissimulation include fuiancial gain for accident victims suing for damages,
financial gain for individuals claiming disability, for the procurement of drugs, or a plea for
help (Rogers, 1997; Rogers, Sewell, Morey, & Ustad, 1996). The Diagnostic and Statistical
Manuai of Mental Disorders - 4" Edition (DSM-N; Amencan Psychiatrie Association,
1 994) defines malingering as the intentional production of false or grossly exaggerated
symptoms that is motivated by extemal incentives. Thus, the DSM-IV categorization of
malingering is comparable to malingering or faking bad (Graham, 1990) or to what Rogers
(1997) refers to as moderate or severe malingering.
Malingering and Test Construction
The MMPI-2
Historically, psychologists have been aware of the potential effects of various
response styles and have included measures to assess their influence. For instance,
Bernreuter (1 933) thought that individuals were tailoring their responses to produce a
favorable self-image, for this reason he questioned the validity of self-report questionnaires.
Detecting Depression 4
Meehl and Hathaway (1 946) declared "one of the most important failings of almost ail
personality tests is their susceptibility to 'faking' or 'lying"' (p. 525).
One of the most prominent psychological instruments to include measures of .
response styles is the Minnesota Multiphasic Personality hventory (MMPI; Hathaway &
McKinley, 1943) and its successor the MMPI-2 (Butcher, Dahlsirom, Graham, Tellegen, &
Kaemmer, 1989). Both instruments have three scales to detect if people are distorting
information about themselves. The L-scde assesses the extent to which peopIe are naïvely
presenting themselves in a positive light The K-scale assesses the extent to which people
present themselves in an overly positive light or an overly negative light. The F-scale
assesses the extent of deviant or atypical responding (e.g., acquiescence, random
responding) .
Although the MMPI-2 is widely used, some authors have cnticized the MMPI-2 as
being an unsuitable diagnostic instrument of psychopathology because it does not meet
current psychometric and theoretical standards. Helmes and Reddon (1993) examined the
MMPI-2 and reported both theoretical and structural problems. One theoretical problem is
the heterogeneous content within scales, which diminishes the meaning of scde scores.
Also, the categoncal modeling of the MMPI-2 designates a high scale score as indicating
probable group membership instead of the severity of the psychological constmct.
Structural problems reported by Helmes and Reddon (1993) include small and
unrepresentative sample sizes (a mode of 50 individuals from Minnesota for each scale),
high fdse positive rates for some scales, a high overlap of item content among scales
(reducing the specincity of scale meaning), a lack of cross-validation of item selection,
outdated and inadequate noms, and problems associated with measures of responw styles
Detecting Depression 5
and social desirability (also see McCrae & Costa, 1983). Helmes and Reddon (1993) also
repmted other general problems such as imbalanced keying within items (Le., an unequal
number of tme- and fdse-keyed items), unscored items (62 items not scored on any clinical,
supplementary, vvalidity, or content scales), and unbalanced scale lengths (clinical scdes
range fiom 33 to 78 items).
Modern Approaches
Authors of psychological measures apply recent advances in psychometric theory to
avert, as best as possible, errors in test construction sirnilar to those pointed out by Helmes
and Reddon (1993) of the MMPI-2. For example, Jackson (1994) States that the goals of
- proper item selection are "(a) to enhance the interna1 consistency reliability of the scales; (b)
to suppress desirability response bias; (c) to maximize discrimination among the scales; and
(d) to identify items yielding scales with nonnal distributions" (p. 40). For the Jackson
Personality inventov - Revised (PI-R; 1994), Jackson began test construction with a pool
of 1800 items and finished with a final totd of 300 items. Some of the items removed to
suppress the desirability response bias included "1 am more easily Untated than others areyy
and "Most people would Say that 1 am cautious and conservative with my money" (Jackson,
1994, p. 43). Subsequent to thorough item selection and analysis for the JPI-R, Jackson
sought to mesure the influence of dissimulation upon test scores. Jackson (1 994) înstnicted
respondents to fake good and found only smaü changes for scale means and standard
deviations. He concluded that the small differences between groups of respondents were a
reflection of ''the method of scale construction in which desirability was suppressed"
(Jackson, 1994, p. 52). Therefore, proper item analysis and selection is the initial step taken
in test construction to minimize the effects of response style. Another psychometric
Detecting Depression 6
measure that was constructed using contemporary psychometric theory is the Persondity
Assessrnent Inventoq (PM; Morey, 199 1).
The PA1 (Morey, 1991) is a 344-item Likert-type scale questionnaire designed to
assess a broad range of psychopathology through 22 non-overlapping scales. The 22 scales
of the PA1 include 4 validity scales, 1 1 clinical scales, 5 treatment scales, and 2 interpersonal
scales. The intemal consistency median alphas are -81 for the normative sample, .86 for the
chical sample, and .82 for the college sample. The test-retest reliability for testing 28 days
apart over the clinical scales was a median of -83 (Morey, 199 1). Morey adopted recent
advances in the field of psychomeâics for constructing the PAI, advances not availabie for
the MMPI and not utilised for the MMPI-2. Advances in psychometnc theory include new
models for understanding constnict validity and the influence of response styles. For
instance, Morey (1991) emphasised construct validity so "that no single quantitative item
parameter should be used as the sole criterion for item selection" (p. 63). Consequently, the
use of multiple criteria by Morey (1991) increased the utility of the scales by describing
various levels of severity. Morey (1 991) decided upon a four-point Likert-type response
scale to provide a greater varïability in response, allowing greater scale reliability with fewer
items. Other advances in psychometric theory inchde the evoluhon of alternative models to
classical psychometric theory and the development and refinement of sophisticated meîhods
of data reduction such as factor analysis and cluster analysis. For example, the PA1 was
constructed with no item overlap between scales to avoid artificial correlations between
scales, and item construction was based upon thoroughly researched theoretical constructs
with specific attention to multidimensional constnicts. Nine of the 1 1 clinical scales were 3
readily divisible (through cluster analysis) into sub-scales to further spec* notable features.
Detecting Depression 7
For example, the Depression sub-scales distinguish between cognitive, affective, and
physiological features, whiie the Schizophrenia sub-scales distinguish between psychotic
experiences, social detachment, and thought disorder. As a result of the application of
contemporary psychornetric views, the PA1 embodies current psychornetric and theoretical
standards.
The PAX Validitv ScaIes
The PA1 contains four validity scdes - Inconsistency, Infiequency, Negative
Impression, and Positive Impression. Clinicians are able to use the inconsistency scale to
discern the consistency with which individu& answered questions with sunilar content.
The Mequency scale is useful for i d e n m g individuals who may have answered the PM
in an atypical manner due to random responding, indifference, carelessness, confusion, or
reading difficulties. Also, the PM has two validity scales and two other vaiidity measures
that may be used by clinicians to assess the possibility of positive impression management
and the possibility of malingering. The PM has two indicators to assess the likelihood of
positive impression management: the Positive Impression scde (PM; Morey, 1991) and the
Defensiveness Index (Morey, 1996). The P M scale is a measure of the degree to which
respondents are presenting a very favourable impression or the denial of relatively minor
fa& (e.g., reversed keyed question 1 44. Sometimes I'm too impatient). The Defensiveness
Index has eight patterns of endorsement that tend to be observed more fiequentiy with
individuals instnicted to present positive impressions (e.g., one item is a Treatment
Rejection scale score r 45T). The PM dso has two indicators to detect the possibility of
malingering: the Negative Impression scale (NIM; Morey, 199 1) and the Malingering Index
(Morey, 1996). The NIM scale is a measure of the degree to which respondents are
Detecting Depression 8
presenting an exaggerated negative impression, more negative than a clinical explmation
wodd warrant (e-g., question 129. I think 1 have 3 or 4 completely dinerent personaiity
inside me). The Malingering Index has patterns of endorsement that tend to be observed in
individuals instmcted to simulate a severe mental disorder (e.g., one item is a Depression
scale score > 85T and a Treatment Rejection scale score 2 45T). Morey (1991) stated that
high scores on the positive and negative impression management scales rnay not always
represent purposeful deception. Instead, it may be that the score in question was due to
careless responding or an exaggeration of good or bad qualities.
The Effectiveness of PAI Impression Management Measures
To examuie the effectiveness of the PIM scde, Morey (1 991) asked college *dents
enrolled in abnomal psychology to sirnulate a very favourable self-impression. Results
presented in the PAI manual indicate that a P M scale score of 18 or above (57T)
successfdly identified 8 1.8% of these individuals. Unfortunately, at the same cut-off score,
30.4% of n o d s were identîfied as presenting themselves in a very favourable light (a
speciticity with respect to normals of 70%, Morey & Lanier, 1998). Therefore, when a
profile includes a PIM score of 18 - 22, Morey (1 991) recommends that caution be
exercised with interpretation of clinical scores because they may be distorted. A P M score
of 23 (68T) or above resulted in the correct identification of 43.2% of the college students
who were instructed to present themselves in a positive light and incorrectly identified only
3.1 % of nomal individuals as presenting themselves in an overly positive light. P M scale
scores of 23 (68T) or above indicate an individual who portrays themselves as k ing fiee
fiom common shortcomings to which most individuals would admit, consequently it is
recommended that no other clinical scale be interpreted. Morey and Lanier (1998) re-
Detecting Depression 9
examined the effectiveness of the PIM scale, again instnicting respondents to manage their
results in a positive rnanner. Although Morey and Lanier (1998) implemented the same
sample sizes and methods as descnbed within the PAI manuai, their results indicated the
PIM scale score of 20 (6 1 T) had sensitivity of 82% for the detection of positive impression
management while the specificity of detection was 93%. Morey and Lanier (1 998) also
demonstrated that the Defensiveness Index, although a valid measure of positive impression
management, was less likely to identify defensive responders who had been idiomed of
how tests measure deception.
To examine the effectiveness of the NIM scale, Morey (1991) askecl subjects "to
simulate the responses of a person with a mental disorder" (p. 96). Results presented in the
PA1 manual indicate that the recommended empirical-derived NIM scale cut-oE score of 8
(73T) or above successfûliy identified 95.5% of these individuals, but it also identified 4.4%
of the normal population as potential malingerers. Morey and Lanier (1 998) re-examined *
the effectiveness of the NIM scale by asking students to simulate the responses of someone
with a severe mental disorder. They found that the MM scale score of 9 (771) had a
sensitivity of 90.9% and a specificity of 86.7%. Rogers, Omduff, and Sewell(1993), using
hancial incentives, examined the ability of the NIM scale to detect the malingering of
various mental disorders with naïve and sophisticated simulators (i?troductory and graduate
psychology students respectively). For these participants, the NIM scale had a successfidly
identified 90.9% attempting to feign schizophrenia, 55.9% sirnulating depression, and
38.7% simulating an anxiety disorder. Only 2.5% of conbol participants were identified as
simulators. Rogers et al. (1996) used discriminant analysis to examine the ability of the PA1
to detect malingerers and found that they could identiQ 68.9,44.7, and 81.8% of naïve
Detecting Depression 10
malingerers for schizophrenia, generalized anxiety, and major depression. These figures,
however, also misclassified almost 20% of the clinical population. Rogers et al. (1996) also
found that sophisticated sinidators (doctoral psychology students gïven a week to prepare)
were idenfied 55.0,0.0, and 19.0% of the time for the above disorders respectively. The
Malingering Index was only slightly beîîer at detecting malingerers (Rogers et al., 1993), but
like the NIM, it had difficulty detecting the less severe mental disorders (Le., depression and
anxiety). In their previous study Rogers, Orndorff, and SeweIl(1993) found no ciifferences
between sophisticated and naïve participants in avoiding detection of mdingering as judged
by NIM scale. Nor did these authors find that the level of preparation affected NIM
outcome scores. The previously cited Morey and Lanier (1998) study had cited the variation
in the effectiveness of the NIM scale found by Rogers et al. (1996), but Morey and Lanier
(1998) deviated fiom the original instructions presented in the PAI manual by adding the
adjective "severe" to mental disorder. Due to the hdings fkom the previously cited study
by Rogers et al. (1996) that described the effectiveness of the NIM scaie as dependent on the
mental disorder that was being malingered, it is possible that by using the word "severe"
Morey and Lanier (1998) influenced the results.
A dissertation by Gaies (1 993) specifically idenîified average Mhd T-scores
associated with the malingering of depression for informed (NIM of 13, 92T) and naïve
malingerers (NIM of 10,81T). Gaies (1993) findings are comparable to the hdings
reported by Morey (1 99 1 ) that NIM scale scores of 8-12 (71 -9 1 T) indicate a moderate
elevation in exaggerated davourable impression. It is surpnsing to find that the informed
rnalingerers had higher NIM scale scores than did naïve participants. Higher NIM scores by
infomied malingerers in the dissertation by Gaies (1 993) indiCa& that infonned rnalingerers
Detechng Depression 1 1
anmitted to problems not associated with depression (the NIM scale asks questions that are
not usually admtted or experienced by ciinical subjects). A possible reason for the
infomed malingeras hi& NIM scale scores was that they were aliowed to keep a
description of depression and were encouraged to refer to their descriptions throughout the
completion of the PM. This description included anxiety, brooding, obsessive wony, panic
attacks, and possible hallucinations and delusions. Due to this description, the test subjects
may have incorrectly inferred some of the NTM items as being syrnptomatic of depression.
For instance, item 249 on the PA1 (a cntical NIM item) states "Sometimes my vision is only
in black and white." Therefore, for the Gaies (1 993) dissertation, the hi& NIM scale scores
for informed participants may have been due to the description of depression she provided.
The effectiveness of the NIM scale to discnminate between people with mental
disorders, people without mental disorders, and people that mahger, is agreed upon to be
fairly good (e.g., Morey & Lanier, 1998; Rogers et al., 1996). However, there is a need for
improvement in the detection of malingering due to the discrepancy among h d i n g . There
is also the need to reduce the number of fdse positives. When attempting to detect
malingering using the NIM scale, there is variation in effectiveness according to the feigned
mental disorder. For example, individuals imtmcted to feign anxiety disorders are much
more difficult to detect than individuals instnicted to feign schizophrenia (Rogers et al.,
1996). Consequently, when examining malingering, it is important to examine the
effectiveness of the PA1 scales with respect to a particular mental disorder.
Response Latencies
Measures of psychopathology have historically relied upon conscious choices from
the respondent as a means of detecting the possibility of deception. For instance, the NIM
Detecting Depression 12
scale (Morey, 19%) uses responses to cpestions such as "Sometimes 1 cannot remember
who 1 am" and "Sometùnes my vision is only in black and white" to assess the validity of
the participant's responses. But more recently, response latencies typicaIly used in the
biologïcal and cognitive areas of psychology have dso attracted attention fiom other fields
of psychology (Fekken & Holden, 1992; Holden, Fekken, & Cotton, 199 1 ; Neubauer &
Malle, i 997).
Response latency is the time-span fiom the moment of stimulus presentation until
the response behaviour occurs. Holden, Fekken, and Cotton (1991) have described the
production of a response fiom an item on a questionnaire as an integrative process that has
the stages of stimulus encoding, stimulus comprehension, the decision process, and finally
the response selection. Item length and subject reading speed afFect the encoding portion of
the response latency, while stimulus comprehension is largely af5ected by the item
ambiguity and inteiligence (g) of the subject. The number of alternative choices and the
motor speed of the respondent a u e n c e response selection. Variables inherent in an
individual such as reading speed, intelligence (g), and motor speed are stable within-subject
factors; that is, they will have an equivalent effect upon al1 questions. For example, all other
variables behg equal, very quick readers will have faster response times than vev slow
readers due to their qui& encoding times. Variables such as item length, item ambiguity,
the number of alternative choices, and item extremity remain constant between groups of
subjects. These factors of response latency (Le., reading speed, intelligence, motor speed,
encoding, comprehension, response selection) can, therefore, be statisticaily portioned fiom
the response latency data by examining the within- and between-subject clifferences (Holden
et al., 1991).
Detedug Depression 13
The decision portion of the response latency has been proposed by Holden et al.
(1991) to be af3ected by item extremity and schema organization. Item extremity is the
degree to which questions m e r in the extent to whîch their purpose is obvious in purpose to
the respondent. For example, an obvious question taken fiom the PAI that assesses
depression may ask, 'Tve forgotten what it's lïke to feel happy." A subtle question
assessing depression may ask, ''1 can't seem to concentrate very well" (Morey, 1991).
Research indicates that people answer obvious questions quickly but respond slowly to
subtle questions (Holden et ai., 1991). Brunetti, Schlottmann, Scott, and Hollrah (1998)
used response latencies with the MMPI to assess validity of test responding. In accordance
with the theory proposed by Fekken and Holden (1 999, Brunetti et al. (1 998) found that
response times were related to the adopted schema (malingering) in that it took longer to
reject obvious items that were wepresentative of their adopted schema. Brunetti et al.
(1998) reasoned that response times were fastm with accepted schema-relevant items and
slower with rejected schema-relevant items.
Schema organization reflects the complexity and order of an individual's schema.
Lewicki (1 984) stated that the rate of socid information processing (i.e., response tirne) is
affected by self-schema Self-schema may influence the manner in which incoming data are
interpreted or coded for the provision of more information, it may infiuence social
information processing to protect or enhance self-concept, and self-schema may influence
the potential to facilitate the categorization of others. Lewicki (1 984) examined response
latencies in regards to schemas and demonstrated that salient or strong personality
characteristics are generally more accessible to the perceiver than are shortcomings, thereby
producing faster reaction times. An individual who rnalingers would be modimg hisher
Detecting Depression 14
schema, consequently creating salient pseudo-personality characteristics. This in tmn would
mod* the decision process portion and response latency.
Holden et al. (1 99 1), expanding upon previous response latency findings, presented
a mode1 for detecting psychopathology, which proposes that response latencies have
construct validity for indicating specinc dimensions of psychopathology. Their mode1
predicts that respondents who adopt a schema (positive or negative dissimulation) will
respond more quickly to items congruent with their adopted schema and slower to items
inconsistent with their adopted schema. Specifically, Fekken and Holden (1 994) descnbe
the relationship between schema organization and response latencies as follows: "when
endorsing an item, the presence of an elaborate, well organized schema is reflected in a shoa
differential response latency; when rejecting an item, the presence of that same elaborate,
well organized schema is reflected in a long latency" (p. 107). In addition, Holden and
Kroner (1992) have theonsed that incongniities (Le., long latencies due to the rejection of
items that reflect an individual's adopted schema) will necessarily occur. Incongruïties may
occur because respondents will not want to appear to be too good or too bad in an attempt to
avoid the detection of dissimulation. Therefore, respondents will endorse some of the
schema-relevant items as not being applicable to them and this will be evident in longer
response latencies in comparison to schema-irrelevant items. These conclusions by Holden
and Kroner (1 992) are supported by findings of Brunetti et al. (1998) that the rejection of
obvious versus subtle schema-relevant items will produce longer response time latencies.
As a result, there may be higher variances for malingered scales than for non-malingered
scales.
Remonse Latencv Findings
Detecting Depression 15
Holden and Kroner (1 992) measured the response latencies of prison inmates using
three self-report inventories: the Basic Personality Inventory, the Marlowe-Crowne Social
Desirability Inventory, and the Edwards Social Desirability Inventory. PreZiminary
multivariate analyses of variance indicated significant group differences between the
standard, faking good, and faking bad conditions. Using discriminant function analysis,
Holden and Kroner (1992) were able to cox~ectly classi@ 52 of the 87 subjects (59.8%),
while traditional scales of dissimulation correctly classified 55 or the 87 inmates (63.2%)).
These authors aiso conclude that "any self-report measure of psychopathology should, in
theory, be amenable to yieiduig response latencies that may be used to produce indices of
invalid responding" (Holden & Kroner, 1992, p. 172). Response score latencies have also
been shown to add ùicremental validity to MMPI scores for predicting training time in the
miiitary (Siem, 1996). Holden, Woermke, and Fekken (1993) found that only a moderate
correlation existed between item response tirne and item-total correlation, indicating that
differential response latencies contain variance extraneous to the item response process.
Fekken and Holden (1 994) found a moderate intemal consistency reliability (mean of .34), a
weak parailel fomis reiiability (means of. 1 7), and a moderate test-retest stability of response
times (mean of .34). They dso found evidence suggesting that the latencies for endoeing
trait relevant items were negatively related to trait rneasures, whereas the latencies for
rejecting items were positively related. Holden (1995) found that through the use of
response latencies and discriminant kc t ion analysis, he could significantly distinguish
between malingerers and honest test responders with University students using a 1 58-item
true/false personnel questionnaire.
Detecting Depression 1 6
Researchers thus far have not compared the response latencies of depressed
individuals to a group of individuals instructed to malinger depression. For practical
applications of response latency findings for individuals malingering fïndings, it is essential
to compare genuîne respondùig by indi~iduds who are genuinely depressed with individuals
who have been instnicted to mahger depression to ver@ real differences between the two
groups of respondents. O d y by way of direct cornparison between the two groups will
researchers be able to endorse the use of response latencies as measure, supplementary to an -
individual's cognizant choice of responses, to aid clinicians in i d e n m g possible
psychopathology. Researchers have theorized that a depressive individual is likely to
produce different response latencies than would a non-depressed individual (Kuiper &
MacDonald, 1982). Thomas, Goudemand, and Rousseau (1 999) examined the attentional
processes of subjects with major depression and found that depressive individuals had
generally a longer reaction time for al1 tasks. Particularly troublesorne for the depressive
individuals were the effortful tasks that required decision making. Therefore, for individuals
with a depressive schema, longer response latencies may be particularly expected when
effortful decisions need to be made. Specifically, depressives have been found to pay more
attention to negative self-relevant information (Kuiper & MacDonald, 1982) and may
therefore produce longer response times to self-relevant information (i.e., questions probing
levels of depression). This k d i n g is in sharp contrast to hdividuals dissimulating
depression, who will tend to answer scherna-relevant questions more quickly than questions
not related to their adopted schema
Kaplan and Saccupo (1993) state that "in psychological testing.. . . we acknowledge
that there wiill always be some inaccuracy or error in our measurements. Our task is to f b d
Detecting Depression 17
the magnitude of this error and to develop ways to rninimize it" (p. 99). The purpose of the
present study is to use response latencies to detect diffkrences between depressed, faked
depressed, and nondepressive individuals. Previous research suggests that the operating
schema will have an impact upon response time. Unlike previous research that has based
evaluations on non-clinical samples, the current study used a clinicat sample of depressed
individuals and took efforts to ensure that the controls and rnalingerers were fiee of any
psychological disorder. Previous research has also ignored other possible important
characteristics (e.g., vocabulary Ievel) of the samples used This study will attempt to
addresses these important gaps in the current fiterature.
We hypothesize the following related to the NIM, PM, Depression (DEP), and DEP
subscales of the PM:
1 - Faster raw response times and faster standardized response latencies will be recorded for
individuals malingering depression than for individuals in the control and the depressive
groups. This ciifference is hypothesized due to the rnalingerers' salient schema of
depression.
2. Slower raw response times and standardized response latencîes will be recorded for
inaviduals experiencing depressive symptoms than for individuals in the control and
malingering group. This merence is hypothesized due to the findings of Thomas et al.
(1 996) stating that depressed individuals have slower response tirnes for al1 tasks.
3. Larger group differences will be evident with the DEP-cognitive subscale due to its
obvious item content. This hypothesis results fÏom the fïndings by Holden et al. (1991) that
response latencies Vary with item extrernity.
Detecting Depression 18
4. The use of response times will add incremental validity to the detection of individuals
experiencing depression and individuals malingering depression. Scale scores have been
proven to be effective at detecting malingering and it is hoped that response times wiU be
able to increase this detection rate.
Method
Testhg was completed over two sessions. The first session was used to iden*
participants as controls, malingerers, or depressed according to the criteria reviewed in the
following sections. During the second session the PM was sdmùiistered and response times
were recorded.
Session 1 - Cateeorization
Participants
Session 1 consisted of two groups of participants, the f k t of which was 122 university
-dents enrolled in an introductory psychology course at Lakehead Universi~ Thunder
Bay, Ontario. Student participants received a bonus mark toward their final introductory
psychology grade for involvement in the study. The second group of participants consisted
of seven individuals receiving treatment fiom the Outpatient Department at the Lakehead
Psychiatric Hospital (LPH). These participants were recruited with the help of unit nurses
who were explained the entrance criteria (see Appendix A). Nurses were requested to aid in
recruiting participants to maintain patient confïdentiality and speed the recruitment process.
Measures
Three instruments were used during Session 1. Participants were asked to complete the
Stnictured Clinical Interview for DSM-IV Screen Patient Questionnaire (SCKD Screen PQ;
Fkst, Gibbon, Williams, & Spitzer, 1997), the Beck Depression Inventor). - 2 @DI-2; Beck,
Detecting Depression 19
Steer, & Brown, 1996), and the Shipley M t u t e of Living Scale - Revised (Shipley;
Zachary, 1991). Total t h e of testing was approximately 40 minutes.
The computerized SCID Screen PQ is a stmctured i n t e ~ e w designed to assess
psychopathology for DSM-N Axis I disorders. Questions were presented to participants
using the Windows 95 operathg system on a 15-inch colour monitor. The SCID Screen PQ
interview covers 6 major diagnostic categones within DSM-IV Axis I (Mood, ANUety,
Substance Use, Somatoform, Eating, and Psychotic disorders). It requires a grade seven
reading level and takes under 20 minutes to complete. The SCiD Screen PQ was designed to
be over-inclusive for positive responses to symptomotology. Questioning fiom the
experimenter followed the computerized interview to substantiate the presence of any
symptomotology characteristic of Axis 1 disorders.
n i e BDId is a 21 -item self-report inventory used to assess the severity of depressive
symptoms in adults and adolescents. Testing time for the BDI-2 is under 1 0 minutes. Beck
et al. (1996) reported that the %DI-2 has high reliability for outpatients and college students
(coefficient alphas of .92 and .93 respectively). Beck et al. (1 996) also reported a test-retest
correlation of .93 for therapy sessions one week apart. The BDI-2 has been widely accepted
and used by psychologists to measure the seventy of depressive symptomotology in
depressed and in normal populations (Piotrowski & Keiler, 1 992).
The Shipley (Zachary, 199 1) is designed to assess general intellectuai functioning in
adults and adolescents aged 14 and over and takes under 20 minutes to complete. The
Shipley consists of a 40-item vocabulary subtest and a 20-item abstract thinking subtest. Of
interest to the present study were the possible confounding influences of verbal ability upon
response times. The full test was, therefore, not necessary and only the vocabulary subtest
Detecting Depression 20
was administered. Zachary (1 99 1) asserts that the vocabulary subtest generally measures the
respondent's verbal ability, which is compnsed of acquired howledge, long-term memory,
verbal comprehension, concept formation, and reading ability. The vocabulary subtest is
self-administered and time of testing is up to 10 minutes. A corrected split-half reliabilïty
coefficient of .92 for the total score fias been reported using the Spearman-Brown
computatiod formal. The test-retest reliability over a median interval of 12 weeks was .60
for the vocabulary score. In addition, the correlation between the Shipley total score and the
Wechler Adult Intelligence Scale - Revised has been reported as -74 (Zachary, 199 1).
Procedure
Participants were administered the SCXD Screen PQ, which allowed the researchers to
1) confm that subjects in the depressed sample met critena for depression; and 2) determine
that participants in al1 categones did not meet criteria for any DSM-N Axis 1 disorders (other
than depression for individuals withui the depressed sarnple). Session 1 then proceeded with
the administration of the BDI-2. The BDI-2 was used to determine if participants of Session
1 were eligible to participate in Session 2. Specifically, individuals with scores of 8 or below
and individuals with scores of 17 or above were eligible to participate in the second session.
Individuals who scored 8 and below (i.e., individuals indicating iittle or no depressive
symptoms) were randornly divided into the control and malingering groups. Individuals who
scored 17 or higher (Le., reporting moderate to severe depressive symptomotology) were
eligible for the depressed group. A score of 17 or above is recomrnended by the authors of
the BDI-2 (Beck et al., 1996) for conductuig research with individuals who are currently
expenencing depressive symptoms. Following the BDI-2, the Shipley was administered. At
the end of the session participants were given verbal feedback on the purpose of Session 1
Detecting Depression 2 1
and were given a debriefing form (Appenduc B). Individuals who met the BDI-2 cut-offs
were asked to participate in Session 2. Upon agreement, a second session was scheduled for
universisr students at their earfiest convenience. Participants fiom the LPH were given a 15-
minute break, &er which the second session began. Immediate testing was conducted for
these participants for the purpose of convenience.
Session 2 - Experhentation
Participants
Fifty-five university students and six participants fiom the Outpatient sample met the
BDI-2 cut-off scores and partook in the second session. University Students were given a
bonus mark on their final grade in their introductory psychologr class for participation in the
second session. Following the completion of testing, individuals who did not meet cnteria
were removed fiom data analysis and the remairing participant data were examined for
outliers (to be described in the following section). The final sample consisted of forty-five
university students (35 females and 8 males) and one LPH participant (1 fernale). The mean
age of the sample was 20.30 years. Ethnic and racial information wzs not collected.
Measures
Participants began the second session by completîng the Balanced Inventory of Social
Desirability Responding - Version 6 Form 40 (BIDR, Pauihus, 1 984, l988), followed by the
BDI-2 (Beck et al., 1996), and a computerized version of the PM (Morey, 19%)
prograrnmed by the authors. Total t h e of testing was approximately 50 minutes.
The BIDR is a 40-item inventory designed to assess self-deceptive positivity and
impression management. Self-deceptive positivity is the tendency to give self-reports that
are honest but positively based, while impression management is the deliberate self-
Detecting Depression 22
presentation to an audience that daers fiom true self-presentation. Coefficients alpha ranged
from .68 to -80 for self-deceptive positivity- and fkom -75 to -86 for impression management
(Paulhus, 1984, 1988). In addition, test-retest reliability over a 5-week period was reported
as .69 for self-deceptive positivity and -65 for impression management (Paulhus, 1984,
1 988). The BIDR data were not included in present analyses.
Procedure
The second session began with the administration of the BIDR. It was administered
before PA1 responding insûuctions were given. The BIDR was administered to collect
ixiformation for future research. Following the BIDR, participants were once again asked to
complete the BDI-2 to ensure that levels of depressive symptorns had not deviated fiom
group membership requirements. The second BDI-2 was scored following the completion of
the session. As such, the computerized PA1 was administered regardless of the BDI-2 score
at the tirne of testing.
The PM was presented on an IBM compatible computer using a 15-inch colour
monitor. Test questions were programmed with GWBasic and displayed using the
Windows95 operathg system (see Appendix C for the command h e s of the computer
program). Ten additional questions were added to the PAI to accustom participants to the
test format. The prograrn displayed questions one at a time to which participants responded
by typing keys I (False), 2 (Slightly True), 3 (Mainly True), or 4 (Very Tnie). The
participants' responses to each question were recorded and the computer prograrn measured
the response time fiom moment of test item presentation to the moment of key press (RTl).
h e d i a t e l y after answering each question, participants were asked to confimi their ansvzr
by entering y (yes) or n (no). A second response tirne, defined as the time fkom moment of
Detecting Depression 23
initial presentation until the moment of confimation, was also recorded (Rn). Should the
participant disagree with h i s k r choice @y choosing n at point of c o ~ a t i o n ) , the response
latency time recorded for RTl was reset and measured fiom the instant of disagreement until
the new answer was keyed.
Non-depressed participants were randomly assigned to either the control or the
malingering condition. Individuals participating in the control and depressed conditions were
asked to complete the PA1 as honestly as possible. Participants in the malingering condition
were asked to attempt to deceive the test by responding as if they were depressed.
Immediately before testing, individuals in the malingering condition were provided with
wxitten instructions for completing the PA1 (Appendix D). These instructions were read
aloud by the experirnenter and the participants were given the opportunity to ask questions.
The instructions aven to these participants were intended to assist them to eEectively
malinger. A portion of these instructions involved tetling participants that the questionnaire
is designed to detect lying; thus they were also given the additional task to avoid detection as
a person who is faking depression They were then told that a $25 prize would be awarded to
the person who avoids detection as a faker and presents with the highest level of depression.
This method for detemiinùig effective malingering was adopted from the format employed
by Rogers et al. (1 993,1996). Specifically, effective malingering was detemüned by (a) 2 T-
score on the Negative Impression Management scale of Tq0 and (b) the highest elevation
on the depression scale. Participants within the depressed condition and the control condition
were each eligible for a random draw of $25. Following the PA1 administration, individuals
were verbaliy debriefed on the purpose of Session 2, given a debriefing form (Appendix E),
and provided with the opportunity to ask questions.
Detecting Depression 24
As previously rnentioned, the total number of Session 2 parîicipants was 61 (55
university students and six outpatients fiom the LPH). Before data analysis began, groups
were examined to ensure that they met previously stated criteria Five participants were
removed from subsequent analyses due to BDI scores that were eitha too high or too low;
one participant was removed due to age differences; and nine participants were removed due
to their endorsements of comorbid a x i s I disorders during the SCID interview. The resulting
h d sample included 15 participants in the control condition, 19 participants in the
malingering condition, and 12 participants in the depressed condition. There were no
differences between groups on sex k2 (2) = -1 1, n-S.], age IF (2,43) = 1.8 1, n-s.], and Shipley
scores [F (2,43) = -665, n.s.1. There were signifïcant group clifferences in BDI-2 scores at
tirne of PA1 administration [F (2,43) = 2 1 0.68, p < -00 1 1. Tukey post-hoc analyses of the
BDI-2 scores revealed that the control and maiingering groups differed significantiy fYom the
depressed group. The BIDR results were not examùied for the present study.
Treatment of Response Times
As previously noted, a response latency has many components. These components
can be roughly separated into individual characteristics (Le., reading speed, intelligence,
encoding, comprehension, decision, motor speed) and item characteristics (length,
vocabdary, complexity, ambiguityy number of choices). Authors (e.g., Fekken & Holden,
1992; Neubauer & Malle, 1997; Robie et al., 2000) agree on the importance of minimizùlgy
as much as possible, the variance in response latencies due to individual attributes and item
attributes, without removing variance due to the schema driven decision process. This
decision process is the c m of al1 research in response iatencies because researchers
D e t e h g Depression 25
conjecture that particular decisions regardhg item content (e.g., simple decisions or difficult
decisions) will be evidenced as differences in response latencies.
The method used to remove variance attzibutable to individual and item
characteristics has not yet been agreed upon and varies fiom author to author (e.g., Fekken
& Holden, 1992; Neubauer & Mdle, 1997; Robie et al., 2000). Most authors cite the works
of Fekken and HoIden (1992) and their double-standardization procedure. The procedure by
Fekken and Holden begins with a -score transformation, the &st standardizaîion in the
double-sbndardization procedure, for each individual on hidher set of raw response
latencies. In this way their response latencies are transformed into a deviation of the
individual's mean responding time; this deviation fiom mean responding may be
attributable to item characteristics and the decision process. In eEect, the first
standardization removes the error variance attributable to individuai characteristics that
remain stable across items. The double-standardization procedure then continues with the 2-
scores obtained fiom the first transformation and standardizes those scores across items. In
this way, the variance due to item attributes are contrded, and it is hypothesized that the
remaining differences in scores foliowing the double-transformation represent differences in
the schema driven decision process. Other authors have disputed Fekken and Holden's
rationale (Neubauer & Malle, 1997; Robie et al., 2000).
Neubauer and Malle (1 997) stated that they agree with the removal of variance due
to item characteristics but they disagree with the removal of variance due to individual
charactenstics. They believe that while individual ". . .variance might reflect individual
ciifferences in reading speed, it may also contain individual merences in self-knowledge,
which are crucial" (p. 1 1 1). Neubauer and Malle (1 997) favored the l o g a r i t c
Detecting Depression 26
transformation of response times, followed by mean deviating the transfomeci latencies for
each item. That is, they calculated a mean for each item and fiom that score they subtracted
the individual's item log latency. However, it seems that the argument put forth by
Neubauer and Malle (1 997) is flawed. Firsf it is unlikely that individual differences in self-
knowledge are removed fiom with the single standardization process. In fact, individual
difYerences in seIf-knowledge wiil Wcely be amplified by removing the variance attributable
other individual characteristics, such as reading speed. This is due to the very nature of self-
knowledge; it is more salient for some items and less distinct with other items. The process
of standardization removes the same proportion of variance attributable to individual
ciifferences for each item, and therefore, standardization cannot remove the effects of seK-
knowledge, which as argued by Neubauer and Malle (1997), is dzferent for each item.
Neubauer and Malle (1 997) also stated that they have "statistical reservations about Holden
et al.3 'double-standardization' procedure" (p. 11 1), because the removal of individual
dinerences creates artificial negative correlations among subscales latencies if the rnean raw
subscde latencies differ fiom each other (i.e., slow response latencies become positive -
scores, quick response latencies become negative -scores). It is incomprehensible how
these correlations could be &cial if the two scales have different mean latencies. The fact
the correlation is negative instead of positive makes little difference. Finally, Neubauer and
Malle (1 997) pedorrned their analyses on both the raw and transformed response latencies
and found no diserences in signincant findings between the two methods. This implies that
their chosen method for response latency transformation was unnecessary.
Robie et al. (2000) also argue against the double-standardization method but adopt a
different position fiom Neubauer and Malle (1 997). Robie et al. (2000) argue that there is
Detecting Depression 27
no strong empKica.1 evidence that the double-standardization method removes variance due
to individual and item characteriçtics. Robie et al. (2000) also state that the fïndings fiom
the double standardization method are not eady put into practice because the mean and
standard deviations fiom separate groups are used in some of the calculations to determine
the adjusted latencies in the faking group (Le., the second standardization across items). The
method chosen by Robie et al. (2000) regressed response latencies on a measure of item
complexity for each individual. Then they used the standardized residuals for each item for
each individual in an individual level regression analyses to obtain what they believed are
estimates of response latencies that explicitly control for sentence complexity and reading
speed- The tool used to measure item complexity was the Flesch-Kincaid grade index.
These authors also estunated item complexity with other meamire and found that all
measures were intercorrelated at .95 (Robie et al., 2000). While it is true that the double
standardization procedure relinquishes applicability, the procedure used by Robie et al.
(2000) introduces e m through the rneasurement of item complexity, followed by
individuai regressions on that ùnperfect measure. Although these authors performed an
adequate job at identifjing the item grade level, in the absence of any control for individual
merences in vocabuIary level they assume that dl items of certain grade levels affect d l
individuals equdy. It may be that some very intelligent individuals are not afEected by item
complexity while some less intelligent individuals may be greatly affected by item
complexity.
The first part of Holden et d.'s (1 99 1) double-standardization procedure, that is
single standardization, appears to be the most appropnate for this study. Cornparisons will
be made across groups and not at the item level; therefore, there is no need for the second
Detecting Depression 28
standarcbation of response latencies. Any effects attributable to item characteristics are
controiled because all groups receive the same items in the same order of presentation.
Also, there may be a problem with the second standardkation in that it assumes that the
a ~ b u t e s of the item will affect al1 groups equally. Instead, it rnay be that item attributes,
such as low complexityy are maximally able to distinguish depressed individuals fkom
individuals attempting to feign depression; an individual experiencing depression may take
more time with a simple item because it has greater meaning for him or her. In addition,
response times standardized within subjects are easily understood and the z-scores can be
readily transfonned back into seconds. In cornparison to scores that are standardized,
double standardized scores are more difficult to interpret and understand in seconds. This
study wiU use the procedure set forth by Fekken and Holden (1992) but only the single
standardization wiil be applied.
Response times were initially examined for outhers. Following the procedure of
previous researchers (Fekken and Holden, 1 992, 1994; Holden 1999, all RTl s and RT2s
were analyzed for times less than 0.5 seconds and greater than 40 seconds and changed to
0.5 and 40 seconds, respectively (5 RTs, -002% of the data, were greater than 40s). Next,
RTI and RT2 were standârdized within individuals to remove idiosyncratic differences in
speed of responding. - . All -scores less than-3 or greater dian +3 were set to these respective
values. The modification of -scores was preferable to the removable of potentially
meanin@ data, especially with the proposed hypothesis that longer latencies will be
recorded for items that are more meanin- to an individual. Following the example of
previous research (Fekken & Holden, 1992, 1994), only -cores for RT1 (initial
responding) were used. The initial response times are poçhilated to represent a more
Detecting Depression 29
impulsive or less thought out answer to item presentation. For the following sets of
statistical procedures, raw response times were examined to verify the effectiveness of the
standardkabon procedure.
Results
Any interpretation of resdts regarding response latencies requires direct
comparisons with scale score findings. In addition, the effectiveness of response latencies in
i d e n m g malingerers can only be determined in cornparison with the proven efficacy of
the PA1 scale scores. Each statistical step, therefore, begins by examining groups for
s i p i k a n t diEerences in scale score responses.
Descrktive Statistics
Descriptive scale score statistics for the NIM, PM, DEP, and DEP subscales are
presented in Table 1. Mean raw response time totals for RTl were as follows: Control
1342.9 s (SD = 299.0 s); Malingering 1405.8 s = 253.6 s); and Depressed 1565.1 s (So
= 377.1 s). Raw response time totals for RT2 were: Control 1584.7 s (SD = 3 3 0.9 s);
Malingering 1612.2 s (- = 284.7 s); and Depressed 1805.7 s (- = 470.4 s). Descriptive
statistics for the mean response time to items in the NIM, PIM, and DEP scales are
presented in Table 2.
For al1 analyses, -scores for each item were added across the scales of interest due
to their nature, namely that the sum of an individual's -scores is O. In actuality the sum of
the -scores was slightly negative, a mean of -.O2 per item, due to the adjustment of z-scores
greater than +3. The means for -scores across groups were: NIM -0.47 (SD 2.79), PIM -
0.40 (- 2.82), DEP -3.90 (- 4-30), DEP-Affective -0.84 a 2-25), DEP-Cognitive -7.16
Detecting Depression 30
(So 2.3 8), DEP-Physiologicd -0.9 1 (SD 2.73). Descriptive statistics for -ore group
means are presented in Table 3.
Findings
A one-way aaalysis of variance was used to examine Merences between groups for
total raw response times and total -scores (i.e., for a 3 4 4 items). Con- to expectations,
no significant differences were found between groups for overall raw response times F T l F
(2,43) = 1.86, as.; RT2 F (2,43) = 1.5 1, n-s.], and according to expectation, no significant
merences were found between groups for total Z-scores [F (2,43) = .36, n.s.1.
Scale scores were examined for differences using a multivariate analysis of variance
(MANOVA), and found signincant ef5ect of group, W&' Lambda F (10,78) = 16.08, p <
-001. Univariate significant differences between groups were as follows: NIM [F (2,43) =
18.97, < .001], PIM (F (2,43) = 9.23, g < .001], DEP IF (2,43) = 64.80 ,~ < .001], DEP-
Affective [F (2,43) = 80.16, E c .001], DEP-Cognitive [F (2,43) = 53.75, p < .001], and
DEP-Physiological [F (2,43) = 25.22, p < .0G1]. Tukey post-hoc tests of significant
differences between groups are presented in Table 4. Examination of these post-hoc results
revealed significant differences between almost al1 possible comparisons, indicating that al1
groups significaotly differed fkom each other in the level of item endorsement.
A MANOVA was then performed to examine group differences on raw response
times (both RT1 and Rn). Multivariate tests found a significant effect of group, W W s
Lambda F (1 0,78) = 3 . O ~ , E = .002. There were significaht univariate differences for NIM
RT1 [F (2,43) = 3.714, p = .016], and the DEP-Cognitive RTI [F (2,43) = 5.627, E = .01].
Tukey post-hoc analyses with NiM RTl times indicated signincant dserences between the
Control and Malingering group @ = .024) and between the Control and Depressed group @
Detecting Depression 3 1
= -047). DSerences for the DEP-Cognitive subscale were between the Depressed and
Control groups @ = -0 15) and between the Depressed and Malingering group @ = -022).
This fiduig indicates that the maluigerers responded to the NIM questions in the same
average time (4.24 s) as depressed individuals, whereas they f d e d to respond to DEP-
Cognitive items in a similar manner as the depressed individuals.
A MANOVA was used to examine group merences for 2-scores. Mdtivariate tests
indicated a significant effect of group, Wilks Lambda F (1 0, 78) = 3.3 6, Q = -00 1.
Univariate results were as foUows: NIM (2,43) = 8.14, E= .001], P M r ( 2 , 4 3 ) = 5.04,
E = .O 1 Il, DEP [F (2,43) = 2.27, ILS.], DEP-Affective IF (2,43) = 3.00, n.s.1, DEP-
Cognitive [F (2,431 = 4.09, Q = 0.241, and DEP-PhysioIogical [F (2,431 = -65 1, n.s]. The
Tukey post-hoc results are iisted in Table 5. The larger F Ratios obtained using -scores, in
cornparison to the raw scores, indicate that the -scores were more effective in
distinguishing ciifferences between groups . Likewise, the larger F ratios obtained using
scale scores also indicate the supenority of scale scores in distinguishing group merences.
Next, we wished to determine ifresponse times are able to add incremental validity
for detecting individuais expenencing depression and individuals malingering depression
discriminant fbnction analyses were conducted. Dischinant fimctions were performed for
scale scores, raw response times, transformed response times, a combination of s a l e scores
and raw response times, and a combination of scale scores and transformed response times.
Only those variables found to have significant univariate F ratios from the MANOVA
analyses (i.e., only variables that were significantly different between groups) were entered
into the discriminant hction.
Detecting Depression 32
A direct discriminant fünction analysis was performed to determine how well scale
scores (MM, PIM, DEP-Affective, DEP-Cognitive, DEP-Physiological) could correctly
classi@ individuals. The three groups were signincantly distinguishable a2 (10, N = 46) =
91 -73, Q < -001. After removal of the largest disrriminant fünction the remaining function
was also signincanf x2 (4, N = 46) = 17.69, E = -001. The two functions accounted for
90.4% and 9.6%, respectively, of the between group variability. The correct classification
rate for the three groups through chance alone is 34.5%. The correct classification rate for
the three groups using scores to discriminate was 87.0%. Table 6 presents the specific
class~cation results using scale scores.
A direct discriminant function analysis was performed to determine how well raw
response h e s (NIM-raw, DEP-Cognitive-raw) could correctly c lasse individuals. The
three groups were significandy distinguishable (4, N = 46) = 18.3 5, E = -0011. M e r the
removal of the Grst discriminant fuaction, the remaining fiinction was also signincant x2 (1,
N = 46) = 8.04, = .005]. The two fûnction accounted for 56.9% and 43.1%, respectively,
of the between group variability. The correct classification rate using response times was
69.6%. Table 7 presents the specinc classification rates.
Next, the effective classification rates for -scores (NIM, PM, DEP-Cognitive) were
examined with a direct discriminant function analysis. The three groups were agah
distinguishable k2 (6, N = 46) = 24.18, Q -= .O0 11. M e r the removal of the first function,
the remaining function was also significant [y2 (2, N = 46) = 7.02, E < -051. The two
function accounted for 73.5% and 26.94, respectively, of the between graup vaiability.
Detecting Depression 3 3
Table 8 presents the specific classincation results using -ores to discriminate between the
tbree groups. The correct classification rate for the -scores was 73 -9%.
As reported the raw response times and transfonned response times were fair
indicators of group membership but not nearly as effective as the s a l e scores. To determine
if the response times (raw and transformed) added incremental abiïty to classify
participants, we entered the scale scores and the raw response times, followed by the scale
scores and the transfonned response times into a direct discriminant function analyses. A
direct discriminant fiinction analysis was perfonned on the scale scores @iIM, P M , DEP-
Affective, DEP-Cognitive, DEP-Physiological) and the raw response times (MM-raw,
DEP-Cognitive-raw). nie three groups were signincantiy distinguishable x2 (14, N = 46) =
92.56, p < .001. After removal of the largest discriminant function the remaining function
was also significant, X2 (6, N = 46) = 18.88, p = .004. The two hct ions accounted for
89.8% and 10.2%, respectively, of the between group variability. The correct classification
rate for the three groups using scores to discriminate was 87.0%. Therefore, the addition of
raw response times did not increase the abiïity to differentiate between groups.
A direct discriminant fûnction analysis was pdormed on the s a l e scores (MM,
PM, DEP-Affective, DEP-Cognitive, DEP-Physiological) and the raw response times
(NIM-raw, DEP-Cognitive-raw). The three groups were significantly distinguishable, a2
(16, N = 46) = 93 - 8 2 , ~ < .O0 1. After removal of the largest discriminant function the
remaining hc t ion was also significant, y2 (7, N = 46) = 2 1.61, p < -003. The two fûnctions
accounted for 87.8% and 12.2%, respectively, of the between group variability. The correct
classification rate for the three groups using scores to discriminate was 89.1%. While the
Detecting Depression 34
increase in classification is only 2.1%, an examination of the classification rates presented
Table 5 and Table 8 indicates the ciifferences as being the ability to properly i d e n a
malingerers, an increase fkom 73.5% to 78 -5%.
In clùlical practice, the fïrst attempt to detect rnalingerers examines the respondent's
NIM scaie score (Morey, 1996). We therefore examined the NIM scde and the NIM
transformed response times, separately and in combination, for theK ability to properly
classi@ the three groups. A direct discriminant function analysis was performed, the NIM
scale was able to sigmfïcantly distinguish groups k2 (2, N = 3 1) = 27.20, E < .001]. The
correct classification rate using the NIM scale scores for the three groups was 56.5% (see
Table 10 for specific classification rates). A direct discriminant hc t ion analysis for the
raw response times did not produced a signifiant fünction, 1L2 (2, N = 46) = 8.22, E = .016.
The correct classification rate using the NIM -scores for the three groups was 58.7%. The
NIM transformed response latencies were also able to significantly distinguish groups [a2
(2, N = 3 1) = 13 -8 1, p = .O0 11. The correct classification rate using the NIM -scores for the
three groups was 63.0% (see Table 11 for specific classincation rates).
A direct discriminant fûnction analysis was pelformed to examine the correct
classification rates for use of the NIM scale scores and NIM raw response times; the groups
were si@cantly disfinguishable [yZ (4, N = 46) = 33.29, E < .O0 11. After rernoval of the
first hction, a second function was also sigmficant k2 (2, N = 46) = 4.57, Q = .033]. The
two functions accounted for 89.5% and 1 OS%, respectively, of the between group
variability. The correct classification rate using the NIM scale scores and the NIM raw
response times was 65.2% (see Table 12 for specific classification rates). Using the
Detecting Depression 3 5
combination of NIM scale scores and NIM p o r e s , the groups were significantly
distinguishable [r2 (4,s = 46) = 30.04, E c .001]. The correct classification rate usïx~g the
NIM scale scores and the NIM g-scores was 65.2% (see Table 13 for specinc classincation
rates). Although the MM raw response times and NIM z-scores appeared to perform
equally when paired with the scale scores, inspection of differences in Tables 12 and 13
indicate that the NIM z-scores were more important for classimg rnalingerers properly. It
would seem, therefore, that the NIM -scores could be used to add incremental validity to
the NIM scale score for detecting the malingering of depression.
Finally, we wished to i d e n e those items that could maximally classify individuals
as belonging to either the malingering or depressed groups. AU -scores recorded fkom the
items in the NIM, PIM, and DEP scales were entered into an independent mst. The 1-test
identified 9 items as being sig&ficantly different. These items, their respective scales, the
mean differences between groups, and -st values are presented in Table 14. Using the 9
significant -scores 5om die -test, a discriminant function analysis was pefiormed to
detennine how well these -scores could classify individuals as being in either the
malingering condition or the depressed group. The correct classification rate by chance is
52.55%; the correct classifkation rate using the 9 -scores was 96.8% (specific classification
rates are presented in Table 15). One depressed person was misclassifïed as being a
malingerer .
Discussion
This shidy intended to M e r previous research on response times and idente
clifferences between individuals not cunently experiencing psychological difficulties,
individuals experiencing depression, and individuals malingering depression. Generally,
Detecting Deprestion 36
results indicated that malingerers have a dif3erent response style than honest individuals and
malingerers also have different rates of infonnation processing. That is, individuals
malingering depression have a distinct set of response latencies. Using this pattern of
response latencies, without the use of s d e scores, it is possible to distinguish behiveen
individuals experiencing depression, individuals malingering depression, and individuals
who are not experiencing any DSM-IV Axis 1 disorders.
The current study was the e s t of its kind to use the PA1 and ïnvestigate whether
response times could aid in the detection of individuals who were malingering depression.
It is also the first study to examine the response times of malingerers against a sample
clinical population of the disorder being malingered. W e previous research has hdicated
&£ferences between malingerers and honest responders, without cornparisons to a group of
indwiduals genuinely expenencing the malingered disorder, practical conclusions cannot be
drawn. Finally, this study is the fïrst to ensure that controls and malingerers were £kee of
any psychological disorder.
Holden et al. (1991) proposed that respondents who adopt a schema (Le.,
malingerers) will respond more quickly to items congruent with their adopted schema. In
this study, the DEP scale items are congruent with the adopted schema of malingerers.
Overall, malingerers did perform more quickly but this difference was only significant for
the Depression - Cognitive subscale and only in cornparison to depressed uidividuals. As
reported, raw response latencies were iderior at providing signincant between-group
ciifferences. An example of the effectiwness of transformed response latencies was the
clifference between depressed individuals and malingerers for the Depression - Cognitive
scale. For raw response latencies, the groups had statistically equivalent mean respondùlg
Detecting Depression 37
t h e for each (depressed group = 4.39 s / item; malingering group = 3.75 s 1 item). But for
the same scale, for transfonned response iatencies, the two groups were significantly
different with depressed individu& having a -score mean of -S8, while malingerers had a
z-score mean of -2.8 1. This example also illustrates the ciifference in meaning between -
response times and response latencies. While malingering and depressed individuals
answered the Depression - Cognitive questions with approximately equivalent response
times, malingering individuals answered these questions much faster than their mean
responding times and depressed individuals answered these questions only slightiy fasta
than their mean responding time.
Kuiper and MacDonald (2982) foiind that depressed individuals pay more attention
to negative self-relevant information. It was thexfore-hypothesised that depressed
individuals would have longer response latencies to self-relevant information (Le., questions
probing levels of depression). This hypothesis was supported with the Depression -
Cognitive subscale between depressed individuals and rnalingerers. Interestingly, relative to
their respective mean response latencies, malingerers were significantly slower than both the
depressed and the control groups at answering questions to the NIM items. Evidently
malingerers had to take extra time to respond to NIM questions, relative to their mean
response latencies, and ask themselves if these questions were applicable to their adopted
response style. Malingerers are actively attempting to present themselves in a negative light,
therefore NIM questions are negatively seE-relevant to malingerers. Malingering
individuals also took significantly less tirne than controls to respond to P M items.
Individuals in the control group had to think about the positive impression questions,
whereas the malingerers presented themselves in an abnormally low light and so they were
Detecting Depression 3 8
not concemed with presenting themselves in a positive light. These fhdings support the
work of Kuiper and MacDonald (1982) that hdividuals pay more attention to self-relevant
information, thereby generating longer response latencies. From examining the trends in
Table 3, m e r research with a Zarger sample may further support this hypothesis.
SpecifïcaIly, a larger sample size may produce significant clifferences between ail groups for
the NTM, PIM scdes and differentiate depressed individuals fiom the other two groups for
the Affective and Cognitive subscales of the Depression scale.
Holden et al. (1 991) indicated that schema organization and item extremity affect the
self-referent decision process. Because of this theory, we had hypothesized that larger
group differences would be evident with the Depression - Cognitive subscale due to its
obvious content (i.e., item extremity). Our hypothesis was supported in that simiificant
differences in response latencies were contingent upon the scale and questions being
anaiysed An example between the malingering and depressed groups where response
latencies were significantly different was Depression - Affective item 286, which states
"I'm almost dways a happy and positive person" While this question was endorsed
similarly by both malingering and depressed individuals, mdingerers answered significantly
more quickly to the question with a mean Z-score of -96 less than the ù lan the depressed
hdividuals. That is, in cornparison to nomal responding rates for each group, malingerers
answered the question a b s t 1 SD faster than did depressed ùidividuals. A specific
instance where differences did not occur in response Iatencies between malingering and
depressed individuals was NIM item 89, which states "Since the day 1 was bom, 1 was
destined to be unhappy." Both malingerers and depressed individuals answered with the
same relative response latencies, whereas the malingering group had an average
Detecting Depression 39
endorsement of MAINLY TRUE and all depressed individuals answered FALSE, NOT AT
ALL TRUE. This would indicate that this question was a m d e d to by both groups equally,
perhaps because the answer to the question is not obvious to both groups. Support for the
subtle item conclusion is that the question contains negative self-relevant information for
both groups as well as the question being only pdally endorsed (MAINLY TRUE) instead
of M y endorsed (VERY TRUE). These results concur with the findings that depressives
pay more attention to negative self-relevant information (Kuiper & MacDonald, 1982) and
may fürther this theory in adding that al2 individuals produce longer response times to self-
relevant ùiformation. Item extremity may refine when merences in response latencies
occur due to negative self-relevant information. We wilI retum to this issue of obvious
versus subtie items in the discussion on the classification rates using a measure constnicted
fiom the moa discriminating items.
To maximally differentiate group response styles, correct ~Iassification rates were
investigated between groups for scde scores, raw response latencies, and standardized
response latencies. The results of this study demonstrated that different groups of
respondents to the PA1 (i.e., depressed, malingerers, controls) could be adequately
discriminated via an analysis of response times. AIso, the evguaiion of PA1 scale scores
indicated Iarge differences between all groups, thereby producing elevated correct
classification rates. We compared the ability of the response latencies to the scale scores in
correct classification rates. It was found that while scale scores were superior at classimg
hdividuals, transformed response latencies could provide additional non-overlapping
information useful in the identification of malingerers. That is, the addition of transformed
response latencies increased the detection of malingerers by 5% (a total of 78.5%).
Detecting Depression 40
Although, this merence was not of s ac i en t magnitude to achieve statistical signincance,
M e r research may strengthen current trends within the data that indicate the ability of
response latencies to distinguish real and malingered psychopathology.
Analyses were then conducted at the item Ievel to discover the transfomed response
latencies that were maximally able to discriminate between malingerers and depressed
îndividuals. A specific set of ûansformed response latencies was able to correctly classe
96.8% of malingering and depressed individuals. The items presented in Table 14 that
produced negative -scores (items that were answered relatively more quickly by
malingerers) were as follows: 46. 'Tve forgotten what it's like to be happy."; 286. "I'm
almost aiways a happy and positive person."; 187. 'Wo matter what 1 do, nothing works.";
275 "I often wake up in the middle of the night."; 144. "Sometimes I'm too impatient.";
264. '1 sometimes make promises I can't keep." These items were responded relatively
more slowly by depressed individuds, but were responded relatively more quickly by
individuals malingering depression. Conversely, items to which malingerers had to ponder
before responding (relative to their other latencies) but to which depressed individuals
answered relatively more quickfy were: 3 15. '1 have Little interest in sex."; 9. ccSometimes 1
cannot remember who I am."; 49. "Sometimes 1 have visions in which I see myself forced to
commit crimes." Although item extremity and the self-relevant information hypothesis
(Kuiper & MacDonald, 1982) are used to explain these fbdings, two of these significant
ciifferences were expected by chance alone, and so more research is necessary to elucidate
these iesuits.
Limitations
Detecting Depression 4 1
It should be noted k t Holden and Kroner (1992) response latencies could be
differentiated on the basis of acceptance or rejection. These authors employed measures
with True or Faise responses, and had an equal number of false-keyed questions. The
application of their approach is problematic due to an unequal number of negative keyed
items (15 of 42 items examined were false keyed) and to a different response format (four-
point Likert-type scale). In addition, false-keyed items are not evenly distributed throughout
the questionnaire. This potentially confounds the previously reported effect of response
latency differences due to the acceptance or rejection of items (Holden & Kroner, 1992)
because there may be variances in response latencies attributable to item presentation at the
beginning versus presentation at the end of the questionnaire. For these reasons, we elected
to not examine tmnsformed response latencies for these effects.
A limitation of this study is inherent In the number of subjects in the depressed
condition. Prior to analyses for outlier data there were 23 individuals in the depressed
condition, with that number reducing to 12. Table 3 exhibits many trends that may be
sigdcantly Werent with more data. To M e r this PO& although Tukey post-hoc
analyses were reported, LSD poçt-hoc analyses were also performed on the transformed
response latencies. Using LSD post-hoc analyses, additional significant clifferences were
detected between depressed individuals and mdingerers in NIM scaie scores, control and
depressed individuals in the Depression - Affective subscale, and between control and
depressed individuals in the Depression - Cognitive subscale. The additional differcnces
obtained using LSD post-hoc analyses confonn to the hypothesis of self-relevant
information processing and response t h e latencies. With a larger depressed sample it is
Detecting Depression 42
Likely that the noted LSD findings would also be significant using the Tukey post-hoc
analyses.
Another Iimiting fxtor was the rigid nature of the cornparisons used for the direct
disMiminant h c t i o n andyses. This study examined the role of the Depression subscales
for c l a s s ~ g individuals. Individuals who endorse items to produce a high Depression
scale score are not uSually classified as malingerers, instead these individuils are considered
to be depressed. In those instances where the Depression scale is used to detect malingerers
it is used as a component in a larger subset. For example, one of the eight configurd
features of the Malingering Index (Morey, 1 993) is calculated in part by using a high
Depression scale score (Malingering Index item 7. DEP 2 85T and Treatment Rejection 2
459. Also, Rogers et al. (1996) use the Depression - Cognitive subscaie T-score as 1 of 20
scores that are inputted into the Rogers Discriminant Function to dent@ malingerers. In
this study, by comparing response latencies to s a l e scores, we chose to examine groups for
differences using the most ngid of criteria Even with these strict criteria, high classification
rates were witnessed by examining transformed response latencies. The possible fbture role
for response latencies may be the creation of a scale at the item IeveI that maximally
dinerentiates groups.
Future Directions
Much of the success of this study can perhaps be attributed to the use of the PA1
(Morey, 1991). It has at least rhree qualities that make it very useful in examining the
effectiveness of malingering. First, the PAI has a Flesch-Kincaid Grade Level of 4, making
it robust to individual ciifferences in vocabulary; there was no correlation between the
Shipley - vocabulary subtest raw scores and the raw response latency totals. Second, it is a
Detecting Depression 43
broad and lengthy instrument with 344 items, so that even ifrnalingerers were aware of the
measurement of response latencies, the breadth and length of the PA1 would likeIy Wear
down the vigilance of malingerers. FinaUy, a PAI scale is assessed with an item every 40
questions (e-g., the DEP - cognitive items are 27,67, 107, 147, 187,227,267,307),
ensuring that if the responding style is altered due to factors such as fatigue or boredom, the
change in responding style will affect all scale response latencies equally. For these rasons,
the PM is an ided measure for examining the effects of malingering and psychopathology
response latencies,
The implications of these hdings also lend themselves to the assessrnent of other
scales on the PAI. Although data were collected for al1 PAI items, this snidy only analyzed
response latencies for 3 of the 22 scales (42 of the 344 items). It rnay be possible to M e r
identify genuine psychopathology or malingering using some of the other scales. For
example, through the analyses of response latencies on the Suicidal Ideation scaie it may be
possible to accurately idente those individuals who are contemplating death, whereas the
obvious item content may make it ideal for identifjing malingerers. Also, response
latencies may be more valuable when attempting to iden* coached mahgerers. Coached
individuals are acutely aware of the constmct being malingered. Consequently, for the scale
being malingered, item content is more obvious and their transformed response latencies
may be that much quicker.
The use of response latencies is a promising technique in the detection of genuine
psychopathology and malingering. As previously reported by Rogers et al. (1 9%), there is a
need for a more efficient and reliable method of identiwg individuals as honest or
malingering respondents. The importance of which is undeniable in the light of the cunent
Detecthg Depression 44
re-stnichlring in our health care system, necessitating an even stronger focus on efficacy and
efficiency .
Detecting Depression 45
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Detecting Depression 49
Appendix A
Procedure for the recruitment of subjects at the LPH for the study Wetecting Depression and Malingering Using Response Times on the PersonaIity Assessrnent Inventory."
1. They have no Axis I diagnosis other than depression. 2. If no Axis I diagnosis exists then any referral for counselling or possible depression or
recurrent depression.
Following the identification of potentiai participants, the nurse will contact these individuals and state the following:
"Hello, my narne is <name> and I'm cdling fiorn the Lakehead Psychiatrie Hospital. A research projeci is being conducted and we were wondering if it would be okay to give your narne and telephone nurnber to the researcher so that he could cal1 you and give you more information about the study. You are in no way obligated to participate. This cal1 is only to ask you if you want to hear more information about the study."
Infornation that can be aven 1. Completely ~ o ~ d e n t i a l - no one at the hospital or outside the hospital will be informed of
your responses or that you participated, you will be assigned a number. 2. Duration - 30 minutes up to 2 hours depending on the responses given 3. Free wffees and a 15 minute break is available. 4. If necessary bus passes will be provided fiee of charge. 5 . There is a random draw for a $25 cash pnze.
The only information tu be given about the purpose of the study - it is examining the effect of mood States, specifically sadness, upon computerized personality assessment.
Name 1 Telephone Number i
Researchers - Derick Cyr, M.A. Cadidate, CIinical Psychology Dwight Mamanian, PhD., C-Psych, Associate Professor of Psychology, L.U.
Detecting- Depression 50
Appendix B
Emotion and Information Processing Debriefing Form: Session 1
The purpose of the present study was to detemine whether students who expenence different emotional states will demonstrate biased information processing that u e congruent with their emotions .
The session in wiiich you have just participated was designed to identiSr shidents who are expenencing emotional states of interest to the present research.
Thank you for participating in Session 1. You will be contacted should you be selected for Session 2 of this study. If you have any questions about the study, please contact Derick Cyr (623-4506) or Dr. Mannanian (343-8257), Department of Psychology, Lakehead Universix Thunder Bay, ON, P7B SEI. If you would like a brief summary of the results you may obtain them by printing your name and permanent mailing address of the self-adhesive address label. Results will no likely be availabIe before August, 2000.
Ifparticipating in this study or completing the questionnaires has distressed you or has raised personal issues that you would like to discuss, or if you just need someone to t& to, the following organizations are available: L.U. Health Center (343-8361), Peer Suppoa Line (343-8255), Chaplain (3 43 -80 1 8), and Counseling and Career Centre (343-80 1 8).
Fekken, G. C. & Holden, R. R. (1 992). Response latency evidence for viewing personality traits as schema uidicators. Journa1 of Research in Personalitv, 26,103-120.
Kaplan, R. M. & Saccuzzo, D. P. (1993). Psvcholoeical testine: Principles, a~olications. and issues. Pacific Grove, CA: BrooksKole Publishing Company.
Lewicki, P. (1 984). Self-schema and social uiforrnation processing. Joumal of Personah and Social Psvchologv. 47,1177- 1 190.
. - - . 120 a s 120 PRmr:PxINT " - - Thank' yau ' f o r .p&ticipating in this 'e tudy . . : PRi NT:PRmT:PRINT . - - - . - L30 PRINPU If - ~ O U bave. rny vcati&s or cohcernc p l e a ~ a feel free to sontact ei. theru : PFUNT q . .. -Dr . Maznianiian.or Derick W.." . ~ 4 0 P ~ : P R I N T ' : ' P R I N T - ! . : ; *. - - A i l . information is strictly conf ident ia ï
8 - 150 -'WA-TIMER- . ' _ - -- . . -
- 190 REM 200 REM 210 REM 220 REM 230 REM
. 240 REM 250 REM 260 ,DfM 270. DIM
-. . 280 DIM 290 DIM 300 DIM 310 DIM 320 D l M 330 D ï M 340 Dpi
- 350 D m 360 DIM 370 REM 380 RE19
- 39q P m 400 410. REM 420
- - 430 ' . 4 4 Q .
450 4 66. 470 480 REM 490 REM 500 Rm
- . - Detecring Depression -52
REM
REM R E M -
CIS:PRINT:PRINT:PRINT mmtn $oui namen :PR=:-INPUT NAM$-- CLS:PRZNT:PRINT:INPVT-wEPter y o u ~ age .'", AGE CLS:PRXNT:PRINT:INPUT "Enttryo- S W C ~ R I SEX$- CLS : P R p T :PRINT: PRINT' " W h a t is 'yous marital status? PRïNT -' (Single, m i e d , Dïvorced, Widowed, ûther) : F R m : IRPUT---Y$ CLç:PRINT:PRfNT:PRINT =-ter the number of y e u s of formal education that yo . - . . u ha~cotnp&tedm . - ..
.63 0 PRINT ' - ( f o r c x a ~ l t , a high school gkadÜ+e. w o G d 'enter 12 1 - - 640 -:INPUT ED 6 5 0 : ~ ~ s . : PR=: . -. PRINT: INPUT "Enter YOIX occupation : I, J O ~ $ - . . - 660 REM . ' . - .
670 REM = . .
6 8 0 ZER - O' OB$ 710 REM -
. ?l
. . exo. PR~?~:PRINT " ~ f t h e statement. ie S L I ~ Y T R ~ , aqtcr the ~Jmber 2 . . - 820 PRINT:PRïNT "If the. statement is MAINL,Y TRUE, enter .the number 3 .-"
' 830. PRINT:PRINT "1 f the statement 'is VERY TRUE, enter the number - 4 . . . . . . 840 PRINT . 850 PRINT:PRLKT Wive y& OWN OP.n<IûN- of yqursclf. 'Be cure to a n s w e r every sta t e m w . ".
. 860. INPm "Press !enter1 to- continuen, CONTI $' - -
* LOOP ..for PAI . item preeentation and recardGg. of times - * . . ******.***+*********+*+********.*~***********+*****+******~****** I
* - . - . -
L
FOR 1 = 1 Tb 354 .
. . CLS:PRmT. PRINT, l~l=False - - 2-Slightly True : .
- - . - - - -. - . . . - -
. - - *
. . Detecting Depréssion 53
GOTO 1-120 . RT2 ( 1 I -'(T=-TS -. IF .CODE3 = 2 TBEN ûQTO 1220
1230 - . - .
1240 **ct*********+**&*.*r*e**e**********.**e****e***************** 2-score calculation and prb t i r rg . - . *. 1250REM* - - *
1260 ~~~***~*~******+i*t+rr+++*+++r+rrt*++rr+t*++t*+t++t+rr** . - . . -
1270 RkM* - - - . . 3.280 ' A-P . .
,3290. SaMRTl 1.0 ' 1300 "SVMRTS = O 1310' - . FOR-A- = 1 ~ 0 . 3 4 4 .
- 1460 PRZNT'XI, "' ' - . .
- . 2470 - PRINT X I , aQue8tion .#; R R (kitting deceion), RT2 (Total ac~eptanee)~
7 . . . ilreo P m #Ir . 1490 - . - FOR ZZ ='l.TO 344 - . 150.0 - F m r ZZ+10 . - 1510 -. 21 ( Z Z ) = (RT (FFV) /SgRTI - .
- 22- (22) = (RT2 ! F W ) -=T2 /SDRT2 - .-1520 1530 .-
. P R ~ #I, Z Z ; .", '; usING-n## .######t#-; "; z1 (zz) 1 '7 ('') - -
1540 h m iz . - - -
1550 REM . - - . . - - . . 1560 - * * ~ ~ ~ * * ~ * * * * * ~ ~ * * ~ * e & * * . * * * * ~ * + * * ~ t ~ - * * * '
1570 REM . DATA lines ( f i r a t 10 of data are the practiee questions) >
1580 REM ~ ~ ~ . ~ ~ ~ * ~ * * * ~ * + ~ * * * ~ t i * * * * * ~ * * * ~ * i * ~ * . c t + . . - - 1590 REM 1600 REM , .
. i610 DATA 1 - am: a spiritual persoa. ", 2 1620 DATA 1 am always on time +or -appointments . a ,2
- 1630 DATA "1 l i k e Bumpeaxi made cars. ", 2 - - - . 1640. DATA '1 drink at l eas t 3 cupa of coff ee -every. &y. ",.2 ' . - -
. 1650 DATA " 5 like country. music.-', 2
Detecting Depression 54
1660 D A T ~ ~somktimes E go to sleep past midnight.",2 1670 PATA "1-enjoy the fresh air.',2-- -. - - 1660 DATA "1 would rather wash diahes than.wzkch tele~ision.~.2 ' -
1690 DATA "1 would like to own a dog.",2 . - 1700 DATA nAstr~logy works when enough -0rmitipn is kown about a personla bir -
- -
th date.",l - - ,
- l7lO DATA 'My friends arc akilahle if 1 need $hem. a, 1 1.72 0 DATA 1 have some inner strugglee that cause problems for me. n-, 1 1730 DATA " M y health cond&tion has res~ricted lay acti~itics.~,O 1740. DATA "1 .am so tense. in certain situations chat 1 have great difficuity iag by." ,o. - -
. :. 1750 DATA .I haveto do s&e things a ccztain way or 1 gtt n&rvoii~.~,O .. 1760 DATA "Much of the- time -1 1 m ead for .no real reason. n , 0 .- 1770 DATA * O f t k ~ ~ 1 thiak-and talk 80 quickly that other people cannot follow train of * thought . ", 0 - *
1780 'DATA . " M o s t of the people f Imow c e 3 e trruted. ', 1 - 1790 DATA nSometimes I caqnot rernember .who 1 ag. 0 - .
1800 DATA "1 have some ideas trhat &thers thirik are strange.n-IO .- 1810 DATA "1 wae usually well-behaved- at school . "-, 1 182 0 DATA "1 Ive .seen. a lot .of -doetors over the yeara . ", 0 183 0. DATA "1 'rn a very sociable pereon. II, 0 . .
1840. DATA " M y mood can shift quite- suddurly. ', 0 1850-DATA 'Sometimes 1 feel quilty about how much T &inka ", 0 1860, DATA "I1m a. -!takt charge1 type of .pcrs~n.~,O 1870' DATA "My attitude 'about myself changes a 10t.~,O 1880 DATP; "People woüld be eurprieed if .f yelled at - somtone . ", 1
. . 1890 DATA 'My relationship have been storiny. 0 1900 DATA "At times 1 wish 1 were deèd. ,O - 1910 DATA nPeople are'afraid'of m y temper.'n,O . - 1320 DATA nSometimes 1 use drugs to'feel better.wI.O.- 1930 DATA "1 Ive tried just about every type of drug.P, 0 1940 DATA nSometirnes 1 let little things bother me too much.",l '
- 1950 DATA "1 often have trouble concentrating because I 1 m nerr0us.~~,0 1960 DATA II 1 o f t r n f ear that 1 *might slip up and say something wrong. ", 0 1970' DATA !t 1 ,f ce1 - that 1 ve let everyone dom. II, O l9B O D&TA 1 - have . many - brilliant ideas. ,O . .
1990 DATA 'Certain people go out- of their way to buther me. O - i 0 0 0 .DATA :I just .don1 t -secm to relate to people very well. ., 0 2.010 DATA 1 Ive borrowed money knowing 1 w o u l d n ! t pay it back. ", 0 20?0 DATA nMuch of the. time:I-donrt feel ~ell.~,O - -
2030 DATA. "1 often feel jitte*. " , 0- - . . 2040 DATA."I kcap reliving aomemng horrible that happcned to me.n,O
DATA DATA DATA DATA DATA DATA
- DATA. DATA
. DATA DATA DATA
- DATA DATx
1 DATA
1 hardly have -any cnergy. O 1 can be very - dcmanding when I, w a n t things dOxk q u k k l y . O aPeople usually treak me pretty fairly. ", 1 "My thinking has become confused. 0 1 get a kick out of doing dangeroi~s t h m . , O- - nMy --favorite poet is Raymond Kertezc. II, O "1 Iike being around m y famil~.~,l - . 1 neta to .makt some important changes in m y life. @ , 1
'
l ye Md. illneaaes that my doctors Eoula not explain. O " 1 canl t do ecme things well ' because of nervou~ess . r O- .I ha- impulses-that 1 fight to keep under c~ntrol.~,O 1 've forgotten 'what it B like to feel happy. ", 0- -, 1 .tee on io many c+tmants- that 1 cana t keep up. O
nI have to be alert to the poesibllity . - thrt people will be upfaSthfu1. "IO 2190. DATA I have visions- in which I oee myself forced to commit crimes. 0. - - 2200 DA.!l?A ' Other people sometixnea put- thougkte in to my head. II , O 2210 DATA 1 l ve deliberarely damaged eomeone ' s -property. ' , O , -
- .
- *
. - . . _. . -. V
. . . e
. . . - . . . . . .
. - - _ . . - . . t . , - .
- . . . . . . . -
- ~ekct ing Depression
- 2220 DATA "My health problems are very complicated. ",? - - . 2230 DATA "1t1s easyforme tomakenewfriend~.~,O - -2240 DATA 'moods- get quf te intense. ", 0 - . ,
2250 DATA 1 have trouble con troll in^. my uae of deohol . "., 0 . . 2260 DATA "I1m a natura1 leader.",o 2270 DATA mSometimee f f e e l terribly empty 'inside. O 2280 DATA "1 tell people -off when they deserve it . ", O 2290 DATA "1 want to Let certain people . h o w how much theylve hurt me.n,O- 2300 DATA RIfve thought about -waya to kill my~elf.~,O 2310 DATA nSomctimes my tenrpek explodes and. 1 cokpletely lose control. ", 0 2320 DATA - nPeopT-i have- told me that I have a drug problern. ", O . - 2330' DATA "1 ncv+r use drugs to help me cope with the ~orld.~,l 234.0 DATA nSometimee Ill1 avoid sorneone 1 really don't like.",l -
2350 DATA "It s often hard for ma to enjoy mysclf becausa I 1 m ofttn worryingA-ab0 ut things.a,O . - , - 23 60 DATA 1 have exaggerated fears r ', O 2370 DATA "Sometimes I thbk I ' m worthless. 0 - 2380 DATA 1 have ~ o m e vcly special talents that f ew 'ot?iero have. 0
- 239.0 DATA nÇome people do thïngs to make. me look bad. a , 0- 2400 DATA "1-donlt have much to Bay to anyone.n,O - - -
2410 DATA "Ltll. take advaatage of othare i f they leave thernselves open- t o it. ". O 2420 DATA I suff er .'from a l o t of pain; Il, 0 2430 -DATA .I worry BO much that at t i m c s I f eel likc 1 am goi& to faint ..N ,O 2-440 DATA "i'houghts about rny past often botber me while Ism thinking about somet . - h b g elee.",û' . - 245.0- DATA - "1 hava no trouble faliing asieep. y.1 2460 DATA nZ get q u i t e -irritated . . i f people tq? to keep me from accomplishing my .
. . . - goals.", O 2470 DATA "1 seem to .have as mucn luck i n life as others- do. ,l 2480; DATA " M y thoughts get scrctmiiled sornetimes. 0 249.0 DATA."I do -a lot of wild things jus+ for the tbrill of it.',O 2500 DATA "Sometimes 1 get ads in the mail that 1 don8t really want.".,l 2510 DATA If 1 m' having psobl-s , X have people- 1 can talk to-. , 1 2520 DATA 1 need to change some things' about myself , ev'en- if it hurts . "., 1 - 2530 DATA- ItI1ve had numbness in parts of my body- that 1 canlt explain.",O 2540 DATA n~onietimes 1 am afraid for no reason. ,O- . - 2550 DATA " It b o t ~ e r ~ me when things are out -of place. 0
' ' 2560 DATA "Everything seemi like a big effort in, 0 .
- 2S?Q DATA nRecently 1 I ve -had much more eaergy than usual . ,O . 2580 DATA "Most people have good intentions.",l
- - 2590- DATA "Since the day 1 vas born. -1 was . destined .to be unhappy. 0 -
2600 DATA- llSopetimes it seeme-that my.thcughts are broadcast su that others can hear them: ., 0 -. 2610 DATA S Ive- d&e eome things.-that .wereal t exactly legal*. ",O 2620 DATA n'Itvs a struggle ?or me to gat things dqne w=th -the-medical &oblems 1 have. n t 0 2630 DATA "I like. to -meek new people. 0- ' . - . - 2640.DATA "My mood as very steady.n,l. . ,
- - 2650 DATA "Thare h m been. times *fien I ve had to cut do- on my %inking. O 2660 - DATA - "-1 would- be good at a job where I tell others what to do. O 2670 DATAInI worry a lot about other people legving rne.",O. .
2680 DATA "Whea 1 get mad at o-ther driver6 on the road, 1 let tbem .know. ", 0 2690 DATA. "People once .close to m e have let me *dpwrr. ", 0 2700--TA llI1ve made plane about how-to k i l l ~ e l f . n f O . C
2710 DATA Sometimes ' 1 m very vio16nt. la, 0 .2720 DATA " M y e g . use hqs caused me f inancial 8trai.a. n t O 273 0 DATA ." 1 ve never had problems at w6rk because of drugs . " , 1 - .
- 2 7 4 0 . D A T k n I eometimea-complairi to~much.~~,l~ . 2750 DATA n I y m o e e n 60 woqied..and ne*ou~ that I can barely st-knd it. ".O
2760 DATA "1 get very ne3ous when 1 have to do eoniething in front of 0thers.~-.0 - . -
. . . . . . - - . .- .. -
. . . - . . . . . - - a . . . . - . -
. .
Detecting Depression - - 56
. - - 2770 DATX "-1 &nt t f ce1 like trying aPymore. U r O 2780 DATA " M y plana will make me famous s~meday.~,O 2790. DATA nPtople around me are faithful to me. 1 2800 DATA "IVm a loner. ' ,O 2810 DATA nI'll do most thiags if the price is right.",O 2820 DAT+ "1 am in good health.n,l 283 0 DATA nSomctimee I feal dirzy when 1 -bcen under à lot .of pressure. ", 0 . 2 840 DATA 1 Ive been troubIed by mernories of a bad expcrience for a long time. " ,
3020 DATA 3030 DATA 3040 DATA 305 O- DATA I O
3060 DATA 30.70 WTA 3080 DATA 3090 DATA 3100 DATA 3 110 DATA 3-12 O RATA 3130 DXCA 3-14 0 - DATA
- . O 2850 DATq "1. rarely have trouble elcepizig. ", 1 2860 DATA nsaaetime~ 1 get- upeet becnise otheire dont t understand e m plans. " ,.O 2870 DATA "1 Ive given a lot, but f havea t gottcn much. i n returri. n t 0 2880 DATA aS.m.etimes 1 have trouble keeping different- thoughts ~ep~ate."iO 2 890- DATA ."My behavior if pretty wild at times . II ,O 2900 DATA "My favorite sports event on. television i s the high jump. O . 2910 DATA -1 spend most of my tirne a10ne.~,O 292O:DATji "1 need *orne help to deal with important prob-~ems.tlIl 2930 DATA m14ve ha& epiiodes of double vision or blurrcd vision.",O 2940 DATA "I.'.m not the kiqd of person who panics -easily. 1 2950 DATA "I-, can relax even if my home is a mess.",l 2960 DATA "Nothing seems . to give me. much pleasure . O 2970 DATA "At times my thoughts move very q~ickly.~;~ 2980 DATA .I usually assume people are telling the trath.",l 2990 DATA .I think ï hav= three-or four.completcly âïfferent personalities insid t'of me.",O- - 3000 DATA -wOthere can read &y thoughts. "., 0 3010 DATA "1 used to. lie a lot -to get out of tight situations. ",O
' " M y medical problems always seem to be hard- +O treat . 0 . NI am a warm person.",O . , - 1 have litrlë. control mer m y . anger . Ir,
" M y F n g seems to. cause problems in my relationships with others. " . .
n'5 have troui>le. standing Gp for myself . 1 . - "11- ofteniwonder what .1 should 60 with my life; 0 " 1 lm not -'af raid to yel' at someone to get m y point across . " ,O 1 rarely. Eeel ve-zy -1onely. " ,1
- 1 Ive re-ceatly been thinking about suicide. ", 0 . . "Sometimes .I smash .thirigs when- 1 ln upset . 0 I neveryuse 'illegal dnigs . ;l . "1- -sometimes do things so impulsively t u t I get into tr~uSle.~,O - '
Sornetimee 1-lm too . impatient. n , 1 - 3150 DATA " M y fr ienh say 1 worry too rn~ch.~,O 3 160 DATA Z.'rn not easily fdghtened: R , 1 3170 DATA "1 cantt eeem to coqcentrate very well. s, O 3180 DATA "I have accomplished some remarkablc th+gs.",O
- 3390 DATA "Some people try to-keeg me frcm getting ahead. ",G - - 3200 DATA "1 dontt feel close to anyone.nfO
- 3 210 DATA 1 can talk my .way o s of juse about anyihing. ', 0 3220 OATA ?I .seldom have complaints about how 1 feel physi~ally.~,l 3230 DATA "1 càn. oftcn fegl Ü y heart pounCiing. ", 0 ' 3240 DATA "1 cantt eeem to get F e r somethin* from m y past.n,O
:3250 DATA "Itve been-moving more slowly than usual.",O 3260 DATA "1 hake great plans and it irritates .nie thaf people try t o interfere." ,O - - 3270 DATA "People dontt appreciate w h a t Tlve donel~or them.",~ 3280 DA^ DSometimesit feele as if eomebody is blocking my'th~bghte.~,~ 3290 DATA P I f 1 get tired- of- a placefz :I just pick up- and Leave. ,O
. 3 300. DATA "Most people - would zath=r win + than -loee. ", 1 -3320-DATA nMost people I1m close to are very supportive. .Z .
. . 3320 . DATA nItm-curious why-1 behave thc way 1 d ~ . ~ , l . . .
. . . . . . - . . .
- . .- . . .
, - _ . . . C
. . . . - - . . . . . - : . . - . - . . . . . - - . * . .
. . -
3330 DATA n..,Q -'
3340 DPTA 3350 RATA 3360 DATA 3370 DATA 3380 DATA 3390 DATA 3400 =A 3410 OATA 3420 DATA 3430 DATA
- 3440 DATA 3450 DATA 3460 DATA 3470 DATA 3480 'DATA 3490 DATA -3500 DATA 3510 DATA 3520 DATA 3530 DATA
- 3540 DATA' '3550 DATA '3560 DATA 3570 DATA 3580 DATA 3590 DATA -3 6 O 0- DATA
. - 3610 F A 3620- DATA 3630 DATA 3646 DATA 3 6 5 0 DATA .-n,o 3660 DATA I O
- 3670 -DATA . 3680 DATA 3690 DATA 3700. DATA 3730 DATA
. Detecting Depressiop 5 7
. - Therc have baui times w h e n my eyc~ight gct uorse and then ba+te=- aga;
. . "1 am a very ' &lm and relaxcd pereon; . l ' "People say that- Irm a perftctioni~t.~,O ' "I1ve lost interest in thLngs 1 used to tnj0y.~,0 - " M y f riends can ' t -keep up with m y social activities . ,'O "People generally hide their reaL motives-*,O People don1 t underetand how mu& 1 euff er . " , O nI1ve heard voices that no one e lee could hear-",O "1 l i k e to see how much 1 can get away with.",O "1 ! ue had only the ueual -heal.th probleme that most people havt - ", 1 "It- takes-me a while ta warm up to people.";l 1 Ive - always beut a pretty happy pereon . 1
" D r i n k i n g helps me set 'dong in social* situations. ", 0 - "1 feel best in. situations where I am the leader.ll.O "1 can1t.tandle separation from those close to me very well-*,O I always- avoid arguments if I c m . * , 1 "I1ve made some real mistakes-in the people I1ve picked aa friends.",O "1 haye thought about suicide for a long time.",0 RI1ve threatened to hurt pe~ple.~,O :I ' ve- ueed prescription drugs to get high. , Q .men I 1.m upset . I typicaiiy do a o m e t w -to h u S rnydif. ..O 1 don' t take criticism very well. If, 1 "1 doalt w o v about things any-more than most pe~ple.~,I 1 ' donl't mind drivisg on f zeeways . , 1 . - - "No matter what 1 do, nothing works . 0 . - ."I think I have the answexs to'eome very important questions.",O "There are people who w a n t to hurt me-",O 1
" 1 enj oy the Company of other people. ", 1 - "1 don1 t like being tied to' one person. " , 0 *I have a bad back.",O n I t l ~ e a s y f o r m e t o r e l a x . n , I - "1 have had some horrible experiences that make me feel guilty-",O 1 often wake up very early in the morning and can t get back td sleap.
. . 1 . : . . - "r+ bother~ m y w h e n other peokls arc too slow to understand my ideas:
n~sually I1ve gotten credit :or what-Irvc d ~ n c - ~ ; l . -
"My thoughts tend te quickly ehift .aroundto differeat things.",O "The idea of 'settling ewn' ha8 never ,appealed to me.",.O "My favorite hobbies.are-archery and stanip-collecting.",O : nl?eople I know. care about me. n.,l . -
372 0 DATA .I. ' m -cornfortable wath myself - the way 1 am. ; O. 3730 DATA nI1ue had episodes when 1.lue lost the feeling in my- hand~.~,O 3740 DATA "1 .often:feel like eomethipg terrible is about to happen.",O . 3750 DATA *I1m usually. aware of -objecta that have a Lot of -gemme O 3760 DATA "1 have no interest j.5 life.n,-O. -- 3770 &'"I feel l i k e 1 neea :to keep active and 'not rest..", 0
- 3780. DATA "People- think I lm tao suspicioii~ . ". 0 3190 DATA "Every once in a while I: .rotaLly losc- m y memory.",O
- 3800 DATA Vhere are people who try to control my th~ughts.~,O . -3810. DATA "1 wae never expelled or suspended from school when.1 was youpg=";l
3 8 2 0 DATA nT1ve had some +meual diseases and illnes~eo.~,O . - - _ 3830.DATA."I.t takee a while for people to get fo know me.",l 3840 DATA "I1ve had timee when 1 waa 80 mad that 1 couldaft .do enqugh.t6 w r e i B
-
. al1 my ' anger . ,O -' . .
. 3850 DATA wSqrae people arouhd me. think that 1 .dz& too - 3860 DATA 'II prkf er ta. let others -make de-cisions . # , 1
- 307D DATA "1 dont t.-get bord very eaeily. n ,l . ' . . - - - - - -
- 3800 DATA *I dont t iike raising. ky voice. .', 1
DA% - DATA DATA DATA DATA DATA' DATA DATA DATA DATA M T A DATA DATA DATA DATA. nATA
- 3890 DATA 3900 DATA 3910 DATA 3920 DATA- 3930 DATA 3940 DATA .3950 DATA 3960 DATA 3970 DATA 3 980 DATA- 3990 .DATA 4000 DATA 4010 DATA 4020 DATA 4030 DATA n r O 4040 D+TA 4050 DATA 4060 DATA 4070 DATA -4080 DATA 4090 DKTA 4100 DATA 4110 DATA 412 O DATA
C . .
- Detecting bepression 58
"Once Borneone is my friend, we stay friends.n,l "Death w W d be a blief . ", O - -
.
1 lve never ~ t i r t c d a physf cal - f ight. as &duit. ., 1 - -. - . "My drug use im out of .cantrol. ", O "Ifm too.impulsive for my own goo&.",O "Sometime~ 1 put thinge qff unt+l the laet minute.',l . - .
"1-donlt w o r r y about thing~that 1 canft c~ntrol.~,l '1 donlt &d heights.",l 1. - think . good. things w i l l hap* to m e in the future. .. 1
* 1 thhk 1 would be a good cornediaa. @ ,.O *People seldohl,'weat m e bad on. ptxxpo~e:~ ; l "1 like to be around other people if I can. Y., l; " 1 don 1 t like to stay in a- relatione@ip very long. 0 - - -
I have a w e a k atomach. ." , O When T lm under a lot of pressure, 1 -sometimes have trodle breathing - .
a 1- have a gaod appet i te . 1. .I have no patient-e ~ 5 t h people who t r y ta hold me back.", 0 = P e o p l e who are suecesefui generally earned their auccess . ", 1' uSometimes 1 wonder if m y thoughts. are being t=akcn-a~ay.~,O - .
like to drive fas t ." , 0 - donlt lika to have. tobuy thinge- that. . - . arc ~. - ove~ri~ed.~.l ' , -
In rny. f amily, w e argue more than w e t a l k , P , O ~~àray-.of my problems are O-. doing: ;-l 1 've had times w h d usy legs. became so w e a k tiiat. 1- couldn t w a l k - - - -
n i - seldom feei anxious- or tense. ", 1 "Peo~lc see me a& a person who pays a i o t of attention to detaal ~ a t e l ~ 1 l ve been happy much of the time - ", i ,
" Reaently 1' have needed les e sleep . th= -usual. r O "Thülgs are rarely as they seem on the surface.",O nSometlmes my vision i s onlylin black and white.",O " 1 have -a sixth sense. that tells me what is going to happen. ", O nI1ve never been in trcuble with the ,la~.~,l "For. my age, .y health i s pretty good. ", 1'
." 1 try to include people who secm &eft out. ", 0 . . "Sometimes 1 have an alcoholic drink . f iret thing in -the tuornino. 'IMy d r i w g has caused m e problems a+ h o m e . ", 0 ."I say whatls on m y mind." ,0 1 ueually do what other people t e l l me . to do-. ? , 1 "1' have a bad temper.n,O
4290 DATA "It .talces a lot to make me a n m . n ,a - 4300 DATA * 1 ve thought- about what 1 -would saf in a suicide note. O
. 4310 DATA. canf t- think of' reaeons to go .on living. ",O - 4320 DATA =I1ve had ,health pro~lems because of m y d=g use. '. 0
4330 DATA "1-spend m o n e y too easily. ", 0 4340 DATA "1 sometirnes make promises 1 canl t keep. y , 1 435 0 DATA "1 usually w o r r y about thinga more than. 1 ehould. ,O+ 4360 DATA ?I I l l -not ride in airplanes. O , 0 4370 DATA. " 1 have sopthing worthwhile to contribute. I r , 1 4380 DATA- " L a t e l y 1 f ce1 so confident that 1 th- 1 can accomplish anything- It. 0 4390 DATA nPeople have had it in for me. ,-O 4400 DATA- "1 make fricnds easily.",l . . 4410 DATA "1 look -er m y s e l f first; let othcrs take tee of thamselGeo. " , O 4420 DATA a get more haadaches .than most people. , O 4430 DATA *I get sweaty hands 0ften.~,0 4440 DATA ';Since 1 had a v e e bad- experience, 1 am no longer interesred in some -thiags that 1 used to enjoy. " ,.O
. . 4450 DATA "1 often. wake up in the middlt of the night'. , O 4460 DATA *At times I a m very touchy and eaaily aan~yed..~,Q -
' 4470 DATA - -4480 DATA
- 4490 DATA 4500 DATA
' , 4510 DATA 4520 DATA.
. - 4530 DATA
. \
- . n I . r m not the type of person to hold a- grudge. 1 "ThougMs in m y head suddenly disappear. ,.O . . . "I1m not-a person who turn~ down a dare.",O "Most people look f orward to a - tr ip. t o the dentist . ,O ?I spend little -tirne w i t b m y family- ", 0 -
=I can eolve problems by myself. ", O . "At tirnee parts of my body have beui paralyzed. ", O
4540 DATA "1 am easily Btartled.w,O 4550 DATA "1 keepmyself under tight c~ntzrol.~,O 4560 DATA I r I <rn almost always a happy and positive person. ,l 4570 DATA "I hardly everr buy tbings on impul~e.~,l 4580 DATA "People bave- ta earn my'trust. a, 0 - - 4590 DATA "1 donlt have any good memories from rny~childh~od.~,O 4600 DATA O 1 donlt believe that there are p-eople who can read rninds.",l 4610 DATA Ive never taken money or. property that wasn ' t mule. ", 1 4620 DATA. " 1 like I o talk w i t h people- about their medical problems . ", 0 4630 DATA "I1m an affcctionate pereon.n,O 4640 DATA "1 never- drive when I1ve beea drinking. 1 4650 DATA "1 hardly ever d-ink alcohol.",l 4660 DATA .nPeople Jistca t o my opinions. ,*O . . - 4670 DATA "If 1 get poor oervice from a *business, 1 let the manager b o w about i t.",O 4680 D A T ~ .My temper navar gcte me i p t o trouble. ",l 4690 DATA "My e g u never gets out of c o ~ t r o ~ . ~ , l 4700 DATA "1 Ive thought about how others wovld rcaet if 1 killed Gelf.. '; 0 4710 DATA "1 have a lot to live for.=,l 4720 DATA IlMy best fxien* are thoee 1 use drugs with. ", 0 4730 EATA nI'm a reckless pcrson.",O- 4740 DATA "There have beeo times w f i e n . 1 c o d d have been more thoughtful than f w as.',l 4-750 DATA Sometirnes 1 get ao nervous that 1 m af raid' I ' m going to . die. n , 0 4760 DATA III donlt mind travcling in a bus 'or train.",l 4770-DATA "I1m'pretty successful at what 1 do.",l - C .4 78 0 DATA I could' never imagine mystlf beixq f amou's. , 1 479.0 DATA 'liI,.rn-the.ta.rget. of a ~onspiracy.~,O - - - . 4800 DATA "1 keep in.touch with my friends.",l . - 4810 DATA "When I m a k e a promise, 5 really don!t need to keep i . + . " , O 4820 DATA I frequently have diarrhea, II, 0 - . . - .
4830 DATA "1 have very steady: hand~.~,l . *
4840 DATA "1 avoid certain things tbat br'ing back bad memorieq. r,0 4850 DATA "1 have little interest in 0- -
. 4860 DATR "1 have little p s i e n c e with those who -di.agrce with my plan~.~,O 4870 DATA "Being helpful to other .people .pays off in the end. ,1 4880. DATA '1 can concentrate now.as weTL as 1 ever could. "1 - . 4890 DATA- "1 never take r iske if 1 c e avoid i.t. ",l 4 900 -=TA - IP my tree- time .I might read, watch TV, o r just relax. " , l - 4910 DATA "1 have a' lot of money pr'oblem~:~~, 0
- 4920 DATA- " M y . l i f e is very unpredictable. ;O . - 4930- DATA "There have; bwrr many changes in my l i f i recently . !l-. 0 - - 4940 DATA "There ienlt much stability at h~me:~,O 4950 DATA " T h i n g s ars not going well my family.n,O - 4960 DATA "1 Lm happy with my job -situation.-", 1 + _ . -
4970 DATA 1 . worxy about having enough money to get by . ; O . . 4980 DATA "My relationship Yith my sp~wc . or partner is not going w e l l . O 4990 DATA "1 have eevere poychological prublems that begm vew suddePly.",O
.
SOOO DATA a 1 lm- a sympathetic pereon. 0 5010 - DATA- "Close relationkhips are important to me. "-, 0- 5020 DATA " I 1 i n very impatient-withpe&le.9,1 - ' . . 3030 DATA "1 have more friends than most people 1 kn~w,~. O ,
5 O40 DATA aMy drinking. has never gotten me into trouQle : . i * . . . . .
- - -
- .. - . . . -
,505 O DATA " MydZlplUng has- caused problems with my work. ,-O * - .
. 5060 DATA N I d ~ n l t 1i.h l e t t i i z g people kaow when 1 disagree'with t h e m . n , l . 5070 DATA .@I lm a very independent .parcron. a , O
5080 DATA When 1 get d d , i t t e h a ~ d for me ta calm d 0 v n . ~ , 0 . - 5090 DATA nPeople th- S'm. aggre~sive.~,O 5100 DATA 1 k considering suiciee . ,,O '
5 l l O DATA .Things have never ,been so bad that 1 thought about s&ide.",l . - Sz20- DATA "My --g uoe ha6 never caused problem o i t h my f amily or £rien&. 1.
5130 DATA RI lm carefe - about how 1 -end my money . 1 5140 -DATA ragely get : in a bad mood.. ", O - S I S 0 QS : PRINT "PZNEFS~ FARI L I 0000, . DWLGBT AND DERTCK' -
5260 REM . . 5 2 7 0 . - - P& - =S(SQ) + ANS ( 7 4 ) + ANS ( 1 1 4 ) + ANS (154) + ANS (194)- + ( 234) . + ANS ( 2 7 4 ) + ANS ( 3 1 4 ) - '+ ANâ ( 3 5 4 ) - - 5280 REM . 5 2 9 0 -
532.0 -REM- . .
5330 - - DEPCS - ANSI37); ANS(77.). + ANS.(IL'I) + ' ~ ~ ~ ( 1 5 7 j ' + ~ N ~ ( 1 9 7 ) +-ANS ( 2 3 7 ) +. ANSf277) + ANS (317) - . . .
-- + 22 ( 2 6 7 ) +- 22 ( 3 0 7 ) . - 5380 REM . .
-5390 . . . DE~A+ - ANS (101 + m ( 5 6 ) + ANS(96) + . m . ( 1 ? 6 ) + + ANE>( . 2 1 6 ) + ANS (25.6) + ANS ( 2 9 6 ) - - .
54OQ REM + RT(216.l + 5410 ~ ~ p m =. ~ ~ ( 1 6 ) + ~ ~ ( 5 6 ) * R T ( 9 6 ) + R T . ( 1 3 6 ) - + RT(i76)
, RT(256) +.RT ( 2 9 6 ) 5420 DEPAZI' Z l ( 6 ) + - z I 1 4 6 ) + =i i e s j + z l ( i 2 6 ) + z l ( 1 6 6 ) + - z l t 2 0 6 ) + . .
5440 RXM . . C
5450 - . . - iEPPS - ~ ~ s . 1 4 5 ) + NS ( 8 5 ) + ANS (125) + ANS (165) + A?S ( 2 0 5 ) * ANS (245) '+ ANS (285) + ANS4325).
5-500 REM 5 510 5510
.PPZ2 - 5530 REM 5540 REM 5550 REM 5560 REM 5570 _REM 5580 REM 5590 5600 - 5610 5620 5630- 5640 - . 5650 5660- 5670 5680 5690 5700 5710 : 5720 5730 5740 5750 5760 5770 - 5780 5790' 5800 . 5810 - . 5820 5830 5840.
5 - i - ***e*~**++*i*+t+t*+*i**+***rtf********t*.*.e********** . -
FILE PRINT-OUT OF TOTAI;is ' - **********************it****.********ff*************** .
P R m #1, PR=: #1, PRiNT #1, P m #1, PRINT #1, PRINT #1; P m #1,- PRrn #1, PRINT #1, P R a T #1, PRINT #1, PRXNT #1, P R V . #1, PRINT #1, PR= #I l PRINT #1, PRZNT #1,.
, PRINT #1, PRINT #1,- PRINT #1, PRINT #Ir PRrm!.#I, PRINT #1, FRINT #I., P R r m #1, P m #1,-
. - " " - WiM Score - ", NIMS "NIM RT - NIMR ."NIM 2-score #1 . . ", NIMZl " N f M z-sCOtC #2 ", m Z 2 "PIM Score - P m -
-, P m "PIMRT- - l C -
"PIM Z-AO~C 11- ., ~ m z i "PIM Z-Score #2 Ir, OIMZ2 "Depression(C) Score - ", DEPCS nDepreeeion(C) RT - -- "., DEPCR nDepression (C) 2-score #l- . Il, DEPCZI nDepreesïon (c)' z-score #2 ", DEPCZ2 nDepression(A) Score - DEPAS nDepression (A) RT . - ", DEPAR "Depression (A) z -score #1 I l , DEPAZl mDepression.(A) z-score #2 DEIAZS nDcprassion (Pl Score - DEPPS .
nDeprcssion(P) RT - ",. DEPPR nDepression (P) -2-score #I. -DEPPZl !Qcpreesion(P) z-score #2 . DEPPZ2 lrDepression (Total.). Score - :DEPTS - - -
nDepres~ian(Total) RT - - ". DEPTR "Dtpreesion (Total) z-score #1 P I - DEPTZI nDcpres6ioa (Total) z-score #2 DEPTZ2. ."End of session - ";TIMES - - - -
CLOSE 5850 5860 REM 5870 CLS : PRINT : PRINT :PRLHT : P F ~hank you for your partic ipationn - 5880- W A d ' I M E R 5890 - Wl=ïNT (WA) :V?2-m+10.
': 5909 W3=INT(TIMER)' - S9lO IF' W3-WZ THEN GOTO 5920 EÏSE aOTO 5900 5920 REM-
- . -
5930 -END
Detecting Depression 62
Instructions for Malingering Respondents.
For this computerized personality test you are asked to respond as if you were feeling depressed. To state it more clearly we would like you fake or pretend being depressed. To help you we are providuig you with key descriptors of what some people who experience depression have reported in the past These people may be experiencing some or ail of the following :
- feeling sad or blue - not getting as much pleasure in things as before or being less interested in thuigs than before - weight loss or eating a lot less than mual/ weight gain or eating a lot more than usual - sleeping more than usual or sleeping less than usual or having restless or disturbed sleep - feeling wound up or slowed down - feeling tired or low on energy - feeling worthless, feeling guilty, low self-esteem - problems concentrating, remembering things, or making decisions - thoughts about death and dying - feeling hopeless about the future
The person who is best at faking sadness will win $25, this instrument was designed to detect people who are not answering sincerely. Therefore, the beçt performance will be judged as one that avoids detection as a person who is answering insincerely the person who has the highest level of depression. To help you here again are some descriptors of people who reported being depressed:
- feeling sad or blue - not getting as much pleanne in things as before or being less interested in things than befxe - weight loss or eating a lot less than usual / weight gain or eating a lot more than wual - sleeping more than usual or sleeping less than usual or having restless or disturbed sleep - feeling wound up or slowed down - feeling tired or low on energy - feeling worthless, feeling guilty, low self-esteem - problems concentrating, rernembering h g s , or makuig decisions : thoughts about death and dying - feeling hopeless about the fuhue
Thank you.
Detecting Depression 63
Emotion and Information Processing Debrieflng Fom: Session 2
The purpose of the present study was to determine whether students who experience different emotions (e.g., feeling sad or not feeling sad) demonstrate biases for idonnation processuig that are congruent with their emotions.
The cornputer questionnaire you completed is a rnodified version of an existing questionnaire. It has been modined to record response î h e s for each question. A number of studies have suggested that participants expenencing an emotion will endorse items with different response times than those individuals who are not experiencing the emotion.
In this study it is hypothesized that students who expenence elevated levels of sadness will take longer to respond to some items in the computerized questionnaire. Please do not inform fnends or associates of the exact nature of this study because it may negatively bias results.
Thank you for your participation in this study. If you have any questiom about the study, please contact Derick Cyr (623-4506), M.A. Clinical Psychology candidate, or Dr. Dwight Maananian (343 -8257), Department of Psychology, Lakehead University, Thunder Bay, ON, P7B SEI. If you would like a bnef summary of the results you may obtain them by printing your full name and permanent mailing address on the self-adhesive address label. Results will not IikeIy be available before August, 2000.
Ifparticipating in this study or completkg the questionnaires has distressed you or has raised personal issues that you would like to discuss, or if you just need someone to t a k to, the following organizations are availabie: L.U. Health Center (343-8361), Peer Support Line (343-8255), Chaplain (343-801 8), and Career Counseling Senices (343-801 8).
Fekken, G. C. & Holden, R. R (1992). Response latency evidence for viewing personality traits as schema indicators. Journal of Research in Personality, 26,103-120.
Fekken, G. C. & Holden, R. R (1994). The constnict validity of dif5erential response latencies in structured personality tests. Canadian Journal of Behavioural Sciences. 26,104- 120.
Detecting Depression 64
Table 1
Means and Standard Deviations for the PM Scales of Interest
Group NIM score PIM score DEP score DEP-A DEP-C DEP-P (SD) (SD) (SD) score (SD) score (SD) score (SD)
Depressed 2.25* 9-75* 34.07 12.83 13.00 1 1.08 (1 2) (1 -86) (3 -55) (6.23) (2.69) (4.18) (3.90)
Note. A = affective, C = cognitive, P = physiological. AU groups were significantly different fiom each other across each scale @ < -01) except for those scores indicated wiîb an asterisk.
Detecting Depression 65
Raw Remonding Time Means and Standard Deviations of Items Within a Scale for RT1 and RT2 - Group NIM MM P M P M DEP DEP (N) RTl RT2 RT1 RT2 RT1 RT2
Control 3.88ab 3.88 4.13 4.82 3.51 4.06 (15) (0-96) (1 .O 1) (0.78) (O -92) (O. 95) (0.98)
Malingering 4.24a 4.59 3 -83 4.54 3.75 4.47 (1 9) (0-56) (0.74) (1 -27) (1 -44) (1.11) (1.34)
Depressed 4.24b 4.99 4 -42 4.99 4.3 9 4.97 (1 2) (1 .23) (1.86) (1 -14) (1.25) (1 .04) (1 -2 1) Note. Values represent seconds of fime per item in the category. Signincant differences are represented by letters a and b @ < .OS).
Detecting Depression 66
Table 3
Means and Standard Deviations for the PA1 2-scores of Interest G~OUP NIM PIM DEP DEP-A DEP-C DEP-P (N> - z-score - z-score - z-score - z-score - z-score z-score -
(SD) (SD) (Sm (SD) (SD) (SD)
Control -2.1 7a 1 -20" -4.50 -1.58 -2.59 -0.32 (1 5 ) (1.70) (3.30) (3.87) (2.16) (2.1 1) (2.60)
Malingering 1 .1 5a -1 .6Sa -4.82 -1 .O3 -2.8 1 b -0.98 (19) (2.95) (1.94) (4.08) (2- 17) (1.73) (3 -29)
Depressed -0.92 -0.42 -1 -70 0.42 -0.58~ -1.53 (12) (2.25) (2.53) (4.72) (2.14) (2.98) (1.83)
Note. A = affective, C = cognitive, P = physiological. Significant Werences between groups are indicated with ietters (for a, p < -0 1; for b, p < -05).
Detecting Depression 67
Table 4
Tukw Post-hoc Dserences Between G~OUDS for the PA1 Scale Scores Scale G~OUP 0 @OUF (J) Mean Sig.
DBerence
Conîrol Malingering - 1 O. 85 ,000 Malingering Depressed 9.80 .O00
control M d i n g e ~ g 6.70 -000 Control Depressed 5.32 .O14
DEP Totsil Control Maluigering -43.53 .O00 Control Depressed -28.18 .O00 MaIingering Depressed 15.35 .O02
DEP - Affective Conîrol Malingering - 1 6.34 .O00 Control Depressed -10.97 .O00 Malingering Depressed 5.38 .O0 1
DEP - Cognitive Contrd Malingering - 1 5 -3 3 ,000 Control Depressed -10.33 .O00 Malingering Depressed 5-00 .O08
DEP - Physiological Control Malingering - 1 1.8 5 .O00 Control Depressed -6.88 ,002 Malingering Depressed 4.97 .O2 1
Detecting Depression 68
Table 5
Tukev Post-hoc Differences Beiween Groum for the 2-scores
( 1 4 ) NIM Control Malingering -3.33 .O01
PIM Control Malingering 2.85 .O08
DEP - Cognitive Malingering Depressed -2.22 .O26
Detecting Depression 69
Table 6
Classification Results Using Scale Scores
Group Predicted Group Membership Total Control Malingering Depressed
Original Comt Control 15 O O 15 Malingering 1 14 4 19 Depressed O 1 1 I 12
YO Control 100.0 .O .O 100.0 Malingering 5.3 73.7 21.1 100.0 Depressed .O 8.3 91.7 l00.0
Note. 87.0% of original cases correctly classified.
Detecting Depression 70
Table 7
Classification Results TJsing: Raw Resvonse Latencies
Group Predicted Group Membership Total Control Malingering Depressed
Original Count Control 11 3 1 15 Malingering 2 15 2 19 Depressed 4 2 6 12
YO Control 73 -3 20.0 6-7 100.0 Malingering 1 0.5 78.9 10.5 100.0 Depressed 33 -3 16.7 50.0 100.0
Note. 69.6% of original cases correctly classified.
Detecting Depression 7 1
Table 8
Classification Resiilts Using Z-scores
Group Predicted Group Mernbership Total Control Malingering Depressed
Original Count Control 11 1 3 15 Malingering Depressed
% Control 73.3 6.7 20 .O 100.0 Malingering 15.8 84.2 .O 100.0 Depressed 25 .O 16.7 58.3 100.0
Note. 73.9% of original cases correctly classified.
Detecting Depression 72
Table 9
Classification Results Usinn Scores and Transformed Response Latencies
Group Predicted Group Membership Total Control Malingering Depressed
OSgkd Comt Control 15 O O 15 Malingering 1 15 3 19 Depressed O 1 1 I 12
YO Control 100.0 .O .O 100.0 Malingering 5 -3 78 -9 15.8 100.0 Depressed .O 8.3 91.7 100.0
Note. 89.1% of original cases correctly classified.
Detecthg Depression 73
Table 10
Classification Results Using NIM Scale Scores
Group Predicted Group Mzmbership Total Control ~ a l & e r i ~ Depressed
Original Count Control 13 2 O 15 Malingering 6 13 O 19 Depressed 11 1 O 12
YO Conîrol 86.7 13.3 .O 100.0 Malingering 31.6 68.4 .O 100.0 -
Depressed 9 1.7 8.3 .O 100.0 Note. 56.5% of original cases correctly classined.
Detecting Depression 74
Table 11
Classification Results Ushg h W Z-scores
Group Predicted Group Membership Total -
Control ~ a l & ~ e r i n ~ ~eiressed Original Count Control 13 2 O 15
Malingering Depressed
Control Malingering Depressed 50.0 50.0 .O 100.0
Note. 63 .O% of original cases correctly classified.
Detecting Depression 75
Table 22
Classification Results Usine NIM Scde Score and MM Raw Response Times
Group Predicted Group Membership Total Control Malingering Depressed
Original Count Controf 11 I 3 15 Malingering Depressed
Control Malingering De~ressed
Note. 65.2% of original cases correctly classified.
Detecting Depression 76
Table 13
Classification Results Usine NIM Scale Score and NIM Z-scores
Group Predicted Group Membership Total Control Malingering ~ e s e s s e d
OrigLial Count Control 13 1 1 15 Malingering Depressed
% Control 86.7 6.7 6.7 100.0 Malingering 15.8 73.7 1 0.5 100.0 Depressed 66.7 8.3 25.0 100.0
Note. 65.2% of original cases correctly classified.
Detecting Depression 77
Table 14
Siaiincant T-test merences For 2-Scores Between the Depressed and Malingering Groups
Item Category 1-test df Sig. Mean Difference
46 DEP - A -2.59 14.35 - .O2 1 -.93 286 DEP - A -3 -00 12.73 .O10 -.96 187 DEP - C -2.24 29 .O3 3 -.3 5 275 DEP - P -3.63 29 .O0 1 9-63 315 DEP - P 2.47 27.00 .O20 -80 9 - NIM 2.73 29 .O1 1 .96 49 NIM 3.22 26.8 1 .O03 -77 144 PIM -2.57 13.71 .O22 -.63 264 PIM -2.2 1 29 .O3 5 -,3 5
Note. Mean ciifferences are calculated by subtracting the mean -score for depressed individuals fiom the mean -score for malingering individuals. T-tests were calculated following Levene's Test for Quality of Variances.
Detecting Depression 78
Table 15
Classincation Rates Usine the 2-scores From 10 Empincallv Derived Items
Group fredicted Group Membership To ta1 Malingering Depressed
Onginai Count Malingering 19 O 19 Depressed 1 1 I 12 Ungrouped 9 6 15 Cases
YO Control 100.0 .O 1 00.0 Malingering 8.3 91 -7 100.0 Ungrouped 60.0 40.0 100.0 Cases
Note. 96.8% of original cases correctly classified.
Recommended