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Measurement Invariance and Structure Validity of Scores on the Center for Epidemiologic Studies Depression - Revised (CESD-R) Scale with a Large University Sample

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Title: Measurement Invariance and Structure Validity of Scores on the Center for Epidemiologic Studies Depression - Revised (CESD-R) Scale with a Large University Sample
Language: English
Authors: Julie Sriken, Bradley T. Erford (ORCID 0000-0001-5891-5770), Martin F. Sherman, Kristen Watson, Heather L. Smith
Source: Measurement and Evaluation in Counseling and Development. 2024 57(1):57-71.
Availability: Routledge. Available from: Taylor & Francis, Ltd. 530 Walnut Street Suite 850, Philadelphia, PA 19106. Tel: 800-354-1420; Tel: 215-625-8900; Fax: 215-207-0050; Web site: http://www.tandf.co.uk/journals
Peer Reviewed: Y
Page Count: 15
Publication Date: 2024
Document Type: Journal Articles
Reports - Research
Education Level: Higher Education
Postsecondary Education
Descriptors: Symptoms (Individual Disorders), Depression (Psychology), Measures (Individuals), Undergraduate Students, Screening Tests, Test Reliability, Psychological Testing, Test Validity, Scores, Racial Differences, Gender Differences
Assessment and Survey Identifiers: Center for Epidemiologic Studies Depression Scale, Marlowe Crowne Social Desirability Scale
DOI: 10.1080/07481756.2023.2215934
ISSN: 0748-1756
1947-6302
Abstract: Psychometric characteristics of CESD-R scores were explored on a sample of 966 undergraduate students. Internal consistency ([alpha] = 0.92), external convergent and discriminant validity, and response bias were adequate to excellent. Strong measurement invariance was evident for gender and race comparisons, and the unidimensional model fit the data best.
Abstractor: As Provided
Entry Date: 2024
Accession Number: EJ1406390
Database: ERIC
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  Value: <anid>AN0174469744;mev01jan.24;2023Dec29.04:23;v2.2.500</anid> <title id="AN0174469744-1">Measurement Invariance and Structure Validity of Scores on the Center for Epidemiologic Studies Depression - Revised (CESD-R) Scale with a Large University Sample </title> <p>Psychometric characteristics of CESD-R scores were explored on a sample of 966 undergraduate students. Internal consistency (α =.92), external convergent and discriminant validity, and response bias were adequate to excellent. Strong measurement invariance was evident for gender and race comparisons, and the unidimensional model fit the data best.</p> <p>Keywords: CESD-R; center for epidemiologic studies depression – revised; depression; confirmatory factor analysis</p> <p>Depression is a common and growing worldwide mental illness affecting more than 300 million individuals across all ages, and the current leading cause of disability worldwide (World Health Organization (WHO), [<reflink idref="bib38" id="ref1">38</reflink>]). In the United States, 17.3 million adults have depression, representing 7.1% of the U.S. adult population (National Institute of Mental Health, [<reflink idref="bib26" id="ref2">26</reflink>]) and approximately 11 million U.S. individuals aged 18 years or older reported a depressive episode with a severe impairment. Of additional concern, depression is commonly associated with suicide and suicide attempts (World Health Organization, [<reflink idref="bib40" id="ref3">40</reflink>]). Suicide occurs worldwide, across all cultures, religions and ethnicities with Lithuania, Russia, Guyana and South Korea identified with the highest suicide rates, at 31.9, 31.0, 29.2, and 26.9 per 100,000 people, respectively. The United States ranks at the 27th highest per capita suicide rate, making death by suicide the 10th leading cause of death in the United States. However, among U.S. individuals aged 15-29 years old suicide is the second leading cause of death, with an estimated 1.4 million suicide attempts in 2017 (NIMH, [<reflink idref="bib26" id="ref4">26</reflink>]).</p> <p>Depression has a significant economic toll on individuals, families and society. Greenberg et al. ([<reflink idref="bib13" id="ref5">13</reflink>]) reported the U.S. economic burden of depression rose from $83.1 billion in 2000 to $210.5 billion in 2010 with 38% of that cost due to major depressive disorder. While more than 300 million people are affected by depression worldwide, the World Health Organization (WHO) ([<reflink idref="bib39" id="ref6">39</reflink>]) reported that fewer than half of people worldwide living with depression received treatment, and in many countries less than 10% receive any form of treatment. There are multiple barriers to effective treatment including social stigma, lack of resources for and training of health-care providers, insufficient screening procedures, and inaccurate assessments. All this points to a substantial need for efficient depression screening tools that yield reliable and valid scores across cultures. One of the most used, free access assessments for depression is the Center for Epidemiologic Studies Depression Scale—Revised (CESD-R; Eaton et al., [<reflink idref="bib11" id="ref7">11</reflink>]).</p> <p>The original CES-D was developed by Radloff ([<reflink idref="bib29" id="ref8">29</reflink>]) to assess symptoms of depression in the general population. The original CES-D was revised into the CESD-R by Eaton et al. ([<reflink idref="bib11" id="ref9">11</reflink>]) to improve psychometric properties and limitations as well as to align more closely with modern diagnostic criteria. The CESD-R is a free access, 20-item self-report scale aligned with the nine primary symptoms of depression as identified in the DSM (American Psychiatric Association, [<reflink idref="bib2" id="ref10">2</reflink>]). Van Dam and Earleywine ([<reflink idref="bib35" id="ref11">35</reflink>]) reported high score internal consistency in a large community sample (α =.923) and a smaller student sample (α = 0.928). In a psychometric synthesis of 18 CESD-R studies in English, Kimong et al. ([<reflink idref="bib18" id="ref12">18</reflink>]) reported an aggregated internal consistency of α = 0.92 showing excellent score reliability for a screening instrument. Interestingly, no study before this current study reported coefficient alphas for the two factors derived from factor analysis. An additional 21 studies reported by Kimong et al. demonstrated convergent validity showing moderate to strong relationships with other depression measure scores and a non-significant relationship with unrelated (discriminant validity) measures. Through exploratory factor analysis, Van Dam and Earleywine ([<reflink idref="bib35" id="ref13">35</reflink>]) identified a likelihood of two factors, one related to negative mood and the second related to functional impairment and called for further exploration of the factor structure and validity of scores in diverse populations. Walsh ([<reflink idref="bib37" id="ref14">37</reflink>]) also identified two factors: negative mood and suicidal ideation.</p> <p>The CESD-R has been translated into at least a dozen different languages, including Bhutanese, Chinese, Croatian, French, German, Indonesian, Korean, Latvian, Lithuanian, Polish, Spanish, and Turkish (Koziara, [<reflink idref="bib20" id="ref15">20</reflink>]; Van Dam & Earleywine, [<reflink idref="bib35" id="ref16">35</reflink>]) making it accessible to many populations worldwide. Validity studies of several translated versions (i.e. Spanish, Korean, Polish, Indonesian) showed strong correlations with other depression measures indicating the translated and adapted versions were probably measuring a similar depression construct (Kimong et al., [<reflink idref="bib18" id="ref17">18</reflink>]).</p> <p>This current study explored the psychometric characteristics of scores on the English version CESD-R with a sample of U.S. undergraduate students. The first hypothesis was that score reliability using Cronbach's alpha would be adequate (≥.80; Erford, [<reflink idref="bib12" id="ref18">12</reflink>]) for the total and factor scores. Second, we hypothesized that data from the internal structural validity analysis using confirmatory factory analysis procedures would reveal adequate fit of the one-factor (Eaton et al., [<reflink idref="bib11" id="ref19">11</reflink>]) and two-factor (Van Dam & Earleywine, [<reflink idref="bib35" id="ref20">35</reflink>]; Walsh, [<reflink idref="bib37" id="ref21">37</reflink>]) models, for which contradictory superior fit evidence exists in the literature. We expect that the 2-factor model will display superior fit. This study represents the first measurement invariance analysis using CESD-R data. Thus, the third hypothesis was that measurement invariance would be demonstrated across various subgroup comparisons (i.e. men and women; White and persons of Color; White and Asian/Pacific Islander). The fourth hypothesis was that external validity (convergent validity) would be demonstrated by comparing scores from the CESD-R with scores from the Generalized Anxiety Disorder Screener (GAD-7; Spitzer et al., [<reflink idref="bib32" id="ref22">32</reflink>]). The fifth hypothesis was that discriminant validity would be demonstrated by comparing scores on the CESD-R with scores from two theoretically unrelated measures/constructs: the Alcohol Use Disorders Identification Test (AUDIT; Babor et al., [<reflink idref="bib3" id="ref23">3</reflink>]) and the Social Justice Scale (SJS; Torres-Harding et al., [<reflink idref="bib34" id="ref24">34</reflink>]). Finally, we hypothesized that response bias (social desirability) influences on the CESD-R would be minimal (<emph>r</emph> ≤.20) as measured by the Marlowe-Crowne Social Desirability Scale (MC-SDS; Crowne & Marlowe, [<reflink idref="bib8" id="ref25">8</reflink>]).</p> <hd id="AN0174469744-2">Method</hd> <p>The construct-based unitary validity model (Messick, [<reflink idref="bib22" id="ref26">22</reflink>]), specifically internal and external aspects of validity, was used to study score validity. Institutional review board approval was obtained for this study and informed consent provided by all participants.</p> <hd id="AN0174469744-3">Participants</hd> <p>The target population for this study was undergraduate university students. Participants (<emph>n</emph> = 966) were undergraduate students attending a Research I university in the southern United States. Participants were young adults (range = 18-23 years, <emph>M</emph> = 19.07, <emph>SD</emph> = 0.95) and predominantly White (<emph>n</emph> = 562, 58.2%). Participants were also of Asian and Pacific Islands (<emph>n</emph> = 194, 20.1%), Black (<emph>n</emph> = 88, 9.1%), Latino/a/x (<emph>n</emph> = 67, 6.9%), Native American or Alaskan Native (<emph>n</emph> = 8, 0.8%), Middle Eastern (<emph>n</emph> = 12, 1.2%), and other (<emph>n</emph> = 4, 0.4%) descent, with 31 participants (3.2%) choosing not to respond to the racial/ethnic identity question. A majority of the sample identified as women (<emph>n</emph> = 600, 62.1%), 365 (37.8) as men, and one as transgender (0.1%). These data are summarized in Table 1.</p> <p>Table 1. Sample demographic characteristics.</p> <p> <ephtml> <table><thead><tr><td>Gender Self-Identification</td><td>Sample n(%)</td></tr><tr><td>Transgender</td><td>1 (0.1%)</td></tr></thead><tbody valign="top"><tr><td>Men</td><td char=".">365(37.8%)</td></tr><tr><td>Women</td><td char=".">600(62.1.%)</td></tr><tr><td>Total</td><td char=".">966</td></tr><tr><td><bold>Race Self-Identification</bold></td></tr><tr><td>Asian/Pacific Islander</td><td char=".">194(20.1.%)</td></tr><tr><td>Black</td><td char=".">88 (9.1%)</td></tr><tr><td>Indigenous</td><td char=".">8 (0.8%)</td></tr><tr><td>Latino/a/x</td><td char=".">67 (6.9%)</td></tr><tr><td>Middle Eastern</td><td char=".">12 (1.2%)</td></tr><tr><td>White</td><td char=".">562(58.2%)</td></tr><tr><td>Other</td><td char=".">4 (0.4%)</td></tr><tr><td>Missing</td><td char=".">31 (3.2%)</td></tr><tr><td>Total</td><td char=".">966</td></tr></tbody></table> </ephtml> </p> <hd id="AN0174469744-4">Instruments</hd> <p>Data were collected using an online survey which included informed consent, demographics questions (e.g. self-identification of age, gender, racial descent), the CESD-R and three additional research instruments: GAD-7, AUDIT, and SJS. These instruments were used to assess the external aspects of validity of the CESD-R. The final instrument, the Marlowe-Crowne Social Desirability Scale (MCSDS), was included to test for social desirability and response bias.</p> <hd id="AN0174469744-5">The Center for Epidemiologic Studies Depression Scale - Revised (CESD-R)</hd> <p>The Center for Epidemiologic Studies Depression Scale-Revised (CESD-R; Eaton et al., [<reflink idref="bib11" id="ref27">11</reflink>]) is intended for use as a screening tool for depressive symptoms occurring during the previous two weeks. Administration of this 20-item instrument can be completed in less than five minutes. Score reliability and validity of the CESD-R were reviewed above in the introduction. While Eaton et al. ([<reflink idref="bib11" id="ref28">11</reflink>]) proposed a unidimensional model underlies CESD-R scores, Van Dam and Earleywine ([<reflink idref="bib35" id="ref29">35</reflink>]) suggested that two factors underlie the 20 CESD-R items: (Factor 1) Functional Impairment (items 1, 3, 5, 7, 10, 11, 12, 13, 16, 18, 19, and 20) and (Factor 2) Negative Mood (items 2, 4, 6, 8, 9, 14, 15, and 17).</p> <p>There are five response options, the fifth being added during the revision process: 0 = "not at all or less than 1 day," 1 = "1–2 days," 2 = "3–4 days," 3 = "5–7 days," 4 = "nearly every day for 2 wk." The addition of the response choice of 4 ("nearly every day for 2 wk") was an adjustment by Eaton et al. ([<reflink idref="bib11" id="ref30">11</reflink>]) to accommodate the DSM (APA, [<reflink idref="bib2" id="ref31">2</reflink>]) 2-week symptoms rule for major depressive disorder. Scores of 4 on any items are changed to 3 when the total scale raw score is computed to align with the previously derived diagnostic validity evidence based on the 0-3 response format supporting the clinical cut score of 16. That is, substantial evidence on the original CES-D supported a diagnostic cut score of 16 for a depression positive decision using the 0-3 response format. Changing the response format to 0-4 would necessitate conducting new diagnostic validity studies. Eaton et al. used the short cut of converting all responses choices of 4 to a 3 before summing the total raw score. Thus, the total raw score is a simple sum of scores from the 20 items with a score range of 0-60. A cutoff score of 16 or higher indicates a possible major depressive episode, while scores below 16 indicate a subthreshold symptom display. For scores higher than 16, additional interpretive categories can be inferred (i.e. possible major depressive episode, probable major depressive episode, meets criteria for major depressive episode) by confirming that additional DSM criteria also exist.</p> <hd id="AN0174469744-6">Generalized Anxiety Disorder Screener (GAD-7)</hd> <p>The Generalized Anxiety Disorder Screener (GAD-7; Spitzer et al., [<reflink idref="bib32" id="ref32">32</reflink>]) is a seven-item screening instrument based on DSM criteria for generalized anxiety disorder (APA, [<reflink idref="bib2" id="ref33">2</reflink>]). Administration of the GAD-7 takes about 1-2 min to complete. Participants rank each item on a 4-point scale indicating the occurrence of anxiety symptoms over the previous two weeks (0 = not at all; 1 = several days; 2 = more than half the days; 3 = nearly every day). To interpret the GAD-7, one must calculate a simple sum of the seven item scores, so total raw scores can range from 0 to 21. These totals are compared against cutoffs for different levels of anxiety: minimal (0-4), mild (<reflink idref="bib5" id="ref34">5-9</reflink>), moderate (<reflink idref="bib10" id="ref35">10-14</reflink>), and severe (<reflink idref="bib15" id="ref36">15-21</reflink>). Those who score 10 points, or more are at risk of generalized anxiety disorder and clinicians are advised to conduct further assessment. In previous research with community samples and medical samples, responses to the GAD-7 have demonstrated adequate internal consistency (α =.89 and α =.92, respectively; Löwe et al., [<reflink idref="bib21" id="ref37">21</reflink>]; Spitzer et al., [<reflink idref="bib32" id="ref38">32</reflink>]). The internal consistency of the responses to the GAD-7 in the current sample was.91. As depression is theoretically associated with anxiety, the GAD-7 was selected to help derive evidence of convergent validity. Sriken et al. ([<reflink idref="bib33" id="ref39">33</reflink>]) reported adequate convergent and discriminant validity for college undergraduates scores on the GAD-7. Measurement invariance was demonstrated for gender and race on a unidimensional model.</p> <hd id="AN0174469744-7">Alcohol Use Disorders Identification Test (AUDIT)</hd> <p>The Alcohol Use Disorders Identification Test (AUDIT; Babor et al., [<reflink idref="bib3" id="ref40">3</reflink>]) is a 10-item scale used in medical and public health venues to screen for alcohol misuse. Administration can be performed orally, in writing, or online, and lasts about 2-3 min. Responses to each item are on a 4-point Likert-type scale of varying response descriptions and summed for a total score possible range of 0-40. For interpretation, higher scores indicate a higher likelihood of alcohol dependence with harmful drinking indicated by raw scores of 8 or higher, dependence by raw scores of 16 or higher, and hazardous drinking by raw scores of 20 or higher (Moehring et al., [<reflink idref="bib23" id="ref41">23</reflink>]). Durbeej et al. ([<reflink idref="bib10" id="ref42">10</reflink>]) reported a correlation of <emph>r</emph> =.66 between scores on the AUDIT and the alcohol problem severity domain of the Addiction Severity Index along with an AUDIT total score α of.89. Moehring et al. ([<reflink idref="bib23" id="ref43">23</reflink>]) found the AUDIT unidimensional model fit very well for measuring alcohol use and abuse across different genders and settings. In the current sample, the coefficient α was.83. As depression is theoretically unrelated to alcohol use, the AUDIT was selected to help derive evidence of discriminant validity.</p> <hd id="AN0174469744-8">Social Justice Scale (SJS)</hd> <p>The Social Justice Scale (SJS; Torres-Harding et al., [<reflink idref="bib34" id="ref44">34</reflink>]) is a 24-item scale intended to measure attitudes, values, and intentions related to social justice behaviors, and are distributed across four subscales: Attitudes Toward Social Justice (11 items), Perceived Behavioral Control (5 items), Subjective Norms (4 items), and Behavioral Intentions (4 items). Participants rate each item on a Likert-type scale from 1 (disagree strongly) to 7 (strongly agree). Scoring is accomplished using simple sum of scores (total score range of 24-168) and interpretation guidelines are absent. In the initial development study, responses to the SJS displayed strong internal consistency for its four subscales (α =.82 to.95). Internal consistency in the current sample was adequate for the full scale (α =.93) and all subscales (α =.83 to.92). Because depression is theoretically unrelated to social justice attitudes and behaviors, the SDS was selected to help derive evidence of discriminant validity.</p> <hd id="AN0174469744-9">Marlowe-Crowne Social Desirability Scale (MCSDS)</hd> <p>The Marlowe-Crowne Social Desirability Scale (MCSDS; Crowne & Marlowe, [<reflink idref="bib8" id="ref45">8</reflink>]) is a 33-item self-report scale that measures social desirability, an individual's tendency to alter responses to be perceived in a more desirable way. Holden and Fekken ([<reflink idref="bib16" id="ref46">16</reflink>]) proposed that the Marlowe-Crown measured a specific subtype of social desirability known as interpersonal sensitivity as opposed to a contrasting subtype known as a sense of general capability. The MCSDS was included in this study to assess whether social desirability potentially affected participant responses (i.e. bias) to the CESD-R. Response bias would be supported by bivariate correlations showing discrimination between scores on the two instruments (<emph>r</emph> ≤.20; Erford, [<reflink idref="bib12" id="ref47">12</reflink>]).</p> <p>Each MCSDS item describes a possible but improbable scenario with the option to respond true or false. For each item, the socially desirable option is scored 1 point and the non-socially desirable option is scored 0 points. To interpret the results, the points are tallied and compared against the following cutoff score ranges: 0-8 points indicate the participant responded most often by selecting the socially less desirable option; 9-19 points suggest an average selection of socially desirable responses; and 20-33 points suggest the participant may be very concerned with social desirability. Other permutations of the MCSDS include the two subscales thought to represent how participants attribute socially desirable traits to themselves (Attribution subscale) and deny socially undesirable traits (Denial subscale; Ramanaiah et al., [<reflink idref="bib30" id="ref48">30</reflink>]). The Attribution subscale is comprised of all of the positively worded items, while the Denial subscale is comprised of all of the negatively worded items. Reynolds ([<reflink idref="bib31" id="ref49">31</reflink>]) also suggested a 13-item short form version of the instrument, the MCSDS-SF.</p> <p>During development, Crowne and Marlowe ([<reflink idref="bib8" id="ref50">8</reflink>]) found adequate score reliability of the MCSDS items for the total score (α =.88). Others reported somewhat lower alphas between.70-.81 (Beretvas et al., [<reflink idref="bib4" id="ref51">4</reflink>]; Holden & Fekken, [<reflink idref="bib16" id="ref52">16</reflink>]; Holden & Passey, [<reflink idref="bib17" id="ref53">17</reflink>]) and highly variable test-retest score reliability from.38 over 2- to 4 wk (Beretvas et al.) to.86 over a month (Crino et al., [<reflink idref="bib7" id="ref54">7</reflink>]). Mixed evidence of structure validity, convergent and discriminant score validity, and even mean sample values have been reported in the literature. For the current sample, the internal consistencies were α =.74 for the full scale, α =.67 for the MCSDS-SF, α =.60 for Attribution subscale and α =.66 for the Denial subscale. Crowne and Marlowe reported moderate concurrent validity with the Minnesota Multiphasic Personality Inventory (MMPI) validity scales (e.g. L <emph>r</emph> =.54; K <emph>r</emph> =.40, F <emph>r</emph> = −0.36).</p> <hd id="AN0174469744-10">Procedure</hd> <p>Data collection took place from January 2018 through December 2021 at a Research I university in the southeastern United States. Undergraduates were recruited from human development courses. Students were offered the chance to volunteer for participation in the study by completing a survey for extra credit in their course. The eligibility criteria were that participants be 18 years of age or older and complete the entire survey. Each class was assigned a unique web address and those who accessed the website viewed the informed consent and were required to specify if they were aged 18 years or older and consented to participate. Anyone who responded that they were under 18 years of age or did not consent to participate could not access the subsequent pages. For participants who provided consent, subsequent pages included demographics items and the five research instruments, counterbalanced by class section. Halfway through the data collection time period we ceased collection of AUDIT and SJS protocols, so the sample size for those instruments analyses was 414. The demographic representation of those 414 was nearly identical to the 502 participants in the extended sample.</p> <p>REDCap (Research Electronic Data Capture; Harris et al., [<reflink idref="bib15" id="ref55">15</reflink>]) was the online survey management system used. REDCap provides a secure online software platform that allows for timing checks for participant speed monitor, attention checks (e.g. choose answer choice d for this question), and response perseveration checking (e.g. pattern analysis to determine if some responses occur more frequently than other responses). Because participants volunteered, were appropriately oriented, and received extra credit for valid protocols (completed all items and passed all validity checks), only a few aberrant protocols were identified and removed from the database.</p> <hd id="AN0174469744-11">Analysis</hd> <p>The current study examined the internal consistency, internal structure validity (confirmatory factor analysis), measurement invariance, external aspects of validity (convergent and discriminant), response bias, and sample descriptive statistics of the CESD-R. Internal consistency (α) was compared against the adequacy guideline of.80 or higher for screening level decisions (Erford, [<reflink idref="bib12" id="ref56">12</reflink>]). The external (convergent and discriminant) validity of the CESD-R was measuring the Pearson correlation (<emph>r</emph>) of its responses to total raw scores on the AUDIT and SJS for discriminant validity, and the GAD-7 for convergent validity. To assess response bias, scores of the CESD-R were correlated with the MCSDS total score and shorter variations. Interpretation of external validity and response bias rely on the effect size guidelines proposed by Cohen ([<reflink idref="bib6" id="ref57">6</reflink>]; i.e. <emph>r</emph> =.10 is small,.30 is medium, and.50 is large). Due to common methods variance, the strength of the correlations may be inflated. As such, the guideline for convergent validity confirmation was set at <emph>r</emph> ≥.50, and <emph>r</emph> ≤.20 for evidence of discriminant validity (Erford, [<reflink idref="bib12" id="ref58">12</reflink>]).</p> <p>Internal aspects of validity were assessed using confirmatory factor analysis with <emph>Mplus</emph> version 8.9 (Muthen & Muthen, [<reflink idref="bib25" id="ref59">25</reflink>]) using weighted least squares means and variances (WLSMV). Guidelines of good model fit (Dimitrov, [<reflink idref="bib9" id="ref60">9</reflink>]) were applied such that adequate fit was indicated by comparative fit index (<emph>CFI</emph>) or Tucker-Lewis index (<emph>TLI</emph>) ≥.90 (≥.95 indicates an excellent fit), root mean square error of approximation (<emph>RMSEA</emph>) ≤.08 (Kline, [<reflink idref="bib19" id="ref61">19</reflink>]), standardized root mean square residual (<emph>SRMR</emph>) ≤.08, and a Chi-squared test where <emph>p</emph> >.05. The CESD-R 2-factor measurement model was subsequently used for measurement invariance testing among various self-identified gender and racial groups with substantial subsample sizes. Several tests were used to examine global model fit including the Chi-squared test (χ<sups>2</sups>) and Chen's ([<reflink idref="bib5" id="ref62">5</reflink>]) criteria were applied to reflect a lack of invariance, including an increase in <emph>RMSEA</emph> or <emph>SRMR</emph> ≥.015 or a decrease in <emph>CFI</emph> ≥.01.</p> <hd id="AN0174469744-12">Results</hd> <p></p> <hd id="AN0174469744-13">Sample Descriptive Statistics</hd> <p>This sample had a mean depression score of 14.13 (<emph>SD</emph> = 11.38) on the CESD-R, which on average is only about two points lower than the criterion associated with a clinically significant depression elevation. Participants who self-identified as women (<emph>n</emph> = 600) yielded a mean depression score of 14.66 (<emph>SD</emph> = 11.60), while participants who self-identified as men (<emph>n</emph> = 365) had a mean CESD-R score of 13.30 (<emph>SD</emph> = 10.98). The skewness and kurtosis of the samples were within normal limits and Levene's test for equality of variance was not significant (<emph>F</emph> = 1.51, <emph>p</emph> =.22). A <emph>t</emph>-test between mean scores for women and men was significant for this sample (<emph>t</emph> [<reflink idref="bib963" id="ref63">963</reflink>] = 1.79, <emph>p</emph> =.04). Thus, the women mean was significantly higher than the men mean score on the CESD-R total score. Cohen's <emph>d</emph> was 0.12[<emph>95% CI</emph>: −0.11, 0.25], a no to small difference. Cohen's <emph>d</emph> is interpreted as small (.20), medium (.50), or large (.80; Cohen, [<reflink idref="bib6" id="ref64">6</reflink>]) effect sizes. Means, standard deviation, and coefficient alphas are presented in Table 2, along with correlations among the CESD-R total score and factor scores.</p> <p>Table 2. Correlations among the CESD-R, GAD-7, AUDIT, SJS, and MCSDS.</p> <p> <ephtml> <table><thead><tr><td>Instrument Name</td><td><italic>n</italic></td><td>CESD-R Total</td><td>CESD-R Factor 1</td><td>CESD-R Factor 2</td></tr></thead><tbody valign="top"><tr><td /><td>M(SD)</td><td char=".">14.13(11.38)</td><td char=".">9.94(7.52)</td><td char=".">4.18(4.61)</td></tr><tr><td>CESD-R Total</td><td char=".">966</td><td>[.92]</td><td /><td /></tr><tr><td>CESD-R Factor 1</td><td char=".">966</td><td char=".">.96*</td><td>[.88]</td><td /></tr><tr><td>CESD-R Factor 2</td><td char=".">966</td><td char=".">.90*</td><td char=".">.75*</td><td>[.88]</td></tr><tr><td>GAD-7 Total</td><td char=".">966</td><td char=".">.67*</td><td char=".">.64*</td><td char=".">.62*</td></tr><tr><td>AUDIT</td><td char=".">414</td><td char=".">.12*</td><td char=".">.13*</td><td char=".">.10*</td></tr><tr><td>SJS Total</td><td char=".">414</td><td char=".">.02</td><td char=".">.04</td><td>−0.02</td></tr><tr><td>MCSDS Total</td><td char=".">966</td><td char=".">.02</td><td char=".">.01</td><td char=".">.03</td></tr><tr><td>MCSDS Attribution</td><td char=".">966</td><td char=".">.13*</td><td char=".">.13*</td><td char=".">.13*</td></tr><tr><td>MCSDS Denial</td><td char=".">966</td><td char=".">.08*</td><td char=".">.09*</td><td char=".">.06*</td></tr><tr><td>MCSDS-SF</td><td char=".">966</td><td char=".">.04</td><td char=".">.05</td><td char=".">.02</td></tr></tbody></table> </ephtml> </p> <p>1 <emph>Notes.</emph> *<emph>p</emph> <.05; Coefficient α on the [diagonal]; 95% confidence interval is <emph>r</emph>±.10 for all coefficients; CESD-R Total = Center for Epidemiological Studies Depression Scale – Revised total score; CESD-R Factor 1 = Functional Impairment; CESD-R Factor 2 = Negative Mood; GAD7 Total = Generalized Anxiety Disorder 7-tem scale total score; AUDIT = Alcohol Use Disorder Identification Test total score; SJS Total = Social Justice Scale total score; MCSDS Total = Marlowe-Crown Social Desirability Scale total score; MCSDS Attribution = Marlowe-Crown Social Desirability Scale Attribution subscale; MCSDS Denial = Marlowe-Crown Social Desirability Scale Denial subscale; MCSDS-SF = Marlowe-Crown Social Desirability Scale 13-item short form.</p> <hd id="AN0174469744-14">Internal Structure Aspects of Validity</hd> <p>The fit of participants responses to the CESD-R was compared using confirmatory factor analysis against the unidimensional model for all 20 items (see Figure 1) proposed by Eaton et al. ([<reflink idref="bib11" id="ref65">11</reflink>]). The two-factor model suggested by Van Dam and Earleywine ([<reflink idref="bib35" id="ref66">35</reflink>]) resulted in a correlation between factor 1 and 2 summed scores of a very high <emph>r</emph> =.75 (see Table 2). While this correlation was much lower than the <emph>r</emph> =.94 reported in Van Dam and Earleywine's study both correlations indicate a high degree of relationship indicating distinct factors may not exist. Thus the 2-factor model was deemed too highly intercorrelated (i.e. degenerate) and eliminated from consideration. CESD-R score data fit the unidimensional model, accordingly: <emph>CFI</emph> of.907, TLI of.896, <emph>RMSEA</emph> of.115 [<emph>95% CI</emph>:.110,.119], <emph>SRMR</emph> of.082, and <emph>χ<sups>2</sups></emph> <.05. Thus, the data fit the model poorly to adequately (<emph>CFI/TLI</emph> ≥.90). Neither the chi-square test, <emph>RMSEA,</emph> nor <emph>SRMR</emph> indicated adequate fit. Prior to proceeding to measurement invariance testing, we improved the model fit by allowing a covariance between items 5 (My sleep was restless) and 19 (I had a lot of trouble getting to sleep).</p> <p>Graph: Figure 1. The CESD-R unidimensional model.</p> <hd id="AN0174469744-15">Measurement Invariance</hd> <p>Single-group CFAs of the modified unidimensional model were conducted to determine the baseline models for White (<emph>n</emph> = 562), participants of Color (<emph>n</emph> = 179; i.e. a mixed grouping of Black, Latino/a/x, Indigenous, Middle Eastern, and Other, but not Asian/Pacific Islander), and Asian/Pacific Islander (<emph>n</emph> = 194) participant subgroups, and the two gender groups [women (<emph>n</emph> = 600) and men (<emph>n</emph> = 365)], separately. Racial group comparisons were determined based on sample size, as recommended sample sizes approaching 200 participants or more are considered optimal for group comparisons (Chen, [<reflink idref="bib5" id="ref67">5</reflink>]). Thus, the subgroup sample sizes of 562 for White and 194 for Asian/Pacific Islanders participants allowed for homogeneous group comparisons, while the remaining participants were collapsed into a persons of Color subgroup. See Table 3 for the initial 1- factor baseline model. To improve model fit prior to invariance testing we allowed covariance between items 5 (My sleep was restless) and 19 (I had a lot of trouble getting to sleep), which we judged to be theoretically related. This modification significantly enhanced model fit (see Table 3) and this modified 1-factor model was used for subsequent measurement invariance testing. This modified model fit the data from all demographic subgroups well across all reported indexes, yielding initial evidence for measurement invariance for scores across groups. The most frequently examined and reported measurement invariance tests include configural, metric, and scalar (Han et al., [<reflink idref="bib14" id="ref68">14</reflink>]). WLSMV subsumes metric within scalar model testing for categorical data (Muthen & Muthen, [<reflink idref="bib25" id="ref69">25</reflink>]). All deltas reported below regarding scalar testing can be located in Table 4.</p> <p>Table 3. Fit Indexes for the 1-factor and the 1-factor modified model by groups for the measurement invariance analyses.</p> <p> <ephtml> <table><thead><tr><td>Model</td><td><italic>n</italic></td><td>χ<sup>2</sup></td><td><italic>df</italic></td><td><italic>CFI</italic></td><td><italic>TLI</italic></td><td><italic>RMSEA</italic>[CI 90%]</td><td>SRMR</td></tr></thead><tbody valign="top"><tr><td>One factor</td><td char=".">966</td><td char=".">2,325.00</td><td char=".">170</td><td char=".">0.907</td><td char=".">0.896</td><td>.115[.110,.119]</td><td char=".">0.082</td></tr><tr><td>*Modified 1-factor</td><td char=".">966</td><td char=".">1,231.20</td><td char=".">169</td><td char=".">0.954</td><td char=".">0.949</td><td>.081[.077,.085]</td><td char=".">0.064</td></tr><tr><td>Men</td><td char=".">365</td><td char=".">486.7</td><td char=".">169</td><td char=".">0.961</td><td char=".">0.965</td><td>.072[.064,.079]</td><td char=".">0.073</td></tr><tr><td>Women</td><td char=".">600</td><td char=".">836.2</td><td char=".">169</td><td char=".">0.957</td><td char=".">0.951</td><td>.081[.076,.087]</td><td char=".">0.066</td></tr><tr><td>White</td><td char=".">562</td><td char=".">713.4</td><td char=".">169</td><td char=".">0.953</td><td char=".">0.947</td><td>.076[.070,.081]</td><td char=".">0.07</td></tr><tr><td>Participants of Color</td><td char=".">373</td><td char=".">527.3</td><td char=".">169</td><td char=".">0.965</td><td char=".">0.961</td><td>.075[.068,.083]</td><td char=".">0.066</td></tr><tr><td>Asian/Pacific Islander</td><td char=".">194</td><td char=".">349.5</td><td char=".">169</td><td char=".">0.967</td><td char=".">0.963</td><td>.074[.063,.085]</td><td char=".">0.083</td></tr></tbody></table> </ephtml> </p> <p>2 <emph>Notes</emph>. χ<sups>2</sups> = Chi-square test statistic (all <emph>p</emph> <.001); <emph>df</emph> = degrees of freedom; <emph>CFI</emph> = comparative fit index; <emph>TLI</emph> =Tucker-Lewis index; <emph>RMSEA</emph> = root mean square error of approximation; <emph>CI90</emph> = 90% confidence interval; <emph>SRMR</emph> =standardized root mean square residual. *Modified using covariance between items 5 and 19.</p> <p>Table 4. Measurement invariance testing by self-identified comparison groups using the modified 1-factor default model.</p> <p> <ephtml> <table><thead><tr><td>Invariance Test</td><td>χ<sup>2</sup>(<italic>df</italic>)</td><td><italic>CFI</italic></td><td>Δ<italic>CFI</italic></td><td><italic>RMSEA</italic>[CI 90%]</td><td>Δ<italic>RMSEA SRMR</italic></td><td>Δ<italic>SRMR</italic></td><td><italic>Models Compared χ<sup>2</sup>(df)[ρ]</italic></td></tr></thead><tbody valign="top"><tr><td><bold>Men & Women Participants</bold></td><td /><td /><td /><td /><td /><td /><td /></tr><tr><td>Configural</td><td char=".">1288.3(338)*</td><td char=".">.960</td><td /><td char=".">.076[.072,.081]</td><td /><td char=".">.069</td><td /></tr><tr><td>Scalar</td><td char=".">1204.2(396)*</td><td char=".">.966</td><td char=".">+.006</td><td char=".">.065[.061,.069]</td><td>−0.011</td><td char=".">.070</td><td char=".">+.001</td></tr><tr><td>Scalar vs. Configural</td><td /><td /><td /><td /><td /><td /><td char=".">83.53(58)[.01]</td></tr><tr><td><bold>White & People of Color Participants</bold></td><td /><td /><td /><td /><td /><td /><td /></tr><tr><td>Configural</td><td char=".">1195.0(338)*</td><td char=".">.959</td><td /><td char=".">.075[.070,.079]</td><td /><td char=".">.069</td><td /></tr><tr><td>Scalar</td><td char=".">1126.1(396)*</td><td char=".">.965</td><td char=".">+.006</td><td char=".">.064[.059,.068]</td><td>−0.011</td><td char=".">.070</td><td char=".">+.001</td></tr><tr><td>Scalar vs. Configural</td><td /><td /><td /><td /><td /><td /><td char=".">81.27(58)[.02]</td></tr><tr><td><bold>White & Asian/Pacific Islander Participants</bold></td><td /><td /><td /><td /><td /><td /><td /></tr><tr><td>Configural</td><td char=".">1020.4(338)*</td><td char=".">.959</td><td /><td char=".">.073[.068,.078]</td><td /><td char=".">.074</td><td /></tr><tr><td>Scalar</td><td char=".">1003.6(396)</td><td char=".">.964</td><td char=".">+.005</td><td char=".">.064[.059,.069]</td><td>−0.009</td><td char=".">.075</td><td char=".">+.001</td></tr><tr><td>Scalar vs. Configural</td><td /><td /><td /><td /><td /><td /><td char=".">91.0(58)[<.01]</td></tr></tbody></table> </ephtml> </p> <p>3 <emph>Notes</emph>. χ<sups>2</sups> = Chi-squared test statistic; <emph>df</emph> = degrees of freedom; * = significance at <emph>p</emph> <.05; <emph>CFI</emph> = comparative fit index; <emph>RMSEA</emph> = root mean square error of approximation; CI90 = 90% confidence interval; <emph>SRMR</emph> = standardized root mean square residual.</p> <hd id="AN0174469744-16">Invariance Testing of Self-Identified White and People of Color Participant Scores</hd> <p>Testing for measurement invariance between scores from White and aggregated participants of Color on the CESD-R scale began by testing configural invariance, which allows free variation of factor loadings and item intercepts for each group while testing whether the CESD-R scale structure differs by racial group [White (<emph>n</emph> = 562) and participants of Color (<emph>n</emph> = 179)]. The structure of the CESD-R for White versus participants of Color was compared using a multi-group CFA. Configural invariance testing revealed that the modified 1-factor structure was similar for both racial groups across all fit indices (see Table 4), confirming configural invariance. Fit indices from the scalar model were all good to excellent, and scalar/metric delta fit indices again revealed no model degradation (</p> <p>Graph</p> <p> <ephtml> <math display="inline" xmlns="http://www.w3.org/1998/Math/MathML"><mo>Δ</mo></math> </ephtml> <emph>CFI</emph> = +.006). Thus, full invariance was documented; in other words, we failed to disconfirm measurement invariance between White and people of Color participant groups, promoting confidence that scores from participants who are White and of Color appear to perceive and perform similarly on the CESD-R items and factors.</p> <hd id="AN0174469744-17">Invariance Testing of Self-Identified White and Asian/Pacific Islander Participant Scores</hd> <p>Potential measurement invariance was then examined for CESD-R scores between students who self-identified as White (non-Latino/a/x; <emph>n</emph> = 562) and of Asian/Pacific Islander descent (<emph>n</emph> = 194). Configural invariance testing of scores revealed similar factor structures across both racial groups with all fit indices suggesting a good to excellent fit (see Table 4). Scalar invariance tests also indicated an adequate fit and no model degradation, which was confirmed by examining the delta fit indices: Δ<emph>CFI</emph> = +.005, Δ<emph>RMSEA</emph> = −0.009, Δ<emph>SRMR</emph> = +.001. Thus, White and Asian/Pacific Islander descent group scores did not vary with regard to factor loadings and thus we failed to disconfirm measurement invariance. Alternatively, we may consider that full measurement invariance was in evidence.</p> <hd id="AN0174469744-18">Invariance Testing of Women and Men CESD-R Scores</hd> <p>Finally, CESD-R measurement invariance was analyzed for scores between women (<emph>n</emph> = 600) and men (<emph>n</emph> = 365) participants. Multi-group CFAs indicated that the CESD-R factor structures provided a good to excellent fit of the model across both groups on all indicators (see Table 3). As Table 4 reveals, testing for scalar invariance resulted in a good to excellent fit across group scores and no degradation of the model shown in the delta comparisons: Δ<emph>CFI</emph> = +.006, Δ<emph>RMSEA</emph> = −0.011, Δ<emph>SRMR</emph> =.001. Thus, upon meeting Chen's ([<reflink idref="bib5" id="ref70">5</reflink>]) criteria for measurement invariance we failed to disconfirm (i.e. we determined support on this sample for) full measurement invariance between the women and men group scores.</p> <hd id="AN0174469744-19">Reliability</hd> <p>The CESD-R responses in this sample had a high internal consistency for the total score as a screening tool (<emph>α</emph> =.92). Additionally, the α coefficients for the CESD-R subscales scores were adequate for Functional Impairment (α =.88) and Negative Mood (<emph>α</emph> =.88).</p> <hd id="AN0174469744-20">Convergent and Discriminant Validity</hd> <p>Responses to the CESD-R were compared with the GAD-7 scores for evidence of convergent validity (<emph>r</emph> ≥.50), and the AUDIT and SJS scores for evidence of discriminant evidence (<emph>r</emph> ≤.20). As presented in Table 2, in an examination of external validity, the CESD-R total score converged with the GAD-7 total score (<emph>r</emph> =.67). In addition, the CESD-R scores diverged from the AUDIT total score (<emph>r</emph> =.12) and SJS total score (<emph>r</emph> =.02). The CESD-R factors 1 (<emph>r</emph> =.13 with AUDIT; <emph>r</emph> =.04 with the SJS) and 2 (<emph>r</emph> =.10 with AUDIT; <emph>r</emph> =.02 with the SJS) scores correlated similarly. Thus, convergent and discriminant results conformed to hypothesized expectations.</p> <hd id="AN0174469744-21">Response Bias Scale Comparisons</hd> <p>The sample's responses to the CESD-R items were compared with responses on the MCSDS using bivariate correlations. Results of this analysis are displayed in Table 2. The correlations among the CESD-R total and subscales (Functional Impairment and Negative Mood) responses and all variants and subscales of the MCSDS were below the recommended cutoff of <emph>r</emph> = |.20| for evidence of response bias, even accounting for potential inflation due to common method variance. All total score and subscale score correlations between the CESD-R and MCSDS fell within the tight range of <emph>r</emph> = |.02 to.13| (shared variance <emph>r<sups>2</sups></emph> of 0.04% − 1.69%), suggesting that participants responses were not influenced by social desirability when answering the CESD-R items.</p> <hd id="AN0174469744-22">Discussion</hd> <p></p> <hd id="AN0174469744-23">Implications for Counseling Practice</hd> <p>The purpose of the current study was to examine the psychometric properties of responses to the CESD-R using a sample of university undergraduate students. Specifically, the goal was to assess score reliability and validity. Internal (structure) validity compared hypothesized one- and two-factor models through confirmatory factor analysis. Measurement invariance was tested for gender and some racial group comparisons. The GAD-7 was administered to test convergent validity, while the AUDIT and SJS were used to test for discriminant validity. The Marlowe-Crowne Social Desirability Scale was also administered to explore potential response bias due to response bias through positive and negative impression management.</p> <p>The results demonstrated that the CESD-R total scores had excellent reliability (α =.92), as did both the Functional Impairment and Negative Mood subscales scores (α =.88 &.88, respectively). The structural aspects of the model indicate preference for the unidimensional model which fit the data mostly adequately. The intercorrelation between factors 1 and 2 of the hypothesized 2-factor model was very high (<emph>r</emph> =.75), effectively eliminating that model from consideration because two distinct factors do not exist. Furthermore, CESD-R convergent and discriminant validity were supported by all three comparisons. As expected, the AUDIT and the SJS scores demonstrated a near zero correlation with the CESD-R scores, and convergence was established with the GAD-7. Importantly, this was the first measurement invariance study completed on CESD-R scores. Full measurement invariance was demonstrated for men and women, participants who were White and Asian/Pacific Islander, and participants who were White and of Color. This means that clinicians can use the English version CESD-R with confidence across varied client groups. However, before confident use of translated/adapted CESD-R versions can be undertaken, similar measurement invariance testing on scores from those translated versions must be completed and compared to the original English version. Until then, clinicians must be wary about differences in how their clients administered the translated/adapted CESD-R versions understand the instrument and should debrief after administration or follow up with extensional questions.</p> <p>Additionally, there was no covariance in responses on the CESD-R and the MCSDS which indicates that social desirability probably did not influence responses. It is also possible that participants demonstrated depressive realism (e.g. people with depression can make realistic inferences, often better than people who are not depressed; Allan et al., [<reflink idref="bib1" id="ref71">1</reflink>]; Moore & Fresco, [<reflink idref="bib24" id="ref72">24</reflink>]) or positive illusory bias (e.g. rating oneself as more competent than objectively defined competence levels indicate; Prevatt et al., [<reflink idref="bib28" id="ref73">28</reflink>]; Volz-Sidiropoulou et al., [<reflink idref="bib36" id="ref74">36</reflink>]). Counselors working with people from populations similar to our sample of university students may find it helpful to probe clients whose CESD-R subthreshold scores approach the cutoff score of 16 to account for any minimization of symptoms. Participants concerned about presenting themselves in a socially accepted manner were more likely to deny depression symptoms (Perinelli & Gremigni, [<reflink idref="bib27" id="ref75">27</reflink>]), usually with a correlation close to <emph>r</emph> =.35. Therefore, counselors are advised to administer a social desirability instrument along with the CESD-R or other depression scales to inform the counselor about how valid the scores may be and whether assessing depression through other means may be necessary.</p> <p>Finally, the results of the CESD-R in this study indicate a very high prevalence of depression among this college student sample: 44% (<emph>z</emph>-score = +0.16) for the total sample, 45% of women (<emph>z</emph>-score = +0.12), and 40% of men (<emph>z</emph>-score = +0.25) using the standard criterion-referenced raw score cutoff score of 16 applied to the sample means in Table 1. This was an exceptionally high proportion of depression-threshold-level participants compared to the 7.1% proportional depression estimate within the U.S. adult population reported by the National Institute of Mental Health ([<reflink idref="bib26" id="ref76">26</reflink>]). Thus, diagnostic validity studies of the CESD-R with university students are sorely needed to be sure that a traditional cutoff score of 16 is optimal for identification. In the current study, a cutoff score of 16 appears to identify an unusually high proportion of university students with possible depression, even considering some data was collected during the COVID-19 pandemic.</p> <p>The selection of depression screening assessments is an important decision for counseling centers and practitioners who serve college students, and some instruments present with minor to substantial barriers, such as cost and length of time-consuming protocols. Furthermore, counselors need screening instruments that provide reliable and valid scores, are easy to administer, and quickly applied to diverse populations. The CESD-R is free-access and administered in about two to three minutes, so evidence of good psychometric properties in the college population would support its use for screening college students. The results of the current study indicate that the CESD-R is a practical screening tool for depression among university students with good score reliability and validity. University counseling centers could use the CESD-R with confidence to identify students presenting with both depression and signs of suicide risk (factor 2 items).</p> <hd id="AN0174469744-24">Study Limitations</hd> <p>This study is limited in several ways. First, the sample is not a representative sample of the U.S. population since it was a university sample; it is unclear whether this university sample is representative of the U.S. university population. Participants were predominantly White at 58.2%, similar to the proportion of the U.S. population identifying as White in the 2020 census. The sample was mostly women and younger than the mean age of the U.S. population. Thus, while convergent and discriminant correlations may be generalizable to the U.S. population, generalization of sample means or other characteristics is probably better applied toward college students than the general U.S. population. The screening assessments in the current study were administered to a university sample versus a community sample; as a subgroup, the university sample may not be reflective of the general population of the United States, although the correlation structure and matrices probably have robust generalizability. The current sample was primarily White and female from a diverse, although still primarily White, research I institution. Thus, the results of this study may be most applicable to university students who are young adults and predominantly White and women.</p> <p>Second, this study did not include any additional depression scales to assess correlations with other commonly used depression screeners. Convergence with the GAD-7 lends some support that the CESD-R is measuring depression in this sample but having actual depression measures would strengthen this conclusion. Similarly, this study relied on participant self-report on the screening tools but did not include any comparisons with actual diagnostic status of the participants by comparing CESD-R responses with actual depression diagnoses (diagnostic validity) to determine the accuracy of using the CESD-R for screening level decisions for depression, suicidal ideation, or other co-morbid symptomology.</p> <hd id="AN0174469744-25">Future Counseling Research Implications</hd> <p>Future research should allow for improved testing of convergent validity with university students. Perhaps future studies could integrate previous diagnoses from private health care professionals or a student health clinic, although such diagnoses are typically categorical in nature. What would be more useful is some other measures of depression in order to extend the nomological network. Studies can include other depression measures and depression diagnoses for comparison with the scores on the CESD-R. Likewise, pertaining to discriminant validity, one can make the distinction between near and far comparisons. Social desirability could be considered a near comparison as it is a potential confound, while the Social Justice Scale comparison could be considered a far comparison because it is a theoretically unrelated construct.</p> <p>Another avenue to study is to examine how social desirability influences responses given on depression screening tools. It would be important to know if variations in administration, item language, or content could result in more truthful responses. Understanding which items of the CESD-R are more likely to result in response bias could suggest to counselors which symptoms should be explored further in session for more accurate and in-depth information.</p> <p>Our research found that the unidimensional CESD-R model resulted in mostly poor to adequate fit with the scores for this sample, while a modified 1-factor version that allowed covariance between items 5 and 19 significantly enhanced model fit. Any revision of the CESD-R should address the overlap in wording and covariance of items 5 (My sleep was restless) and 19 (I had a lot of trouble getting to sleep), which we judged to be theoretically related. In addition, research that examines the factor structure would help with developing an understanding of the structure validity of the scale perhaps by eliminating or replacing inefficient items.</p> <p>The CESD-R has been translated into about a dozen languages at this time and before those translated/adapted versions can be used with confidence, measurement invariance comparisons with the original English version should be conducted to establish language version equivalence. In addition, small sample sizes in some subgroups in the current study (White/Latino/a/x <emph>n</emph> = 67; Black <emph>n</emph> = 88; Middle Eastern <emph>n</emph> = 12; Indigenous <emph>n</emph> = 8) meant that the samples were too small for specific measurement invariance testing. Future studies should explore larger samples of these underrepresented groups to determine whether the CESD-R can be used with confidence and provide support that the CESD-R is measuring the same construct and its items are being interpreted similarly by the groups being compared. This would allow for raw scores and the use of criterion cutoff scores to be interpreted similarly for most people among these groups. Measurement invariance also should be conducted with robust sample sizes of diverse participant comparison subgroups (e.g. gender diverse), and diverse age groups (e.g. adolescent, undergraduate, young adult, middle adult, etc.). Understanding whether the CESD-R performs in an equivalent manner across these varying groups will add to the usefulness, interpretation, and generalizability of participant scores.</p> <p>The general literature around the use of the CESD-R with university students lacks diagnostic validity information for the sample population. In the current study it was unknown whether an individual who scored above the cutoff score for depression had a related diagnosis, leaving uncertainty as to whether the CESD-R could accurately alert counselors to actual counseling issues. Therefore, studies of diagnostic validity in university students using the CESD-R are greatly needed at this time. Diagnostic validity studies involve administration of the CESD-R along with collection of a criterion of diagnosis for various depression disorders, allowing computation of total classification accuracy, sensitivity, specificity, positive predictive power, and negative predictive power. Accuracy of decisions rendered is perhaps the most important characteristic of a depression screening test to assess whether a cut score of 16 is appropriate for the university student population.</p> <hd id="AN0174469744-26">Conclusion</hd> <p>The CESD-R is an easy to administer screening tool that is free of charge, readily available, and has been translated/adapted into multiple languages. The CESD-R could be a useful depression instrument for counselors working with university and college populations as well as young adults because of its good score reliability and external validity. But the unsettled question around the internal structure of the model (e.g., 1 vs 2 factors; covariance of redundant items) and few diagnostic validity studies with this population are drawbacks. The next revision of the CESD-R should address these drawbacks to enhance clinical, research, and policy applications.</p> <hd id="AN0174469744-27">Disclosure statement</hd> <p>No potential conflict of interest was reported by the authors.</p> <ref id="AN0174469744-28"> <title> References </title> <blist> <bibl id="bib1" idref="ref71" type="bt">1</bibl> <bibtext> Allan, L. G., Siegel, S., & Hannah, S. (2007). The sad truth about depressive realism. Quarterly Journal of Experimental Psychology (2006), 60 (3), 482 – 495. https://doi.org/10.1080/17470210601002686</bibtext> </blist> <blist> <bibl id="bib2" idref="ref10" type="bt">2</bibl> <bibtext> American Psychiatric Association. (2022). Diagnostic and statistical manual of mental disorders (5th ed., text rev., DSM-5-TR). American Psychiatric Press.</bibtext> </blist> <blist> <bibl id="bib3" idref="ref23" type="bt">3</bibl> <bibtext> Babor, T. F., Higgins-Biddle, J. C., Saunders, J. B., & Monteiro, M. G. (2001). 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  Data: Measurement Invariance and Structure Validity of Scores on the Center for Epidemiologic Studies Depression - Revised (CESD-R) Scale with a Large University Sample
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  Data: <searchLink fieldCode="SO" term="%22Measurement+and+Evaluation+in+Counseling+and+Development%22"><i>Measurement and Evaluation in Counseling and Development</i></searchLink>. 2024 57(1):57-71.
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  Data: Routledge. Available from: Taylor & Francis, Ltd. 530 Walnut Street Suite 850, Philadelphia, PA 19106. Tel: 800-354-1420; Tel: 215-625-8900; Fax: 215-207-0050; Web site: http://www.tandf.co.uk/journals
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  Data: Psychometric characteristics of CESD-R scores were explored on a sample of 966 undergraduate students. Internal consistency ([alpha] = 0.92), external convergent and discriminant validity, and response bias were adequate to excellent. Strong measurement invariance was evident for gender and race comparisons, and the unidimensional model fit the data best.
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