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BACKGROUND: Obsessive-compulsive disorder (OCD) is an often disabling and chronic condition that is normally assessed using diagnostic interviews or lengthy self-report questionnaires. This makes routine screening in general health settings impractical, and as a result OCD is often under-(or mis-)recognized. The present study reports on the development of an ultra-brief version of the Obsessive-Compulsive Inventory-Child Version (OCI-CV) which may be administered routinely as a screener for pediatric OCD. METHOD: A total of 489 youth diagnosed with OCD, 259 non-clinical controls, and 299 youth with other disorders completed the OCI-CV and other indices of psychopathology. Using item analyses, we extracted five items and examined the measure’s factor structure, sensitivity and specificity, and convergent and discriminant validity. RESULTS: We extracted five items that assess different dimensions of OCD (washing, checking, ordering, obsessing, neutralizing/counting), termed the OCI-CV-5. Results revealed that the measure possesses good to excellent psychometric properties, and a cutoff off (≥2) yielded optimal sensitivity and specificity. LIMITATIONS: Participants were predominantly White. In addition, more research is needed to examine the OCI-CV-5’s test-retest reliability and sensitivity to treatment. CONCLUSIONS: The OCI-CV-5 shows promise as an ultra-brief self-report screener for identifying OCD in youth when in-depth assessment is unfeasible.

Adopting the constructs of exposure, reactivity, and recovery, from stress and coping frameworks, this study investigated three models of discrimination, adjustment, and ethnic/racial identity among 76 African American, 145 Asian American, and 129 Latinx adolescents who were majority United States-born. The sample includes adolescents sampled from public schools in a large urban area in the northeastern United States, 62% female and with an average age of 14.3 years. Multilevel analyses support an exposure effect (Model 1) where a higher level of ethnic/racial identity (ERI) commitment was associated with a 28% reduction in experiencing discrimination stress. The negative effects of discrimination were attenuated by ERI commitment and centrality/private regard, while effects were exacerbated by ERI exploration (Model 2). Two approaches investigated next-day and longer-term recovery from discrimination (Model 3). With the exception of positive mood and anxiety, the data support recovery from discrimination stress. Discrimination is discussed in the development and maintenance of health disparities. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Background Hypertension and HIV are salient risk factors for cerebral small vessel disease and neurocognitive impairment, yet the effects of hypertension on neurocognitive performance in persons living with HIV remain poorly understood. This is the first study to examine the longitudinal associations between blood pressure, hypertension, and pulse pressure with neurocognitive performance in persons living with HIV. Setting New York City. Methods Analysis of medical, neurocognitive, and virologic data from 485 HIV+ participants collected by the Manhattan HIV Brain Bank, a prospective, observational, longitudinal study of neuroHIV. A series of multilevel linear growth curve models with random intercepts and slopes were estimated for blood pressure, hypertension status, and pulse pressure to predict change in neurocognitive performance. Results The baseline prevalence of hypertension was 23%. Longitudinal change in diastolic and systolic pressure were associated with 10.5-second and 4-second increase in Grooved Pegboard Test non-dominant hand performance, respectively. Longitudinal change in diastolic blood pressure was also associated a .3-point decline in correct categories and 3-point increase in perseverative responses and total errors on the Wisconsin Card Sorting Test. Increasing odds of prevalent and/or incident hypertension was associated with a .1-point decrease in correct categories and a .8-point increase in total errors on the Wisconsin Card Sorting Test. There was no association between pulse pressure and neurocognitive performance. Conclusions Results indicate linear longitudinal relations for blood pressure and hypertension with poorer neurocognitive test performance, particularly in psychomotor and executive functions in persons with HIV.

Unfair treatment based on race is an unfortunate reality. While there is increasing interest in mapping the daily and longer-term impact of discrimination in psychology, studies that examine the psychometric properties of indicators spanning these timeframes are limited. Item response analysis examined the measurement characteristics of two daily measures of ethnic/racial discrimination: (a) the six-item Racial/Ethnic Discrimination Index (REDI), and (b) the modified five-item Everyday Discrimination Scale (EDS; Williams et al., Journal of Health Psychology, 1997, 2, 335). This study investigated whether the two scales can be appropriately adapted to access adolescents' daily-level ethnic/racial discrimination experiences. Both measures were administered for 14 consecutive days in a sample of 350 adolescents attending public schools in a large, urban area. Results suggest that the REDI has high loading and high difficulty. All REDI items functioned similarly at daily and person levels, suggesting that any single REDI item measured on a single day is sufficient for measuring daily ethnic/racial discrimination experiences. The EDS also shows high loading and high difficulty. However, EDS items functioned differently at the daily and person levels. REDI items were invariant across gender and race/ethnicity (African Americans, Asians, and Latinx). Recommendations for measuring daily ethnic/racial discrimination are discussed. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

OBJECTIVE: In patients with cancer across the illness trajectory, treatment decisions are often influenced by one’s perception of their prognosis (i.e., curability of disease, life expectancy, quality of life). However, research on how patients understand their prognosis (i.e., prognostic understanding) has been limited by simplistic measurement tools that fail to capture the complexity of the construct. This study describes the initial development of a measure of prognostic understanding: the Prognostic Understanding Perceptions Scale (PUPS) for use in patients with advanced cancer. METHOD: An initial pool of 16 candidate items were developed through semi-structured interviews with 15 experts (oncology, psycho-oncology and palliative care professionals) and 30 advanced cancer patients. We investigated the dimensionality, internal item structure, item difficulty and item discrimination of the item pool using exploratory factor analysis (EFA), classical test theory (CTT) and item response theory (IRT) analyses. Convergent and divergent validity were based on correlations between PUPS, terminal illness acknowledgement, self-report measures of depression, anxiety, hopelessness, and death acceptance. RESULTS: The final measure was comprised of nine items encompassing three factors (perceived curability, illness trajectory, treatment options), yielding strong psychometric properties. CONCLUSION: These results provide preliminarily support for PUPS as a multifaceted measure of prognostic understanding developed for use in patients with advanced cancer. Preliminary findings also highlight the potential utility of the PUPS for clinical settings, as a means of enhancing communication between patients and physicians.

Latent moderated structural equations (LMS) is a popular method in estimating latent interaction effects. Mplus has implemented a variant of LMS (LMS-cat) that uses categorical confirmatory factor ...

Extensive literature highlights positive outcomes experienced by students whose parents and teachers have strong relationships, but less is known about the factors that influence parent-tea...

Abstract. Accurate measurement of depressive symptoms in the cancer setting is critical for ensuring optimal quality of life and patient outcomes. The present study compared the one-factor, correlated two-factor, correlated four-factor, and second-order factor models of the Center for Epidemiologic Studies Depression Scale (CES-D), a commonly used measure in oncology settings. Given the importance of adequate psychometric performance of the CES-D across age groups, a second aim was to examine measurement invariance between younger and older adults with cancer. Participants ( N = 663) were recruited from outpatient clinics at a large cancer center. Over one-fourth of the sample endorsed clinically significant depressive symptoms (25.9%, n = 165). Confirmatory factor analysis of the CES-D supported the hypothesized correlated four-factor model as the best fit. The second-order factor also demonstrated good fit, but interpretations of the factors were more complex. Factors were highly correlated (range = .38–.91). There was also support for full scalar invariance between age groups, suggesting that regardless of age, respondents endorse the same response category for the same level of the latent trait (i.e., depression) on the CES-D. Taken together, the results suggest that the CES-D is a viable depression screening option for oncology settings and does not require scoring adjustments for respondent age.

BACKGROUND: The Obsessive-Compulsive Inventory-Children’s Version (OCI-CV) was developed to assess obsessive-compulsive symptoms in youth. Recent changes in the Diagnostic and Statistical Manual (DSM-5) exclude hoarding from inclusion in the diagnosis of obsessive-compulsive disorder (OCD). Accordingly, the present study examined the reliability, validity, factorial structure, and diagnostic sensitivity of a revised version of the scale – the OCI-CV-R– that excludes items assessing hoarding. METHODS: Participant were 1047 youth, including 489 meeting DSM criteria for primary OCD, 298 clinical controls, and 260 nonclinical controls, who completed the OCI-CV and measures of obsessive-compulsive symptom severity, depression, and anxiety at various treatment and research centers. RESULTS: Findings support a five-factor structure (doubting/checking, obsessing, washing, ordering, and neutralizing), with a higher order factor. Factorial invariance was found for older (12 to 17 years) and younger (7 to 11 years) children. Internal consistency of the OCI-CV-R was acceptable, and discriminant and convergent validity were adequate and akin to that of its progenitor. Diagnostic sensitivity and specificity were found for a total score of 8 and higher. CONCLUSION: It is recommended that the OCI-CV-R replace the former version, and that this measure serve as part of a comprehensive clinical assessment of youth with OCD. Recommendations for further research with ethnically and racially diverse samples, as well as the need to establish benchmark scores are discussed.

Objectives This study examined the measurement invariance and longitudinal trajectories of multidimensional self-perceptions of aging (SPA) and factors that predict between-person variability in the level and change of SPA in middle-aged and older adults. Method Data were drawn from the German Ageing Survey spanning four waves, covering a 15-year period. Multidimensional SPA was assessed with the Personal Experience of Aging Scale, consisting of three dimensions, physical decline, social loss, and continuous growth. Results The measurement invariance models across age groups (middle-aged versus older adults) and across time showed a good fit after allowing one item to vary at metric and/or scalar levels. Growth curve models showed only minor declining trajectories in two of the three dimensions of SPA, social loss and continuous growth dimensions, toward more negative views. Participants with poor resources in general were more likely to have negative SPA across all three dimensions. The protective effect of having a spouse was observed on only the social dimension of SPA, supporting a domain-specific effect of having a spouse. Discussion The study demonstrates the usefulness of a multidimensional understanding of SPA and recognizes the need for identifying different factors that may promote positive perceptions on aging in different dimensions of life.

Methods to handle ordered-categorical indicators in latent variable interactions have been developed, yet they have not been widely applied. This article compares the performance of two popular latent variable interaction modeling approaches in handling ordered-categorical indicators: unconstrained product indicator (UPI) and latent moderated structural equations (LMS). We conducted a simulation study across sample sizes, indicators’ distributions and category conditions. We also studied four strategies to create sets of product indicators for UPI. Results supported using a parceling strategy to create product indicators in the UPI approach or using the LMS approach when the categorical indicators are symmetrically distributed. We applied these models to study the interaction effect between third- to fifth-grade students’ social skills improvement and teacher–student closeness on their state English language arts test scores.

This study examines how everyday discrimination is associated with 6-day trajectories of sleep/wake problems, operationalized as sleep disturbance and daytime dysfunction, among 350 diverse adolescents (Mage = 14.27, SD = 0.61, 69% female; 22% African American, 41% Asian American, 37% Latinx; 24% multiethnic/racial; across participating schools, 72% of students eligible for free/reduced price lunch) in the Northeastern United States. Adolescents encountering discrimination experienced changes in sleep/wake problem trajectories (i.e., significant increases in same-day sleep/wake problems), whereas adolescents reporting no discrimination experienced no changes in trajectories (Cohen's ds = .51-.55). Multiethnic/racial (compared to monoethnic/racial) adolescents experiencing everyday discrimination reported greater same-day sleep/wake problems, yet steeper decreases in sleep/wake problems suggesting stronger impact coupled with faster return to baseline levels.

The aging of America will include a significant increase in the number of older patients with cancer, many of whom will experience significant depressive symptoms. Although geriatric depression is a well-studied construct, its symptom presentation in the context of cancer is less clear. Latent profile analysis was conducted on depressive symptoms in younger (40-64 years) and older (≥65 years) patients with cancer ( N = 636). The sample was clinically heterogeneous (i.e., included all stages, dominated by advanced stage disease). Participants completed questionnaires including the Center for Epidemiological Studies Depression Scale, which was used for the latent profile analysis. A four-class pattern was supported for each age group. However, the four-class pattern was significantly different between the younger and older groups in terms of the item means within each corresponding latent class; differences were primarily driven by severity such that across classes, older adults endorsed milder symptoms. An unexpected measurement issue was uncovered regarding reverse-coded items, suggesting that they may generate unreliable scores on the Center for Epidemiological Studies Depression Scale for a significant subset of patients. The results indicate that cancer clinicians can expect to see depressive symptoms along a continuum of severity for patients of any age, with less severe symptoms among older patients.

Depression remains poorly managed in oncology, in part because of the difficulty of reliably screening and assessing for depression in the context of medical illness. Whether somatic items really skew the ability to identify "true" depression, or represent meaningful indicators of depression, remains to be determined. This study utilized item response theory (IRT) to compare the performance of traditional depression criteria with Endicott's substitutive criteria (ESC; tearfulness or depressed appearance; social withdrawal; brooding; cannot be cheered up). The Patient Health Questionnaire (PHQ-9), ESC, and Center for Epidemiologic Studies Depression Scale (CES-D) were administered to 558 outpatients with cancer. IRT models were utilized to evaluate global and item fit for traditional PHQ-9 items compared with a modified version replacing the 4 somatic items with ESC. The modified PHQ-9 ESC scale was the best fit using a partial credit model; model fit was improved after collapsing the middle 2 response categories and removing psychomotor agitation/retardation. This improved model showed satisfactory scale precision and internal consistency, and was free from differential item functioning for gender, age, and race. Concurrent and criterion validity were supported. Thus, as many have speculated, utilizing the ESC may result in more accurate identification of depressive symptoms in oncology. Depressed mood, anhedonia, and suicidal ideation retained their expected properties in the modified scale, indicating that the traditional underlying syndrome of depression likely remains the same, but the ESC may provide more specificity when assessing patients with cancer. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

This study employs slope-as-mediator techniques to explore how the daily association between ethnic/racial discrimination and sleep disturbances serves as an intermediary link between ethnic/racial identity (ERI) and psychological adjustment. In a diverse sample of 264 adolescents (Mage = 14.3 years old, 70% female, 76% United States born, 25% African American, 32% Asian American, 43% Latinx), discrimination was associated with sleep disturbance. Furthermore, ERI commitment buffered the impact of discrimination on sleep, whereas ERI exploration exacerbated the impact of discrimination. Finally, the daily level association between discrimination and sleep (i.e., daily slope) mediated the association between ERI and adolescent adjustment. Substantive links between discrimination and sleep are discussed as well as broader applications of slope-as-mediator techniques.

This study investigates the same-day associations between discrimination and sleep among 350 adolescents ages 13?15 (M = 14.29, SD = 0.65; Asian = 41%, Black = 22%, Latinx = 37%). Assessing sleep duration, sleep onset latency, and wake minutes after sleep onset using wrist actigraphy, Black adolescents slept 35 min less than Asian and 36 min less than Latinx youth. Black adolescents suffered the most wake minutes after sleep onset, followed by Latinx and Asian youth. Latinx youth reported the highest levels of sleep disturbance, whereas Asian youth reported the highest levels of daytime dysfunction. Daily discrimination was associated with lower levels of same-night sleep onset latency, more sleep disturbance, more next-day daytime dysfunction, and higher next-day daytime sleepiness.

Vandecandelaere, Vansteelandt, De Fraine, and Van Damme (this issue) described marginal structural modeling (MSM) and used it to estimate the effects of a time-varying intervention, retention (holding back) in school grades, on students' math achievement. This commentary supplements Vandecandelaere et al. (this issue) and discusses several topics in retention studies and MSM. First, we discuss the importance of equating time-varying confounders in retention studies. Second, we discuss same-grade and same-age comparisons in retention studies. Third, we discuss one important section in the authors' overview of MSM: why standard methods (e.g., ANCOVA, propensity score analysis) cannot properly adjust for time-varying confounders. Finally, using the grade retention analyses in Vandecandelaere et al. (this issue) as an example, we provide our insights on four aspects of MSM: (a) covariate selection, (b) estimation of weights

This study reports on the findings from a 6-year follow-up of a randomized trial of the Family Bereavement Program (FBP) on the outcomes for spousally bereaved parents. Spousally bereaved parents (N= 131) participated in the trial in which they were randomly assigned to receive the FBP (N= 72) or literature control (N= 59). Parents were assessed at four time points: pretest, posttest, and 11-month and 6-year follow-up. They reported on mental health problems, grief, and parenting at all four time periods. At the 6-year follow-up, parents reported on additional measures of persistent complex bereavement disorder, alcohol abuse problems, and coping efficacy. Bereaved parents in the FBP as compared to those in the literature control had lower levels of symptoms of depression, general psychiatric distress, prolonged grief, and alcohol problems, and higher coping efficacy (for mothers) at the 6-year follow-up. Multiple characteristics of the parent (e.g., gender, age, and baseline mental health problems) and of the spousal death (e.g., cause of death) were tested as moderators of program effects on each outcome, but only 3 of 45 tests of moderation were significant. Latent growth modeling found that the effects of the FBP on depression, psychiatric distress, and grief occurred immediately following program participation and were maintained over 6 years. Mediation analysis found that improvement in positive parenting partially mediated program effects to reduce depression and psychiatric distress, but had an indirect effect to higher levels of grief at the 6-year follow-up. Mediation analysis also found that improved parenting at the 6-year follow-up was partially mediated by program effects to reduce depression and that program effects to increase coping efficacy at the 6-year follow-up was partially mediated through reduced depression and grief and improved parenting. FBP reduced mental health problems, prolonged grief, and alcohol abuse, and increased coping efficacy of spousally bereaved parents 6 years later. Mediation pathways for program effects differed across outcomes at the 6-year follow-up.

Supplemental material, Online_supplement-R1 for Latent Variable Interactions With Ordered-Categorical Indicators: Comparisons of Unconstrained Product Indicator and Latent Moderated Structural Equations Approaches by Ezgi Aytürk, Heining Cham, Patricia A. Jennings and Joshua L. Brown in Educational and Psychological Measurement

Previous research has consistently shown that subjective aging, defined as how individuals perceive their own aging, has long-term effects on various indicators of developmental outcomes, such as health and longevity. In the recent literature, self-perceptions of aging (SPAs) have been conceptualized and assessed in a multidimensional way, recognizing that individuals’ subjective experiences of aging involve both gains and losses. The current study examined the effects of multidimensional SPAs on longevity over a 15-year period. Data came from the four waves of the German Ageing Survey (1996, 2002, 2008, 2011), a nationally representative survey of community-dwelling German adults over 40 years old. Multidimensional SPAs were assessed with the Personal Experience of Aging scale (Steverink et al., 2001), consisting of three dimensions: physical decline, social loss, and continuous growth. After we controlled for variables regarding sociodemographics, health, and social resources, our Cox hazard regression analyses indicated that a higher level of the SPA dimension of continuous growth was associated with a decreased risk of mortality, whereas the physical decline and social loss dimensions were not associated with an increased mortality risk. Consistent with previous research, the current findings support the association between SPAs and longevity; in particular, it is noteworthy that the positive dimension of SPAs had a significant effect on longevity among three dimensions. The findings also support the idea that different dimensions of SPAs contribute to developmental outcomes differently, providing further evidence regarding the usefulness of a multidimensional understanding of subjective aging experiences.

Using longitudinal, experience sampling data from 214 ethnic/racial minority adolescents (Wave 1 Mean age = 15.24), the present study investigated how the longitudinal effect of parental cultural socialization on adolescent private regard was mediated through various daily pathways and novel constructs. Both the mean levels and variability of adolescents’ ethnic feelings (i.e. private regard) and social interactions (i.e. intragroup contact) in daily situations, as well as the situational association between intragroup contact and private regard, emerged as mediators. Greater cultural socialization promoted greater and more stable ethnic feelings and interactions, as well as their situational association, all of which promoted private regard over time. This study provides a framework to explore how development occurs in daily lives.

Objectives Meaning-Centered Group Psychotherapy (MCGP) has been demonstrated to be an effective method for improving advanced cancer patients’ quality of life and reducing their depression, hopelessness, and desire for hastened death. To further understand MCGP, this study examined the mechanisms of change in MCGP on these outcomes via advanced cancer patients’ changes of sense of meaning and peace in life. Methods The sample data were from two randomized control trials that compared MCGP (n = 124) to supportive group psychotherapy (n = 94). Mediation effects of treatment status on outcomes (two-month after completion of treatment) via patients’ change of sense of meaning and peace (post-treatment minus pre-treatment) were tested. The outcome variables used in these analyses were quality-of-life, depression, hopelessness and desire for hastened death. Results Significant mediation effects via change of sense of meaning and peace on these outcomes were found. Consistent results were found using intention-to-treated statuses. Weaker, but still significant mediation effects via change of sense of faith on these outcomes were also found. Conclusions Results supported the hypotheses that improvement due to MCGP is mediated by advanced cancer patients’ enhanced sense of meaning. These findings highlight the importance of interventions focused on enhancing sense of meaning, as this appears to be a viable route to improve quality of life and decrease psychological distress among patients with advanced cancer.

Very little is known about the interrelationships among social stigma, depression, and HIV-status among injection drug users (IDUs) in China. To better understand these relationships, the authors assessed depression, perceived social stigma, and HIV status in a sample of 45 IDUs in a high-risk region of China. Data were analyzed using analyses of covariance and pair-wise correlations. Perceived social stigma was elevated among IDUs and significantly related to depression; IDUs report comparable levels of depression regardless of HIV serostatus. Implications for further research and study limitations are discussed.

The Adolescent Motivation for Educational Attainment Questionnaire is a 32-item questionnaire (we drew 20 items from 3 subscales of the Educational Motivation Questionnaire; Murdock, 1999) that was developed to measure multiple potential dimensions of adolescents’ motivation to complete high school and enroll in post-secondary education, including competence and effort beliefs; perceived value of education; and peer, teacher, and parent support for educational attainment. We assessed a multiethnic sample (N = 569) of low-achieving students who started 1st grade together in 1 urban and 2 small city school districts. Participants were assessed over 2 consecutive years (Grades 8 and 9 given prior grade retention, or Grades 9 and 10 if not retained). Exploratory factor analyses identified 4 correlated dimensions underlying the questionnaire responses. Subsequent confirmatory factor analyses provided support for a bifactor model, which includes a general factor of students’ basic educational motivation, and specific factors of (a) teacher educational expectations, (b) peer aspirations, and (c) value of education. Measurement invariance of the bifactor model was established across students’ gender and ethnicity (Caucasian, African American, and Hispanic) and year of testing. Criterion-related validity of the general and specific factors with students’ school belonging, student–teacher warmth and conflict, disciplinary practices, letter grade, conduct problems, and behavioral engagement was examined. Practical implications of the measure are discussed.

The existing missing data literature does not provide a clear prescription for estimating interaction effects with missing data, particularly when the interaction involves a pair of continuous variables. In this article, we describe maximum likelihood and multiple imputation procedures for this common analysis problem. We outline 3 latent variable model specifications for interaction analyses with missing data. These models apply procedures from the latent variable interaction literature to analyses with a single indicator per construct (e.g., a regression analysis with scale scores). We also discuss multiple imputation for interaction effects, emphasizing an approach that applies standard imputation procedures to the product of 2 raw score predictors. We thoroughly describe the process of probing interaction effects with maximum likelihood and multiple imputation. For both missing data handling techniques, we outline centering and transformation strategies that researchers can implement in popular software packages, and we use a series of real data analyses to illustrate these methods. Finally, we use computer simulations to evaluate the performance of the proposed techniques.

Early-maturing girls are at risk for internalizing and externalizing problems. Research concerning pubertal timing and mental health among Mexican Americans or the influence of parenting behaviors on these relations has been scarce. This study addressed these gaps. This was a prospective examination of 362 Mexican-origin girls and their mothers in 3 waves of data. Measures included girls' self-report of pubertal development and girls' and mothers' report of maternal harsh parenting and daughters' mental health. Using structural equation modeling, we examined whether pubertal timing in 5th grade predicted girls' internalizing and externalizing outcomes in 10th grade. We also examined the mediating and moderating effects of harsh parenting on the relations between pubertal timing and internalizing and externalizing behaviors, as well as the influence of mothers' and daughters' nativity on these relations. Results differed depending on reporter and maternal nativity. Using daughters' report, we found that Mexican American mothers' harsh parenting acted as a moderator. At high levels of harsh parenting, early pubertal timing predicted higher externalizing scores, while at low levels of harsh parenting, early timing predicted lower externalizing scores. For Mexican immigrant mothers, harsh parenting mediated the effects of pubertal timing on girls' internalizing and externalizing problems. There were no significant pubertal effects for mothers' report. Findings suggest that maternal harsh parenting plays a key role in the relations between early pubertal timing and behavioral and emotional outcomes among Mexican-origin girls.

Despite the increasing popularity of incorporating salivary cortisol measurement into health and social science research, relatively little empirical work has been conducted on the number of saliva samples across the day required to capture key features of the diurnal cortisol rhythm, such as the diurnal cortisol slope, the area under the curve (AUC), and the cortisol awakening response (CAR). The primary purpose of this study is to compare slope, AUC, and CAR measures obtained from an intensive sampling protocol with estimates from less intensive protocols, to identify sampling protocols with minimal participant burden that still provide reasonably accurate assessment of each of these measures. Twenty-four healthy adults provided samples four times in the first hour awake, and then every hour throughout the rest of the day until bedtime (M = 17.8 samples/day; SD = 2.0), over two consecutive days (N = 862 total samples). We compared measures calculated from this maximum intensity protocol to measures calculated from two to six sampling points per day. Overall, results show that salivary cortisol protocols with two fixed samples (waking and bedtime) and three additional daily samples, closely approximates the full cortisol decline (slope). Abbreviated sampling protocols of total cortisol exposure across the day (AUC), however, were not well approximated by reduced sampling protocols. CAR measures based on only two samples, including waking cortisol and a second sample measured at a fixed time point between 30 and 60 min after waking, provided a measure of the CAR that closely approximated CAR measures obtained from 3 or 4 sampling points.

Propensity score analysis is a method that equates treatment and control groups on a comprehensive set of measured confounders in observational (nonrandomized) studies. A successful propensity score analysis reduces bias in the estimate of the average treatment effect in a nonrandomized study, making the estimate more comparable with that obtained from a randomized experiment. This article reviews and discusses an important practical issue in propensity analysis, in which the baseline covariates (potential confounders) and the outcome have missing values (incompletely observed). We review the statistical theory of propensity score analysis and estimation methods for propensity scores with incompletely observed covariates. Traditional logistic regression and modern machine learning methods (e.g., random forests, generalized boosted modeling) as estimation methods for incompletely observed covariates are reviewed. Balance diagnostics and equating methods for incompletely observed covariates are briefly described. Using an empirical example, the propensity score estimation methods for incompletely observed covariates are illustrated and compared. (PsycINFO Database Record

Interaction and quadratic effects in latent variable models have to date only rarely been tested in practice. Traditional product indicator approaches need to create product indicators (e.g., x 1 2, x 1 x 4) to serve as indicators of each nonlinear latent construct. These approaches require the use of complex nonlinear constraints and additional model specifications and do not directly address the nonnormal distribution of the product terms. In contrast, recently developed, easy-to-use distribution analytic approaches do not use product indicators, but rather directly model the nonlinear multivariate distribution of the measured indicators. This article outlines the theoretical properties of the distribution analytic Latent Moderated Structural Equations (LMS; Klein & Moosbrugger, 2000) and Quasi-Maximum Likelihood (QML; Klein & Muthen, 2007) estimators. It compares the properties of LMS and QML to those of the product indicator approaches. A small simulation study compares the two approaches and illustra...

Traditional statistical analyses can be compromised when data are collected from groups or multiple observations are collected from individuals. We present an introduction to multilevel models designed to address dependency in data. We review current use of multilevel modeling in 3 personality journals showing use concentrated in the 2 areas of experience sampling and longitudinal growth. Using an empirical example, we illustrate specification and interpretation of the results of series of models as predictor variables are introduced at Levels 1 and 2. Attention is given to possible trends and cycles in longitudinal data and to different forms of centering. We consider issues that may arise in estimation, model comparison, model evaluation, and data evaluation (outliers), highlighting similarities to and differences from standard regression approaches. Finally, we consider newer developments, including 3-level models, cross-classified models, nonstandard (limited) dependent variables, multilevel structural equation modeling, and nonlinear growth. Multilevel approaches both address traditional problems of dependency in data and provide personality researchers with the opportunity to ask new questions of their data.

Researchers have developed missing data handling techniques for estimating interaction effects in multiple regression. Extending to latent variable interactions, we investigated full information maximum likelihood (FIML) estimation to handle incompletely observed indicators for product indicator (PI) and latent moderated structural equations (LMS) methods. Drawing on the analytic work on missing data handling techniques in multiple regression with interaction effects, we compared the performance of FIML for PI and LMS analytically. We performed a simulation study to compare FIML for PI and LMS. We recommend using FIML for LMS when the indicators are missing completely at random (MCAR) or missing at random (MAR) and when they are normally distributed. FIML for LMS produces unbiased parameter estimates with small variances, correct Type I error rates, and high statistical power of interaction effects. We illustrated the use of these methods by analyzing the interaction effect between advanced cancer patients' depression and change of inner peace well-being on future hopelessness levels.

This study aims at identifying the association between perfectionism, academic burnout and engagement in college students. A dual-process model was tested in which negative perfectionism (doubts about actions, concerns over mistakes, et al.) were related to burnout symptoms while positive perfectionism (personal standards and organization) to engagement. A sample of Chinese undergraduates (N = 482) completed a battery of questionnaires including the Frost Multidimensional Perfectionism Scale (FMPS), the Maslach Burnout Inventory-Student Survey (MBI-SS), and the Utrecht Work Engagement Scale for Students (UWES-S). Results confirm our hypothesis by indicating that: (1) burnout and engagement were moderately and negatively correlated conceptions, with efficacy, the positively worded subscale of MBI, better loaded as an extended engagement dimension; (2) maladaptive aspects of perfectionism were mainly correlated with burnout, whereas positive perfectionism with engagement; (3) the dual-process model fitted well to the data, with cross-links identified. Implication of the current study for school counseling was also proposed.

Participants were 204 academically at-risk Latino students recruited into a study when in first grade and followed for 9 years. Using piecewise latent growth curve analyses, we investigated trajectories of teacher-rated behavioral engagement and student-reported school belonging during elementary school and middle school and the association between trajectories and enrollment in bilingual education classes in elementary school and a change in school ethnic congruence across the transition to middle school. Overall, students experienced a drop in school belonging and behavioral engagement across the transition. A moderating effect of ethnic congruence on bilingual enrollment was found. A decline in ethnic congruence was associated with more positive trajectories for students previously enrolled in bilingual classes but more negative trajectories for non-bilingual students.

Propensity scores represent the probability that an individual is assigned to a treatment group given the individual's scores on a set of covariates. Propensity scores are used in nonrandomized studies to equate treatment and control groups on a large number of covariates measured at baseline. Assumptions necessary for propensity score analysis to yield a valid estimate of the causal effect are presented. The five steps involved in a propensity score analysis are reviewed: (a) selecting the covariates, (b) estimating the propensity scores, (c) conditioning on propensity scores, (d) checking covariates for balance, and (e) estimating the causal effect. Complexities including designs with more than two groups, covariates with missing values, multilevel designs, and sensitivity analysis to check for the potential effects of unmeasured covariates are briefly considered. Finally, a short evaluation of the performance of the propensity score approach is presented. Keywords: data analysis in psychology; experimental design; causal inference; cause-and-effect-relationships; matching, propensity score; nonrandomized design; observational study

A propensity score is the probability that a participant is assigned to the treatment group based on a set of baseline covariates. Propensity scores provide an excellent basis for equating treatment groups on a large set of covariates when randomization is not possible. This article provides a nontechnical introduction to propensity scores for clinical researchers. If all important covariates are measured, then methods that equate on propensity scores can achieve balance on a large set of covariates that mimics that achieved by a randomized experiment. We present an illustration of the steps in the construction and checking of propensity scores in a study of the effectiveness of a health coach versus treatment as usual on the well-being of seriously ill individuals. We then consider alternative methods of equating groups on propensity scores and estimating treatment effects including matching, stratification, weighting, and analysis of covariance. We illustrate a sensitivity analysis that can probe for the potential effects of omitted covariates on the estimate of the causal effect. Finally, we briefly consider several practical and theoretical issues in the use of propensity scores in applied settings. Propensity score methods have advantages over alternative approaches to equating groups particularly when the treatment and control groups do not fully overlap, and there are nonlinear relationships between covariates and the outcome.

Little research has examined factors influencing statistical power to detect the correct number of latent classes using latent profile analysis (LPA). This simulation study examined power related to inter-class distance between latent classes given true number of classes, sample size, and number of indicators. Seven model selection methods were evaluated. None had adequate power to select the correct number of classes with a small (Cohen's d = .2) or medium (d = .5) degree of separation. With a very large degree of separation (d = 1.5), the Lo-Mendell-Rubin test (LMR), adjusted LMR, bootstrap likelihood-ratio test, BIC, and sample-size adjusted BIC were good at selecting the correct number of classes. However, with a large degree of separation (d = .8), power depended on number of indicators and sample size. The AIC and entropy poorly selected the correct number of classes, regardless of degree of separation, number of indicators, or sample size.

A Monte Carlo simulation was conducted to investigate the robustness of four latent variable interaction modeling approaches (Constrained Product Indicator [CPI], Generalized Appended Product Indicator [GAPI], Unconstrained Product Indicator [UPI], and Latent Moderated Structural Equations [LMS]) under high degrees of non-normality of the observed exogenous variables. Results showed that the CPI and LMS approaches yielded biased estimates of the interaction effect when the exogenous variables were highly non-normal. When the violation of non-normality was not severe (normal; symmetric with excess kurtosis < 1), the LMS approach yielded the most efficient estimates of the latent interaction effect with the highest statistical power. In highly non-normal conditions, the GAPI and UPI approaches with ML estimation yielded unbiased latent interaction effect estimates, with acceptable actual Type-I error rates for both the Wald and likelihood ratio tests of interaction effect at N ≥ 500. An empirical example illustrated the use of the four approaches in testing a latent variable interaction between academic self-efficacy and positive family role models in the prediction of academic performance.