Are the PHQ-9 and GAD-7 Suitable for Use in India? A Psychometric Analysis

BackgroundCross-cultural evidence on the factorial structure and invariance of the PHQ-9 and the GAD-7 is lacking for South Asia. Recommendations on the use of unit-weighted scores of these scales (the sum of items’ scores) are not well-founded. This study aims to address these contextual and methodological gaps using data from a rural Indian population.MethodsThe study surveyed 1,209 participants of the Kerala Diabetes Prevention Program aged 30–60 years (n at risk of diabetes = 1,007 and n with diabetes = 202). 1,007 participants were surveyed over 2 years using the PHQ-9 and the GAD-7. Bifactor-(S – 1) modeling and multigroup confirmatory factor analysis were used.ResultsFactor analysis supported the existence of a somatic and cognitive/affective subcomponent for both scales, but less explicitly for the GAD-7. Hierarchical omega values were 0.72 for the PHQ-9 and 0.76 for the GAD-7. Both scales showed full scalar invariance and full or partial residual invariance across age, gender, education, status of diabetes and over time. Effect sizes between categories measured by unit-weighted scores versus latent means followed a similar trend but were systematically higher for the latent means. For both disorders, female gender and lower education were associated with higher symptom severity scores, which corresponds with regional and global trends.ConclusionsFor both scales, psychometric properties were comparable to studies in western settings. Distinct clinical profiles (somatic-cognitive) were supported for depression, and to a lesser extent for anxiety. Unit-weighted scores of the full scales should be used with caution, while scoring subscales is not recommended. The stability of these scales supports their use and allows for meaningful comparison across tested subgroups.Clinical Trial RegistrationAustralia and New Zealand Clinical Trials Registry: ACTRN12611000262909http://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=336603&isReview=true.

Age and gender differences in socially aversive (“dark”) personality traits

The strong overlap of personality traits discussed under the label of “dark personality” (e.g., psychopathy, spitefulness, moral disengagement) endorses a common framework for socially aversive traits over and beyond the dark triad. Despite the rapidly growing research on socially aversive traits, there is a lack of studies addressing age-associated differences in these traits. In the present study ( N = 12,501), we investigated the structure of the D Factor of Personality across age and gender using local structural equation modeling, thereby expressing the model parameters as a quasi-continuous, nonparametric function of age. Specifically, we evaluated loadings, reliabilities, factor (co-)variances, and means across 35 locally weighted age groups (from 20 to 54 years), separately for females and males. Results indicated that measurement models were highly stable, thereby supporting the conceptualization of the D factor independent of age and gender. Men exhibited uniformly higher latent means than females and all latent means decreased with increasing age. Overall, D and its themes were invariant across age and gender. Therefore, future studies can meaningfully pursue causes of mean differences across age and between genders.

Assessing the Measurement Invariance of the Gratitude Questionnaire–5 in Chinese and American Adolescents

Given the possibility of cultural differences in the meaning and levels of gratitude among children, we evaluated the measurement invariance of the Gratitude Questionnaire–5 (GQ–5) and differences in latent means across adolescents from two distinct cultures, China and America. Data were obtained from 1,991 Chinese and 1,685 American adolescents. Confirmatory factor analysis and multigroup confirmatory factor analysis were performed to examine the factor structure and the measurement equivalence across Chinese and American adolescents. The Cronbach’s alpha and Item-total Correlations of the GQ–5 were also evaluated. Results of confirmatory factor analyses provided support for the expected one-factor structure. Also, a series of multi-group confirmatory factor analyses supported full configural invariance, full metric invariance, and partial scalar invariance between the two groups. Furthermore, the findings suggested that the GQ–5 is suitable for conducting mean level comparisons. The subsequent comparison of latent means revealed that the Chinese adolescents reported significantly lower gratitude than American adolescents.

Finding clusters of groups with measurement invariance: Unraveling intercept non-invariance with mixture multigroup factor analysis

Comparisons of latent constructs across groups are ubiquitous in behavioral research and, nowadays, often numerous groups are involved. Measurement invariance of the constructs across the groups is imperative for valid comparisons and can be tested by multigroup factor analysis. For many groups, metric invariance (invariant factor loadings) often holds, whereas scalar invariance (invariant intercepts) is rarely supported. Scalar invariance is a prerequisite for comparing latent means, however. One may inspect group-specific intercepts to pinpoint non-invariances, but this is a daunting task in case of many groups. This paper presents mixture multigroup factor analysis (MMG-FA) for clustering groups based on their intercepts. Clusters of groups with scalar invariance are obtained by imposing cluster-specific intercepts and invariant loadings whereas unique variances, factor means and factor (co)variances can differ between groups. Thus, MMG-FA ties down the number of intercepts to inspect and generates clusters of groups wherein latent means can be validly compared.

Finding clusters of groups with measurement invariance: Unraveling intercept non-invariance with mixture multigroup factor analysis

Comparisons of latent constructs across groups are ubiquitous in behavioral research and, nowadays, often numerous groups are involved. Measurement invariance of the constructs across the groups is imperative for valid comparisons and can be tested by multigroup factor analysis. For many groups, metric invariance (invariant factor loadings) often holds, whereas scalar invariance (invariant intercepts) is rarely supported. Scalar invariance is a prerequisite for comparing latent means, however. One may inspect group-specific intercepts to pinpoint non-invariances, but this is a daunting task in case of many groups. This paper presents mixture multigroup factor analysis (MMG-FA) for clustering groups based on their intercepts. Clusters of groups with scalar invariance are obtained by imposing cluster-specific intercepts and invariant loadings whereas unique variances, factor means and factor (co)variances can differ between groups. Thus, MMG-FA ties down the number of intercepts to inspect and generates clusters of groups wherein latent means can be validly compared.

Measurement Invariance Across Age Groups and Over 20 Years’ Time of the Negative and Positive Affect Scale (NAPAS)

The factor structure and measurement invariance across gender of Mroczek’s and Kolarz’s scales of positive affect (PA) and negative affect (NA) have been examined in past studies; however, little is known about the measurement invariance across age groups and over time, which are important psychometric properties for developmental research. The current study sought to fill this gap using the data from the National Survey of Midlife Development in the United States (MIDUS). Multi-group confirmatory factor analysis (CFA) was used to examine increasing levels of measurement invariance across gender and age groups. Longitudinal CFA was also used to test measurement invariance over three time points using the data from MIDUS 1 ( N = 3,748), MIDUS 2 ( N = 2,257), and MIDUS 3 ( N = 1,414). Results supported full scalar invariance across gender, age groups, and over time. The latent means for NA were significantly different between men and women at time 1 and 2, but not at time 3; the latent means for both PA and NA were also different across age groups. There were no significant differences for PA and only trivial differences for NA over time within individuals. Implications of these results for longitudinal research are discussed.

Spanish Validation of the Child and Adolescent Perfectionism Scale: Factorial Invariance and Latent Means Differences across Sex and Age

The present study analyzed the psychometric properties of a Spanish translation of the child–adolescent perfectionism scale (CAPS-S), as well as its factorial invariance and latent means differences across sex and age. A sample of 1809 Spanish students of Primary Education, aged between 8 and 11 (Mage = 9.53, SD = 1.11), was used. Confirmatory factor analyses and multigroup confirmatory factor analyses were applied to examine the factor structure of the CAPS-S. The results revealed that a model made up of 13 items structured in 3 factors—Self-Oriented Perfectionism-Striving (SOP-Striving), Self-Oriented Perfectionism-Critical (SOP-Critical), and Socially Prescribed Perfectionism (SPP)—showed a better fit than any of the previously tested models, and it was invariant across sex and age. SOP-Striving did not significantly correlate with school anxiety and aggression, whereas significant and positive correlations were found in the case of SOP-Critical and SPP. The levels of reliability and stability of the scale were ω = 0.91, 0.74, 0.73, and 0.80, and rxx = 0.73, 0.62, 0.73, and 0.74, for the total CAPS-S and for the SOP-Striving, SOP-Critical, and SPP dimensions, respectively. Analysis of latent means differences revealed that boys scored significantly higher than girls in SOP-Critical. The 9-year-olds scored significantly lower in SPP than their 8-year-old peers. Conversely, 11-year-olds scored higher in SOP-Critical than 8-year-olds. In addition, 10- and 11-year-olds scored higher than their 9-year-old peers. The CAPS-S presented in this research is a reliable and valid instrument to assess perfectionism in Spanish child population.