Redefining effect size interpretations for psychotherapy RCTs in depression.

INTRODUCTION: Effect sizes are often used to interpret the magnitude of a result and in power calculations when planning research studies. However, as effect size interpretations are context-dependent, Jacob Cohen's suggested guidelines for what represents a small, medium, and large effect are unlikely to be suitable for a diverse range of research populations and interventions. Our objective here is to determine empirically-derived effect size thresholds associated with psychotherapy randomized controlled trials (RCTs) in depression by calculating the effect size distribution. METHODS: We extracted effect sizes from 366 RCTs provided by the systematic review of Cuijpers and colleagues (2020) on psychotherapy for depressive disorders across all age groups. The 50th percentile effect size, as this represents a medium effect size, and the 25th (small) and 75th (large) percentile effect sizes were calculated to determine empirically-derived effect size thresholds. RESULTS: After adjusting for publication bias, 0.27, 0.53, and 0.86 represent small, medium, and large effect sizes, respectively, for psychotherapy treatment for depressive disorders. DISCUSSION: The effect size distribution for psychotherapy treatment of depression indicates that observed effect size thresholds are larger than Cohen's suggested effect size thresholds (0.2, 0.5, and 0.8). These results have implications for the interpretation of study effects and the planning of future studies via power analyses, which often use effect size thresholds.

Social jetlag is associated with adverse cardiometabolic latent traits in early adolescence: an observational study.

Introduction: Adolescence is marked by physiological and social changes, such as puberty, increased responsibilities and earlier school start times. This often leads to insufficient sleep on school nights and the need to compensate for lost sleep on weekends, causing a misalignment between biological and social times, which has been termed social jetlag (SJL). SJL triggers stress responses and is associated with several negative health outcomes, including higher cardiometabolic risk in adults. In adolescence, however, SJL has only been consistently related to increases in adiposity but its association with other cardiometabolic indicators are unclear. Method: In a sample of 278 healthy early adolescents (9-15 years of age; 168 girls) we investigated: 1) whether self-reported SJL is associated (using path analyses) with a cardiometabolic status latent factor obtained by testing the best fitting model via confirmatory factor analyses from an initial set of eight indicators [body mass index (BMI), waist/height ratio, triglyceride concentration, diastolic and systolic blood pressure, glycated hemoglobin, total cholesterol/high-density lipoprotein ratio (chol/HDL), and % body fat]; and 2) whether age and/or pubertal status influence the association between SJL and cardiometabolic status. Result: We found that, for girls, higher SJL was associated with more adverse cardiometabolic latent scores (the shared variance of BMI, waist/height ratio, chol/HDL and systolic blood pressure, which had acceptable model fit indices). However, the role of age and pubertal status in this association was unclear for both sexes. Discussion: SJL was associated with adverse cardiometabolic latent traits beyond increases in adiposity in this observational study in early female adolescents. Because disruptions of circadian rhythms are believed to lead to dysregulated energy homeostasis and not vice-versa, our findings highlight the need for sleep interventions in adolescence to help reduce the global burden of cardiometabolic ill health, especially in girls.

Establishing new cutoffs for Cohen's d: An application using known effect sizes from trials for improving sleep quality on composite mental health.

OBJECTIVE: Cohen's d conventional effect size cutoffs [small (0.2), medium (0.5), and large (0.8)] might not be representative of the reported distribution of effect sizes across the different areas of health. Effect size cutoffs might vary not only depending on the area of research, but also on the type of intervention and population. That is, they are context dependent. Therefore, we present strategies to redefine small, medium, and large effect size based on 25, 50, and 75th percentile, respectively. METHODS: We illustrate these techniques applying them to 72 effect sizes, derived from 65 randomized controlled trials described in a recent meta-analysis (10.1016/j.smrv.2021.101556) of improving sleep quality on composite mental health. Such percentiles are equally distanced from the average effect size as suggested by Jacob Cohen and checked for potential attenuation effects (via weight selection model) and outliers (via OutRules). RESULTS: new cutoffs for effect size distribution of -0.177, -0.329, and -0.557, for small, medium, and large effect size were found, respectively. applying Cohen's effect size thresholds (0.2, 0.5, and 0.8) for trials of improving sleep quality on composite mental health might over-estimate effect sizes compared to the real-world context, especially around medium and large effect sizes.

Moving Forward to a World Beyond 0.2, 0.5, and 0.8 Effects Sizes: New Cutoffs for School-Based Anti-Bullying Interventions.

Effect sizes of school-based intervention are commonly described as small to moderate when using Cohen's conventional effect size cutoffs (small [0.2], medium [0.5], and large [0.8]). However, Jacob Cohen's rule of thumb might vary across different areas of research, nature of the intervention, and population, because effect sizes are context-dependent. Moreover, when planning research studies, minimum detectable effect sizes are used to calculate the sample size. In the present study, we investigate whether conventional effect size cutoffs (small [0.2], medium [0.5], and large [0.8]) represent the reported distribution of effect sizes in school-based anti-bullying intervention. To determine small, medium, and large effect sizes, we calculated the effect size distribution (ESD) using 50th percentile effect size (medium effect) of the distributions of effect sizes provided by a recent meta-analysis on school-based anti-bullying intervention. Also, the 25th and 75th percentile effects, as they are equidistant from the average effect size, were used redefining small and large effects, respectively. Results showed that 0.07, 0.123, and 0.227 represent small, medium, and large effect sizes in anti-bullying interventions. Our results indicate that Cohen's suggested effect size thresholds (0.2, 0.5, and 0.8) overestimate effect sizes when compared to the real-world context of school based anti-bullying interventions. We also propose sample sizes required to reliably detect small, medium, and large percentile effect sizes in anti-bullying interventions.

Factors that influence morningness-eveningness and daytime sleepiness: A cross-cultural comparison of Iranian and Brazilian adolescents.

As adolescents get older, they become more evening oriented and, because they are usually expected to wake early to attend school, they often present daytime sleepiness, which is associated with negative outcomes. It is still unclear if this is similar cross-culturally. Here, we studied morningness-eveningness and daytime sleepiness in early adolescence from two different developing nations (Brazil and Iran). A total sample of 697 Iranian and Brazilian early adolescents (9- to 15-year-old; 358 boys) from Tehran, Iran, and São Paulo, Brazil, varying in age and parental schooling (a proxy of socioeconomic status: SES) completed the Morningness-Eveningness Scale for Children (MESC) and the Pediatric Daytime Sleepiness Scale (PDSS) and reported their total sleep time on school nights. They also filled in the Pubertal Developmental Scale to determine their pubertal status. A negligible cross-cultural difference in morningness-eveningness was found, indicating that Brazilians showed a slight circadian-phase delay compared with Iranians throughout all tested ages. There was also seen a very slight increase in phase delay as early adolescents aged, indicative of more eveningness. However, there were no country differences in daytime sleepiness once total sleep time during school nights was controlled for, which was the only factor that affects PDSS scores.

Probing different aspects of short and ill-timed sleep in adolescents using the Morningness-Eveningness Scale for Children.

Sleep problems among adolescents are believed to be related to the circadian changes that occur at this age. Therefore, most self-report instruments that measure sleep patterns in adolescence focus solely on measuring circadian rhythms. However, sleep-wake cycles reflect both circadian and homeostatic processes. Recently, it was shown that answers to the Morningness-Eveningness Questionnaire for adults, which is used to assess circadian typology, were able to identify three interrelated latent factors: two that can be conceptualized as homeostatic (sensitivity to the build-up of sleep pressure and efficiency of dissipation of sleep pressure) and a less well-defined factor related to activity preference time (APT). To better understand self-reported changes in sleep patterns in adolescents we applied confirmatory factor analysis to explore whether responses to the Morningness-Eveningness Scale for Children (MESC) could also identify these three factors. The sample comprised 397, 9- to 17-year-olds. A three-correlated and a bifactor-(S-1) model (with sleep onset characteristics as a reference factor) had acceptable/good fit indices. This indicates that the MESC captures dissociable, but interrelated, homeostatic and circadian processes in addition to APT. These factors correlated with corresponding reported sleep habits, showing individual differences that may be more associated with sleep difficulties than the effects of age, which only correlated very modestly with some sleep habits. Our results indicate that the MESC can show distinct individual differences in three sleep factors that can help identify adolescents at higher risk of sleep-related problems that may require factor-specific interventions.

Factor structure and psychometric properties of the Persian versions of the Pediatric Daytime Sleepiness Scale and Morningness-Eveningness Scale for Children.

BACKGROUND: The Pediatric Daytime Sleepiness Scale (PDSS) and the Morningness-Eveningness Scale for Children (MESC) are widely used to measure two important facets of sleep patterns, but neither have been adapted and validated for use in Iran. The purpose of this study was to examine the psychometric properties and factor structure of the Persian versions of the PDSS and the MESC in a sample of Iranian adolescents. MATERIALS AND METHODS: The Persian versions of PDSS and MESC were translated and administered to a representative sample (n = 407) of Iranian early adolescents, aged 9-15 years, who attended school in morning shifts. The factor structure of both scales, found in prior studies, was tested using Confirmatory Factor Analyses to assess their validity and reliability. RESULTS: The results revealed that the model fit indices of the one factor solution of the PDSS and the two factor solution of the MESC were acceptable to good. A high Pearson correlation was found between raw and latent factor scores for the PDSS and the two factors derived from the MESC (i.e., Morningness and Planning). Furthermore, the higher the PDSS score (more daytime sleepiness), the lower the MESC scores (more eveningness), indicating criterion validity of the scales showing the expected increase in daytime sleepiness in evening oriented adolescents who wake up early for attending school. CONCLUSION: The Persian versions of the PDSS and the MESC can be considered reliable and valid tools for evaluating, respectively, daytime sleepiness and morningness-eveningness in the adolescent population of Iran.

What are we measuring with the morningness-eveningness questionnaire? Exploratory factor analysis across four samples from two countries.

Individual variability in diurnal preference or chronotype is commonly assessed with self-report scales such as the widely used morningness-eveningness questionnaire (MEQ). We sought to investigate the MEQ's internal consistency by applying exploratory factor analysis (EFA) to determine the number of underlying latent factors in four different adult samples, two each from the United Kingdom and Brazil (total N = 3,457). We focused on factors that were apparent in all samples, irrespective of particular sociocultural diversity and geographical characteristics, so as to show a common core reproducible structure across samples. Results showed a three-factor solution with acceptable to good model fit indexes in all studied populations. Twelve of the 19 MEQ items in the three-correlated factor solution loaded onto the same factors across the four samples. This shows that the scale measures three distinguishable, yet correlated constructs: (1) items related to how people feel in the morning, which we termed efficiency of dissipation of sleep pressure (recovery process) (items 1, 3, 4, 5, 7, 9, 13, and 19); (2) items related to how people feel before sleep, which we called sensitivity to buildup of sleep pressure (items 2, 10, and 12); and (3) peak time of cognitive arousal (item 11). Although the third factor was not regarded as consistent since only one item was common among all samples, it might represent subjective amplitude. These results suggested that the latent constructs of the MEQ reflect dissociable homeostatic processes in addition to a less consistent propensity for cognitive arousal at different times of the day. By analyzing answers to MEQ items that compose these latent factors, it may be possible to extract further knowledge of factors that affect morningness-eveningness.