Exploratory factor analysis of the Illness Intrusiveness Rating Scale for parents of children with atypical genital appearance due to differences of sex development (DSD).

OBJECTIVE: Illness intrusiveness refers to the subjective cognitive appraisal of a chronic health condition interfering in daily, valued activities and may be highly relevant for parents of children with atypical genital appearance due to differences of sex development (DSD). However, a measure of illness intrusiveness has not been validated for this population. The current study aimed to evaluate the factor structure of the Illness Intrusiveness Scale for Parents (IIS-P) and examine convergent validity. METHODS: Participants included 102 parents (Mage = 33.39 years, SD = 6.48; 58% mothers) of 65 children (<2 years old) diagnosed with DSD participating in a larger, longitudinal study. Parents completed the IIS-P as well as self-report measures of stigma, and anxious and depressive symptoms. An exploratory factor analysis (EFA) was conducted. RESULTS: EFA results supported a 1-factor intrusiveness solution (α = .93), as well as a 2-factor solution measuring intrusiveness on daily living (α = .92) and community connectedness (α = .85). The 1-factor solution and both factors of the 2-factor solution demonstrated significant convergent validity with stigma as well as anxious and depressive symptoms. CONCLUSIONS: Support emerged for both 1- and 2-factor solutions of the IIS-P in parents of children with DSD. The decision to evaluate illness intrusiveness as a total score or to examine the subscales of daily living and community connectedness should be tailored to the unique aims of researchers and clinicians. Future research should conduct a confirmatory factor analysis with both 1- and 2-factor models with larger, more diverse samples of caregivers.

Many nonnormalities, one simulation: Do different data generation algorithms affect study results?

Monte Carlo simulation studies are among the primary scientific outputs contributed by methodologists, guiding application of various statistical tools in practice. Although methodological researchers routinely extend simulation study findings through follow-up work, few studies are ever replicated. Simulation studies are susceptible to factors that can contribute to replicability failures, however. This paper sought to conduct a meta-scientific study by replicating one highly cited simulation study (Curran et al., Psychological Methods, 1, 16-29, 1996) that investigated the robustness of normal theory maximum likelihood (ML)-based chi-square fit statistics under multivariate nonnormality. We further examined the generalizability of the original study findings across different nonnormal data generation algorithms. Our replication results were generally consistent with original findings, but we discerned several differences. Our generalizability results were more mixed. Only two results observed under the original data generation algorithm held completely across other algorithms examined. One of the most striking findings we observed was that results associated with the independent generator (IG) data generation algorithm vastly differed from other procedures examined and suggested that ML was robust to nonnormality for the particular factor model used in the simulation. Findings point to the reality that extant methodological recommendations may not be universally valid in contexts where multiple data generation algorithms exist for a given data characteristic. We recommend that researchers consider multiple approaches to generating a specific data or model characteristic (when more than one is available) to optimize the generalizability of simulation results.

Maternal childhood adversity and prenatal depression: the protective role of father support.

Depression during pregnancy is common, and previous research suggests childhood adversity may increase the risk for prenatal depression. Support during pregnancy can buffer these risks, and paternal support is associated with improved maternal well-being during pregnancy. There is evidence to suggest that increased support from fathers may be particularly helpful in combatting depressive symptoms for mothers with adverse childhood experiences. The study aims to explore the role of biological father support as a protective factor against the risks associated with childhood adversity for maternal prenatal depression. Sample included 133 pregnant women recruited from two university-affiliated OB-GYN clinics serving diverse and low-income patients. Participants completed measures on childhood adversity, prenatal depressive symptoms, and father support. Results showed a significant moderating effect of father support on the relation between maternal ACEs and prenatal depressive symptoms, suggesting that higher levels of father support are protective against prenatal depressive symptoms, specifically in mothers with low-to-moderate ACEs. These results highlight the positive impact of paternal support for maternal well-being during pregnancy. Although mothers with low-to-moderate ACEs experience a buffering effect of father support, mothers with high levels of childhood adversity remain at elevated risk for prenatal depressive symptoms even with high father support. As such, screening mothers for ACEs in addition to father support may help identify those at higher risk of prenatal depression.

Baseline associations between biomarkers, cognitive function, and self-regulation indices in the Cognitive and Self-regulatory Mechanisms of Obesity Study.

OBJECTIVE: Understanding how biological, cognitive, and self-regulatory factors are related to obesity, and weight regulation is clearly needed to optimize obesity prevention and treatment. The objective of this investigation was to understand how baseline biological, cognitive, and self-regulatory factors are related to adiposity at the initiation of a behavioral weight loss intervention among treatment-seeking adults with overweight/obesity. METHODS: Participants (N = 107) in the Cognitive and Self-regulatory Mechanisms of Obesity Study (Identifier-NCT02786238) completed a baseline assessment with anthropometric, cardiometabolic, inflammatory, cognitive function, and self-regulation measures as part of a larger on-going trial. Data were analyzed with linear regression. RESULTS: At baseline, body mass index, body fat percentage, and waist circumference (WC) were positively associated with fasting insulin and insulin resistance. Higher WC was related to higher fasting glucose and hemoglobin A1c (HbA1c). Higher glucose and insulin resistance levels were related to lower list sorting working memory. Higher glucose and HbA1c levels were negatively associated with reading scores. Cognitive function and self-regulation indices were unrelated. CONCLUSIONS: In adults with overweight/obesity entering a weight loss treatment study: (1) elevated WC and associated glycemic impairment were negatively associated with cognition, (2) poorer executive function and reading abilities were associated with poorer glycemic control, and (3) objectively measured cognitive functions were unrelated to self-reported/behavioral measures of self-regulation. Such findings increase understanding of the relationships between adiposity, biomarkers, cognition, and self-regulation at treatment initiation and may ultimately inform barriers to successful obesity treatment response.

Faith and science mindsets as predictors of COVID-19 concern: A three-wave longitudinal study.

The COVID-19 pandemic allowed for a naturalistic, longitudinal investigation of the relationship between faith and science mindsets and concern about COVID-19. Our goal was to examine two possible directional relationships: (Model 1) COVID-19 concern ➔ disease avoidance and self-protection motivations ➔ science and faith mindsets versus (Model 2) science and faith mindsets ➔ COVID-19 concern. We surveyed 858 Mechanical Turk workers in three waves of a study conducted in March, April, and June 2020. We found that science mindsets increased whereas faith mindsets decreased (regardless of religious type) during the early months of the pandemic. Further, bivariate correlations and autoregressive cross-lagged analyses indicated that science mindset was positive predictor of COVID-19 concern, in support of Model 2. Faith mindset was not associated with COVID-19 concern. However, faith mindset was a negative predictor of science mindset. We discuss the need for more research regarding the influence of science and faith mindsets as well as the societal consequences of the pandemic.

Longitudinal smoking patterns and adult cardiometabolic risk among African Americans.

OBJECTIVE: To better understand mechanisms influencing health in African Americans (AAs), the aims of this study were (a) to identify longitudinal cigarette smoking classes among AAs across adolescence and into young adulthood; (b) to identify risk factors for smoking and how cardiometabolic health in adulthood differs by smoking class; and (c) to investigate whether smoking mediates the relation between adolescent risk factors and adult cardiometabolic health. METHOD: This study used 4 waves of nationally representative data, restricted to an AA subsample (N = 2,009). Participants self-reported on multilevel risk factors in adolescence and smoking across adolescence and young adulthood; cardiometabolic risk was assessed in adulthood. Growth mixture modeling and structural equation modeling were conducted. RESULTS: Five classes emerged: nonsmoker; early onset, heavier smoking; later onset; early onset, light smoking; and maturing out or declining smoking. Predictors of class membership included living with individuals who smoke, having friends who smoke, and limited access to medical care. The early onset, light smoking class had the greatest cardiometabolic risk. Smoking class mediated the relation between living with people who smoke in adolescence and adult cardiometabolic risk. CONCLUSIONS: Nuanced smoking patterns among AAs were identified, and 23% fell into classes characterized by an early onset and persistent smoking trajectory. The early onset, light smoking class had the greatest cardiometabolic risk in adulthood. The results suggest unique protective factors may be present for youth who remain nonsmokers even when their family smokes. Results have implications for health promotion and tobacco prevention efforts among AA families. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

The Five Factor Borderline Inventory: Behavioral outcomes across time.

The Five-Factor Borderline Inventory Short Form (FFBI-SF) is a 48-item dimensional measure of borderline personality disorder (BPD) that was developed from the Five-factor model (FFM). Previous research has examined the relationships of the FFBI-SF to the FFM and BPD. The purpose of the current study was to investigate the relationship of FFBI-SF scales with behavioral outcomes, such as self-injury, physical fights, panic symptoms, promiscuous sex, theft, attempted suicide, reckless driving, and binge eating. A potential advantage of the FFBI-SF, relative to other measures of BPD, is the provision of subscales, which provides a more precise and differentiated assessment. In the current study, the predictive validity of the FFBI-SF in relation to various impulsive behaviors was investigated across a 2-month time period. Additional comparisons were also made with respect to a more traditional measure of borderline personality disorder and an assessment of the normal range of the FFM. Undergraduate students in psychology courses (T1 = 938, T2 = 284, T3 = 163) and workers from Amazon Mechanical Turk (T1 = 215, T2 = 167, T3 = 157) were administered personality measures and a measure of impulsive behaviors across 3 time points. The results are discussed with respect to the comparative validity of the FFBI-SF, relative to traditional measures of borderline personality disorder and the FFM. Overall, the study provided evidence that the FFBI-SF is able to predict specific maladaptive behaviors over time and therefore may be useful in clinical and research settings. (PsycINFO Database Record

Grit, Illness-Related Distress, and Psychosocial Outcomes in College Students With a Chronic Medical Condition: A Path Analysis.

Objective: Adolescents and young adults (AYAs) with chronic medical conditions are at increased risk for a host of negative psychosocial outcomes, including depressive and anxious symptoms. Although studies have shown that illness appraisals (e.g., illness intrusiveness [II] and illness uncertainty [IU]) demonstrate consistent associations with such outcomes, few studies have examined positive factors that may relate to better psychosocial outcomes and appraisals. The present study evaluated grit (i.e., perseverance and passion for long-term goals), a novel construct in pediatric psychology, as a positive factor that relates to reduced untoward effects of II and IU on psychosocial outcomes in AYAs with chronic medical conditions. Methods: College students with a chronic medical condition (N = 120) completed questionnaires online, including measures of grit, II, IU, depression, anxiety, and emotional well-being (EWB). Results: The overall path analysis demonstrated that increased grit is directly associated with decreased depressive and anxious symptoms and increased EWB (p < .05). Further, analyses indicated that the positive association between grit and psychosocial outcomes is partially mediated by illness appraisals (p < .05). Conclusions: This study identified grit as a positive personal asset among AYAs with chronic medical conditions. By introducing a novel construct to the AYA literature, the study expands on the integration of positive psychology and pediatric psychology and underscores the need for greater research on the role of grit in chronic medical condition populations.

Mediation Analysis with Survival Outcomes: Accelerated Failure Time vs. Proportional Hazards Models.

OBJECTIVE: Survival time is an important type of outcome variable in treatment research. Currently, limited guidance is available regarding performing mediation analyses with survival outcomes, which generally do not have normally distributed errors, and contain unobserved (censored) events. We present considerations for choosing an approach, using a comparison of semi-parametric proportional hazards (PH) and fully parametric accelerated failure time (AFT) approaches for illustration. METHOD: We compare PH and AFT models and procedures in their integration into mediation models and review their ability to produce coefficients that estimate causal effects. Using simulation studies modeling Weibull-distributed survival times, we compare statistical properties of mediation analyses incorporating PH and AFT approaches (employing SAS procedures PHREG and LIFEREG, respectively) under varied data conditions, some including censoring. A simulated data set illustrates the findings. RESULTS: AFT models integrate more easily than PH models into mediation models. Furthermore, mediation analyses incorporating LIFEREG produce coefficients that can estimate causal effects, and demonstrate superior statistical properties. Censoring introduces bias in the coefficient estimate representing the treatment effect on outcome-underestimation in LIFEREG, and overestimation in PHREG. With LIFEREG, this bias can be addressed using an alternative estimate obtained from combining other coefficients, whereas this is not possible with PHREG. CONCLUSIONS: When Weibull assumptions are not violated, there are compelling advantages to using LIFEREG over PHREG for mediation analyses involving survival-time outcomes. Irrespective of the procedures used, the interpretation of coefficients, effects of censoring on coefficient estimates, and statistical properties should be taken into account when reporting results.

Parent Perceptions of Illness Uncertainty and Child Depressive Symptoms in Juvenile Rheumatic Diseases: Examining Caregiver Demand and Parent Distress as Mediators.

OBJECTIVE: Examine caregiver demand and general parent distress as mediators in the parent illness uncertainty-child depressive symptom association in youth with juvenile rheumatic diseases. METHODS: Children and adolescents completed the Child Depression Inventory; caregivers completed the Parent Perceptions of Uncertainty Scale, the Care for My Child with Rheumatic Disease Scale, and the Brief Symptom Inventory. The pediatric rheumatologist provided ratings of clinical disease status. RESULTS: Analyses revealed significant direct associations between illness uncertainty and caregiver demand, and between caregiver demand and both parent distress and child depressive symptoms. Results also revealed significant parent uncertainty → caregiver demand → parent distress and parent uncertainty → caregiver demand → child depressive symptom indirect paths. CONCLUSIONS: Results highlight the role of illness appraisals in adjustment to juvenile rheumatic diseases, and provide preliminary evidence that parent appraisals of illness uncertainty impact parent distress and child depressive symptoms indirectly through increased perceptions of caregiver demand.

Estimating interaction effects with incomplete predictor variables.

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.

Sweetened drink and snacking cues in adolescents: a study using ecological momentary assessment.

The objective of this study was to identify physical, social, and intrapersonal cues that were associated with the consumption of sweetened beverages and sweet and salty snacks among adolescents from lower SES neighborhoods. Students were recruited from high schools with a minimum level of 25% free or reduced cost lunches. Using ecological momentary assessment, participants (N=158) were trained to answer brief questionnaires on handheld PDA devices: (a) each time they ate or drank, (b) when prompted randomly, and (c) once each evening. Data were collected over 7days for each participant. Participants reported their location (e.g., school grounds, home), mood, social environment, activities (e.g., watching TV, texting), cravings, food cues (e.g., saw a snack), and food choices. Results showed that having unhealthy snacks or sweet drinks among adolescents was associated with being at school, being with friends, feeling lonely or bored, craving a drink or snack, and being exposed to food cues. Surprisingly, sweet drink consumption was associated with exercising. Watching TV was associated with consuming sweet snacks but not with salty snacks or sweet drinks. These findings identify important environmental and intrapersonal cues to poor snacking choices that may be applied to interventions designed to disrupt these food-related, cue-behavior linked habits.

Guidelines for the Investigation of Mediating Variables in Business Research.

Business theories often specify the mediating mechanisms by which a predictor variable affects an outcome variable. In the last 30 years, investigations of mediating processes have become more widespread with corresponding developments in statistical methods to conduct these tests. The purpose of this article is to provide guidelines for mediation studies by focusing on decisions made prior to the research study that affect the clarity of conclusions from a mediation study, the statistical models for mediation analysis, and methods to improve interpretation of mediation results after the research study. Throughout this article, the importance of a program of experimental and observational research for investigating mediating mechanisms is emphasized.

Evidence for association of hyperprolinemia with schizophrenia and a measure of clinical outcome.

There are multiple genetic links between schizophrenia and a deficit of proline dehydrogenase (PRODH) enzyme activity. However, reports testing for an association of schizophrenia with the resulting proline elevation have been conflicting. The objectives of this study were to investigate whether hyperprolinemia is associated with schizophrenia, and to measure the relationship between plasma proline, and clinical features and symptoms of schizophrenia. We performed a cross-sectional case-control study, comparing fasting plasma proline in 90 control subjects and 64 schizophrenic patients and testing for association of mild to moderate hyperprolinemia with schizophrenia. As secondary analyses, the relationship between hyperprolinemia and five measures of clinical onset, symptoms and outcome were investigated. Patients had significantly higher plasma proline than matched controls (p<0.0001), and categorical analysis of gender adjusted hyperprolinemia showed a significant association with schizophrenia (OR 6.15, p=0.0003). Hyperprolinemic patients were significantly older at their first hospitalization (p=0.015 following correction for multiple testing). While plasma proline level was not related to total, positive or negative symptoms, hyperprolinemic status had a significant effect on length of hospital stay (p=0.005), following adjustment for race, BPRS score, and cross-sectional time from admission to proline measurement. Mild to moderate hyperprolinemia is a significant risk factor for schizophrenia, and may represent an intermediate phenotype in the disease. Hyperprolinemic patients have a significantly later age of first psychiatric hospitalization, suggestive of later onset, and hospital stays 46% longer than non-hyperprolinemic subjects. These findings have implications in the etiology of schizophrenia, and for the clinical management of these patients.

An introduction to modern missing data analyses.

A great deal of recent methodological research has focused on two modern missing data analysis methods: maximum likelihood and multiple imputation. These approaches are advantageous to traditional techniques (e.g. deletion and mean imputation techniques) because they require less stringent assumptions and mitigate the pitfalls of traditional techniques. This article explains the theoretical underpinnings of missing data analyses, gives an overview of traditional missing data techniques, and provides accessible descriptions of maximum likelihood and multiple imputation. In particular, this article focuses on maximum likelihood estimation and presents two analysis examples from the Longitudinal Study of American Youth data. One of these examples includes a description of the use of auxiliary variables. Finally, the paper illustrates ways that researchers can use intentional, or planned, missing data to enhance their research designs.