The Fatigue and Altered Cognition Scale among SARS-CoV-2 Survivors: Psychometric Properties and Item Correlations with Depression and Anxiety Symptoms.

Background/Objectives: This study examined the psychometric properties of the Fatigue and Altered Cognition Scale (FACs) among adult COVID-19 survivors and its unique ability to assess symptomology not accounted for by measures of depression and anxiety. Methods: COVID-19 survivors completed an online survey that included the FACs, a measure of brain fog and central fatigue with 20 items rated on a digital-analog scale. Useable data from 559 participants were analyzed to test the two-factor structure of the FACs, test for measurement invariance by sex and device was used to complete the survey (hand-held, computer), and item correlations with symptoms of depression and anxiety were examined. Results: The two-factor structure of the FACs replicated, supporting the separate assessments of brain fog and fatigue, χ2(164) = 1028.363, p < 0.001, CFI = 0.934, TLI = 0.923, RMSEA = 0.097, SRMR = 0.053. The FACs exhibited invariance at the scalar level, indicating item and factor integrity regardless of sex and device type. Using a correlation > 0.70 as a criterion (i.e., indicating more than 50% shared variance between two items), items on the FACs (assessing fatigue and lack of energy) were highly correlated with feeling tired or having little energy on the depression measure. No other items correlated with any anxiety symptom larger than 0.70. Conclusions: The FACs appears to be a psychometrically sound and efficient measure for use with COVID-19 survivors, assessing symptoms of brain fog and central fatigue that are not attributable to symptoms assessed by established measures of depression and anxiety.

The Fracture Risk of Elderly Patients With Atopic Dermatitis.

Background: A higher fracture risk has been reported previously in patients with atopic dermatitis (AD). The bone mineral density (BMD) was not accounted for in these studies. Objective: To investigate the fracture risk in AD patients after adjustment for factors including BMD. Methods: We retrospectively analyzed AD patients (≥45 years) who underwent BMD examination at our hospital from July 2010 to February 2023. Individuals who received BMD examinations during a health checkup were identified as the controls. We documented their clinical characteristics, BMD, 10-year risk for a major fracture based on FRAX (Fracture Risk Assessment Tool), and development of osteoporotic fractures. Patients were followed until development of new onset fracture or the end of the study period. A cross-sectional comparison of BMD between AD patients and controls at baseline was performed using the Mann-Whitney U test after propensity score matching (PSM). Their fracture risks were compared using the multivariate Cox regression model. BMD and fracture risk were also compared between AD patients who received systemic therapy and those who did not. Results: A total of 50 AD patients and 386 controls were enrolled. The median age was older in AD patients when compared with controls (70 years vs 60 years). Their BMD at all sites was similar after PSM. After a median follow-up of 1.7-2.0 years, 13 osteoporotic fractures were identified. In the multivariate Cox regression analysis, AD was not associated with new onset fractures of all sites (adjusted hazard ratio [aHR] 2.55, 95% confidence interval [CI] 0.72-9.01) but was significantly associated with new onset vertebral fractures (aHR 6.80, 95% CI 1.77-26.17). The BMD and incidence of fractures were similar between AD who received systemic therapy and those who did not. Conclusions: Elderly AD patients had similar BMD but a higher short-term risk for vertebral fractures when compared with the controls.

Efficient assessment of brain fog and fatigue: Development of the Fatigue and Altered Cognition Scale (FACs).

Debilitating symptoms of fatigue and accompanying "brain fog" are observed among patients with various chronic health conditions. Unfortunately, an efficient and psychometrically sound instrument to assess these co-occurring symptoms is unavailable. Here, we report the development and initial psychometric properties of the Fatigue and Altered Cognition Scale (the FACs), a measure of self-reported central fatigue and brain fog. Traumatic brain injury (TBI) was chosen to model and develop the FACs due to research team expertise and established links between TBI and the symptom complex. Potential items were generated by researchers and clinicians with experience treating these symptoms, drawing from relevant literature and review of patient responses to measures from past and current TBI studies. The 20 candidate items for the FACs-ten each to assess altered cognition (i.e., brain fog) and central fatigue-were formatted on an electronic visual analogue response scale (eVAS) via an online survey. Demographic information and history of TBI were obtained. A total of 519 participants consented and provided usable data (average age = 40.23 years; 73% female), 204 of whom self-reported a history of TBI (75% reported mild TBI). Internal consistency and reliability values were calculated. Confirmatory factor analysis (CFA) examined the presumed two-factor structure of the FACs and a one-factor solution for comparison. A measurement invariance test of the two latent constructs (altered cognition, fatigue) among participants with and without TBI was conducted. All items demonstrated normal distribution. Cronbach's alpha coefficients indicated good internal consistency for both factors (α's = .95). Omega reliability values were favorable (α's = .95). CFA supported the presumed two-factor model and item loadings which outperformed the one-factor model. Measurement invariance found the two-factor structure was consistent between the two groups. Implications of these findings, study limitations, and potential use of the FACs in clinical research and practice are discussed.

The physiological, perceptual, and thermoregulatory responses to facemask use during exercise.

The use of masks in public settings and when around people has been recommended to limit the spread of Coronavirus disease 2019 (COVID-19) by major public health agencies. Several different types of masks classified as either medical- or non-medical grade are commonly used among the public. However, concerns with difficulty breathing, re-breathing exhaled carbon dioxide, a decrease in arterial oxygen saturation, and a decrease in exercise performance have been raised regarding the use of mask during exercise. We review the current knowledge related to the effect of different masks during exercise on cardiorespiratory, metabolic, thermoregulatory, and perceptual responses. As such, the current literature seems to suggest that there are minimal changes to cardiovascular, metabolic, and no changes to thermoregulatory parameters with facemask use. However, differences in ventilatory parameters have been reported with submaximal and maximal intensity exercise to volitional fatigue. Literature on perceptual responses to exercise indicate an impact on ratings of perceived exertion, dyspnea, and overall discomfort dependent on mask use as well as exercise intensity. In conclusion, data from the current literature suggests a minimal impact on physiological, perceptual, and thermoregulatory responses dependent on the type of mask used during exercise.

Teacher's Corner: An R Shiny App for Sensitivity Analysis for Latent Growth Curve Mediation.

Mechanisms of behavior change are the processes through which interventions are hypothesized to cause changes in outcomes. Latent growth curve mediation models (LGCMM) are recommended for investigating the mechanisms of behavior change because LGCMM models establish temporal precedence of change from the mediator to the outcome variable. The Correlated Augmented Mediation Sensitivity Analyses (CAMSA) App implements sensitivity analysis for LGCMM models to evaluate if a mediating path (mechanism) is robust to potential confounding variables. The CAMSA approach is described and applied to simulated data, and data from a research study exploring a mechanism of change in the treatment of substance use disorder.

Facemask Use During High Intensity Interval Exercise in Temperate and Hot Environments.

OBJECTIVE: The purpose of this study was to investigate the effects of surgical mask use during high intensity interval exercise (HIIE) on physiological and perceptual responses in hot and temperate environments. METHODS: In a randomized fashion, 10 healthy participants completed two HIIE sessions in a 36°C hot (HUE-HOT) and two HIIE sessions in a 23°C temperate environment (HIIE-TEMP) while wearing (MASK) and not wearing a surgical mask (CON). RESULTS: No differences in physiological variables were found between MASK and CON during HIIE. An increase in perceived dyspnea and average RPE was found comparing MASK and CON. Interaction effects showed the greatest changes in perceived dyspnea and average RPE occurred in the HIIE-HOT/MASK condition. CONCLUSION: Wearing a surgical mask during HIIE increases the perception of dyspnea and exertion with the greatest effect occurring in hot environments.

Factors Influencing Family Health History Collection among Young Adults: A Structural Equation Modeling.

Family health history (FHH) can serve as an entry point for preventive medicine by providing risk estimations for many common health conditions. College is a critical time for young adults to begin to understand the value of FHH collection, and to establish healthy behaviors to prevent FHH-related diseases. This study seeks to develop an integrated theoretical framework to examine FHH collection behavior and associated factors among college students. A sample of 2670 college students with an average age of 21.1 years completed a web-based survey. Less than half (49.8%) reported actively seeking FHH information from their family members. Respondents' knowledge about FHH were generally low. Structural equation modeling findings suggested an adequate model fit between our survey data and the proposed integrated theoretical framework. Respondents who were members of racial/ethnic minority groups exhibited higher levels of anxiety and intention to obtain FHH information but had lower confidence in their ability to gather FHH information than non-Hispanic White respondents. Therefore, educational programs designed to enhance the level of young adults' FHH knowledge, efficacy, and behavior in FHH collection, and change subjective norms are critically needed in the future, especially for these who are members of racial/ethnic minority groups.

Two-stage path analysis with definition variables: An alternative framework to account for measurement error.

When estimating path coefficients among psychological constructs measured with error, structural equation modeling (SEM), which simultaneously estimates the measurement and structural parameters, is generally regarded as the gold standard. In practice, however, researchers usually first compute composite scores or factor scores, and use those as observed variables in a path analysis, for purposes of simplifying the model or avoiding model convergence issues. Whereas recent approaches, such as reliability adjustment methods and factor score regression, has been proposed to mitigate the bias induced by ignoring measurement error in composite/factor scores with continuous indicators, those approaches are not yet applicable to models with categorical indicators. In this article, we introduce the two-stage path analysis (2S-PA) with definition variables as a general framework for path modeling to handle categorical indicators, in which estimation of factor scores and path coefficients are separated. It thus allows for different estimation methods in the measurement and the structural path models and easier diagnoses of violations of model assumptions. We conducted three simulation studies, ranging from latent regression to mediation analysis with categorical indicators, and showed that 2S-PA generally produced similar estimates to those using SEM in large samples, but gave better convergence rates, less standard error bias, and better control of Type I error rates in small samples. We illustrate 2S-PA using data from a national data set, and show how researchers can implement it in Mplus and OpenMx. Possible extensions and future directions of 2S-PA are discussed. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Predictive model specific to young adults for estimating thoracic gas volume for air-displacement plethysmography.

BACKGROUND: Thoracic gas volume either measured (mTGV) or predicted by the BodPod® (bpTGV) is used during air-displacement plethysmography to obtain a better estimate of percent body fat. Evidence suggests that bpTGV underestimates mTGV for young adults and this is especially evident for young males. AIMS: We developed, validated, and cross-validated a TGV prediction model (pTGV) for males and females 18-30 years of age to address this underestimation. MATERIALS & METHODS: Participants (N = 181; 18-30 years) that had their body composition assessed with the BodPod® were retrospectively randomly assigned to one of two independent subgroups, a validation (n = 145) or cross-validation (n = 36) sample. Ten iterations of the k-fold validation procedure were performed to assess the internal replicability of pTGV within the validation sample. External replicability of pTGV was evaluated by assessing the difference and standard error of the estimate (SEE) compared to mTGV in the cross-validation group. RESULTS: The model using height, sex and body mass yielded the highest adjusted R2 (0.627) and the lowest SEE (0.56 L): pTGV = 0.615338 × Sex (0 = Female, 1 = Male) + 0.056267 × Height (cm) - 0.011006 × Body Mass (kg) - 5.358839. R2 remained stable across 10 iterations of the k-fold procedure (average R2 = 0.64). Differences between pTGV and mTGV were not significantly different than zero for the total cross-validation sample (-0.06 ± 0.7 L; SEE = 3.0%), for males (-0.11 ± 0.7 L; SEE = 3.7%), or for females (-0.02 ± 0.7 L; SEE = 5.3%). CONCLUSION: We recommend that when it is impractical to obtain mTGV, the strong internal and external replicability of the new prediction model supports its use for males and females ages 18-30 years old during air-displacement plethysmography.

The relationship between outdoor air pollutants and atopic dermatitis of adults: A systematic review and meta-analysis.

BACKGROUND: Atopic dermatitis (AD) poses a significant disease burden in adults. Environmental factors are essential in its pathogenesis. OBJECTIVE: Given the possible role of air pollutants in allergic diseases, it is worthwhile to summarize the effects of outdoor air pollution on adult AD. METHODS: We undertook a systematic review based on PubMed and EMBASE as of August 16, 2021, and found 20 relevant studies. A random-effects meta-analysis was carried out. RESULTS: Regarding long-term effects (within months to years), traffic-related air pollution and particulate matter < 2.5 µm in diameter (PM2.5, per 10 µg/m³ increment) are associated with the prevalence of adult AD (OR 1.40, 95%CI [1.24, 1.58] and 1.67, 95%CI [1.26, 2.21]). Exposures to PM2.5 and nitrogen dioxide are associated with incident AD, with ORs of 2.30 (95%CI: 1.25, 4.25) and 1.30 (95%CI: 1.04, 1.61) per 10 µg/m³ increment. In terms of short term effects (within days), exposure to particulate matter < 10 µm in diameter (PM10) and sulfur dioxide (SO2) are associated with exacerbations of AD at lag day 0 based on those time-series studies, with an excessive risk of 2.9%, in particular, per 10 µg/m³ increment in SO2 exposure. In addition, both short-term and long-term exposures to these air pollutants are associated with AD symptoms (eczema, pruritus, and sleep disturbance). CONCLUSIONS: Outdoor air pollutants exert both short-term and long-term adverse effects on adult AD, contributing to its development, severity and exacerbation of symptoms. The influence of air pollution should be considered in the management of adult AD.

Hierarchy and Reliability of the Preschool Language Scales-Fifth Edition: Mokken Scale Analysis.

Purpose This study examined the psychometric properties of the Preschool Language Scales-Fifth Edition (PLS-5 English) among preschool children from low-socioeconomic status (SES) families. Method The PLS-5 was administered individually to 169 3- to 4-year-old children enrolled in Head Start programs. We carried out a Mokken scale analysis (MSA), which is a nonparametric item response theory analysis, to examine the hierarchy among items and the reliability of test scores of the PLS-5 Auditory Comprehension (AC) and Expressive Communication (EC) scales. Results The PLS-5 EC items retained a moderate Mokken scale with the inclusion of all the items. On the other hand, the PLS-5 AC items formed a moderate Mokken scale only with the exclusion of five unscalable items. The latent class reliability coefficients for the AC and the EC scale scores were both above .90. Several items that violated the invariant item ordering assumption were found for both scales. Conclusions MSA can be used to examine the relationship between the latent language ability and the probability of passing an item with ordinal responses. Results indicate that for preschool children from low-SES families, it is appropriate to use the PLS-5 EC scale scores for comparing individuals' expressive language abilities; however, researchers and speech-language pathologists should be cautious when using the PLS-5 AC scale scores to evaluate individuals' receptive language abilities. Other implications of the MSA results are further discussed.

Modeling Measurement Errors of the Exogenous Composites From Congeneric Measures in Interaction Models.

We investigated the performance of two single indicator methods: latent moderated structural equation (LMS) and reliability-adjusted product indicator (RAPI) methods, on testing interaction effects with congeneric measures, which vary in factor loadings and error variances under a common factor. Additionally, in the simulation study, we compared the performance of four reliability estimates (Cronbach's alpha, omega composite, Coefficient H, and greatest lower bound [GLB]) to adjust for the exogenous composites' measurement errors. Results from the study showed that: while estimating interaction effects with exogenous composites from congeneric measures, the four reliability estimates performed comparably well. Recommendations on the choice of reliability estimates between the LMS and the RAPI methods under different sample sizes and population reliability conditions are further discussed.

Applying methods for personalized medicine to the treatment of alcohol use disorder.

OBJECTIVE: Numerous behavioral treatments for alcohol use disorder (AUD) are effective, but there are substantial individual differences in treatment response. This study examines the potential use of new methods for personalized medicine to test for individual differences in the effects of cognitive behavioral therapy (CBT) versus motivational enhancement therapy (MET) and to provide predictions of which will work best for individuals with AUD. We highlight both the potential contribution and the limitations of these methods. METHOD: We performed secondary analyses of abstinence among 1,144 participants with AUD participating in either outpatient or aftercare treatment who were randomized to receive either CBT or MET in Project MATCH. We first obtained predicted individual treatment effects (PITEs), as a function of 19 baseline client characteristics identified a priori by MATCH investigators. Then, we tested for the significance of individual differences and examined the predicted individual differences in abstinence 1 year following treatment. Predictive intervals were estimated for each individual to determine if they were 80% more likely to achieve abstinence in one treatment versus the other. RESULTS: Results indicated that individual differences in the likelihood of abstinence at 1 year following treatment were significant for those in the outpatient sample, but not for those in the aftercare sample. Individual predictive intervals showed that 37% had a better chance of abstinence with CBT than MET, and 16% had a better chance of abstinence with MET. Obtaining predictions for a new individual is demonstrated. CONCLUSIONS: Personalized medicine methods, and PITE in particular, have the potential to identify individuals most likely to benefit from one versus another intervention. New personalized medicine methods play an important role in putting together differential effects due to previously identified variables into one prediction designed to be useful to clinicians and clients choosing between treatment options. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

The Differential Importance of Component Skills on Reading Comprehension Test Performance Among Struggling Adolescent Readers.

Reading comprehension tests vary in format and characteristics, which may influence the extent to which component skills are involved in test performance. With students in Grades 6 to 8 with reading difficulties, dominance analyses examined the differential importance of component reading and language skills (word- and text-reading fluency, vocabulary, listening comprehension, and working memory) on several standardized tests of reading comprehension: The Gates-MacGinitie Reading Test, 4th edition (GMRT), Group Reading Assessment and Diagnostic Evaluation, Gray Oral Reading Test, 5th edition (GORT-5), and the Test of Silent Reading Efficiency and Comprehension (TOSREC). Students' word- and text-reading fluency skills were generally the most dominant predictors of performance on most reading comprehension tests, especially those with a time limit (GMRT and TOSREC). Listening comprehension was most important on the GORT-5, a test in which students read passages orally and listen to questions read by an examiner. Working memory was the least important component skill across the reading comprehension tests. Overall, results were consistent with previous work indicating that reading comprehension measures vary with regard to the skills or knowledge sources that are most important for test performance and extend these findings to struggling adolescent readers. Implications for research and practice are discussed.

Latent Class Mediation: A Comparison of Six Approaches.

Latent class mediation modeling is designed to estimate the mediation effect when both the mediator and the outcome are latent class variables. We suggest using an adjusted one-step approach in which the latent class models for the mediator and the outcome are estimated first to decide on the number of classes, then the latent class models and the mediation model are jointly estimated. We present both an empirical demonstration and a simulation study to compare the performance of this one-step approach to a standard three-step approach with modal assignment (modal) and four different modern three-step approaches. Results from the study indicate that unadjusted modal, which ignores the classification errors of the latent class models, produced biased mediation effects. On the other hand, the adjusted one-step approach and the modern three-step approaches performed well with respect to bias for estimating mediation effects, regardless of measurement quality (i.e., model entropy) and latent class size. Among the three-step approaches we investigated, the maximum likelihood method with modal assignment and the BCH correction with robust standard error estimators are good alternatives to the adjusted one-step approach, given their unbiased standard error estimations.

Resilience facilitates adjustment through greater psychological flexibility among Iraq/Afghanistan war veterans with and without mild traumatic brain injury.

OBJECTIVES: Although many Iraq/Afghanistan warzone veterans report few problems with adjustment, a substantial proportion report debilitating mental health symptoms and functional impairment, suggesting the influence of personal factors that may promote adjustment. A significant minority also incur warzone-related traumatic brain injury (TBI), the majority of which are of mild severity (mTBI). We tested direct and indirect pathways through which a resilient personality prototype predicts adjustment of warzone veterans with and without mTBI over time. METHOD: A sample of 264 war veterans (181 men) completed measures of lifetime and warzone-related TBIs, personality traits, psychological adjustment, quality of life, and functional impairment. Social support, coping, and psychological flexibility were examined as mediators of the resilience-adjustment relationship. Instruments were administered at baseline, 4-, 8-, and 12-month assessments. Structural equation models accounted for combat exposure and response style. RESULTS: Compared with a nonresilient personality prototype, a resilient prototype was directly associated with lower PTSD, depression, and functional disability, and higher quality of life at all time-points. Warzone mTBIs frequency was associated with higher scores on a measure of functional disability. Indirect effects via psychological flexibility were observed from personality to all outcomes, and from warzone-related mTBIs to PTSD, depression, and functional disability, at each time-point. CONCLUSIONS: Several characteristics differentiate veterans who are resilient from those who are less so. These findings reveal several factors through which a resilient personality prototype and the number of mTBIs may be associated with veteran adjustment. Psychological flexibility appears to be a critical modifiable factor in veteran adjustment. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Sensitivity Analysis of the No-Omitted Confounder Assumption in Latent Growth Curve Mediation Models.

Latent growth curve mediation models are increasingly used to assess mechanisms of behavior change. For latent growth mediation model, like any another mediation model, even with random treatment assignment, a critical but untestable assumption for valid and unbiased estimates of the indirect effects is that there should be no omitted variable that confounds indirect effects. One way to address this untestable assumption is to conduct sensitivity analysis to assess whether the inference about an indirect effect would change under varying degrees of confounding bias. We developed a sensitivity analysis technique for a latent growth curve mediation model. We compute the biasing effect of confounding on point and confidence interval estimates of the indirect effects in a structural equation modeling framework. We illustrate sensitivity plots to visualize the effects of confounding on each indirect effect and present an empirical example to illustrate the application of the sensitivity analysis.

The (Lack of) Replication of Self-Reported Mindfulness as a Mechanism of Change in Mindfulness-Based Relapse Prevention for Substance Use Disorders.

The development and evaluation of mindfulness-based interventions for a variety of psychological and medical disorders has grown exponentially over the past 20 years. Yet, calls for increasing the rigor of mindfulness research and recognition of the difficulties of conducting research on the topic of mindfulness have also increased. One of the major difficulties is the measurement of mindfulness, with varying definitions across studies and ambiguity with respect to the meaning of mindfulness. There is also concern about the reproducibility of findings given few attempts at replication. The current secondary analysis addressed the issue of reproducibility and robustness of the construct of self-reported mindfulness across two separate randomized clinical trials of mindfulness-based relapse prevention (MBRP), as an aftercare treatment for substance use disorder. Specifically, we tested the robustness of our previously published findings, which identified a latent construct of mindfulness as a significant mediator of the effect of MBRP on reducing craving following treatment. First, we attempted to replicate the findings in a separate randomized clinical trial of MBRP. Second, we conducted sensitivity analyses to test the assumption of the no-omitted confounder bias in a mediation model. The effect of MBRP on self-reported mindfulness and overall mediation effect failed to replicate in a new sample. The effect of self-reported mindfulness in predicting craving following treatment did replicate and was robust to the no-omitted confounder bias. The results of this work shine a light on the difficulties in the measurement of mindfulness and the importance of examining the robustness of findings.

The Impact of Partial Measurement Invariance on Testing Moderation for Single and Multi-Level Data.

Moderation effect is a commonly used concept in the field of social and behavioral science. Several studies regarding the implication of moderation effects have been done; however, little is known about how partial measurement invariance influences the properties of tests for moderation effects when categorical moderators were used. Additionally, whether the impact is the same across single and multilevel data is still unknown. Hence, the purpose of the present study is twofold: (a) To investigate the performance of the moderation test in single-level studies when measurement invariance does not hold; (b) To examine whether unique features of multilevel data, such as intraclass correlation (ICC) and number of clusters, influence the effect of measurement non-invariance on the performance of tests for moderation. Simulation results indicated that falsely assuming measurement invariance lead to biased estimates, inflated Type I error rates, and more gain or more loss in power (depends on simulation conditions) for the test of moderation effects. Such patterns were more salient as sample size and the number of non-invariant items increase for both single- and multi-level data. With multilevel data, the cluster size seemed to have a larger impact than the number of clusters when falsely assuming measurement invariance in the moderation estimation. ICC was trivially related to the moderation estimates. Overall, when testing moderation effects with categorical moderators, employing a model that accounts for the measurement (non)invariance structure of the predictor and/or the outcome is recommended.