RESUMO
There is evidence for intergenerational transmission of substance use and disorder. However, it is unclear whether separation from a parent with substance use disorder (SUD) moderates intergenerational transmission, and no studies have tested this question across three generations. In a three-generation study of families oversampled for familial SUD, we tested whether separation between father (G1; first generation) and child (G2; second generation) moderated the effect of G1 father SUDs on G2 child SUDs. We also tested whether separation between father (G2) and child (G3; third generation) moderated the effect of G2 SUDs on G3 drinking. Finally, we tested whether G1-G2 or G2-G3 separation moderated the mediated effect of G1 SUDs on G3 drinking through G2 SUDs. G1 father-G2 child separation moderated intergenerational transmission. In families with G1-G2 separation, there were no significant effects of father SUD on G2 SUD or G3 drinking. However, in nonseparated families, greater G1 father SUDs predicted heightened G2 SUDs and G3 grandchild drinking. In nonseparated families, G1 father SUDs significantly predicted G2 SUDs, which predicted G3 drinking. However, G2-G3 separation predicted heightened G3 drinking regardless of G2 and G1 SUDs. Parental separation may introduce risk for SUDs and drinking among youth with lower familial risk.
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Pais , Transtornos Relacionados ao Uso de Substâncias , Adolescente , Humanos , Transtornos Relacionados ao Uso de Substâncias/genética , Relação entre Gerações , Relações Pais-FilhoRESUMO
PURPOSE: There is variable and suboptimal use of fascia iliaca compartment nerve blocks (FICBs) in hip fracture care. Our objective was to use an evidence-based and theory-informed implementation science approach to analyze barriers and facilitators to timely administration of FICB and select evidence-based interventions to enhance uptake. METHODS: We conducted a qualitative study at a single centre using semistructured interviews and site observations. We interviewed 35 stakeholders including health care providers, managers, patients, and caregivers. We mapped barriers and facilitators to the Theoretical Domains Framework (TDF) and Consolidated Framework for Implementation Research (CFIR). We compared the rate and timeliness of FICB administration before and after evidence-based implementation strategies were applied. RESULTS: The study identified 18 barriers and 11 facilitators within seven themes of influences of FICB use: interpersonal relationships between health care professionals; clinician knowledge and skills related to FICB; roles, responsibilities, and processes for delivering FICB; perceptions on using FICB for pain; patient and caregiver perceptions on using FICB for pain; communication of hip fracture care between departments; and resources for delivering FICBs. We mapped the behaviour change domains to eight implementation strategies: restructure the environment, create and distribute educational materials, prepare patients to be active participants, perform audits and give feedback, use local opinion leaders, use champions, train staff on FICB procedures, and mandate change. We observed an increase in the rates of FICBs administered (48% vs 65%) and a decrease in the median time to administration (1.63 vs 0.81 days). CONCLUSION: Our study explains why FICBs are underused and shows that the TDF and CFIR provide a framework to identify barriers and facilitators to FICB implementation. The mapped implementation strategies can guide institutions to improve use of FICB in hip fracture care.
RéSUMé: OBJECTIF: Il existe une utilisation variable et sous-optimale des blocs nerveux du compartiment fascia iliaca (FICB) dans les soins des fractures de la hanche. Notre objectif était d'utiliser une approche scientifique de la mise en Åuvre fondée sur des données probantes et sur la théorie pour analyser les obstacles et les facilitateurs à l'administration opportune d'un FICB et pour sélectionner des interventions fondées sur des données probantes pour améliorer l'adoption de cette technique. MéTHODE: Nous avons mené une étude qualitative dans un seul centre à l'aide d'entrevues semi-structurées et d'observations sur place. Nous avons interviewé 35 intervenant·es, y compris des prestataires de soins de santé, des gestionnaires, des patient·es et des soignant·es. Nous avons cartographié les obstacles et les facilitateurs du cadre des domaines théoriques (Theoretical Domains Framework, TDF) et du cadre consolidé pour la recherche sur la mise en Åuvre (Consolidated Framework for Implementation Research, CFIR). Nous avons comparé le taux et la rapidité d'administration d'un FICB avant et après l'application des stratégies de mise en Åuvre fondées sur des données probantes. RéSULTATS: L'étude a identifié 18 obstacles et 11 facilitateurs dans sept thèmes d'influence de l'utilisation du FICB : les relations interpersonnelles entre les professionnel·les de la santé; les connaissances et les compétences des clinicien·nes liées au FICB; les rôles, responsabilités et processus d'exécution des FICB; les perceptions de l'utilisation des FICB pour soulager la douleur; les perceptions des patient·es et des soignant·es concernant l'utilisation de FICB pour soulager la douleur; la communication des soins des fractures de la hanche entre les services; et les ressources nécessaires à l'exécution des FICB. Nous avons mis en correspondance les domaines de changement de comportement avec huit stratégies de mise en Åuvre : restructurer l'environnement, créer et distribuer du matériel éducatif, préparer les patient·es à participer activement, effectuer des audits et donner de la rétroaction, faire appel à des leaders d'opinion locales et locaux, utiliser des champion·nes, former le personnel sur les interventions de FICB et forcer au changement. Nous avons observé une augmentation des taux de FICB administrés (48% vs 65%) et une diminution du délai médian d'administration (1,63 vs 0,81 jour). CONCLUSION: Notre étude explique pourquoi les FICB sont sous-utilisés et montre que le TDF et le CFIR fournissent un cadre pour identifier les obstacles et les facilitateurs à la mise en Åuvre des FICB. Les stratégies de mise en Åuvre cartographiées peuvent aider les établissements à améliorer l'utilisation des FICB dans le traitement des fractures de la hanche.
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Mediation analysis is an important statistical method in prevention research, as it can be used to determine effective intervention components. Traditional mediation analysis defines direct and indirect effects in terms of linear regression coefficients. It is unclear how these traditional effects are estimated in settings with binary variables. An important recent methodological advancement in the mediation analysis literature is the development of the causal mediation analysis framework. Causal mediation analysis defines causal effects as the difference between two potential outcomes. These definitions can be applied to any mediation model to estimate natural direct and indirect effects, including models with binary variables and an exposure-mediator interaction. This paper aims to clarify the similarities and differences between the causal and traditional effect estimates for mediation models with a binary mediator and a binary outcome. Causal and traditional mediation analyses were applied to an empirical example to demonstrate these similarities and differences. Causal and traditional mediation analysis provided similar controlled direct effect estimates, but different estimates of the natural direct effects, natural indirect effects, and total effect. Traditional mediation analysis methods do not generalize well to mediation models with binary variables, while the natural effect definitions can be applied to any mediation model. Causal mediation analysis is therefore the preferred method for the analysis of mediation models with binary variables.
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Análise de Mediação , Projetos de Pesquisa , Humanos , Causalidade , Modelos Lineares , Modelos EstatísticosRESUMO
OBJECTIVE: Naltrexone is an effective treatment for heavy drinking among young adults. Laboratory-based studies have shown that naltrexone dampens the subjective response to alcohol and craving. However, few studies have tested naltrexone's dynamic, within-person effects on subjective response and craving among young adults in natural drinking environments. METHODS: Using daily diary data from a randomized, placebo-controlled study of naltrexone's efficacy in young adults, we examined the between-person effects of treatment condition (i.e., naltrexone vs. placebo) and medication dosage (i.e., daily, targeted, and daily + targeted) on the subjective response to alcohol and craving on drinking days. Multilevel mediation models predicted subjective response and craving from treatment condition (between-person) and medication dosage (within-person), accounting for drinking levels. All effects were disaggregated within and between persons. RESULTS: At the between-person level, naltrexone directly blunted intense subjective effects (i.e., "impaired", "drunk") and indirectly blunted subjective effects through reduced drinking. Naltrexone was not associated with craving. Between-person effects were not significant after alpha correction, but their effect sizes (bs = 0.14 to 0.17) exceeded the smallest effect size of interest. At the within-person level, taking two (vs. 1) pills was associated with heavier drinking, and taking one (vs. 0) pill was associated with lighter drinking, and lighter drinking was associated with a lower subjective response and craving. Treatment condition did not moderate the within-person effects of dosing on outcomes. CONCLUSIONS: Our findings suggest that the direct between-person effect of naltrexone was largest on intense subjective responses, blunting feelings of being "drunk" and "impaired". Future research using momentary (rather than daily) assessments could confirm and extend these findings.
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Alcoolismo , Naltrexona , Consumo de Bebidas Alcoólicas/tratamento farmacológico , Alcoolismo/tratamento farmacológico , Fissura , Método Duplo-Cego , Etanol/farmacologia , Humanos , Naltrexona/farmacologia , Naltrexona/uso terapêutico , Antagonistas de Entorpecentes/farmacologia , Antagonistas de Entorpecentes/uso terapêutico , Adulto JovemRESUMO
The ability to regulate behavior in service of long-term goals is a widely studied psychological construct known as self-regulation. This wide interest is in part due to the putative relations between self-regulation and a range of real-world behaviors. Self-regulation is generally viewed as a trait, and individual differences are quantified using a diverse set of measures, including self-report surveys and behavioral tasks. Accurate characterization of individual differences requires measurement reliability, a property frequently characterized in self-report surveys, but rarely assessed in behavioral tasks. We remedy this gap by (i) providing a comprehensive literature review on an extensive set of self-regulation measures and (ii) empirically evaluating test-retest reliability of this battery in a new sample. We find that dependent variables (DVs) from self-report surveys of self-regulation have high test-retest reliability, while DVs derived from behavioral tasks do not. This holds both in the literature and in our sample, although the test-retest reliability estimates in the literature are highly variable. We confirm that this is due to differences in between-subject variability. We also compare different types of task DVs (e.g., model parameters vs. raw response times) in their suitability as individual difference DVs, finding that certain model parameters are as stable as raw DVs. Our results provide greater psychometric footing for the study of self-regulation and provide guidance for future studies of individual differences in this domain.
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Testes Psicológicos/normas , Autocontrole , Humanos , Individualidade , Modelos Estatísticos , Reprodutibilidade dos Testes , Autorrelato/normas , Autocontrole/psicologiaRESUMO
Science is an inherently cumulative process, and knowledge on a specific topic is organized through synthesis of findings from related studies. Meta-analysis has been the most common statistical method for synthesizing findings from multiple studies in prevention science and other fields. In recent years, Bayesian statistics have been put forth as another way to synthesize findings and have been praised for providing a natural framework for update existing knowledge with new data. This article presents a Bayesian method for cumulative science and describes a SAS macro %SBDS for synthesizing findings from multiple studies or multiple data sets from a single study using three different methods: meta-analysis using raw data, sequential Bayesian data synthesis, and a single-level analysis on pooled data. Sequential Bayesian data synthesis and Bayesian statistics in general are discussed in an accessible manner, and guidelines are provided on how researchers can use the accompanying SAS macro for synthesizing data from their own studies. Four alcohol use studies were used to demonstrate how to apply the three data synthesis methods using the SAS macro.
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Teorema de Bayes , Humanos , Análise de RegressãoRESUMO
The literature on latent change score models does not discuss the importance of using a precise time metric when structuring the data. This study examined the influence of time metric precision on model estimation, model interpretation, and parameter estimate accuracy in bivariate LCS (BLCS) models through simulation. Longitudinal data were generated with a panel study where assessments took place during a given time window with variation in start time and measurement lag. The data were analyzed using precise time metric, where variation in time was accounted for, and then analyzed using coarse time metric indicating only that the assessment took place during the time window. Results indicated that models estimated using the coarse time metric resulted in biased parameter estimates as well as larger standard errors and larger variances and covariances for intercept and slope. In particular, the coupling parameter estimates-which are unique to BLCS models-were biased with larger standard errors. An illustrative example of longitudinal bivariate relations between math and reading achievement in a nationally representative survey of children is then used to demonstrate how results and conclusions differ when using time metrics of varying precision. Implications and future directions are discussed.
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Logro , Leitura , Criança , Simulação por Computador , Humanos , MatemáticaRESUMO
BACKGROUND: Low-intensity psychosocial interventions have been effective in targeting perinatal depression, but relevant mechanisms of change remain unknown. AIMS: To examine three theoretically informed mediators of the Thinking Healthy Programme Peer-delivered (THPP), an evidence-based psychosocial intervention for perinatal depression, on symptom severity in two parallel, randomised controlled trials in Goa, India and Rawalpindi, Pakistan. METHOD: Participants included pregnant women aged ≥18 years with moderate to severe depression, as defined by a Patient Health Questionnaire 9 (PHQ-9) score ≥10, and were randomised to either THPP or enhanced usual care. We examine whether three prespecified variables (patient activation, social support and mother-child attachment) at 3 months post-childbirth mediated the effects of THPP interventions of perinatal depressive symptom severity (PHQ-9) at the primary end-point of 6 months post-childbirth. We first examined individual mediation within each trial (n = 280 in India and n = 570 in Pakistan), followed by a pooled analysis across both trials (N = 850). RESULTS: In both site-specific and pooled analyses, patient activation and support at 3 months independently mediated the intervention effects on depressive symptom severity at 6 months, accounting for 23.6 and 18.2% of the total effect of THPP, respectively. The intervention had no effect on mother-child attachment scores, thus there was no evidence that this factor mediated the intervention effect. CONCLUSIONS: The effects of the psychosocial intervention on depression outcomes in mothers were mediated by the same two factors in both contexts, suggesting that such interventions seeking to alleviate perinatal depression should target both social support and patient activation levels. DECLARATION OF INTEREST: None.
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Depressão , Análise de Mediação , Adolescente , Adulto , Criança , Depressão/terapia , Feminino , Humanos , Índia , Paquistão , Grupo Associado , GravidezRESUMO
BACKGROUND: Mediation analysis methodology underwent many advancements throughout the years, with the most recent and important advancement being the development of causal mediation analysis based on the counterfactual framework. However, a previous review showed that for experimental studies the uptake of causal mediation analysis remains low. The aim of this paper is to review the methodological characteristics of mediation analyses performed in observational epidemiologic studies published between 2015 and 2019 and to provide recommendations for the application of mediation analysis in future studies. METHODS: We searched the MEDLINE and EMBASE databases for observational epidemiologic studies published between 2015 and 2019 in which mediation analysis was applied as one of the primary analysis methods. Information was extracted on the characteristics of the mediation model and the applied mediation analysis method. RESULTS: We included 174 studies, most of which applied traditional mediation analysis methods (n = 123, 70.7%). Causal mediation analysis was not often used to analyze more complicated mediation models, such as multiple mediator models. Most studies adjusted their analyses for measured confounders, but did not perform sensitivity analyses for unmeasured confounders and did not assess the presence of an exposure-mediator interaction. CONCLUSIONS: To ensure a causal interpretation of the effect estimates in the mediation model, we recommend that researchers use causal mediation analysis and assess the plausibility of the causal assumptions. The uptake of causal mediation analysis can be enhanced through tutorial papers that demonstrate the application of causal mediation analysis, and through the development of software packages that facilitate the causal mediation analysis of relatively complicated mediation models.
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Análise de Mediação , Projetos de Pesquisa , Causalidade , Estudos Epidemiológicos , Humanos , Modelos Estatísticos , Estudos Observacionais como AssuntoRESUMO
Knowledge of causal processes through mediation analysis can help improve the effectiveness and reduce costs of public health programs, like HIV prevention and treatment interventions. Advancements in mediation using the potential outcomes framework provide a method for estimating the causal effect of interventions on outcomes via a mediating variable. The purpose of this paper is to provide practical information about mediation and the potential outcomes framework that can enhance data analysis and causal inference for intervention studies. Causal mediation effects are defined and then estimated using data from an HIV intervention randomized trial among people who inject drugs (PWID) in Ukraine. Results from a potential outcomes mediation analysis show that the intervention had a total causal effect on incident HIV infection such that participants in the experimental group were 36% less likely to become infected during the 12-month study than those in the control arm, but that neither self-efficacy nor network communication mediated this effect. Because neither putative mediator was significant, measurement and confounding issues should be investigated to rule out these mediators. Other putative mediators, such as injection frequency, route of administration, or HIV knowledge can be considered. Future research is underway to examine additional, multiple mediators explaining efficacy of the current intervention and sensitivity to confounding effects.
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Infecções por HIV , Causalidade , Infecções por HIV/epidemiologia , Infecções por HIV/prevenção & controle , Humanos , Negociação , Autoeficácia , UcrâniaRESUMO
Third-variable effects, such as mediation and confounding, are core concepts in prevention science, providing the theoretical basis for investigating how risk factors affect behavior and how interventions change behavior. Another third variable, the collider, is not commonly considered but is also important for prevention science. This paper describes the importance of the collider effect as well as the similarities and differences between these three third-variable effects. The single mediator model in which the third variable (T) is a mediator of the independent variable (X) to dependent variable (Y) effect is used to demonstrate how to estimate each third-variable effect. We provide difference in coefficients and product of coefficients estimators of the effects and demonstrate how to calculate these values with real data. Suppression effects are defined for each type of third-variable effect. Future directions and implications of these results are discussed.
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Medicina Preventiva , Humanos , Fatores de RiscoRESUMO
In psychology, there have been vast creative efforts in proposing new constructs and developing measures to assess them. Less effort has been spent in investigating construct overlap to prevent bifurcated literatures, wasted research efforts, and jingle-jangle fallacies. For example, researchers could gather validity evidence to evaluate if two measures with the same label actually assess different constructs (jingle fallacy), or if two measures with different labels actually assess the same construct (jangle fallacy). In this paper, we discuss the concept of extrinsic convergent validity, a source of validity evidence demonstrated when two measures of the same construct, or two measures of seemingly different constructs, have comparable correlations with external criteria. We introduce a formal approach to obtain extrinsic convergent validity evidence using tests of dependent correlations and evaluate the tests using Monte Carlo simulations. Also, we illustrate the methods by examining the overlap between the self-control and grit constructs, and the overlap among seven seemingly different measures of the connectedness to nature construct. Finally, we discuss how extrinsic convergent validity evidence supplements other sources of evidence that support validity arguments of construct overlap.
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Reprodutibilidade dos Testes , PsicometriaRESUMO
In manifest variable models, Bayesian methods for mediation analysis can have better statistical properties than commonly used frequentist methods. However, with latent variables, Bayesian mediation analysis with diffuse priors can yield worse statistical properties than frequentist methods, and no study to date has evaluated the impact of informative priors on statistical properties of point and interval summaries of the mediated effect. This article describes the first examination of using fully conjugate and informative (accurate and inaccurate) priors in Bayesian mediation analysis with latent variables. Results suggest that fully conjugate priors and informative priors with the same relative prior sample sizes have notably different effects at N = 200 and 400, than at N = 50 and 100. Consequences of a small amount of inaccuracy in priors for loadings can be alleviated by making the prior less informative, whereas the same is not always true of inaccuracy in priors for structural paths. Finally, the consequences of using informative priors depend on the inferential goals of the analysis: inaccurate priors are more detrimental for accurately estimating the mediated effect than for evaluating whether the mediated effect is nonzero. Recommendations are provided about when to gainfully employ Bayesian mediation analysis with latent variables.
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Modelos Estatísticos , Teorema de Bayes , Tamanho da AmostraRESUMO
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.
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Modelos Estatísticos , Viés , Simulação por Computador , Análise de Classes LatentesRESUMO
Wayne Velicer is remembered for a mind where mathematical concepts and calculations intrigued him, behavioral science beckoned him, and people fascinated him. Born in Green Bay, Wisconsin on March 4, 1944, he was raised on a farm, although early influences extended far beyond that beginning. His Mathematics BS and Psychology minor at Wisconsin State University in Oshkosh, and his PhD in Quantitative Psychology from Purdue led him to a fruitful and far-reaching career. He was honored several times as a high-impact author, was a renowned scholar in quantitative and health psychology, and had more than 300 scholarly publications and 54,000+ citations of his work, advancing the arenas of quantitative methodology and behavioral health. In his methodological work, Velicer sought out ways to measure, synthesize, categorize, and assess people and constructs across behaviors and time, largely through principal components analysis, time series, and cluster analysis. Further, he and several colleagues developed a method called Testing Theory-based Quantitative Predictions, successfully applied to predicting outcomes and effect sizes in smoking cessation, diet behavior, and sun protection, with the potential for wider applications. With $60,000,000 in external funding, Velicer also helped engage a large cadre of students and other colleagues to study methodological models for a myriad of health behaviors in a widely applied Transtheoretical Model of Change. Unwittingly, he has engendered indelible memories and gratitude to all who crossed his path. Although Wayne Velicer left this world on October 15, 2017 after battling an aggressive cancer, he is still very present among us.
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Medicina do Comportamento , Tutoria , HumanosRESUMO
Importance: Mediation analyses of randomized trials and observational studies can generate evidence about the mechanisms by which interventions and exposures may influence health outcomes. Publications of mediation analyses are increasing, but the quality of their reporting is suboptimal. Objective: To develop international, consensus-based guidance for the reporting of mediation analyses of randomized trials and observational studies (A Guideline for Reporting Mediation Analyses; AGReMA). Design, Setting, and Participants: The AGReMA statement was developed using the Enhancing Quality and Transparency of Health Research (EQUATOR) methodological framework for developing reporting guidelines. The guideline development process included (1) an overview of systematic reviews to assess the need for a reporting guideline; (2) review of systematic reviews of relevant evidence on reporting mediation analyses; (3) conducting a Delphi survey with panel members that included methodologists, statisticians, clinical trialists, epidemiologists, psychologists, applied clinical researchers, clinicians, implementation scientists, evidence synthesis experts, representatives from the EQUATOR Network, and journal editors (n = 19; June-November 2019); (4) having a consensus meeting (n = 15; April 28-29, 2020); and (5) conducting a 4-week external review and pilot test that included methodologists and potential users of AGReMA (n = 21; November 2020). Results: A previously reported overview of 54 systematic reviews of mediation studies demonstrated the need for a reporting guideline. Thirty-three potential reporting items were identified from 3 systematic reviews of mediation studies. Over 3 rounds, the Delphi panelists ranked the importance of these items, provided 60 qualitative comments for item refinement and prioritization, and suggested new items for consideration. All items were reviewed during a 2-day consensus meeting and participants agreed on a 25-item AGReMA statement for studies in which mediation analyses are the primary focus and a 9-item short-form AGReMA statement for studies in which mediation analyses are a secondary focus. These checklists were externally reviewed and pilot tested by 21 expert methodologists and potential users, which led to minor adjustments and consolidation of the checklists. Conclusions and Relevance: The AGReMA statement provides recommendations for reporting primary and secondary mediation analyses of randomized trials and observational studies. Improved reporting of studies that use mediation analyses could facilitate peer review and help produce publications that are complete, accurate, transparent, and reproducible.
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Guias como Assunto , Análise de Mediação , Estudos Observacionais como Assunto , Ensaios Clínicos Controlados Aleatórios como Assunto , Lista de Checagem , Técnica Delphi , Humanos , Revisão por Pares , Revisões Sistemáticas como AssuntoRESUMO
Self-regulation is studied across various disciplines, including personality, social, cognitive, health, developmental, and clinical psychology; psychiatry; neuroscience; medicine; pharmacology; and economics. Widespread interest in self-regulation has led to confusion regarding both the constructs within the nomological network of self-regulation and the measures used to assess these constructs. To facilitate the integration of cross-disciplinary measures of self-regulation, we estimated product-moment and distance correlations among 60 cross-disciplinary measures of self-regulation (23 self-report surveys, 37 cognitive tasks) and measures of health and substance use based on 522 participants. The correlations showed substantial variability, though the surveys demonstrated greater convergent validity than did the cognitive tasks. Variables derived from the surveys only weakly correlated with variables derived from the cognitive tasks (M = .049, range = .000 to .271 for the absolute value of the product-moment correlation; M = .085, range = .028 to .241 for the distance correlation), thus challenging the notion that these surveys and cognitive tasks measure the same construct. We conclude by outlining several potential uses for this publicly available database of correlations.
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Cognição , Personalidade , Autorrelato , Autocontrole , Transtornos Relacionados ao Uso de Substâncias/psicologia , Adulto , Feminino , Humanos , Masculino , Psicometria , Reprodutibilidade dos Testes , Autoimagem , Inquéritos e QuestionáriosRESUMO
METHOD: Two hundred Hispanic emerging adults from Arizona (n = 99) and Florida (n = 101) completed a cross-sectional survey, and data were analyzed using hierarchical multiple regression and moderation analyses. RESULTS: Higher social media discrimination was associated with higher symptoms of depression and generalized anxiety. Moderation analyses indicated that higher social media discrimination was only associated with symptoms of depression and generalized anxiety among men, but not women. CONCLUSION: This is likely the first study on social media discrimination and mental health among emerging adults; thus, expanding this emerging field of research to a distinct developmental period.
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Ansiedade/psicologia , Depressão/psicologia , Hispânico ou Latino/psicologia , Racismo/psicologia , Mídias Sociais , Ansiedade/epidemiologia , Estudos Transversais , Depressão/epidemiologia , Feminino , Humanos , Masculino , Fatores Sexuais , Adulto JovemRESUMO
Mediation analysis is a methodology used to understand how and why behavioral phenomena occur. New mediation methods based on the potential outcomes framework are a seminal advancement for mediation analysis because they focus on the causal basis of mediation. Despite the importance of the potential outcomes framework in other fields, the methods are not well known in prevention and other disciplines. The interaction of a treatment (X) and a mediator (M) on an outcome variable (Y) is central to the potential outcomes framework for causal mediation analysis and provides a way to link traditional and modern causal mediation methods. As described in the paper, for a continuous mediator and outcome, if the XM interaction is zero, then potential outcomes estimators of the mediated effect are equal to the traditional model estimators. If the XM interaction is nonzero, the potential outcomes estimators correspond to simple direct and simple mediated contrasts for the treatment and the control groups in traditional mediation analysis. Links between traditional and causal mediation estimators clarify the meaning of potential outcomes framework mediation quantities. A simulation study demonstrates that testing for a XM interaction that is zero in the population can reduce power to detect mediated effects, and ignoring a nonzero XM interaction in the population can also reduce power to detect mediated effects in some situations. We recommend that prevention scientists incorporate evaluation of the XM interaction in their research.
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Medicina Preventiva , Pesquisa , Análise de Causa Fundamental , Algoritmos , Interpretação Estatística de Dados , Humanos , Ensaios Clínicos Controlados Aleatórios como Assunto , Transtornos Relacionados ao Uso de Substâncias/prevenção & controle , Congêneres da TestosteronaRESUMO
Two methods from the potential outcomes framework - inverse propensity weighting (IPW) and sequential G-estimation - were evaluated and compared to linear regression for estimating the mediated effect in a two-wave design with a randomized intervention and continuous mediator and outcome. Baseline measures of the mediator and outcome can be considered confounders of the follow-up mediator - outcome relation for which adjustment is necessary to eliminate bias. To adjust for baseline measures of the mediator and outcome, IPW uses stabilized inverse propensity weights whereas sequential G-estimation uses regression adjustment. Theoretical differences between the models are described, and Monte Carlo simulations compared the performance of linear regression; IPW without weight truncation; IPW with weights truncated at the 1st/99th, 5th/95th, and 10th/90th percentiles; and sequential G-estimation. Sequential G-estimation performed similarly to linear regression, but IPW provided a biased estimate of the mediated effect, lower power, lower confidence interval coverage, and higher mean squared error. Simulation results show that IPW failed to fully adjust the follow-up mediator - outcome relation for confounding due to the baseline measures. We then compared the mediated effect estimates using data from a randomized experiment evaluating a steroid prevention program for high school athletes. Implications and future directions are discussed.