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Description
Despite the established co-prevalence of substance use (SU) and disordered eating (DE), few longitudinal studies have sought to examine their shared development. Findings have been inconsistent within the extant literature. This may be attributable in part to several methodological aspects, including overlooking distinct psychopharmacological properties of common substances of abuse,

Despite the established co-prevalence of substance use (SU) and disordered eating (DE), few longitudinal studies have sought to examine their shared development. Findings have been inconsistent within the extant literature. This may be attributable in part to several methodological aspects, including overlooking distinct psychopharmacological properties of common substances of abuse, examining only between-person relations, and failing to account for shared risk factors. The current study sought to address these gaps by applying latent curve models with structured residuals (LCM-SR) to a preexisting, national sample of adolescent girls followed into adulthood, Add Health. In Aim 1, between-person effects examined the simultaneous development of alcohol, tobacco, and marijuana use and DE behaviors in substance-specific models. In Aim 2, bivariate latent curve models were expanded to account for within-person effects (LCM-SR) in order to examine the potentially bidirectional, prospective relationship between use of a specific substance and DE. Lastly, models accounted for shared developmental risk factors. Findings of the current study demonstrate preliminary evidence of substance-specific effects with DE emerging in adolescence. Across model-building steps, DE engagement in early adolescence was significantly associated with growth in tobacco use and marginally associated with marijuana use. Appetitive side-effects of both substances may link use with DE behaviors and enhance instrumental use for weight control. Significant associations did not emerge between alcohol and DE, and results of the conditional model indicate this co-occurrence is best explained by third variable mechanisms. Implications for prevention are discussed.
ContributorsBruening, Amanda B (Author) / Corbin, William (Thesis advisor) / Chassin, Laurie (Committee member) / Meier, Madeline (Committee member) / McNeish, Daniel (Committee member) / Arizona State University (Publisher)
Created2021
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Description
Attendance and engagement in available parenting interventions in both research and community settings is often inconsistent. Recent research suggests that varying the delivery modality of the intervention (i.e., in-person, telehealth, or online) has the potential to increase engagement with evidence-based parenting programs. However, while it is known that both facilitator

Attendance and engagement in available parenting interventions in both research and community settings is often inconsistent. Recent research suggests that varying the delivery modality of the intervention (i.e., in-person, telehealth, or online) has the potential to increase engagement with evidence-based parenting programs. However, while it is known that both facilitator and parent characteristics also influence engagement, no study has evaluated whether those characteristics moderate the influence that modality has on engagement. Utilizing data from the randomized controlled comparative effectiveness trial of the After Deployment, Adaptive Parenting Tools intervention, this study aimed to assess whether facilitators’ gender, military background, and competence moderated the effect of modality on parents’ engagement. Results suggested that parents were significantly more likely to have attended when they were randomized to the telehealth condition. Additionally, while there were no moderating relationships, female facilitators and facilitators who were more competent had overall higher attendance. Additionally, in the group format, facilitators with military backgrounds had higher engagement than those who did not. Understanding the effects that delivery modality and facilitators have on parental engagement is critical to continue and amplify implementation efforts in community settings.
ContributorsBasha, Sydni A. J. (Author) / Gewirtz, Abigail H (Thesis advisor) / Berkel, Cady (Committee member) / McNeish, Daniel (Committee member) / Arizona State University (Publisher)
Created2022
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Description
Mediation analysis is integral to psychology, investigating human behavior’s causal mechanisms. The diversity of explanations for human behavior has implications for the estimation and interpretation of statistical mediation models. Individuals can have similar observed outcomes while undergoing different causal processes or different observed outcomes while receiving the same treatment. Researchers

Mediation analysis is integral to psychology, investigating human behavior’s causal mechanisms. The diversity of explanations for human behavior has implications for the estimation and interpretation of statistical mediation models. Individuals can have similar observed outcomes while undergoing different causal processes or different observed outcomes while receiving the same treatment. Researchers can employ diverse strategies when studying individual differences in multiple mediation pathways, including individual fit measures and analysis of residuals. This dissertation investigates the use of individual residuals and fit measures to identify individual differences in multiple mediation pathways. More specifically, this study focuses on mediation model residuals in a heterogeneous population in which some people experience indirect effects through one mediator and others experience indirect effects through a different mediator. A simulation study investigates 162 conditions defined by effect size and sample size for three proposed methods: residual differences, delta z, and generalized Cook’s distance. Results indicate that analogs of Type 1 error rates are generally acceptable for the method of residual differences, but statistical power is limited. Likewise, neither delta z nor gCd could reliably distinguish between contrasts that had true effects and those that did not. The outcomes of this study reveal the potential for statistical measures of individual mediation. However, limitations related to unequal subpopulation variances, multiple dependent variables, the inherent relationship between direct effects and unestimated indirect effects, and minimal contrast effects require more research to develop a simple method that researchers can use on single data sets.
ContributorsSmyth, Heather Lynn (Author) / MacKinnon, David (Thesis advisor) / Tein, Jenn-Yun (Committee member) / McNeish, Daniel (Committee member) / Grimm, Kevin (Committee member) / Arizona State University (Publisher)
Created2022
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Description
Introduction: Edibles, THC-infused food products, are a popular type of cannabis. However, there is limited research on how acute effects of edibles differ from more traditional cannabis types, such as smoked flower (e.g., dried bud). The current study examined the subjective response of cannabis between smoked flower and edibles using

Introduction: Edibles, THC-infused food products, are a popular type of cannabis. However, there is limited research on how acute effects of edibles differ from more traditional cannabis types, such as smoked flower (e.g., dried bud). The current study examined the subjective response of cannabis between smoked flower and edibles using a two-week long ecological momentary assessment (EMA). Sex differences were also examined.Method: Individuals (n=101) using both edibles and flower at least once weekly completed a cannabis report within 30 minutes (T1) of first cannabis use each day as well as two follow-up reports sent 1.5 (T2) and 3 hours (T3) after initial use. Participants additionally completed assessments throughout the day for fourteen consecutive days to examine daily affect. Multi-level models examined whether overall high, low-arousal negative effects, high-arousal negative effects, and general positive effects differed by edibles and flower. Given time differences in effects between cannabis types, subjective effects were examined at T1, T2, and T3, as well as for the peak effects across the three-hour time window. Covariates included demographics, variant- and invariant- cannabis use characteristics, and daily affect. Results: At T1, edibles produced lesser positive effects (b=-0.60, S.E.=0.16, p=0.001) and overall high (b=-2.00, S.E.=0.27, p<0.001) relative to flower. At T2, edibles produced greater positive effects (b=0.52, S.E.=0.21, p=0.01) relative to flower. At T3, edibles produced greater low-arousal negative effects (b=0.63, S.E.=0.23, p=0.01) relative to flower. Edibles produced greater peak low-arousal effects relative to flower (b=0.59, S.E.=0.21, p=0.01), With respect to sex differences, there was an interaction between sex and cannabis type at T1 for positive effects (b=-0.99, S.E.=0.31, p=0.001), such that males reported greater positive effects for flower. Males additionally reported lesser low-arousal effects at T1 (b=-0.60, S.E.=0.30, p=0.05) and greater overall high at T3 relative to females (b=1.24, S.E.=0.56, p=0.03). Discussion: Smoked flower produced greater effects immediately and edibles produced greater delayed effects. Edibles appear to have greater peak levels of low-arousal effects (e.g., sluggish, drowsy, slow) relative to smoked flower. Males may be more sensitive to the rewarding effects of cannabis, particularly when smoking flower.
ContributorsOkey, Sarah (Author) / Corbin, William (Thesis advisor) / Doane, Leah (Committee member) / Cruz, Rick (Committee member) / McNeish, Daniel (Committee member) / Arizona State University (Publisher)
Created2023
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Description
This project studied a four-variable single mediator model, a single mediator model: X (independent variable) to M (mediator) to Y (dependent variable), and a confounder (U) that influences M and Y. Confounding represents a threat to the causal interpretation in mediation analysis. For instance, if X represents random assignment to

This project studied a four-variable single mediator model, a single mediator model: X (independent variable) to M (mediator) to Y (dependent variable), and a confounder (U) that influences M and Y. Confounding represents a threat to the causal interpretation in mediation analysis. For instance, if X represents random assignment to control and treatment conditions, the effect of X on M and the effect of X on Y have a causal interpretation under certain reasonable assumptions. However, the randomization of X does not allow for a causal interpretation of the M to Y effect unless certain confounding assumptions are satisfied. The aim of this project was to develop a significance test and an effect size comparison for two sensitivity to confounding analyses methods: Left Out Variables Error (L.O.V.E.) and the correlated residuals method. Further, the project assessed the accuracy of the methods for identifying confounding bias by simulating data with and without confounding bias.
ContributorsAlvarez Bartolo, Diana (Author) / Mackinnon, David P. (Thesis advisor) / Grimm, Kevin J. (Committee member) / McNeish, Daniel (Committee member) / Arizona State University (Publisher)
Created2022