ArticleMultivariate behavioral research2013
An Idiographic Examination of Day-to-Day Patterns of Substance Use Craving, Negative Affect and Tobacco Use among Young Adults in Recovery.
Article in Multivariate behavioral research, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 1 of them a synthesis that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
21 citing papers in PubMed, 1 synthesis or guideline pooled it, 37 citations in OpenAlex.
- A meta-analytic review of the effectiveness of mood inductions in eliciting emotion-based behavioral risk-taking and craving in the laboratory.Emotion (Washington, D.C.) · 2023Pooled it
- Ecological momentary assessments and interventions for youth substance use across clinical settings: A systematic review.Research square · 2026Article
- Non-death losses experienced by Black adults who use opioids.Journal of loss & trauma · 2026Article
- Developing a collegiate recovery program from the ground up: identifying priorities, promoting collaboration, assessing needs, and offering recommendations.Addiction science & clinical practice · 2025Article
- Modeling Idiographic Longitudinal Relationships between Affect and Cigarette Use: An Ecological Momentary Assessment Study.Substance use & misuse · 2023Article
- Examining Within- and Between-Person Facets of Negative Affect and Associations with Daily Craving Among Young Adults in Substance Use Disorder Recovery.Addiction research & theory · 2023Article
- "Can we get a Black rehabilitation center"? Factors impacting the treatment experiences of Black people who use opioids.Journal of substance abuse treatment · 2022Article
- Efficient estimation of bounded gradient-drift diffusion models for affect on CPU and GPU.Behavior research methods · 2022Article
- Penalized Estimation and Forecasting of Multiple Subject Intensive Longitudinal Data.Psychometrika · 2022Article
- Examining the effect of exercise on the relationship between affect and cravings among smokers engaged in cessation treatment.Addictive behaviors · 2022Article
- Health Label and Behavioral Feature Prediction Using Bayesian Hierarchical Vector Autoregression Models.Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference · 2021Article
- College programming for students in addiction recovery: A PRISMA-guided scoping review.Addictive behaviors · 2021Article
- The Affective Ising Model: A computational account of human affect dynamics.PLoS computational biology · 2020Article
- A Bayesian Vector Autoregressive Model with Nonignorable Missingness in Dependent Variables and Covariates: Development, Evaluation, and Application to Family Processes.Structural equation modeling : a multidisciplinary journal · 2020Article
- Involving stakeholders in the design of ecological momentary assessment research: An example from smoking cessation.PloS one · 2019Article
- Bayesian hierarchical vector autoregressive models for patient-level predictive modeling.PloS one · 2018Article
- Recovery schools for improving behavioral and academic outcomes among students in recovery from substance use disorders: a systematic review.Campbell systematic reviews · 2018Article
- The Clinical Trials Mosaic: Toward a Range of Clinical Trials Designs to Optimize Evidence-Based Treatment.Journal for person-oriented research · 2017Article
- As Good as GOLD: Gram-Schmidt Orthogonalization by Another Name.Psychometrika · 2016Article
- Illustrating idiographic methods for translation research: moderation effects, natural clinical experiments, and complex treatment-by-subgroup interactions.Translational behavioral medicine · 2016Article
Corrections and comments
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Authors and funding
5 authors at 3 institutions in 1 country.
Funding
Abstract
Psychological constructs, such as negative affect and substance use cravings that closely predict relapse, show substantial intra-individual day-to-day variability. This intra-individual variability of relevant psychological states combined with the "one day of a time" nature of sustained abstinence warrant a day-to-day investigation of substance use recovery. This study examines day-to-day associations among substance use cravings, negative affect, and tobacco use among 30 college students in 12-step recovery from drug and alcohol addictions. To account for individual variability in day-to-day process, it applies an idiographic approach. The sample of 20 males and 10 females (mean age = 21) was drawn from members of a collegiate recovery community at a large university. Data were collected with end-of-day data collections taking place over an average of 26.7 days. First-order vector autoregression models were fit to each individual predicting daily levels of substance use cravings, negative affect, and tobacco use from the same three variables one day prior. Individual model results demonstrated substantial inter-individual differences in intra-individual recovery process. Based on estimates from individual models, cluster analyses were used to group individuals into two homogeneous subgroups. Group comparisons demonstrate distinct patterns in the day-to-day associations among substance use cravings, negative affect, and tobacco use, suggesting the importance of idiographic approaches to recovery management and that the potential value of focusing on negative affect or tobacco use as prevention targets depends on idiosyncratic processes.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.