ReviewAddictive behaviors2018
Advancing statistical analysis of ambulatory assessment data in the study of addictive behavior: A primer on three person-oriented techniques.
Review in Addictive behaviors, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.
What it found
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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
11 citing papers in PubMed, 1 synthesis or guideline pooled it.
- A meta-analysis on the affect regulation function of real-time self-injurious thoughts and behaviours.Nature human behaviour · 2022Pooled it
- Monthly patterns of depressive symptoms and substance use and their relation to longer-term hazardous substance use and mental health problems: Examining mutual maintenance using monthly data from young adults.Addictive behaviors · 2025Article
- Positioning adolescence in the developmental timeline.Journal of research on adolescence : the official journal of the Society for Research on Adolescence · 2024Article
- The link between daily affective complexity and anxiety is altered by oral contraceptive use.International journal of psychophysiology : official journal of the International Organization of Psychophysiology · 2024Article
- Using the experience sampling method to support clinical practice: An illustration with problematic cannabis use.Psychotherapy research : journal of the Society for Psychotherapy Research · 2024Article
- Commentary on Stull et al.: Considering person-specific heterogeneity when modeling time-varying trends.Addiction (Abingdon, England) · 2023Article
- Examining Associations Between Negative Affect and Substance Use in Treatment-Seeking Samples: A Review of Studies Using Intensive Longitudinal Methods.Current addiction reports · 2022Article
- Identifying person-specific coping responses to suicidal urges: A case series analysis and illustration of the idiographic method.Suicide & life-threatening behavior · 2022Article
- Individualized learning potential in stressful times: How to leverage intensive longitudinal data to inform online learning.Computers in human behavior · 2021Article
- Methodological Advances in Leveraging Neuroimaging Datasets in Adolescent Substance Use Research.Current addiction reports · 2019Article
- Focusing personality assessment on the person: Modeling general, shared, and person specific processes in personality and psychopathology.Psychological assessment · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
Ambulatory assessment (AA) methodologies have the potential to increase understanding and treatment of addictive behavior in seemingly unprecedented ways, due in part, to their emphasis on intensive repeated assessments of an individual's addictive behavior in context. But, many analytic techniques traditionally applied to AA data - techniques that average across people and time - do not fully leverage this potential. In an effort to take advantage of the individualized, temporal nature of AA data on addictive behavior, the current paper considers three underutilized person-oriented analytic techniques: multilevel modeling, p-technique, and group iterative multiple model estimation. After reviewing prevailing analytic techniques, each person-oriented technique is presented, AA data specifications are mentioned, an example analysis using generated data is provided, and advantages and limitations are discussed; the paper closes with a brief comparison across techniques. Increasing use of person-oriented techniques will substantially enhance inferences that can be drawn from AA data on addictive behavior and has implications for the development of individualized interventions.
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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.