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Dynamic association between negative affect and alcohol lapses following alcohol treatment.
Open accessAbstract
Clinical research has found a strong association between negative affect and returning to alcohol use after a period of abstinence. Yet little is known about the probability of a lapse given a particular level of negative affect or whether there is a reciprocal relationship between negative affect and alcohol use across time. The goal of the current study was to examine the association between negative affect and drinking behavior in the 1st year following alcohol treatment. The authors applied an associative latent transition analysis to the Project MATCH outpatient data (n = 952) and then replicated the model in the Project MATCH aftercare data (n = 774). Changes in drinking following treatment were significantly associated with current and prior changes in negative affect, and changes in negative affect were related to prior changes in drinking (effect size range = 0.13-0.33). The results supported the hypothesis that negative affect and alcohol lapses are dynamically linked and suggest that targeting the relationship between negative affect and alcohol use could greatly decrease the probability of lapses and improve alcohol treatment outcomes.
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“Overall, the results showed that individuals who reported higher negative affect or increased negative affect over time had the highest probability of heavy and frequent drinking following treatment, and had a near-zero probability of transitioning to moderate drinking.”
From Relapse prevention for addictive behaviors (2011) · cites this paper as [72]
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“Heavier and more frequent alcohol use predicted a greater probability of high negative affect and increased negative affect over time.”
From Relapse prevention for addictive behaviors (2011) · cites this paper as [72]
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“Although elevations in negative mood are often associated with relapse (57–59), evidence also suggests that this relationship is mediated by increases in craving (60).”
Hallihan, H., Wu, Y., Lee, S., Adomah, R., & Rospenda, K. M. (2026) · Archives of Psychiatric Nursing · doi:10.1016/j.apnu.2026.152242
Metadata
- Authors
- Witkiewitz, K., & Villarroel, N. A.
- Affiliations
- University of Washington (US)
- ORCID
- Witkiewitz, Katie
- Venue
- Journal of Consulting and Clinical Psychology
- Published
- 2009-08
- Volume
- 77
- Issue
- 4
- Pages
- 633-644
- ISSN
- 0022-006X (ISSN-L)
- 1939-2117
- PMC
- PMC2911993
- OpenAlex
- W2048965316
- Cited by
- 179
- References
- 69
- Citations by year
- 2026: 6 · 2025: 7 · 2024: 8 · 2023: 12 · 2022: 18 · 2021: 6 · 2020: 12 · 2019: 11 · 2018: 5 · 2017: 12 · 2016: 9 · 2015: 11 · 2014: 10 · 2013: 19 · 2012: 14
- FWCI
- 7.16
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Journal of Consulting and Clinical Psychology (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institute on Alcohol Abuse and Alcoholism (RO3-AA016322)
- Topics
- Health Sciences › Medicine › Epidemiology › Substance Abuse Treatment and Outcomes
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Anxiety, Depression, Psychometrics, Treatment, Cognitive Processes
- Social Sciences › Psychology › Clinical Psychology › Psychotherapy Techniques and Applications
- Keywords
- negative affect, relapse, alcohol treatment, alcohol consumption, Project MATCH, latent transition analysis, outpatient care, follow-up care, bidirectional relationship, abstinence
- MeSH terms
- Adult, Aftercare, Alcoholics Anonymous, Alcoholism, Ambulatory Care, Anger, Depression, Female, Follow-Up Studies, Humans, Male, Middle Aged, Models, Psychological, Motivation, Personality Inventory, Psychometrics, Psychotherapy, Recurrence, Risk Factors, Temperance, Multicenter Studies as Topic, Cognitive Behavioral Therapy, Randomized Controlled Trials as Topic
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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