Comparison of a smartphone app for alcohol use disorders with an Internet-based intervention plus bibliotherapy: a pilot study
Open accessAbstract
OBJECTIVE: To date, no research has evaluated the efficacy of a stand-alone, smartphone-based intervention for individuals with an alcohol use disorder. The current pilot study evaluated the short-term outcomes of a smartphone-based intervention for alcohol use disorders compared with an Internet-based brief motivational intervention plus bibliotherapy. METHOD: Adults (18 to 45 years old) with an alcohol use disorder received either the Location-Based Monitoring and Intervention for Alcohol Use Disorders (LBMI-A; n = 28), a smartphone-based intervention, or the online Drinker's Check-up plus bibliotherapy (DCU + bib; n = 26). These groups were compared using the Timeline Followback interview for percent days abstinent (PDA), percent heavy drinking days (PHDD), and drinks per week (DPW) from baseline to 6 weeks after the introduction of the interventions. RESULTS: Multilevel models revealed that the LBMI-A resulted in a significant increase in PDA over the course of the study, whereas the DCU + bib did not. Effect sizes for change from baseline for PDA suggest that the DCU + bib resulted in moderate a decrease, whereas the LBMI-A resulted in a large increase in PDA. Both interventions resulted in significant decreases in PHDD and DPW. The LBMI-A produced larger reductions in the first 3 to 4 weeks after the intervention was introduced than the DCU + bib. On weeks with greater LBMI-A usage, participants reported less DPW and PHDD. CONCLUSIONS: Both interventions resulted in significant decreases in alcohol use over the 6-week trial, which is promising for stand-alone technology-based intervention systems aimed at individuals with an alcohol use disorder. (PsycINFO Database Record
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
DBCIs have the potential to generate datasets sufficiently large to reliably model and experimentally test mediation of outcomes by engagement with particular intervention components and to statistically control for confounding moderator effects such as baseline motivation levels.
“DBCIs have the potential to generate datasets sufficiently large to be able to reliably model and experimentally test 34 mediation of outcomes by engagement with particular intervention components and to statistically control for confounding moderator effects such as baseline motivation levels.22,26,35,36”
From Understanding and Promoting Effective Engagement With Digital Behavior Change Interventions (2016) · cites this paper as [35]
At 6-week follow-up, both groups showed a significant decrease in number of drinks per week and percentage of days of heavy drinking, but the effect was greater for the Location-based Monitoring and Intervention for Alcohol Use Disorders group.
“For both groups: significant ↓ in number of drinks/week and % of days of heavy drinking, but the effect is greater for the LBMI-A.”
From Online and Mobile Interventions for Problem Gambling, Alcohol, and Drugs: A Systematic Review (2017) · cites this paper as Gonzalez and Dulin (2015)
At 6-week follow-up, only the Location-based Monitoring and Intervention for Alcohol Use Disorders group reported a significant increase in number of days abstinent.
“6-week follow-up: Only the LMBI-A group reported a significant ↑ in number of days abstinent.”
From Online and Mobile Interventions for Problem Gambling, Alcohol, and Drugs: A Systematic Review (2017) · cites this paper as Gonzalez and Dulin (2015)
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
The citation lists haven’t been fetched yet
References 35 · Cited by 118
Research works printed but not linked: 2
- First MB Spitzer RL Gibbon M Williams JBW 2002 Structured Clinical Interview for DSM-IV-TR Axis I Disorders, research version, non-patient edition. (SCID-I/NP) New York Biometrics Research, New York State Psychiatric Institute
- Tabachnick B Fidell L 2007 Using multivariate statistics 5 Boston, MA Allyn & Bacon/Pearson Education
- Authors
- Gonzalez, V. M., & Dulin, P. L.
- Affiliations
- University of Alaska Anchorage (US)
- Venue
- Journal of Consulting and Clinical Psychology
- Published
- 2015-04
- Volume
- 83
- Issue
- 2
- Pages
- 335-345
- ISSN
- 0022-006X (ISSN-L)
- 1939-2117
- PMC
- PMC4426096
- OpenAlex
- W1971744924
- Cited by
- 118
- References
- 35
- Citations by year
- 2026: 3 · 2025: 4 · 2024: 8 · 2023: 11 · 2022: 14 · 2021: 10 · 2020: 16 · 2019: 11 · 2018: 17 · 2017: 14 · 2016: 6 · 2015: 3 · 2014: 1
- FWCI
- 10.45
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Locations
- Journal of Consulting and Clinical Psychology (publishedVersion, other-oa)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institute on Alcohol Abuse and Alcoholism (RC2AA019422)
- Topics
- Health Sciences › Medicine › Epidemiology › Substance Abuse Treatment and Outcomes
- Social Sciences › Psychology › Applied Psychology › Digital Mental Health Interventions
- Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
- Keywords
- alcoholism, smartphone-based intervention, online intervention, bibliotherapy, motivational interviewing, brief motivational intervention, heavy drinking, alcohol abstinence
- MeSH terms
- Smartphone, Adolescent, Adult, Bibliotherapy, Female, Humans, Male, Middle Aged, Motivation, Pilot Projects, Treatment Outcome, Alcohol-Related Disorders, Internet, Young Adult
About these checks
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.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review