Evidence map›Paper›PMID 40125561›Full record

ArticleJMIR mHealth and uHealth2025

Preferences for Mobile Apps That Aim to Modify Alcohol Use: Thematic Content Analysis of User Reviews.

Megan Kirouac, Christina Gillezeau

Abstract read
In one paragraph

Article in JMIR mHealth and uHealth, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Megan KirouacCenter on Alcohol, Substance use, And Addictions, The University of New Mexico, Albuquerque, NM, United States, 1 505-925-2300, 1 505-925-2351.ORCID 0000-0001-7533-197X
Christina GillezeauCenter on Alcohol, Substance use, And Addictions, The University of New Mexico, Albuquerque, NM, United States, 1 505-925-2300, 1 505-925-2351.ORCID 0000-0003-1318-8316

Funding

Integrative Treatment for Achieving Holistic Recovery from Comorbid Chronic Pain and Opioid Use DisorderRM1DA055301 · NIDA · UNIVERSITY OF NEW MEXICO · PI PEARSON, MATTHEW RYAN, WITKIEWITZ, KATIE A · 2021 to 2025
$10.5M
Alcohol Research Training: Methods & MechanismsT32AA018108 · NIAAA · UNIVERSITY OF NEW MEXICO · PI Katie A Witkiewitz · 2010 to 2026
$5.6M
Mindfulness-Based Relapse Prevention as Video Conferencing Continuing Care to Promote Long Term Recovery from Alcohol Use DisorderR01AA031159 · NIAAA · UNIVERSITY OF NEW MEXICO · PI Katie A Witkiewitz · 2023 to 2026
$2.6M
NIAAA NIH HHS R01 AA031159NIAAA NIH HHS T32 AA018108NIDA NIH HHS RM1 DA055301
6 · The paper itself

Abstract

Background: Nearly one-third of adults in the United States will meet criteria for alcohol use disorder in their lifetime, yet fewer than 10% of individuals who meet for alcohol use disorder criteria will receive treatment for it. Mobile health (mHealth) applications (apps) have been suggested as a potential mechanism for closing this treatment gap, yet there is a wide variety of quality and integrity within these apps, leading to potential harms to users. objectives: The aim of this paper is to systematically record and qualitatively examine user reviews or mHealth apps to identify features in the existing apps that may impact usefulness and adoption of them. Methods: The researchers used Apple App and Google Play stores to identify mHealth apps that were focused on modifying alcohol use and treating common comorbidities. Apps that were free without in-app purchases and provided multiple features for users were included. User reviews from the apps were downloaded and coded using content analysis. Results: A total of 425 unique apps were found in our search. Of these, the majority of apps (n=301) were excluded from the present analyses for not focusing on reducing alcohol-related concerns (eg, many apps were for purchasing alcohol). Eight apps were identified and had user reviews downloaded. The apps examined in this study were VetChange, SMART, DrinkCoach, SayingWhen, AlcoStat, Celebrate Recovery, TryDry, and Construction Industry Helpline. A total of 370 reviews were downloaded and 1353 phrases were coded from those reviews into a total of 11 codes. The 5 most common themes identified were praise (498 counts coded; 36.831%), tools (150 counts coded; 11.062%), suggestions for improvement (118 counts coded; 8.756%), criticism (105 counts coded; 7.768%), and tracking (104 counts coded; 7.724%). Conclusions: The current findings suggest that alcohol mobile app users broadly found the apps helpful in reducing their drinking or meeting their drinking goals. Users were able to identify features that they liked or found helpful in the apps, as well as provide concrete feedback about features that they would like included or improved. Specifically, flexible and expansive tracking features and comprehensive whole health tools were cited as valuable and desired. App developers and those looking to expand access to and uptake of alcohol reduction apps may find these user reviews helpful in guiding their app development.

Indexed as

Alcohol DrinkingConsumer BehaviorMobile ApplicationsHumansQualitative ResearchTelemedicineUnited Statesalcoholalcohol mobile appalcohol use disordercontent analysisdrinkinghealth toolmHealthmobile health appreviewsusefulnessuseruser-centereduser-centered design

Identifiers

PMID40125561
PMCPMC11938989

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.