Evidence map›Paper›PMID 42746052›Full record

ReviewAddiction & health2026

Smoking Cessation Apps and Technology Acceptance Factors: Focusing on the Sense2Quit Application.

Samaneh Ghanbarzadeh, Elham Maserat

Abstract readReview
In one paragraph

Review in Addiction & health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Samaneh GhanbarzadehDepartment of Medical Informatics, Faculty of Medical Sciences, Tarbiat Modares University, Tehran, Iran.ORCID https://orcid.org/0009-0007-8387-2718
Elham MaseratDepartment of Medical Informatics, Faculty of Medical Sciences, Tarbiat Modares University, Tehran, Iran.ORCID https://orcid.org/0000-0003-1359-8024

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Cigarette smoking remains a leading cause of preventable deaths worldwide, with significant health and economic consequences. Mobile health (mHealth) applications such as Sense2Quit, which integrate advanced technologies (e.g., smart watch-based detection of smoking gestures) and leverage technology acceptance theories (TAM, TPB, UTAUT), have emerged as innovative tools for smoking cessation. Methods: This study employed a Meta-synthesis of 38 studies retrieved from reputable databases to evaluate factors influencing app acceptance at individual organizational and supra-organizational levels. The research adopted an interpretive-critical meta-synthesis approach, following the methodological framework established by Sandelowski and Barroso. Thematic coding was simultaneously applied to extract emerging concepts from qualitative data. The data extraction and coding were performed manually through dual researcher consensus to ensure rigorous interpretation of qualitative content, particularly given the limited number of eligible studies. Findings: Findings revealed that Sense2Quit excels in high-accuracy detection of smoking gestures, personalized interventions (e.g., progress tracking, Cognitive-behavioral exercises, and social support), and user-centered design, particularly among high-risk populations such as people living with HIV (PWH). Key acceptance factors included perceived usefulness, ease of use, intrinsic motivation (aligned with SDT), and technological infrastructure compatibility. Conclusion: However, challenges such as limited digital literacy among older adults and chronic patients and socio-economic barriers in developing countries were identified. Proposed solutions include localized user interfaces, collaboration with local institutions, and policy reforms. Ultimately, Sense2Quit exemplifies how blending technical innovation with community-specific interventions can enhance smoking cessation efforts, while underscoring the need to address contextual challenges and strengthen digital infrastructure for broader public health impact.

Indexed as

Mobile healthSmoking cessationTechnology acceptance model

Identifiers

PMID42746052
PMCPMC13575653

What Socratic holds

Textmetadata
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 Socratic graph.