Evidence map›Paper›PMID 42310647›Full record

ArticleBMC public health2026

Integration technology into health care: a scoping review of digital interventions for adult obesity management.

Sabah Al-Marwani, Zaidah Murang, Nik Aa Tuah

Abstract readScoping Review
In one paragraph

Article in BMC public 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

3 authors.

Sabah Al-MarwaniPAPRSB Institute of Health Sciences, Universiti Brunei Darussalam, Bandar Seri Begawan, Brunei Darussalam. saalmarwani20@med.just.edu.jo.
Zaidah MurangPAPRSB Institute of Health Sciences, Universiti Brunei Darussalam, Bandar Seri Begawan, Brunei Darussalam.
Nik Aa TuahPAPRSB Institute of Health Sciences, Universiti Brunei Darussalam, Bandar Seri Begawan, Brunei Darussalam.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDigital health interventions are emerging as an approach to support obesity management through self-management and remote care. However, utilization, impact, and practicality remain unclear. This study aims to map research on digital health interventions for obesity management among adults, describing their characteristics, uses, and outcomes, and identifying gaps.

methodsA comprehensive scoping review following Arksey and O'Malley's methodological framework, in accordance with the Joanna Briggs Institute's guidelines and reported in line with the PRISMA-ScR guidelines, examined studies published between 2015 and 2025 across four databases: PubMed, Google Scholar, Scopus, and APA PsycNet.

resultsA total of 43 studies met the eligibility criteria. Digital health interventions for obesity encompassed consultations and education on healthy lifestyle, behavioral change strategies, physical activity, dietary management, weight goal setting, intermittent fasting, gamification, and psychological support. Digital health interventions were delivered through telehealth, mobile apps, web-based programs, multicomponent digital approaches integrating several digital tools, and hybrid models combining digital delivery with face-to-face communication. These interventions often supported by devices such as digital scales, wearable trackers, and telemonitoring units to enhance self-monitoring, adherence, and engagement. The interventions were implemented across clinical, workplace, and community settings, including adaptations developed during the COVID-19 pandemic. The included studies showed varying and inconsistently reported outcomes, with some showing significant weight loss, improvements in metabolic markers and behavioral outcomes, including dietary adherence, physical activity, and self-monitoring, as well as favorable feasibility outcomes and the potential to maintain continuity of service delivery during the COVID-19 outbreak.

conclusionsDigital health interventions used telehealth, mobile applications, web-based, multicomponent, and hybrid models across different settings, including healthcare settings (e.g., clinical and primary care) and community settings. Digital devices, such as scales, wearables, and activity trackers, were often incorporated to support self-tracking, adherence, and engagement. Reported outcomes included weight loss, improved self-monitoring, and behavioral changes such as enhanced dietary adherence and increased physical activity, and a favorable feasibility outcome; however, these outcomes were not consistently reported across all studies. Key gaps included short follow-up periods and limited evidence from LMICs. Future research should prioritize sustainable, equitable, scalable, culturally adapted, and cost-effective digital interventions.

Indexed as

ObesityObesity ManagementAdultCOVID-19Digital HealthDigital MediaHumansTelemedicineAIDigital interventionE-healthM-healthObesityTechnologyTelehealth

Identifiers

PMID42310647
PMCPMC13637373

What OpenQuestion holds

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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.