Evidence map›Paper›PMID 40417205›Full record

ReviewThe Malaysian journal of medical sciences : MJMS2025

Emerging Trends in Telehealth and AI-Driven Approaches for Obesity Management: A New Perspective.

Thai Hau Koo, Xue Bin Leong, Jet Kwan Ng, Nicholas Kay Beng Tan, Mafauzy Mohamed

Abstract readReview
In one paragraph

Review in The Malaysian journal of medical sciences : MJMS, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Trial
  2. Article
  3. Review
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

5 authors.

Thai Hau KooDivision of Endocrinology, Department of Internal Medicine, Hospital Universiti Sains Malaysia, Kelantan, Malaysia.
Xue Bin LeongDivision of Endocrinology, Department of Internal Medicine, Hospital Universiti Sains Malaysia, Kelantan, Malaysia.
Jet Kwan NgSchool of Medical Sciences, Universiti Sains Malaysia, Health Campus, Kelantan, Malaysia.
Nicholas Kay Beng TanInnoDev Digital Enterprise, Kuala Lumpur, Malaysia.
Mafauzy MohamedDivision of Endocrinology, Department of Internal Medicine, Hospital Universiti Sains Malaysia, Kelantan, Malaysia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

One in eight people globally, prevalent mainly in some ethnic groups and those from low socioeconomic backgrounds, is a critical global health challenge of obesity. The telehealth system would be valuable in arresting obesity, with better access to care and a supporting digital community that encourages regular practice of physical activities, healthy diets, and health monitoring, all within reach and at affordable prices. Digital health interventions such as telehealth, mHealth applications, and wearable devices are new modalities for the treatment of obesity that increase monitoring of energy expenditure, physical activity level, and caloric intake. These technologies enhance the possibilities of therapy against barriers, such as maintaining motivation and improving the diet. This review summarises current evidence regarding digital health interventions for obesity management by considering and evaluating various global digital strategies to reduce obesity. The literature emphasises the effectiveness of eHealth interventions toward weight loss and maintenance. Furthermore, artificial intelligence (AI) and Information and Communications Technology (ICT) can predict and prevent paediatric obesity. By contrast, virtual reality (VR) applications can determine real-world behaviour in clinical practice. These digital interventions could increase the reach and efficacy of traditional weight management programmes by becoming more embedded in clinical practice. However, because of their broad implementation across different clinical settings, concerns regarding the security and privacy of these technologies must be addressed.

Indexed as

interventionsobesitytechnologytelehealth

Identifiers

PMID40417205
PMCPMC12097168

What Socratic 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 Socratic graph.