Evidence map›Paper›PMID 41143094›Full record

ReviewDigital health

A review of systematic reviews for evidence on use of mobile applications for mental disorders, including substance use disorders, in low and middle-income countries.

Riya Kaur Bhatia, Parag Bhardwaj, Anshika Chaudhry, Abhishek Ghosh, Arpit Parmar, Yashita Ahluwalia, Gunjan Singh, Deepshikha Prasad, Pulkit Verma, Neha Dahiya and 3 more

Abstract readReview
In one paragraph

Review in Digital health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 1 pooled it
–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

4 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Trial
  3. Review
  4. 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

13 authors.

Riya Kaur BhatiaNational Drug Dependence Treatment Centre (NDDTC), All India Institute of Medical Sciences (AIIMS), New Delhi, India.
Parag BhardwajNational Drug Dependence Treatment Centre (NDDTC), All India Institute of Medical Sciences (AIIMS), New Delhi, India.
Anshika ChaudhryNational Drug Dependence Treatment Centre (NDDTC), All India Institute of Medical Sciences (AIIMS), New Delhi, India.ORCID https://orcid.org/0009-0002-4394-3415
Abhishek GhoshPostgraduate Institute of Medical Education and Research, Chandigarh, India.
Arpit ParmarDepartment of Psychiatry, All India Institute of Medical Sciences Bhubaneswar, Bhubaneswar, India.
Yashita AhluwaliaNational Drug Dependence Treatment Centre (NDDTC), All India Institute of Medical Sciences (AIIMS), New Delhi, India.
Gunjan SinghDelivery Division, ICMR Hqs, New Delhi, India.ORCID https://orcid.org/0009-0004-8463-4752
Deepshikha PrasadDelivery Division, ICMR Hqs, New Delhi, India.ORCID https://orcid.org/0009-0000-9668-5507
Pulkit VermaData Centre, Indian Council of Medical Research, Headquarters, New Delhi, India.
Neha DahiyaDelivery Division, ICMR Hqs, New Delhi, India.
Ashoo GroverDelivery Division, ICMR Hqs, New Delhi, India.
Siddharth SarkarNational Drug Dependence Treatment Centre (NDDTC), All India Institute of Medical Sciences (AIIMS), New Delhi, India.
Yatan Pal Singh BalharaNational Drug Dependence Treatment Centre (NDDTC), All India Institute of Medical Sciences (AIIMS), New Delhi, India.ORCID https://orcid.org/0000-0003-1616-6403

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background and objectives: There is an increased burden of mental disorders, including substance use disorders (MSUD) in low- and middle-income countries (LMICs). Digital technology offers a viable avenue to scale up the services for MSUD in such settings. This review aims to synthesize existing evidence from systematic reviews and meta-analyses on the use of mobile applications for mental disorders, including substance use disorders in LMICs. Methods: A comprehensive search for review articles and meta-analyses was conducted in January 2025 and encompassed all relevant studies published until then using the electronic databases PubMed, Scopus, and Embase. Rayyan software was employed to remove duplicates. Data extraction included information such as publication date, title, author, country, number of participants, study design, data collection procedures, instruments/tools used, the profile of healthcare workers, the profile of patients, name of the mobile application, use of the mobile application and privacy policy. Evaluation of risk of bias and quality assessment for the included studies was carried out using the Cochrane tool for assessing risk of bias RoB 2, ROBINS-I for nonrandomized studies, and the Mixed Methods Appraisal Tool. The quality of the included systematic reviews was assessed using A MeaSurement Tool to Assess systematic Reviews. Results: Twenty-three individual studies that met the eligibility criteria were included in the review. The effectiveness of mobile applications for mental health in LMICs varied significantly across studies. Despite the high burden of substance use disorders in LMICs, only a few studies evaluated mobile applications targeting substance use disorders. While mobile applications offer numerous advantages, significant barriers to widespread implementation remain. Conclusions: The findings of this review have significant implications for future research, policy, and practice. Given the potential of mobile applications to improve mental health care in LMICs, efforts should focus on enhancing their cultural relevance, usability, and long-term effectiveness.

Indexed as

digital interventionslow- and middle-income countriesMental healthmHealth appsmobile applicationssubstance use disorderssystematic review

Identifiers

PMID41143094
PMCPMC12547136

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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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.