Digital Interventions for Common Mental Disorders in Low- and Middle-Income Countries: A Systematic Review and Meta-Analysis
Open accessAbstract
Abstract Background In low-resource settings, e-mental health may substantially increase access to evidence-based interventions for common mental disorders. We conducted a systematic literature search to identify randomised trials examining the effects of digital interventions with or without therapeutic guidance compared to control conditions in individuals with anxiety and/or depression symptoms in low- and middle-income countries (LMICs). Methods The main outcome was the reduction in symptoms at the post-test. Secondary outcomes included improvements in quality of life and longer-term effects (≥20 weeks post-randomisation). The effect size Hedges’ g was calculated using the random effects model. Results A total of 21 studies (23 comparisons) with 5.296 participants were included. Digital interventions were more effective than controls in reducing symptoms of common mental disorders at the post-test ( g = −0.89, 95% confidence interval [CI] −1.26 to −0.52, p < 0.001; NNT = 2.91). These significant effects were confirmed when examining depressive ( g = −0.77, 95% CI −1.11; −0.44) and anxiety symptoms separately ( g = −1.02, 95% CI −1.53 to −0.52) and across all other sensitivity analyses. Digital interventions also resulted in a small but significant effect in improving quality of life ( g = 0.32, 95% CI 0.19 to 0.45) at the post-test. Over the longer term, the effects were smaller but remained significant for all examined outcomes. Heterogeneity was moderate to high in all analyses. Subgroup and meta-regression analyses did not result in significant outcomes in any of the examined variables (e.g., guided vs. unguided interventions). Conclusions Digital interventions, with or without guidance, may effectively bridge the gap between treatment supply and demand in LMICs. Nevertheless, more studies are needed to draw firm conclusions regarding the magnitude of the effects of digital interventions.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
There is growing evidence that digital interventions can be successfully implemented in low-resource settings.
“There is growing evidence that digital interventions can be successfully implemented in low-resource settings [20].”
From Effects of a self-guided digital mental health self-help intervention for Syrian refugees in Egypt: A pragmatic randomized controlled trial (2024) · cites this paper as [20]
The Impact statement reports a growing number of trials in low- and middle-income countries, and the Discussion reports that digital interventions reduced depression and anxiety symptoms there. But the paper assesses effectiveness rather than whether interventions were successfully implemented at scale; its Discussion also says the eligible studies came only from lower-middle- and upper-middle-income countries, not low-income countries. No page numbers are available in our copy. (LLM, conf=0.82)
Experimental — accuracy not yet measuredThe results add to the growing evidence base for low-threshold digital mental health offers aimed at underserved populations in low- and middle-income countries.
“The results add to the growing evidence base for low-threshold digital mental health offers aimed at underserved populations in low- and middle-income countries [20,57].”
From Effects of a self-guided digital mental health self-help intervention for Syrian refugees in Egypt: A pragmatic randomized controlled trial (2024) · cites this paper as [20]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
Measuring inconsistency in meta-analyses
Higgins, J. P. T., Thompson, S. G., Deeks, J. J., & Altman, D. G. (2003) · BMJ · doi:10.1136/bmj.327.7414.557 · Cited by 63,139 · see citing works
Bias in meta-analysis detected by a simple, graphical test
Egger, M., Smith, G. D., Schneider, M., & Minder, C. (1997) · BMJ · doi:10.1136/bmj.315.7109.629 · Cited by 56,722 · see citing works
RoB 2: a revised tool for assessing risk of bias in randomised trials
Sterne, J. A. C., Savović, J., Page, M. J., Elbers, R. G., Blencowe, N. S., Boutron, I., Cates, C. J., Cheng, H.-Y., Corbett, M. S., Eldridge, S. M., et al. (2019) · BMJ · doi:10.1136/bmj.l4898 · Cited by 33,583 · see citing works
Conducting Meta-Analyses in <i>R</i> with the <b>metafor</b> Package
Viechtbauer, W. (2010) · Journal of Statistical Software · doi:10.18637/jss.v036.i03 · Cited by 20,464 · see citing works
Duval, S., & Tweedie, R. (2000) · Biometrics · doi:10.1111/j.0006-341x.2000.00455.x · Cited by 14,099 · see citing works
The PRISMA 2020 Statement: An Updated Guideline for Reporting Systematic Reviews
Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., Shamseer, L., Tetzlaff, J. M., Akl, E. A., Brennan, S. E., et al. (2021) · International Journal of Surgery · doi:10.1016/j.ijsu.2021.105906 · Cited by 11,748 · see citing works
Wasserman, S. S., Hedges, L. V., & Olkin, I. (1988) · Journal of Educational Statistics · doi:10.2307/1164953 · Cited by 10,347 · see citing works
How to perform a meta-analysis with R: a practical tutorial
Balduzzi, S., Rücker, G., & Schwarzer, G. (2019) · Evidence Based Mental Health · doi:10.1136/ebmental-2019-300117 · Cited by 5,827 · see citing works
The Lancet Commission on global mental health and sustainable development
Patel, V., Saxena, S., Lund, C., Thornicroft, G., Baingana, F., Bolton, P., Chisholm, D., Collins, P. Y., Cooper, J. L., Eaton, J., et al. (2018) · The Lancet · doi:10.1016/s0140-6736(18)31612-x · Cited by 3,692 · see citing works
Self-citationOutlier and influence diagnostics for meta-analysis
Viechtbauer, W., & Cheung, M. W.-L. (2010) · Research Synthesis Methods · doi:10.1002/jrsm.11 · Cited by 2,949 · see citing works
The global prevalence of common mental disorders: a systematic review and meta-analysis 1980–2013
Steel, Z., Marnane, C., Iranpour, C., Chey, T., Jackson, J. W., Patel, V., & Silove, D. (2014) · International Journal of Epidemiology · doi:10.1093/ije/dyu038 · Cited by 2,846 · see citing works
Self-citationIntHout, J., Ioannidis, J. P., & Borm, G. F. (2014) · BMC Medical Research Methodology · doi:10.1186/1471-2288-14-25 · Cited by 2,419 · see citing works
Doing Meta-Analysis with R: A Hands-On Guide
Harrer, M., Cuijpers, P., Furukawa, T. A., & Ebert, D. D. (2021) · doi:10.1201/9781003107347 · Cited by 1,850 · see citing works
Self-citationBasics of meta‐analysis: <i>I</i> <sup>2</sup> is not an absolute measure of heterogeneity
Borenstein, M., Higgins, J. P. T., Hedges, L. V., & Rothstein, H. R. (2017) · Research Synthesis Methods · doi:10.1002/jrsm.1230 · Cited by 1,848 · see citing works
Cheung, M. W.-L. (2014) · Psychological Methods · doi:10.1037/a0032968 · Cited by 1,342 · see citing works
Time for united action on depression: a Lancet–World Psychiatric Association Commission
Herrman, H., Patel, V., Kieling, C., Berk, M., Buchweitz, C., Cuijpers, P., Furukawa, T. A., Kessler, R. C., Kohrt, B. A., Maj, M., et al. (2022) · The Lancet · doi:10.1016/s0140-6736(21)02141-3 · Cited by 1,104 · cited 1× · see citing works
“The global burden of these disorders is devastating globally and particularly high in low-and middle-income countries (LMICs; Herrman et al., 2022; WHO, 2022).”
BackgroundSelf-citationKaryotaki, E., Efthimiou, O., Miguel, C., Maas genannt Bermpohl, F., Furukawa, T. A., Cuijpers, P., Individual Patient Data Meta-Analyses for Depression (IPDMA-DE) Collaboration, Riper, H., Patel, V., Mira, A., et al. (2021) · JAMA Psychiatry · doi:10.1001/jamapsychiatry.2020.4364 · Cited by 866 · see citing works
Self-citationKaryotaki, E., Riper, H., Twisk, J., Hoogendoorn, A., Kleiboer, A., Mira, A., Mackinnon, A., Meyer, B., Botella, C., Littlewood, E., et al. (2017) · JAMA Psychiatry · doi:10.1001/jamapsychiatry.2017.0044 · Cited by 691 · see citing works
Self-citationNaslund, J. A., Aschbrenner, K. A., Araya, R., Marsch, L. A., Unützer, J., Patel, V., & Bartels, S. J. (2017) · The Lancet Psychiatry · doi:10.1016/s2215-0366(17)30096-2 · Cited by 638 · see citing works
Self-citationCuijpers, P., Noma, H., Karyotaki, E., Vinkers, C. H., Cipriani, A., & Furukawa, T. A. (2020) · World Psychiatry · doi:10.1002/wps.20701 · Cited by 540 · see citing works
Self-citationThe impact of digital technology on psychological treatments and their dissemination
Fairburn, C. G., & Patel, V. (2017) · Behaviour Research and Therapy · doi:10.1016/j.brat.2016.08.012 · Cited by 448 · cited 1× · see citing works
“Considering the rapidly increasing penetration rate of digital technologies in LMICs, digital interventions may be an effective approach to fill the gap between treatment supply and demand (Fairburn and Patel, 2017; Karyotaki et al., 2017; Naslund et al., 2017).”
BackgroundSelf-citationDepression: The disorder and the burden
Reddy, M. S. (2010) · Indian Journal of Psychological Medicine · doi:10.4103/0253-7176.70510 · Cited by 392 · see citing works
Digital interventions for the treatment of depression: a meta-analytic review
Moshe, I., Terhorst, Y., Philippi, P., Domhardt, M., Cuijpers, P., Cristea, I., Pulkki-Råback, L., Baumeister, H., & Sander, L. B. (2021) · Psychological Bulletin · doi:10.1037/bul0000334 · Cited by 390 · see citing works
Self-citationFu, Z., Burger, H., Arjadi, R., & Bockting, C. L. H. (2020) · The Lancet Psychiatry · doi:10.1016/s2215-0366(20)30256-x · Cited by 336 · see citing works
Andersson, G., Carlbring, P., Titov, N., & Lindefors, N. (2019) · The Canadian Journal of Psychiatry · doi:10.1177/0706743719839381 · Cited by 324 · cited 1× · see citing works
“Besides cost reduction, such interventions can overcome many other treatment barriers since they do not exclusively rely on face-to-face sessions and mental health specialists (Andersson et al., 2019).”
BackgroundHarper Shehadeh, M., Heim, E., Chowdhary, N., Maercker, A., & Albanese, E. (2016) · JMIR Mental Health · doi:10.2196/mental.5776 · Cited by 188 · cited 1× · see citing works
“It should be noted, though, that the method of cultural adaptation was minimally reported across the included studies, suggesting that the actual extent of cultural adaptation might have an effect on digital interventions ’ efficacy, as reported before (Shehadeh et al., 2016).”
ResultPauley, D., Cuijpers, P., Papola, D., Miguel, C., & Karyotaki, E. (2021) · Psychological Medicine · doi:10.1017/s0033291721001999 · Cited by 170 · see citing works
Self-citationSun, Y., Li, Y., Wang, J., Chen, Q., Bazzano, A. N., & Cao, F. (2021) · Journal of Medical Internet Research · doi:10.2196/23410 · Cited by 165 · see citing works
Psychotherapies for depression in low- and middle-income countries: a meta-analysis
Cuijpers, P., Karyotaki, E., Reijnders, M., Purgato, M., & Barbui, C. (2018) · World Psychiatry · doi:10.1002/wps.20493 · Cited by 159 · cited 4× · see citing works
“Such differences have been previously identified in the literature on psychotherapy trials (Cuijpers et al., 2018) and raise important considerations.”
BackgroundResultInfluentialSelf-citationEffect of psychotherapy for depression on quality of life: meta-analysis
Kolovos, S., Kleiboer, A., & Cuijpers, P. (2016) · British Journal of Psychiatry · doi:10.1192/bjp.bp.115.175059 · Cited by 153 · cited 1× · see citing works
“This finding is in line with previous meta-analyses on psy-chotherapies that have found almost identical effects on quality of life ( g = 0.33) (Kolovos et al., 2016).”
ResultInfluentialSelf-citationArjadi, R., Nauta, M. H., Scholte, W. F., Hollon, S. D., Chowdhary, N., Suryani, A. O., Uiterwaal, C. S. P. M., & Bockting, C. (2018) · The Lancet Psychiatry · doi:10.1016/s2215-0366(18)30223-2 · Cited by 128 · see citing works
Jannati, N., Mazhari, S., Ahmadian, L., & Mirzaee, M. (2020) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2020.104145 · Cited by 124 · see citing works
Cuijpers, P., Heim, E., Abi Ramia, J., Burchert, S., Carswell, K., Cornelisz, I., Knaevelsrud, C., Noun, P., van Klaveren, C., van’t Hof, E., et al. (2022) · PLoS Medicine · doi:10.1371/journal.pmed.1004025 · Cited by 118 · cited 1× · see citing works
“…Moeini et al., 2019; Jannati et al., 2020; Salamanca-Sanabria et al., 2020; Wang et al., 2020; Araya et al., 2021; Ghosh et al., 2023; Heim et al., 2021; Latif Cambridge Prisms: Global Mental Health et al., 2021; Newman et al., 2021; Sun et al., 2021; Cuijpers et al., 2022; Zhao et al., 2022).”
BackgroundSelf-citationAraya, R., Menezes, P. R., Claro, H. G., Brandt, L. R., Daley, K., Quayle, J., Diez‐Canseco, F., Peters, T. J., Cruz, D. V., Toyama, M., et al. (2021) · JAMA · doi:10.1001/jama.2021.4348 · Cited by 98 · see citing works
Self-citationSalamanca-Sanabria, A., Richards, D., Timulak, L., Connell, S., Mojica Perilla, M., Parra-Villa, Y., & Castro-Camacho, L. (2020) · JMIR Mental Health · doi:10.2196/13392 · Cited by 83 · see citing works
Tulbure, B. T., Szentagotai, A., David, O., Ștefan, S., Månsson, K. N. T., David, D., & Andersson, G. (2015) · PLOS ONE · doi:10.1371/journal.pone.0123997 · Cited by 81 · see citing works
Karyotaki, E., Araya, R., Kessler, R. C., Waqas, A., Bhana, A., Rahman, A., Matsuzaka, C. T., Miguel, C., Lund, C., Garman, E. C., et al. (2022) · JAMA Psychiatry · doi:10.1001/jamapsychiatry.2022.0301 · Cited by 67 · see citing works
Self-citationHeim, E., Ramia, J. A., Hana, R. A., Burchert, S., Carswell, K., Cornelisz, I., Cuijpers, P., El Chammay, R., Noun, P., van Klaveren, C., et al. (2021) · Internet Interventions · doi:10.1016/j.invent.2021.100380 · Cited by 61 · see citing works
Self-citationYeung, A., Wang, F., Feng, F., Zhang, J., Cooper, A. R., Hong, L., Wang, W., Griffiths, K. M., Bennett, K., Bennett, A., et al. (2017) · Asian Journal of Psychiatry · doi:10.1016/j.ajp.2017.11.007 · Cited by 60 · see citing works
Ciuca, A. M., Berger, T., Crişan, L. G., & Miclea, M. (2018) · Journal of Anxiety Disorders · doi:10.1016/j.janxdis.2018.03.009 · Cited by 58 · see citing works
Moeini, B., Bashirian, S., Soltanian, A. R., Ghaleiha, A., & Taheri, M. (2019) · PubMed Central · Cited by 52 · see citing works
Wang, H., Zhao, Q., Mu, W., Rodriguez, M. A., Qian, M., & Berger, T. (2020) · JMIR Mental Health · doi:10.2196/15797 · Cited by 43 · see citing works
Zhao, C., Wampold, B. E., Ren, Z., Zhang, L., & Guangrong, J. (2022) · Journal of Clinical Psychology · doi:10.1002/jclp.23329 · Cited by 38 · see citing works
Newman, M. G., Kanuri, N., Rackoff, G. N., Jacobson, N. C., Bell, M. J., & Taylor, C. B. (2021) · Psychotherapy · doi:10.1037/pst0000383 · Cited by 34 · see citing works
Mogoașe, C., Brailean, A., & David, D. (2013) · Cognitive Therapy and Research · doi:10.1007/s10608-012-9514-z · Cited by 31 · see citing works
Karbasi, A., & Haratian, A. (2018) · Advanced Biomedical Research · doi:10.4103/abr.abr_203_16 · Cited by 24 · see citing works
Ghosh, A., Cherian, R. J., Wagle, S., Sharma, P., Kannan, K. R., Bajpai, A., & Gupta, N. (2023) · Journal of Medical Internet Research · doi:10.2196/41005 · Cited by 23 · see citing works
Latif, M., Awan, F., Gul, M., Husain, M. O., Husain, M. I., Sayyed, K., Magsi, T., Naz, S., Aylem, O., Phiri, P., et al. (2021) · The Cognitive Behaviour Therapist · doi:10.1017/s1754470x21000313 · Cited by 20 · see citing works
Flagged first, then by citations
Research works printed but not linked: 2
- Hedges LV and Olkin I (2014) Statistical Methods for Meta-Analysis. London: Academic Press.
- Yeung A, Wang F, Feng F, Zhang J, Cooper A, Hong L, Wang W, Griffiths K, Bennett K, Bennett A, Alpert J and Fava M (2017) Outcomes of an online computerized cognitive behavioral treatment program for treating chinese patients with depression: A pilot study. Asian Journal of Psychiatry 38, 102– 107. 29146042
Cited by
Sorted by citations
Digital mental health interventions for the treatment of depression: A multiverse meta-analysis
Plessen, C. Y., Panagiotopoulou, O. M., Tong, L., Cuijpers, P., & Karyotaki, E. (2025) · Journal of Affective Disorders · doi:10.1016/j.jad.2024.10.018 · Cited by 53 · see citing works
Self-citationBurchert, S., Alkneme, M. S., Alsaod, A., Cuijpers, P., Heim, E., Hessling, J., Hosny, N., Sijbrandij, M., van’t Hof, E., Ventevogel, P., et al. (2024) · PLoS Medicine · doi:10.1371/journal.pmed.1004460 · Cited by 18 · see citing works
Self-citation
- Authors
- Karyotaki, E., Miguel, C., Panagiotopoulou, O. M., Harrer, M., Seward, N., Sijbrandij, M., Araya, R., Patel, V., & Cuijpers, P.
- Affiliations
- Amsterdam Public Health (NL)
- Vrije Universiteit Amsterdam (NL)
- Friedrich-Alexander-Universität Erlangen-Nürnberg (DE)
- King's College London (GB)
- Harvard University (US)
- Corresponding author
- Karyotaki, Eirini
- ORCID
- Venue
- Cambridge Prisms Global Mental Health
- Publisher
- Cambridge University Press (CUP)
- Published
- 2023
- Volume
- 10
- Pages
- e68-e68
- ISSN
- 2054-4251 (ISSN-L)
- PMC
- PMC10643260
- OpenAlex
- W4386778703
- Cited by
- 56
- References
- 48
- Citations by year
- 2026: 21 · 2025: 14 · 2024: 10 · 2023: 11
- FWCI
- 1.89
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Cambridge Prisms Global Mental Health (publishedVersion, cc-by-nc-nd)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Research Portal (King's College London) (publishedVersion, cc-by)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Edinburgh Research Explorer (University of Edinburgh) (submittedVersion, cc-by)
- VU Research Portal (submittedVersion, other-oa)
- Funders
- Nederlandse Organisatie voor Wetenschappelijk Onderzoek (VI.Veni.201G.053)
- Topics
- Social Sciences › Psychology › Applied Psychology › Digital Mental Health Interventions
- Social Sciences › Psychology › Social Psychology › Mental Health Treatment and Access
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Anxiety, Depression, Psychometrics, Treatment, Cognitive Processes
- Keywords
- digital interventions, e-mental health, common mental disorders, depression, anxiety, low- and middle-income countries, quality of life, long-term treatment outcomes, access to mental health care
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review