Guidelines for reporting of health interventions using mobile phones: mobile health (mHealth) evidence reporting and assessment (mERA) checklist
Open accessAbstract
To improve the completeness of reporting of mobile health (mHealth) interventions, the WHO mHealth Technical Evidence Review Group developed the mHealth evidence reporting and assessment (mERA) checklist. The development process for mERA consisted of convening an expert group to recommend an appropriate approach, convening a global expert review panel for checklist development, and pilot testing the checklist. The guiding principle for the development of these criteria was to identify a minimum set of information needed to define what the mHealth intervention is (content), where it is being implemented (context), and how it was implemented (technical features), to support replication of the intervention. This paper presents the resulting 16 item checklist and a detailed explanation and elaboration for each item, with illustrative reporting examples. Through widespread adoption, we expect that the use of these guidelines will standardise the quality of mHealth evidence reporting, and indirectly improve the quality of mHealth evidence.
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mHealth has the potential to extend the scope, accessibility, and quality of health services and increase workforce capacity.
“In pursuit of universal health coverage, mobile health has the potential to extend the scope, accessibility and quality of health services, to increase the accountability mechanisms, to expand the population base accessing health services, and to increase capacity of the healthcare workforce”
From Health workers' perceptions and experiences of using mHealth technologies to deliver primary healthcare services: a qualitative evidence synthesis (2020) · cites this paper as Agarwal 2016
The Abstract (page unavailable) says mobile technologies may improve access to and use of health services, particularly for underserved populations, and that mHealth aims to improve health-system efficiency and outcomes. It does not specifically support the attributed potential to extend the scope or quality of services, strengthen accountability mechanisms, or increase healthcare workforce capacity. (LLM, conf=0.85)
Experimental — accuracy not yet measuredMobile health has the potential to extend the scope, accessibility and quality of health services, increase accountability mechanisms, expand the population base accessing health services, and increase capacity of the healthcare workforce.
“In pursuit of universal health coverage, mobile health has the potential to extend the scope, accessibility and quality of health services, to increase the accountability mechanisms, to expand the population base accessing health services, and to increase capacity of the healthcare workforce (Agarwal 2016; Labrique 2013a; Labrique 2013b; Mehl 2014).”
From Health workers' perceptions and experiences of using mHealth technologies to deliver primary healthcare services: a qualitative evidence synthesis (2020) · cites this paper as Agarwal 2016
The Abstract (page not provided) says mobile technologies have the potential to improve access to and use of health services, particularly among underserved populations, and that mHealth aims to improve health-system efficiency. That supports the access and reach portions of the claim, but the passages do not establish the claimed potential to increase accountability mechanisms or healthcare workforce capacity, or specifically to improve service quality. (LLM, conf=0.86)
Experimental — accuracy not yet measuredThis manuscript complies with the mHealth evidence reporting and assessment (mERA) checklist.
“This manuscript complies with the mHealth evidence reporting and assessment (mERA) checklist on reporting of health interventions using mobile technologies [60].”
The protocol followed the SPIRIT 2013, CONSORT 2010, TIDieR, and mERA reporting guidelines.
“This protocol followed the guidelines of SPIRIT 2013 (Chan et al., 2013), CONSORT 2010 (the CONSORT Group et al., 2010), the TIDieR checklist (Hoffmann et al., 2014), and the mHealth Evidence Reporting and Assessment (mERA) Checklist (Agarwal et al., 2016) (see Appendix A).”
From Efficacy and mechanisms of mobile application-delivered Acceptance and Commitment Therapy for posttraumatic stress disorder in China: Study protocol for a randomized controlled trial (2022) · cites this paper as Agarwal et al., 2016
There is a gap between expected and actual benefits of mHealth and a lack of an evidence base regarding the actual impact of mHealth initiatives.
“Despite such expectations, it has become common within scholarly literature to lament the gap between expected and actual benefits and the lack of an evidence base regarding the actual impact of mHealth initiatives [3, 6, 28].”
From Situating mobile health: a qualitative study of mHealth expectations in the rural health district of Nouna, Burkina Faso (2017) · cites this paper as [28]
In 2016 the WHO mHealth Technical Evidence Review group released a checklist detailing 16 key criteria for reporting and assessing mHealth interventions, developed to help researchers develop and assess the evidence by providing a checklist for reporting the quality of the intervention.
“In 2016, the WHO mHealth Technical Evidence Review group released a checklist detailing 16 key criteria for reporting and assessing mHealth interventions.24”
From Designing evaluation plans for health promotion mHealth interventions: a case study of the <i>Milk Man</i> mobile app (2016) · cites this paper as [24]
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- Authors
- Agarwal, S., LeFevre, A. E., Lee, J., L’Engle, K., Mehl, G., Sinha, C., & Labrique, A.
- Affiliations
- University of North Carolina at Chapel Hill (US)
- Johns Hopkins University (US)
- Family Health International 360 (US)
- World Health Organization (CH)
- International Development Research Centre (CA)
- Corresponding author
- Labrique, Alain
- Venue
- BMJ
- Publisher
- BMJ
- Published
- 2016-03-17
- Volume
- 352
- Pages
- i1174
- ISSN
- 1756-1833 (ISSN-L)
- OpenAlex
- W2300936160
- Cited by
- 639
- References
- 31
- Citations by year
- 2026: 68 · 2025: 65 · 2024: 48 · 2023: 64 · 2022: 70 · 2021: 62 · 2020: 76 · 2019: 64 · 2018: 52 · 2017: 51 · 2016: 18 · 2015: 1
- FWCI
- 114.83
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- BMJ (publishedVersion)
- PubMed (publishedVersion)
- Carolina Digital Repository (University of North Carolina at Chapel Hill) (submittedVersion)
- HighWire Press Open Archive (submittedVersion)
- UNC Libraries
- Funders
- World Health Organization
- UNICEF
- United Nations Foundation
- Norwegian Institute of Public Health
- Topics
- Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
- Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
- Social Sciences › Psychology › Applied Psychology › Digital Mental Health Interventions
- Keywords
- mobile health, mobile health intervention, reporting guidelines, reporting checklist, intervention definition, intervention context, technical features, intervention replication, quality of evidence, health interventions
- MeSH terms
- Health Planning Guidelines, Health Services Accessibility, Humans, Quality of Health Care, Program Development, Telemedicine, Cell Phone, Checklist, Quality Improvement
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 ›
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