A health app developer’s guide to law and policy: a multi-sector policy analysis
Open accessAbstract
BACKGROUND: Apps targeted at health and wellbeing sit in a rapidly growing industry associated with widespread optimism about their potential to deliver accessible and cost-effective healthcare. App developers might not be aware of all the regulatory requirements and best practice principles are emergent. Health apps are regulated in order to minimise their potential for harm due to, for example, loss of personal health privacy, financial costs, and health harms from delayed or unnecessary diagnosis, monitoring and treatment. We aimed to produce a comprehensive guide to assist app developers in producing health apps that are legally compliant and in keeping with high professional standards of user protection. METHODS: We conducted a case study analysis of the Australian and related international policy environment for mental health apps to identify relevant sectors, policy actors, and policy solutions. RESULTS: We identified 29 policies produced by governments and non-government organisations that provide oversight of health apps. In consultation with stakeholders, we developed an interactive tool targeted at app developers, summarising key features of the policy environment and highlighting legislative, industry and professional standards around seven relevant domains: privacy, security, content, promotion and advertising, consumer finances, medical device efficacy and safety, and professional ethics. We annotated this developer guidance tool with information about: the relevance of each domain; existing legislative and non-legislative guidance; critiques of existing policy; recommendations for developers; and suggestions for other key stakeholders. CONCLUSIONS: We anticipate that mental health apps developed in accordance with this tool will be more likely to conform to regulatory requirements, protect consumer privacy, protect consumer finances, and deliver health benefit; and less likely to attract regulatory penalties, offend consumers and communities, mislead consumers, or deliver health harms. We encourage government, industry and consumer organisations to use and publicise the tool.
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Studies report very few mental health applications with an adequate privacy policy or secure data transmission methods.
“Studies report very few mental health applications with an adequate privacy policy or secure data transmission methods (119–121).”
From Mobile intervention for individuals with psychosis, dual disorders, and their common comorbidities: A literature review (2019) · cites this paper as [121]
The Results > Consumer privacy section says many mental health apps lack privacy policies and that existing policies are often difficult for non-technical users to understand. The Results > Data security section recommends strong protections, but the passages found do not report how many apps use secure data transmission methods. No page numbers are provided in our copy. (LLM, conf=0.84)
Experimental — accuracy not yet measuredPolicies protecting app users are not rigorously applied today and lack information in important areas such as third-party data use.
“Unfortunately, policies protecting app users are not rigorously being applied today and are lacking information in some important areas such as the use of data by a third party (121).”
From Mobile intervention for individuals with psychosis, dual disorders, and their common comorbidities: A literature review (2019) · cites this paper as [121]
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- Authors
- Parker, L., Karliychuk, T., Gillies, D., Mintzes, B., Raven, M., & Grundy, Q.
- Affiliations
- The University of Sydney (AU)
- Australian Communications Consumer Action Network (AU)
- Western Sydney Local Health District (AU)
- The University of Adelaide (AU)
- Corresponding author
- Parker, Lisa
- Venue
- BMC Medical Informatics and Decision Making
- Published
- 2017-10-02
- Volume
- 17
- Issue
- 1
- Pages
- 141-141
- ISSN
- 1472-6947 (ISSN-L)
- PMC
- PMC5625720
- OpenAlex
- W2762469592
- Cited by
- 71
- References
- 25
- Citations by year
- 2026: 1 · 2025: 5 · 2024: 2 · 2023: 7 · 2022: 6 · 2021: 15 · 2020: 19 · 2019: 10 · 2018: 6
- FWCI
- 15.51
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- BMC Medical Informatics and Decision Making (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- Australian Communications Consumer Action Network
- Topics
- Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
- Social Sciences › Psychology › Applied Psychology › Digital Mental Health Interventions
- Health Sciences › Health Professions › Health Information Management › Healthcare Regulation
- Keywords
- health apps, mental health apps, app regulation, health policy, privacy, data security, consumer protection, medical device regulation, professional ethics, Australian health policy
- MeSH terms
- Australia, Ethics, Medical, Health Policy, Humans, Mental Health, Policy Making, Privacy, Mobile Applications
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.
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