ArticleJMIR mHealth and uHealth2020
Barriers and Facilitators to the Adoption of Mobile Health Among Health Care Professionals From the United Kingdom: Discrete Choice Experiment.
Article in JMIR mHealth and uHealth, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05449561 (Beyond Efficacy- Eliciting Preference for Face-to-face and Internet-based Psychotherapy Among People with Depression), which is not on this map. Cited by 47 papers, 6 of them syntheses that pooled 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.
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.
Beyond Efficacy- Eliciting Preference for Face-to-face and Internet-based Psychotherapy Among People with Depression: Using Discrete Choice Experiment to Advance Future Service Implementation
Who cites it
47 citing papers in PubMed, 6 syntheses or guidelines pooled it, 81 citations in OpenAlex.
- Adherence to Usability and Accessibility Principles in Digital Health Applications for Patients With Diabetes: Systematic Review.Journal of medical Internet research · 2025Pooled it
- A systematic review of influences on engagement with remote health interventions targeting weight management for individuals living with excess weight.International journal of obesity (2005) · 2025Pooled it
- The Evolving Landscape of Discrete Choice Experiments in Health Economics: A Systematic Review.PharmacoEconomics · 2025Pooled it
- Health Providers' Perceptions and Experiences of Using mHealth for Chronic Noncommunicable Diseases: Qualitative Systematic Review and Meta-Synthesis.Journal of medical Internet research · 2023Pooled it
- Interventions Aimed at Enhancing Health Care Providers' Behavior Toward the Prescription of Mobile Health Apps: Systematic Review.JMIR mHealth and uHealth · 2023Pooled it
- Effectiveness of eHealth and mHealth Interventions Supporting Children and Young People Living With Juvenile Idiopathic Arthritis: Systematic Review and Meta-analysis.Journal of medical Internet research · 2022Pooled it
- Understanding patient priorities in teledermatology for psoriasis: A discrete choice experiment.Journal of the European Academy of Dermatology and Venereology : JEADV · 2025Trial
- Considerations for Nurses in Recommending mHealth Apps for People Living With Chronic Conditions: A Qualitative Study.Nursing open · 2026Article
- Unraveling acceptance of healthcare innovations in neurorehabilitation: results from a discrete choice experiment.The European journal of health economics : HEPAC : health economics in prevention and care · 2026Article
- Patient and Clinician Attitudes Toward Mobile Health Apps: Qualitative Study.JMIR mHealth and uHealth · 2026Article
- Digital Health Interventions to Support Chronic Disease Management: Systematic Scoping Review.JMIR mHealth and uHealth · 2026Article
- Multi Perspective Considerations for Health Smart Home: Early Phase Exploratory Study.Journal of advanced nursing · 2026Article
- Genie in the bottle? a qualitative study of general practitioners' perspectives and information needs concerning digital mental health applications in Germany.BMC primary care · 2025Article
- Weighing Costs and Benefits of Delay and the Acceptance of Two Decision Support Tools in Mental Health Care: Scoping Study Using Quantitative and Qualitative Data.JMIR human factors · 2025Article
- Understanding Health Care Workers' Attitudes and Preferences Toward Digital Patient Monitoring Platforms: Cross-Country Survey Study.JMIR formative research · 2025Article
- Impact of the ABxSG Mobile Application on Antibiotic Prescribing: An Interrupted Time Series Study.Antibiotics (Basel, Switzerland) · 2025Article
- Evaluation of the acceptability of ESIDA app, a smartphone-based clinical decision support application to improve infectious disease outbreak detection in Tanzania: clinician perspectives.BMC public health · 2025Article
- A choice based conjoint analysis of mobile healthcare application preferences among physicians, patients, and individuals.NPJ digital medicine · 2025Article
- A systematic review of consumers' and healthcare professionals' trust in digital healthcare.NPJ digital medicine · 2025Article
- Health Professionals' Preferences for Next-Generation Sequencing in the Diagnosis of Suspected Genetic Disorders in the Paediatric Population.Journal of personalized medicine · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundDespite the increasing availability of mobile health services, clinical engagement remains minimal.
objectiveThis study aims to identify and weight barriers to and drivers of health app use among health care professionals (HCPs) from the United Kingdom.
methodsA discrete choice experiment was conducted with 222 HCPs using a web-based survey between March 2019 and June 2019. Participants were recruited to take part via social media and asked to choose their preferred option of 2 hypothetical health apps to prescribe to a hypothetical patient or to prescribe neither. Choices were characterized by differing levels of patient age, cost, published evidence bases, whether they had a National Health Service (NHS) stamp of approval, personal familiarity with the technology, and whether they were recommended by a fellow HCP. The results were analyzed using a mixed logit model, with subgroup analyses to account for heterogeneity.
resultsWe received 230 responses, a total of 96.5% (n=222/230) of respondents understood the survey task and passed the test of rationality. The median age was between 36 and 45 years, and 62.6% (n=139/222) of the health care providers responding to the survey had previously recommended the use of health apps to patients. Health apps were most likely to be prescribed to patients if they had an NHS stamp of approval or if they were recommended by another HCP (both P<.001). Published studies detailing clinical effectiveness were important (P<.001), but it would take five published studies to have the same impact on prescribing behavior as an NHS stamp of approval and two studies to be as convincing as having used the technology personally. Increasing patient age and costs resulted in significant reductions in digital health prescribing (P<.001), none more so than among allied health professionals. Willingness-to-pay for health apps increased by £124.61 (US $151.14) if an NHS stamp of approval was present and by £29.20 (US $35.42) for each published study. Overall, 8.1% (n=18/222) of respondents were reluctant to use health apps, always choosing the I would prescribe neither option, particularly among older HCPs, nurses, and those who do not use health apps personally. Subgroup analyses revealed significant differences in preferences among HCPs of differing ages and clinical backgrounds.
conclusionsAn NHS stamp of approval, published studies, and recommendations from fellow HCPs are significant facilitators of digital prescribing, whereas increasing costs and patient age are significant barriers to engagement. These findings suggest that demonstrating assurances of health apps and supporting both the dissemination and peer-to-peer recommendation of evidence-based technologies are critical if the NHS is to achieve its long-term digital transformation ambitions.
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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.