Current Issues and Future Directions for Research Into Digital Behavior Change Interventions
Open accessThe 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?
Engagement with health interventions is a precondition for effectiveness.
“Engagement with health interventions is a precondition for effectiveness; this is a particular concern for digital behavior change interventions (DBCIs), i.e., interventions that employ digital technologies such as the internet, telephones and mobile and environmental sensors. 1”
From Understanding and Promoting Effective Engagement With Digital Behavior Change Interventions (2016) · cites this paper as [1]
Heterogeneity in the design and implementation of BCTs has been a considerable challenge.
“Heterogeneity in the design and implementation of BCTs has been a considerable challenge and efforts have been made to standardize the methods to create these tools103.”
From Smart wearable devices in cardiovascular care: Where we are and how to move forward (2021) · cites this paper as [103]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
The citation lists haven’t been fetched yet
References 5 · Cited by 112
Research works printed but not linked: 2
- Hekler EB, Michie S, Rivera DE, et al. Developing and refining models and theories suitable for digital health interventions. Am J Prev Med. 2016; In press.
- Patrick K, Hekler EB, Estrin D, et al. Rapid rate of technological development and its implications for research on digital behavior change interventions. Am J Prev Med. 2016; In press.
- Authors
- Yardley, L., Choudhury, T., Patrick, K., & Michie, S.
- Affiliations
- University of Southampton (GB)
- Cornell University (US)
- University of California San Diego (US)
- University College London (GB)
- Corresponding author
- Yardley, Lucy
- Venue
- American Journal of Preventive Medicine
- Publisher
- Elsevier BV
- Published
- 2016-11
- Volume
- 51
- Issue
- 5
- Pages
- 814-815
- ISSN
- 0749-3797 (ISSN-L)
- OpenAlex
- W2531568331
- Cited by
- 112
- References
- 5
- Citations by year
- 2026: 6 · 2025: 11 · 2024: 12 · 2023: 15 · 2022: 12 · 2021: 17 · 2020: 7 · 2019: 16 · 2018: 8 · 2017: 5 · 2016: 2 · 2015: 1
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- American Journal of Preventive Medicine (publishedVersion)
- PubMed (publishedVersion)
- Explore Bristol Research (publishedVersion, cc-by-nc-nd)
- ePrints Soton (University of Southampton) (acceptedVersion)
- UCL Discovery (University College London) (submittedVersion)
- Bristol Research (University of Bristol) (submittedVersion, cc-by-nc-nd)
- Funders
- National Science Foundation (1539846)
- National Institute for Health and Care Research (NF-SI-0512-10002)
- National Institutes of Health
- Medical Research Council
- Economic and Social Research Council (ES/F029624/1)
- Office of Behavioral and Social Sciences Research
- Topics
- Social Sciences › Psychology › Applied Psychology › Digital Mental Health Interventions
- Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
- Social Sciences › Psychology › Applied Psychology › Behavioral Health and Interventions
- Keywords
- digital behaviour change interventions, behavior change, digital health interventions, intervention development, intervention evaluation, cost-effectiveness, research priorities, methodological advances, expert consensus
- MeSH terms
- Behavior Therapy, Forecasting, Humans, Research, Internet
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