The DOI matches its Crossref record; 15 of the 16 references it cites were found in a registry or an index.
Assessing the acceptability of a text messaging service and smartphone app to support patient adherence to medications prescribed for high blood pressure: a pilot study
Open accessPublished version of a preprint
Abstract
Aims and objectives: This paper describes a pilot non-randomised controlled study of a highly tailored 56-day text messaging and smartphone app prototype intervention to increase adherence to anti-hypertensive medication in primary care. The aim of this study was to evaluate the acceptability of the intervention and obtain patients’ views about the intervention content, the delivery mode, and the mechanisms by which the intervention supported medication adherence. Methods: Patients diagnosed with hypertension were invited and recruited to the study via general practice text messages and attended a face to face meeting with a member of the researcher team. Participants were asked to test the text messaging intervention for 28 consecutive days and switch to the smartphone app for 28 more days. Participants completed baseline and follow-up questionnaires and took part in semi-structured telephone interviews. Digital log files captured patients’ engagement with the intervention. Participant transcripts were analysed using thematic analysis. Descriptive statistics were used to summarise data from questionnaires and log files. A mixed methods analysis generated data to respond to the research questions. Results: Seventy-nine patients expressed interest to participate in this study, of whom 23 (64% male, 82% above 60 years old) were registered to take part. With one drop-out, 22 participants tested the text messaging delivery mode (with 20 being interviewed) and four of them (17%) switched to the app (with 3 being interviewed). All participants engaged and interacted with the text messages and app notifications, and all participants found the intervention content and delivery mode acceptable. They also self-reported that the interactive elements of the intervention motivated them to take their medications as prescribed. Conclusion: This study provides evidence that the digital intervention is acceptable by hypertensive patients recruited in primary care. Future research could usefully investigate its feasibility and effectiveness using rigorous research methods. Trial registration: ISRCTN12805654
Overview
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
Verification
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?
The satisfactoriness of SMS and smartphone app interventions by patients with hypertension has been established in healthcare delivery.
“Additionally, the satisfactoriness of SMS and smartphone app interventions by patients with hypertension has been established in healthcare delivery.12,54”
From Effectiveness of digital health interventions on blood pressure control, lifestyle behaviours and adherence to medication in patients with hypertension in low-income and middle-income countries: a systematic review and meta-analysis of randomised controlled trials (2024) · cites this paper as [54]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Mixed Methods Research: A Research Paradigm Whose Time Has Come
Johnson, R. B., & Onwuegbuzie, A. J. (2004) · Educational Researcher · doi:10.3102/0013189x033007014 · Cited by 11,170 · cited 1×
“A mixed method approach was used to synthesise quantitative and qualitative data to provide answers to our research questions [15].”
MethodMichie, S., Richardson, M., Johnston, M., Abraham, C., Francis, J., Hardeman, W., Eccles, M. P., Cane, J., & Wood, C. E. (2013) · Annals of Behavioral Medicine · doi:10.1007/s12160-013-9486-6 · Cited by 7,629
Self-citationMethods of data collection in qualitative research: interviews and focus groups
Gill, P., Stewart, K., Treasure, E. T., & Chadwick, B. L. (2008) · BDJ · doi:10.1038/bdj.2008.192 · Cited by 2,779
Mazzaglia, G., Ambrosioni, E., Alacqua, M., Filippi, A., Sessa, E., Immordino, V., Borghi, C., Brignoli, O., Caputi, A. P., Cricelli, C., et al. (2009) · Circulation · doi:10.1161/circulationaha.108.830299 · Cited by 637
Comorbidities of Diabetes and Hypertension: Mechanisms and Approach to Target Organ Protection
Long, A. N., & Dagogo-Jack, S. E. (2011) · Journal of Clinical Hypertension · doi:10.1111/j.1751-7176.2011.00434.x · Cited by 516
Nunes, V. M. D. A., Neilson, J., O’Flynn, N., Calvert, N., Kuntze, S., Smithson, H., BENSON, J. A., Blair, J., Bowser, A., Clyne, W., et al. (2009) · University of Huddersfield Repository (University of Huddersfield) · Cited by 384
The Sage handbook of health psychology
(2005) · Choice Reviews Online · doi:10.5860/choice.42-6538 · Cited by 256
Armitage, L. C., Kassavou, A., & Sutton, S. R. (2020) · BMJ Open · doi:10.1136/bmjopen-2019-032045 · Cited by 135
Self-citationEnhancing antiepileptic drug adherence: A randomized controlled trial
Brown, I., Sheeran, P., & Reuber, M. (2009) · Epilepsy & Behavior · doi:10.1016/j.yebeh.2009.09.014 · Cited by 118
Benefits of adherence to anti-hypertensive drug therapy
Flack, J. M., Novikov, S. V., & Ferrario, C. M. (1996) · European Heart Journal · doi:10.1093/eurheartj/17.suppl_a.16 · Cited by 111
Should we consider non-compliance a medical error?
Barber, N. (2002) · BMJ Quality & Safety · doi:10.1136/qhc.11.1.81 · Cited by 98
Kassavou, A., & Sutton, S. R. (2017) · Health Psychology Review · doi:10.1080/17437199.2017.1365617 · Cited by 85
Self-citationFactor structure and longitudinal invariance of the Medical Adherence Report Scale-Asthma
Mora, P. A., Berkowitz, A. B., Contrada, R. J., Wisnivesky, J. P., Horne, R., Leventhal, H., & Halm, E. A. (2011) · Psychology and Health · doi:10.1080/08870446.2010.490585 · Cited by 63
Kassavou, A., Mirzaei, V., Brimicombe, J. D., Edwards, S. J., Massou, E., Prevost, A. T., Griffin, S. J., & Sutton, S. R. (2020) · Journal of Medical Internet Research · doi:10.2196/16629 · Cited by 49
Self-citationKassavou, A., Houghton, V., Edwards, S. J., Brimicombe, J. D., & Sutton, S. R. (2019) · BMJ Open · doi:10.1136/bmjopen-2018-024121 · Cited by 23
Self-citation
Flagged first, then by citations
1 of the 16 references couldn’t be matched to a known paper.
Cited by
Sorted by citations
Eaton, C. K., Vallejo, N., McDonald, X., Wu, J., Rodríguez, R., Muthusamy, N., Mathioudakis, N. N., & Riekert, K. A. (2024) · Journal of Medical Internet Research · doi:10.2196/50508 · Cited by 108
Siopis, G., Moschonis, G., Eweka, E., Jung, J., Kwasnicka, D., Asare, B. Y.-A., Kodithuwakku, V., Willems, R., Verhaeghe, N., Annemans, L., et al. (2023) · The Lancet Digital Health · doi:10.1016/s2589-7500(23)00002-x · Cited by 87
Boima, V., Doku, A., Agyekum, F., Tuglo, L. S., & Agyemang, C. (2024) · EClinicalMedicine · doi:10.1016/j.eclinm.2024.102432 · Cited by 82
“12,54 We found the odds of BP control to be 2.20 times greater in the delivery of digital health intervention compared to usual care.”
BackgroundInfluentialvan Acker, J., Maenhout, L., & Compernolle, S. (2023) · Innovation in Aging · doi:10.1093/geroni/igad007 · Cited by 68
Sakima, A., Akagi, Y., Akasaki, Y., Fujii, T., Haze, T., Kawakami-Mori, F., Kitajima, K., Kobayashi, Y., Matayoshi, T., Sakaguchi, T., et al. (2024) · Hypertension Research · doi:10.1038/s41440-024-01792-7 · Cited by 32
Emadi, F., Ghanbarzadegan, A., Ghahramani, S., Bastani, P., & Baysari, M. T. (2022) · Archives of Public Health · doi:10.1186/s13690-022-00960-w · Cited by 35
Emmenis, M. V., Jamison, J. Q., Kassavou, A., Hardeman, W., Naughton, F., A’Court, C., Sutton, S., & Eborall, H. (2022) · BMJ Open · doi:10.1136/bmjopen-2021-053183 · Cited by 13
Self-citationArenas, J., Becker, S., Seay, H., Frisard, C., Hoque, S., Spano, M. A., Lindenauer, P. K., Sadasivam, R. S., Pbert, L. A., & Trivedi, M. K. (2022) · Pediatric Pulmonology · doi:10.1002/ppul.25851 · Cited by 11
Kassavou, A., Mirzaei, V., Shpendi, S., Brimicombe, J. D., Chauhan, J., Bhattacharya, D., Naughton, F., Hardeman, W., Eborall, H., Emmenis, M. V., et al. (2021) · Scientific Reports · doi:10.1038/s41598-021-88170-2 · Cited by 11
Self-citationmHealth Asthma Management App’s Content Creation, Stakeholders’ Values and Design Features
Almutairi, N., Vlahu‐Gjorgievska, E., & Win, K. T. (2024) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2024.2338326 · Cited by 5
Application of digital health products in community-dwelling older adults: A scoping review
Guo, Y., Peng, R., Zhang, C., Li, X., Du, Y., Chen, Y., Lu, Y., Li, Z., & Feng, H. (2025) · Geriatric Nursing · doi:10.1016/j.gerinurse.2025.103420 · Cited by 3
Kassavou, A., A’Court, C. E., Chauhan, J., Brimicombe, J. D., Bhattacharya, D., Naughton, F., Hardeman, W., Cecilia Mascolo, C., & Sutton, S. R. (2020) · Pilot and Feasibility Studies · doi:10.1186/s40814-020-00698-8
Self-citationSutton, S. R., Jamison, J., Beardsell, K., Fineberg, M., Conceição, R., Mirzaei, V., Alvarez, C. T., Shpendi, S., Brimicombe, J. D., Bhattacharya, D., et al. (2026) · NIHR Open Research · doi:10.3310/nihropenres.14136.1
Self-citationSutton, S. R., Beardsell, K., Bhattacharya, D., Brimicombe, J. D., Cadorna, G., Conceição, R., Simoni, A. D., Eborall, H., Griffin, S. J., Gupta, P., et al. (2025) · Programme Grants for Applied Research · doi:10.3310/gjss0929
Self-citation
Metadata
- Authors
- Kassavou, A., A’Court, C. E., Chauhan, J., Brimicombe, J. D., Bhattacharya, D., Naughton, F., Hardeman, W., Mascolo, C., & Sutton, S.
- Affiliations
- University of Cambridge (GB)
- University of East Anglia (GB)
- Corresponding author
- Kassavou, Aikaterini
- ORCID
- Venue
- Pilot and Feasibility Studies
- Published
- 2020-09-21
- Volume
- 6
- Issue
- 1
- Pages
- 134-134
- ISSN
- 2055-5784 (ISSN-L)
- PMC
- PMC7504598
- OpenAlex
- W3083655139
- Cited by
- 14
- References
- 16
- Citations by year
- 2026: 1 · 2025: 2 · 2024: 4 · 2023: 2 · 2022: 3 · 2021: 1 · 2020: 1
- FWCI
- 1.83
- Type
- journal article
- Language
- en
- Update notices
- correction (2020-10-07)
- Open access
- gold
- doi.org
- Locations
- Pilot and Feasibility Studies (publishedVersion, cc-by)
- Research Square (acceptedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- UEA Digital Repository (University of East Anglia) (acceptedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Cambridge University Engineering Department Publications Database (submittedVersion)
- Apollo (University of Cambridge) (submittedVersion, cc-by)
- Apollo (cc-by)
- Apollo
- Funders
- Programme Grants for Applied Research (RP-PG-0615-20013)
- Topics
- Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
- Health Sciences › Medicine › Family Practice › Medication Adherence and Compliance
- Health Sciences › Health Professions › Health Information Management › Health, Technology, Consumer Behavior
- Keywords
- medication adherence, hypertension, text messaging, mobile application, digital health interventions, acceptability, antihypertensive drugs, primary care, patient engagement, personalized interventions
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
