ArticleBMC digital health2024
Article in BMC digital health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- The impact of sleep and movement behaviour on daily mood in people with type 2 diabetes: A smartphone-based digital phenotyping study.Diabetic medicine : a journal of the British Diabetic Association · 2026Article
- Ecological Momentary Assessment of Person-Reported Outcomes in Diabetes: Unlocking Insights with Continuous Glucose Monitoring and the Potential for Precision Medicine.Current diabetes reports · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Digital phenotyping, the in-situ collection of passive (phone sensor) and active (daily surveys) data using a digital device, may provide new insights into the complex relationship between daily behaviour and mood for people with type 2 diabetes. However, there are critical knowledge gaps regarding its use in people with type 2 diabetes. This study assessed feasibility, tolerability, and user experience of digital phenotyping in people with and without type 2 diabetes after participation in a 2-month digital phenotyping study in Ireland. At study completion, participants rated methodology elements from "not a problem" to a "serious problem" on a 5-point scale and reported their comfort with the potential future use of digital phenotyping in healthcare, with space for qualitative expansion. Results: Eighty-two participants completed baseline. Attrition was 18.8%. Missing data ranged from 9-44% depending on data stream. Sixty-eight participants (82.9%) completed the user experience questionnaire (51.5% with type 2 diabetes; 61.8% female; median age-group 50-59). Tolerability of digital phenotyping was high, with "not a problem" being selected 76.5%-89.7% of the time across questions. People with type 2 diabetes (93.9%) were significantly more likely to be comfortable with their future healthcare provider having access to their digital phenotyping data than those without (53.1%), χ2 (1) = 14.01, Conclusions: An uncompensated, 2-month digital phenotyping study was feasible among people with and without diabetes, with low attrition and reasonable missing data rates. Participants found digital phenotyping to be acceptable, and even enjoyable. The potential benefits of digital phenotyping for healthcare may be more apparent to people with type 2 diabetes than the general population. Supplementary Information: The online version contains supplementary material available at 10.1186/s44247-024-00116-6.
Indexed as
Identifiers
What Socratic holds
Registered trials
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 Socratic graph.