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Record W2788900848 · doi:10.2196/mhealth.8876

Exploring the Influence of a Smartphone App (Young with Diabetes) on Young People’s Self-Management: Qualitative Study

2018· article· en· W2788900848 on OpenAlexvenueno aff
Gitte Reventlov Husted, Janne Weis, Grete Teilmann, Pernille Castensøe‐Seidenfaden

Bibliographic record

VenueJMIR mhealth and uhealth · 2018
Typearticle
Languageen
FieldHealth Professions
TopicAdolescent and Pediatric Healthcare
Canadian institutionsnot available
FundersRegion HovedstadenHerlev Hospital
KeywordsSelf-managementmHealthQualitative researchPsychologyGerontologyApplied psychologyMedicineComputer sciencePsychological interventionSociologyPsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND: Adequate self-management is the cornerstone of preventing type 1 diabetes mellitus (T1DM) complications. However, T1DM self-management is challenging for young people, who often struggle during the transition from childhood to adulthood. The mobile health (mHealth) app Young with Diabetes (YWD) was developed in collaboration with young people to enhance their T1DM self-management during this transition. OBJECTIVE: The purpose of this study was to explore the influence of YWD on young people's self-management during a 12-month period. METHODS: A qualitative explorative approach was used, comprising a purposive sample of 20 young people (11 females and 9 males, ages 15 to 23 years, with app use of 3 to 64 days) from 3 pediatric and 3 adult departments. Participants were interviewed individually using a semistructured interview guide. Data were collected from January to March 2017 and analyzed using thematic analysis. RESULTS: A total of 5 themes were identified: (1) not feeling alone anymore ("we are in this together"); (2) gaining competence by sharing experiences and practical knowledge ("they know what they are talking about"); (3) feeling safer ("it's just a click away"); (4) breaking the ice by starting to share thoughts and feelings and asking for help ("it is an outstretched hand"); and (5) lack of motivating factors ("done with the app"). Young people reported that YWD promoted self-management by peer-to-peer social support, exchanging messages with health care providers, and sharing YWD with parents. Participants recommended YWD as a supplement to self-management for newly diagnosed young people with T1DM and suggested improvements in app content and functionality. CONCLUSIONS: The mHealth app YWD has the potential to support self-management. In particular, peer-to-peer support reduced feelings of loneliness and helped young people to gain knowledge and skills for managing T1DM. A need exists for alternative ways to train health care providers in using YWD and to support collaboration between young people and their parents to further improve young people's self-management of T1DM.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.302
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.119
GPT teacher head0.448
Teacher spread0.330 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations65
Published2018
Admission routes1
Has abstractyes

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