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Record W4307969561 · doi:10.1080/17483107.2022.2138999

Co-creation of mHealth intervention for older adults with hip fracture and family caregivers: a qualitative study

2022· article· en· W4307969561 on OpenAlexaff
Patrocinio Ariza‐Vega, Rafael Prieto‐Moreno, Marta Mora‐Traverso, Pablo Molina‐García, Maureen C. Ashe, Miguel Martín‐Matillas

Bibliographic record

VenueDisability and Rehabilitation Assistive Technology · 2022
Typearticle
Languageen
FieldMedicine
TopicHip and Femur Fractures
Canadian institutionsUniversity of British Columbia
FundersEIT Health
KeywordsmHealthFocus groupHip fractureMedicineQualitative researchHealth careIntervention (counseling)ModerationNursingGerontologyPsychological interventionPsychology

Abstract

fetched live from OpenAlex

PURPOSE: Hip fracture results in an older person's loss of independence. Limited healthcare resources make mobile Health (mHealth) an alternative. Engaging key stakeholders in health technology development is essential to overcome existing barriers. The aim of this study was to establish perspectives of older adults with hip fracture, family caregivers and health professionals (stakeholders) on the development of a mHealth system. MATERIALS AND METHODS: = 2)] with 45 participants (14 older adults, 21 caregivers and 10 health providers). Inclusion criteria were older adults ≥ 65 years who sustained a hip fracture in the previous 3 months; family caregiver of a person with hip fracture; and health providers with 2+ years of clinical experience working older adults with hip fracture. We followed standard methods for focus groups, including recording sessions, transcription and conducting an inductive content analysis. The same moderator, with clinical and research experience, conducted all focus groups. RESULTS: Three themes were generated to consider for a future mHealth intervention: (1) user-friendly design; (2) content to include recovery and prevention information; and (3) implementation factors. Our mHealth system was developed based on feedback from participants. CONCLUSIONS: Co-creating mHealth technology with stakeholders is essential for uptake and adherence. We provide an overview of the development of ActiveHip+, an mHealth system for the clinical care of older adults with hip fracture.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.287
Threshold uncertainty score0.466

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.011
GPT teacher head0.360
Teacher spread0.349 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations18
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueDisability and Rehabilitation Assistive TechnologySame topicHip and Femur FracturesFrench-language works237,207