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Record W2112850360 · doi:10.2196/resprot.2725

Combining Users’ Needs With Health Behavior Models in Designing an Internet- and Mobile-Based Intervention for Physical Activity in Cardiac Rehabilitation

2014· article· en· W2112850360 on OpenAlexvenueno aff
Konstantinos Antypas, Silje C Wangberg

Bibliographic record

VenueJMIR Research Protocols · 2014
Typearticle
Languageen
FieldMedicine
TopicPhysical Activity and Health
Canadian institutionsnot available
FundersHelse Nord RHFUniversitetet i Tromsø
KeywordsPsychological interventionThe InternetRehabilitationIntervention (counseling)Applied psychologyBehavior changeBehavior change methodsPsychologyMedicineInternet privacyPhysical medicine and rehabilitationPhysical therapyComputer scienceNursingWorld Wide WebSocial psychology

Abstract

fetched live from OpenAlex

BACKGROUND: Internet-based physical activity interventions have great potential in supporting patients in cardiac rehabilitation. Health behavior change theories and user input are identified as important contributors in the effectiveness of the interventions, but they are rarely combined in a systematic way in the design of the interventions. OBJECTIVE: The aim of this study is to identify the appropriate theoretical framework, along with the needs of the users of a physical activity intervention for cardiac rehabilitation, and to combine them into an effective Internet- and mobile-based intervention. METHODS: We explain the theoretical framework of the intervention in a narrative overview of the existing health behavior change literature as it applies to physical activity. We also conducted a focus group with 11 participants of a cardiac rehabilitation program and used thematic analysis to identify and analyze patterns of meaning in the transcribed data. RESULTS: We chose stage-based approaches, specifically the transtheoretical model and the health action process approach as our main framework for tailoring, supplemented with other theoretical concepts such as regulatory focus within the appropriate stages. From the thematic analysis of the focus group data, we identified seven themes: (1) social, (2) motivation, (3) integration into everyday life, (4) information, (5) planning, (6) monitoring and feedback, and (7) concerns and potential problems. The final design of the intervention was based on both the theoretical review and the user input, and it is explained in detail. CONCLUSIONS: We applied a combination of health behavioral theory and user input in designing our intervention. We think this is a promising design approach with the potential to combine the high efficacy of theory-based interventions with the higher perceived usefulness of interventions designed according to user input. TRIAL REGISTRATION: Clinicaltrials.gov NCT01223170; http://clinicaltrials.gov/show/NCT01223170 (Archived by WebCite at http://www.webcitation.org/6M5FqT9Q2).

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.598
Threshold uncertainty score0.479

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.266
GPT teacher head0.558
Teacher spread0.293 · 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 designOther design
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

Citations38
Published2014
Admission routes1
Has abstractyes

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