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Record W4401606135 · doi:10.2196/56189

The Internet-Based Intervention Strategies for Empowering Activities in Everyday Life: Qualitative Study of Experiences of Clients With Stroke

2024· article· en· W4401606135 on OpenAlexvenueno aff
Ida-Maria Barchéus, Maria Ranner, Eva Månsson Lexell, Lars Jacobsson, Maria Larsson-Lund

Bibliographic record

VenueJMIR Formative Research · 2024
Typearticle
Languageen
FieldMedicine
TopicStroke Rehabilitation and Recovery
Canadian institutionsnot available
FundersFamiljen Kamprads Stiftelse
KeywordsEveryday lifeIntervention (counseling)Grounded theoryPsychologyRelevance (law)The InternetQualitative researchAgency (philosophy)Process (computing)Applied psychologySociologyComputer scienceWorld Wide WebPolitical science

Abstract

fetched live from OpenAlex

BACKGROUND: There is a need to enhance access to and support for self-management of activities in everyday life after a stroke. Internet-based solutions have the potential to contribute to this development. Consequently, an internet-based intervention called Strategies for Empowering Activities in Everyday Life (SEE) was developed. The intervention aims to assist clients in developing management strategies that promote a healthy distribution and balanced engagement in various activities performed in different places and with other people. To further support the development and feasibility of this intervention, more knowledge is needed about clients' experiences during the intervention process. OBJECTIVE: This study aims to explore and describe how clients with stroke experienced the SEE intervention process and whether participation in SEE influenced their experience of everyday life. METHODS: Overall, 9 clients with stroke who received SEE participated in the study-4 (44%) women and 5 (56%) men aged 37 to 73 years. Qualitative interviews about experiences with SEE were conducted twice during the intervention process with each participant. The data were analyzed using the constant comparative method of grounded theory. RESULTS: The participants' experiences with the intervention process of SEE formed the core category, conceptualized as The relevance of and readiness for entering a change process in activities of everyday life differ among clients, constituting of two main categories: (1) an eye-opener providing agency for a change process and (2) never beginning a change process in activities in everyday life. The results showed that the relevance of and readiness for SEE differed between the participants. The experiences of 78% (7/9) of the participants reflected that the intervention process provided them with an agency to drive their own change process for activities in everyday life to promote health. Overall, 22% (2/9) of the participants refrained from entering a change process during SEE as they did not recognize any need for changes in their activities. When SEE was relevant and adopted as expected, the participants described it as an eye-opener for how they can alter their health based on how they distribute and spend their time on various activities. CONCLUSIONS: SEE has the potential to support clients' development of self-management and to take an active role in influencing their engagement in activities in everyday life and health. This study identified necessary improvements in the educational program for professionals to enhance delivery and strengthen the therapeutic mechanisms of SEE for future research. To effectively implement internet-based interventions such as SEE, it is crucial to identify clients who express a need for self-management in activities and are ready to invest the effort required to adopt a change process. Furthermore, it is indicated that participants' self-analysis of their everyday activities empowers them to adopt new self-management strategies, which can also benefit other interventions.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.008
metaresearch head score (Gemma)0.016
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.042

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.016
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0090.008
Scholarly communication0.0040.004
Open science0.0020.005
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0030.000

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 head0.070
GPT teacher head0.491
Teacher spread0.422 · 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 source (direct Gemma or distilled Codex), not a consensus.

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

Citations4
Published2024
Admission routes1
Has abstractyes

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