Family Members’ Experiences of a Person-Centered Information and Communication Technology–Supported Intervention for Stroke Rehabilitation (F@ce 2.0): Qualitative Analysis
Bibliographic record
Abstract
Background: Stroke often leads to long-term effects on daily activities and participation. Consequences impact not only stroke survivors but also their close networks, and capturing their experiences is crucial for the development of effective interventions. F@ce 2.0 is a person-centered, information and communication technology (ICT)-supported stroke rehabilitation intervention currently being evaluated. Objective: This study aims to describe family members' experiences of the F@ce 2.0 intervention from the perspective of being a caregiver to a stroke survivor. Methods: Participants were family members (n=7) of stroke survivors participating in the intervention. Semistructured interviews were conducted at 2 time points, postintervention and 6 months postbaseline, resulting in a total of 13 interviews. Data was analyzed using qualitative inductive content analysis. Results: An overarching theme was developed from 4 categories. The main theme was the potential of F@ce 2.0 as a support for family members of stroke survivors in the sudden change of life. The categories were: dialogue and partnership with the F@ce 2.0 team, resuming daily activities lowers the demand for family support, support and involvement through the ICT component of F@ce 2.0, and engagement in F@ce 2.0, leading to suggestions for development. Conclusions: This study aligns with previous research delineating the effects of stroke on family members of stroke survivors. Participants highlighted the positive impact of the focus on daily activities within the intervention. Furthermore, the ICT component was perceived as a support in structuring rehabilitation. Participants, however, suggested further development, both in terms of content and technology.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.007 | 0.005 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".