Co-designing a Program to Improve Post-stroke Sexual Rehabilitation: The Promise of Innovative Methods
Bibliographic record
Abstract
Introduction: Most people who sustain a stroke are likely to experience sexual difficulties during their recovery. However, few people get the opportunity to address sexuality during their rehabilitation because of factors related to the organization (e.g., culture), managers (e.g., lack of resources), clinicians (e.g., perceived lack of knowledge, skills, and comfort), and clients (e.g., taboo). A multifactorial program tailored to stakeholders' needs with various complementary interventions is needed to lead to a change of practice in post-stroke sexual rehabilitation. Objective: To co-design with stakeholders (i.e., people with stroke, partners, clinicians, managers and researchers) a theory-driven multifactorial program to improve post-stroke sexual rehabilitation services. Methods: This qualitative study will be conducted in four steps using an Intervention Mapping approach and a co-design methodology divided into four phases: (1) exploration; (2) co-design; (3) validation; and (4) development. Persons with stroke, partners, clinicians and managers from five distinct stroke rehabilitation centres in the province of Quebec (Canada), and researchers will be recruited to either participate in an advisory committee or working groups throughout the study. A combination of contributions from three different types of groups (advisory group, Lego® groups, work groups) will be used for data collection. Qualitative data analysis will first be realized by two independent reviewers using the Theoretical Domains Framework, and preliminary results of analysis will be validated with the advisory and working groups. Conclusion: This study will lead to the co-design of the first theory-driven program intended to optimize post-stroke sexual rehabilitation services.
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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 | 0.064 | 0.051 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".