Conception and development of Sexual Health indicators to advance the quality of spinal cord injury rehabilitation: SCI-High Project
Bibliographic record
Abstract
CONTEXT: Although self-management is linked to reduced secondary health complications (SHCs) and enhanced overall quality of life post-spinal cord injury or disease (SCI/D), it is poorly integrated into the current rehabilitation process. Promoting self-management and assuring equity in care delivery is critical. Herein, we describe the selection of Self-Management structure, process and outcome indicators for adults with SCI/D in the first 18 months after rehabilitation admission. METHODS: Experts in self-management across Canada completed the following tasks: (1) defined the Self-Management construct; (2) conducted a systematic search of available outcomes and their psychometric properties; and (3) created a Driver diagram summarizing available evidence related to Self-Management. Facilitated meetings allowed development and selection following rapid-cycle evaluations of proposed structure, process and outcome indicators. RESULTS: The structure indicator is the proportion of staff with appropriate education and training in self-management principles. The process indicator is the proportion of SCI/D inpatients who have received a self-management assessment related to specific patient self-management goal(s) within 30 days of admission. The outcome indicator is the Skill and Technique Acquisition, and Self-Monitoring and Insight subscores of the modified Health Education Impact Questionnaire. CONCLUSION: The structure indicator will heighten awareness among administrators and policy makers regarding the need to provide staff with ongoing training related to promoting self-management skill acquisition. Successful implementation of the Self-Management process and outcome indicators will promote self-management education and skill acquisition as a rehabilitation priority, allow for personalization of skills related to the individual's self-management goal(s), and empower individuals with SCI/D to manage their health and daily activities while successfully integrating into the community.
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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 | 0.045 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".