Patient's perspective on an integrated knowledge translation tool in homecare occupational therapy
Bibliographic record
Abstract
Abstract Background Patient engagement and integrated knowledge translation (IKT) approaches involving end-users of knowledge are increasingly documented for their social benefits in the subsequent application of health innovations. Algo is an IKT-based algorithm conceived with occupational therapists (OTs; supervisors) and non-OTs (users) in Quebec's (Canada) public homecare services (HCS) to support skill mix for bathing equipment selection. However, the unknown patient experience related to Algo's utilization in HCS hinders the deployment of adjusted facilitation strategies for the beneficiaries. Methods A multiple case study (case: a HCS minimally including an OT, a non-OT and a manager) was performed with semi-structured interviews and focus groups, based on the integrated-Promoting Action on Research Implementation in Health Services (i-PARIHS) model. For intra-case analysis, extracts related to patient's experience were analyzed thematically according to the i-PARIHS components (Innovation, Recipients and Context) by a patient collaborator who shares its recommendations. Results Seventy-four (74) extracts from 5 cases referring to different trajectories of Algo's IKT process were analyzed by the patient collaborator and discussed through 5 interviews over 14 months. The following themes were identified: the promotion of Algo's relative advantage (Innovation) adjusted to the recipients' mandates, the consolidation of interprofessional collaboration between OTs, non-OTs, and managers (Recipients) and the development of their leadership abilities through the HCS instances (Context). Conclusions Patient's recommendations on Algo's IKT process in public HCS will orientate next facilitation orientations for supporting its utilization with patients living occupational difficulties during hygiene care at home. The integration of these findings expands the epistemic perspectives considered for developing public health policies to positively impact on quality of patient care. Key messages Patient’s perspective should be involved in integrated knowledge translation studies in order to expand end-users’ consideration in the development and application of knowledge. Patient’s feedback on the knowledge translation process (i.e., knowledge, recipients and context characteristics) offers a holistic perspective of analysis for improving facilitation orientations.
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 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 | 0.017 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.007 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".