Should we feed back research results in the midst of a study?
Bibliographic record
Abstract
BACKGROUND: This report is an introduction to a series of three research papers that describe the evolution of the approaches taken by the Translating Research in Elder Care (TREC) research team during its first four years to feed back the research findings to study participants. TREC is an observational multi-method health services research project underway in 36 nursing homes in the prairie provinces of Canada. TREC has actively involved decision makers from the sector in all stages from initial planning, through data collection to dissemination activities. However, it was not planned as a fully integrated knowledge translation project. These three papers describe our progress towards fully integrated knowledge translation--with respect to timely and requested feedback processes. The first paper reports on the process and outcomes of creating and evaluating the feedback of research findings to healthcare aides (unregulated health professionals). These aides provide over 80% of the direct care in our sample and actively requested the feedback as a condition of their continued cooperation in the data acquisition process. The second paper describes feedback from nursing home administrators on preliminary research findings (a facility annual report) and evaluation of the reports' utility. The third paper discusses an approach to providing a more in-depth form of feedback (expanded feedback report) at one of the TREC nursing homes. FINDINGS: Survey and interview feedback from healthcare aides is presented in the first paper. Overall, healthcare aides' opinions about presentation of the feedback report and the understand ability, usability, and usefulness of the content were positive. The second paper describes the use of telephone interviews with facility administrators and indicates that the majority of contextual areas (e.g., staff job satisfaction) addressed in facility annual report to be useful, meaningful, and understandable. More than one-half of the administrators would have liked to have received information on additional areas. The third paper explores how a case study that examined how involvement with the TREC study influenced management and staff at one of the TREC nursing homes. The importance of understanding organizational routines and the impact of corporate restructuring were key themes emerging from the case study. In addition, the Director of Care suggested changes to the structure and format of the feedback report that would have improved its usefulness. CONCLUSIONS: We believe that these findings will inform others undertaking integrated knowledge translation activities and will encourage others to become more engaged in feedback processes.
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 | 0.609 | 0.820 |
| Meta-epidemiology (narrow) | 0.002 | 0.003 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.010 | 0.012 |
| Science and technology studies | 0.011 | 0.023 |
| Scholarly communication | 0.045 | 0.056 |
| Open science | 0.007 | 0.019 |
| Research integrity | 0.015 | 0.019 |
| Insufficient payload (model declined to judge) | 0.010 | 0.008 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".