Student experiences with an interprofessional hope-based healthy aging research project
Bibliographic record
Abstract
Interprofessional education (IPE) and research enhances learning, team-based communication, and cross-disciplinary collaborations, which can result in higher quality care for older adults. Despite the importance of IPE, it remains underutilized in higher education, demonstrating the need for extracurricular IPE opportunities. This study describes an interprofessional research project that brought together faculty, undergraduate, and graduate students from several health and social science disciplines to design and deliver a 15-week healthy aging program for older adults living in the urban Circumpolar North. Five faculty and one graduate research assistant led the project while eight students team-taught weekly, 1-hour sessions in the community focusing on healthy lifestyles within a framework of Persuasive Hope Theory. This paper describes the project, the student training procedures, and reports the results of the student satisfaction survey regarding their involvement with the research. Using a student self-assessment survey, students report gains in thinking like a scientist, increased confidence conducting research tasks, benefits from teamwork, and greater consideration of the needs of older adults in their field of study. Despite a small sample size, this study also suggests that students may be more likely to consider a career working with older adults if given hands-on experiences.
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 | 0.008 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".