An activity theory perspective on interprofessional teamwork in long-term care
Bibliographic record
Abstract
Background: Teamwork in healthcare is shaped by reciprocal interactions among individual team members and their clinical context. Cultural Historical Activity Theory (CHAT) provides a framework to study teamwork from a developmental perspective. We observed interactions between members of an Interprofessional Healthcare Team (IHT) to identify practical guidelines for educators. Method: Three Health Care Providers (HCPs) with more than 22-years' experience in a semi-urban LTC facility participated. We video-recorded two regular IHT meetings and selected excerpts for subsequent video-recall interviews. The excerpts were shown and discussed first with each team member, then with members in pairs and finally with all members reunited. We prompted participants to explain what was happening on the videos. All interviews were recorded, transcribed, and analyzed using CHAT's unit of analysis based on Activity Systems. Findings: We observed contradictions within the Activity Systems involving diverging views on outcomes of enhancing or maintaining quality of life; using non-traditional tools and spaces to sustain resident mobility; safeguarding community and patient safety despite time constraints and job titles, and unease for being paid to perform unconventional interventions. The contradictions have been grouped into three themes reflecting the Activity Systems: 1) enhancing versus maintaining quality of life; 2) improvising to achieve care goals; and 3) role fluidity. Discussion: Our findings show that practical goal-oriented and contextual adaptations rely heavily on improvisation and dialogue. Educating HCPs for interprofessional teamwork should focus on developing situational awareness to foster continuous adaptation of disciplinary interventions.
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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 | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.019 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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".