Nurses’ perspectives on the characteristics of high-functioning teams in primary care during the COVID-19 pandemic
Bibliographic record
Abstract
Context : The COVID-19 pandemic provides an opportunity to explore the qualities that enable greater team adaptability, as a team’s ability to respond effectively to disruption is a good indicator of how well it functions. Considering that effective teamwork develops over time and that the activities of primary care nurses are largely dependent on team functioning, highlighting what best promotes effective teamwork from their perspective could contribute to a better understanding of how to support team-based primary care. Objective : To explore nurses’ perspectives on the qualities that characterize high-functioning primary care teams and how these qualities contributed to effective team functioning during the COVID-19 pandemic. Study Design and Analysis : Semi-structured qualitative interviews conducted as part of a larger qualitative case study using a thematic analysis approach based on the four dimensions of Levesque’s (2017) teamwork framework: structural, operational, relational and functional. Setting or Dataset : Data from four Canadian regions: British Columbia, Ontario, Nova Scotia and Newfoundland and Labrador. Population Studied : Nurse Practitioners, Registered Nurses and Licensed Practical Nurses (Registered Practical Nurses in Ontario) working in primary care Intervention/Instrument: N/A. Outcome Measures N/A. Results : A total of 76 nurses were interviewed. Structurally, optimal teamwork required an inclusive perspective on team members, with particular emphasis on the impact of clerical staff on team functioning. From an operational perspective, effective communication was supported through keeping communication channels open with regular meetings adapted to new modes of care delivery, daily huddles, and electronic tools. From a relational perspective, having contributions recognized by colleagues was key to maintaining effective team functioning. Finally, from a functional perspective, high functioning required team members to be interested in and aware of each other’s responsibilities in order to share the workload of clinical and non-clinical activities. Conclusions: This study highlights specific characteristics that enabled primary care teams to cope better with change and disruption during the pandemic. As teamwork is multi-dimensional and complex, these findings provide insight into priority aspects to be supported with tools and interventions in order to build effective teamwork and increase the ability for teams to adapt.
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 | 0.011 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.006 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".