Measuring Team Functioning During the COVID-19 Pandemic: Perspectives of Cancer Care Team Members
Bibliographic record
Abstract
Samar Attieh,1 Kelley Kilpatrick,2 Denis Chênevert,3 Marie-Pascale Pomey,4– 6 Carmen G Loiselle7– 9 1Department of Experimental Medicine, Faculty of Medicine and Health Sciences, McGill University, Montréal, QC, Canada; 2Susan E. French Chair in Nursing Research and Innovative Practice, Ingram School of Nursing, Faculty of Medicine and Health Sciences, McGill University, Montréal, QC, Canada; 3Department of Human Resources Management, HEC Montréal, Montréal, QC, Canada; 4Research Centre of the University of Montreal Hospital Centre, Montréal, QC, Canada; 5Centre d’excellence sur le partenariat avec les patients et le public, Montréal, QC, Canada; 6Department of Health Policy, Management and Evaluation, School of Public Health, University of Montréal, Montréal, QC, Canada; 7Ingram School of Nursing, Faculty of Medicine and Health Sciences, McGill University, Montréal, Canada; 8Department of Oncology, Faculty of Medicine and Health Sciences, McGill University, Montréal, Canada; 9Segal Cancer Center, Jewish General Hospital, Montréal, CanadaCorrespondence: Samar Attieh, Department of Experimental Medicine, Faculty of Medicine and Health Sciences, McGill University, 550 Sherbrooke Street West, West Towers, Suite 775, Montréal, QC, H3A 1B9, Canada, Email samar.attieh@mail.mcgill.caBackground: In a public health crisis such as COVID-19, cancer teams face significant challenges including acute work disruptions, rapid shifts in clinical practice, and burnout. Within this context, it is crucial to explore team functioning from the perspectives of multiple stakeholders.Objective: This quantitative pilot study aimed to 1) measure perceptions of multi-stakeholders on key indicators of team functioning (Team Effectiveness, TE, and Team Relational Coordination, TRC) during COVID-19 and its transition, and 2) document whether patient perceptions of TE/TRC are significantly associated with their cancer care experiences.Methods: A descriptive design with repeated measures was used. Through convenience sampling, participants were recruited from two outpatient cancer clinics at a large university-affiliated hospital, in Montréal, Qc, Canada. Sixty-six participants (ie, 13 healthcare professionals, 40 patients, 6 informal caregivers, and 7 volunteers) completed e-measures at T1 (years 2021– 2022) and n = 44 at T2 (year 2023).Results: At T1, participants reported high perceptions of Team Effectiveness (scale 1 to 6) M = 4.47; SD = 0.7 (Mdn = 4.54; IQR: 4.06– 5) and Relational Coordination (scale 1 to 5) M = 3.77; SD = 0.77 (Mdn = 3.81; IQR: 3.12– 4.38) with no significant differences in perceptions across the four groups. At T2, no significant changes in TE/TRC perceptions were found. At both time points, patient perceptions of TE/TRC were significantly correlated with positive cancer care experiences (Spearman rank correlation rs ranging from 0.69 and 0.83; p < 0.01).Conclusion: To our knowledge, this is the first study documenting perceptions of cancer team functioning amidst the pandemic as reported by multiple stakeholders. Significant relationships between patient perceptions of TE/TRC and their cancer care experiences underscore the importance of including patients’ views in team functioning processes. Future work should rely on larger sample sizes to further explore key elements of optimal team functioning.Keywords: team functioning, team effectiveness, team relational coordination, cancer care, patient satisfaction, patient experiences, COVID-19, pandemic, health crisis
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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 | 0.019 | 0.062 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.001 | 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".