A Parallel Process of Staff–Family Distress in Long-Term Care: A Challenge to Collaboration
Bibliographic record
Abstract
Introduction: Supporting persons living with advanced dementia in long-term care (LTC) homes requires strong collaborative partnerships between staff, family members, and residents. Yet, relational tensions-such as differing expectations around care decisions-can inhibit the implementation of collaborative partnerships at this critical point in the trajectory of care. Objective: This study aims to explore the emotional experiences of families and staff during shared decision-making processes for individuals with advanced dementia in LTC. Method: = 16) collaborating in two Canadian LTC homes. Data was collected through semistructured interviews lasting 45-60 min, which facilitated a detailed exploration of participants' narratives. The interviews were audio-recorded, transcribed, and analyzed using reflexive thematic analysis facilitated by a combination of inductive and deductive approaches. Results: Our analysis revealed a complex parallel process of trauma and grief including accumulated distress, isolation, and feelings of devalue that worked together to create distance between staff and families at a time when connection was critical. Our findings further suggested that a lack of time and space for reflection and validation for staff and family, resulted in a cycle whereby staff and families engaged in a push and pull dynamic with each viewing the other as adversaries rather than allies. Conclusion: Our findings highlight the critical need for reflexive opportunities in LTC homes to overcome and attend to the emotional barriers that interfere with true collaboration between staff and families. We hope that the proposed cycle serves as a preliminary framework to support staff in navigating difficult conversations and emotions, and fosters reflexive care that enhances, rather than obstructs, connections.
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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 | 0.031 | 0.039 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.023 | 0.035 |
| Scholarly communication | 0.013 | 0.009 |
| Open science | 0.004 | 0.017 |
| Research integrity | 0.003 | 0.005 |
| 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".