Navigating Workforce Challenges in Long-Term Care: A Co-Design Approach to Solutions
Bibliographic record
Abstract
(1) Background: The enduring impact of COVID-19 on the long-term care (LTC) sector remains uncertain, necessitating targeted efforts to address current and emerging challenges. This study aims to identify the key stressors faced by healthcare workers (HCWs) in LTC and to co-develop innovative, actionable strategies that mitigate these stressors, foster resilience, and promote workforce retention. (2) Methods: This study utilized a qualitative co-design methodology within a mixed-methods, multi-phase framework conducted between July 2023 and October 2024. This article focuses on Phase 1, which involved 11 semi-structured focus groups and steering group discussions with 24 HCWs, including personal support workers (PSWs), nurses, and LTC administrators across Ontario to explore workplace-related distress and foster a shared understanding of challenges in the LTC sector. Data were audio-recorded, transcribed verbatim, and analyzed using thematic analysis to derive key themes and actionable insights. (3) Results: Key themes emerging from co-design sessions included the need for (i) effective workload management tools, (ii) the prioritization of psychological safety and mental health services, (iii) reducing regulatory and bureaucratic burdens, (iv) strengthening management practices, and (v) fostering recognition and a positive sector image. Co-design sessions with HCWs and leaders facilitated the identification of priority issues and high-level solutions, including addressing workload issues, implementing mental health and support programs, enhancing work-life integration, improving management training, and promoting psychological safety in LTC settings. (4) Conclusions: This study deepens our understanding of workplace challenges in the LTC sector and the factors contributing to HCWs' mental distress. Leveraging a co-design approach offers valuable insights into the lived experiences of HCWs and leaders. The findings provide actionable guidance for LTC leaders and policymakers to create effective, tailored interventions that actively engage HCWs in addressing workplace stressors and mitigating recurrent challenges.
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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 | 0.076 | 0.056 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.009 | 0.013 |
| Scholarly communication | 0.014 | 0.007 |
| Open science | 0.005 | 0.013 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 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".