Sustainability of a rural volunteer program (Nav-CARE): a case study
Bibliographic record
Abstract
INTRODUCTION: Nav-CARE (Navigation: Connecting, Accessing, Resourcing and Engaging) is an evidence-based program that was implemented over 1 year in a rural community in western Canada. Nav-CARE uses volunteers who are trained in navigation to facilitate access to resources and provide social support to older persons living in the community with serious illness such as cancer, congestive heart failure and chronic obstructive pulmonary disease. Following implementation in which Nav-CARE was found to be feasible, acceptable and have positive outcomes, Nav-CARE was integrated into the local community-based hospice society program. Two years after a successful implementation, it continued to be sustainable in this same rural community. The purpose of this study was to explore the key factors that facilitated the sustainability of Nav-CARE in a rural hospice society. METHODS: A qualitative single case study design was used with data from several sources collected at different times: (a) pre-implementation, (b) Nav-CARE program implementation (1-year time period), (c) immediately after implementation and (d) 6 months to 2 years after implementation). Data included individual interviews with community stakeholders (n=9), the study volunteer coordinator (n=1), hospice society coordinator (n=1) and Nav-CARE volunteers (n=9). It also included meeting notes of volunteer debriefing sessions and meetings with stakeholders planning for sustainability of Nav-CARE that were held during the 1-year implementation. Data were organized using the i-PARIHS (integrated Promoting Action on Research Implementation in Health Services) framework (a well known implementation framework). Data were analyzed using Yin's qualitative case study approach. RESULTS: The findings from this case study suggested that key factors in facilitating sustainability of a rural community intervention (Nav-CARE) were the organizational context (inner context) and facilitation (facilitator and facilitation processes). Additionally, the inner context included the fit of Nav-CARE with the organization's priorities, the absorptive capacity of the organization, and organizational structure and mechanisms to integrate Nav-CARE into current programs. The hospice society was well established and supported by the rural community. The role of the facilitator and the planned facilitation processes (training of volunteer navigators, ongoing support and planning events) were key factors in the sustainability of the Nav-CARE program. The findings found that the formal role of the facilitator in the implementation and sustainability of Nav-CARE in this rural community required skills and knowledge, as well as ongoing mentorship. As well, the facilitation process for Nav-CARE included formal sustainability planning meetings involving stakeholders. CONCLUSION: Using the i-PARIHS framework and a case study approach, key factors for facilitating sustainability were identified. The role of the facilitator, the facilitation processes and the characteristics of the organizational context were important for the sustainability of Nav-CARE. Future research is needed to understand how to assess and enhance an organization's sustainability capacity and the impact of additional facilitator training and mentoring. This study provides a foundation for future research and adds to the discussion of the issue of sustainability of evidence-based interventions in rural community settings.
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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 | 0.007 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.002 |
| 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".