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Record W3092522942 · doi:10.22605/rrh6112

Sustainability of a rural volunteer program (Nav-CARE): a case study

2020· article· en· W3092522942 on OpenAlexaffabout
Wendy Duggleby, Barbara Pesut, Grace Warner, Cheryl Nekolaichuk, Lars Hällström, Brittany Elliott, Jennifer Swindle, Sunita Ghosh

Bibliographic record

VenueRural and Remote Health · 2020
Typearticle
Languageen
FieldHealth Professions
TopicHealth Policy Implementation Science
Canadian institutionsDalhousie UniversityAlberta Health ServicesUniversity of British Columbia, Okanagan CampusUniversity of British ColumbiaUniversity of Alberta
Fundersnot available
KeywordsMedicineSustainabilityNursing

Abstract

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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.

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 imitation

Not 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.

metaresearch head score (Codex)0.007
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score0.043

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0110.003
Scholarly communication0.0020.002
Open science0.0020.004
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.266
GPT teacher head0.620
Teacher spread0.354 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

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Citations15
Published2020
Admission routes2
Has abstractyes

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