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Record W4390939727 · doi:10.5334/ijic.icic23183

Empowering the voices of persons with disabilities: Co-creating and implementing a community engagement framework for inclusive program design and organizational development

2023· article· en· W4390939727 on OpenAlexaffabout
Alana Armas, Joseph Fulton, Hayley R. Crooks, Gift Tshuma, Karen Whitehead-Lye, W. Francis Fung, Rambel Palsis, Tram Nguyen, Sasha Elford, Barbara Moore, Michelle Nelson

Bibliographic record

VenueInternational Journal of Integrated Care · 2023
Typearticle
Languageen
FieldHealth Professions
TopicMental Health and Patient Involvement
Canadian institutionsUniversity of ManitobaSinai Health SystemMarch of Dimes Canada
Fundersnot available
KeywordsCommunity engagementPublic relationsPublic engagementBest practiceKnowledge managementPsychologySociologyPolitical scienceComputer science

Abstract

fetched live from OpenAlex

Increasing efforts in public and patient engagement have resulted in several approaches, theories, models, and frameworks. While many of these efforts have merit, they tend to be designed for engagement in healthcare organizations and services, or research. Focusing on these specific areas is useful, but these approaches lack the contextual considerations community-based organizations must work through when looking to change or improve their engagement practices. March of Dimes Canada (MODC) is a complex national organization that serves people with disabilities, operating across multiple jurisdictions and health authorities to provide community health and social care services, conducts research, provides peer support programming, and engages in advocacy work. MODC recognizes the need to improve engagement practices across all aspects of the organization, however it is difficult to implement a single engagement model or framework consistently across the organization. For this reason, our study aimed to co-create a community engagement framework that is contextually relevant to MODC and our communities, supporting the improvement of engagement practices within all aspects of the organization. We are using a co-design approach to complete the study; inviting MODC’s clients, who are people with disabilities to participate as co-researchers in this work. The co-creation of the framework is currently underway and consists of three phases. Phase one included: conducting surveys, group interviews, and a document analysis of current organizational engagement practices. Phase two included: conducting an environmental scan of other community organizations’ engagement practices; and completing a rapid review to identify theories, models and frameworks for client and public engagement. Phase three, which is currently underway, includes establishing an advisory committee of individuals who: 1) reside in Canada, and 2) have experience living with a disability. The advisory committee will co-design the engagement framework and co-create the implementation materials and processes for the resulting framework. During this phase we will also convene working groups with specific populations (i.e., caregivers, youth and their families, frontline staff, management etc.) to review the framework for validation and further refinement. To date results from phase one have found Canadian non-profit organizations that provide services and supports for people with disabilities are moving towards including clients more meaningfully through advisory committees, having people with disabilities as board members, and moving away from the charitable model of disability and tokenism. Some barriers to meaningful client engagement include funding constraints, organizational policies, accessibility, and lack of action following client feedback. These findings, along with the rapid review findings will inform the engagement framework co-design with the advisory committee. This study can provide insight on the process of developing and implementing a contextually relevant engagement framework that guides more meaningful community engagement for program design, creating organizational policies, conducting research and advocacy activities, and strategic planning. The framework will be evaluated following its implementation for continuous refinement and improvement across all levels of the organization. There will also be ongoing knowledge translation and mobilization activities to share the process, experiences, and results from the framework development within the disability and non-profit communities.

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)0.125
metaresearch head score (Gemma)0.055
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: none
Teacher disagreement score0.125
Threshold uncertainty score0.661

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1250.055
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0080.003
Science and technology studies0.0210.035
Scholarly communication0.0190.016
Open science0.0060.037
Research integrity0.0060.009
Insufficient payload (model declined to judge)0.0020.001

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.

Opus teacher head0.153
GPT teacher head0.476
Teacher spread0.323 · 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".

Quick stats

Citations0
Published2023
Admission routes2
Has abstractyes

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