A Community of Practice for Social Determinants of Health Practitioners in an Ontario Health Team
Bibliographic record
Abstract
Background: Addressing the social determinants of health (SDOH) is an important and evolving area of population health management which prompts a need for an initiative, such as a Community of Practice, that can support traditionally unregulated practitioners who serve clients whose health is impacted by SDOH. Approach: A community of practice (CoP) was established in the Frontenac, Lennox & Addington Ontario Health Team (FLA OHT) to connect practitioners working with the SDOH to share knowledge, facilitate navigation, and improve practitioner experience. SDOH practitioners include Community Services Workers (CSWs), who provide person-centered care to connect clients to community-based services aiming to support SDOH impacted health needs. Two CSWs from two Ontario Health Team partner organizations were consulted in the design of this CoP to gain a better understanding of their roles and how the SDOH CoP could be structured to provide benefit to similar community providers. Other SDOH focused practitioners, such as social services workers and practical assistance workers, share a focus on system navigation and support. There is currently no established regulatory body to support CSWs and other SDOH practitioners in their work, prompting a need for this CoP to be created. This study will evaluate the effectiveness of the FLA OHT CoP in supporting SDOH practitioners with the broader goal of better targeting SDOH in the FLA region. An online survey was created based on a previously developed framework for evaluating extra-organizational CoPs. Outcomes of interest focus on individual benefits of the CoP, assessment of CoP function and broader field impacts. Members of SDOH CoP will be invited to participate. Survey distribution began in early June 2024 and will be completed by the time of the NACIC 2024 conference. Results: Since inception in February 2023, the CoP has had 8 bimonthly meetings, presentations from community services and a wide variety of resources shared electronically. The CoP distribution list has 50+ participants and continues to grow. An early informal planning survey completed in January 2024 with responses from 2 CoP members found positive reception. The knowledge gained from partner organization presentations and opportunities to connect with other professionals that they would not typically interact with were notable highlights from participants. The formal evaluation is expected to show similar positive results on individual, group, and community outcomes. Implications: Study findings have the potential to provide evidence for implementing CoPs to support SDOH practitioners and help promote the spread and scale of such networks to other communities and OHTs with the overarching goal of improving population health and wellbeing. The audience of this presentation will gain practical knowledge on how to implement a CoP for SDOH Practitioners within their own region, including logistics such as executive sponsorship, membership recruitment, meeting organization, resource sharing methods, etc. They will also gain insight on the effectiveness of a CoP for SDOH practitioners based on evaluation results regarding individual perceived utility, CoP group function, and broader field impacts.
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 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 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.010 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.026 | 0.002 |
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".