Where are the links? Using a causal loop diagram to assess interactions in healthcare coordination for youth experiencing homelessness in Toronto, Canada
Bibliographic record
Abstract
BACKGROUND: Youth experiencing homelessness (YEH) suffer from poorer physical and mental health outcomes than stably housed youth. Additionally, YEH are forced to navigate fragmented health and social service systems on their own, where they often get lost between systems when transitioning or post-discharge. Inevitably, YEH require support with health system navigation and healthcare coordination. The aim of this study is to understand interactions within and between the emergency youth shelter (EYS) and health systems that affect healthcare coordination for YEH in Toronto, Canada, and how these interactions can be targeted to improve healthcare coordination for YEH. METHODS: This study is part of a larger qualitative case study informed by the framework for transformative systems change. To understand interactions in healthcare coordination for YEH within and between the EYS and health systems, we developed a causal loop diagram (CLD) using in-depth interview data from 24 key informants at various levels of both systems. Open and focused codes developed during analysis using Charmaz's constructivist grounded theory methodology were re-analysed to identify key variables, and links between them to create the CLD. The CLD was then validated by six stakeholders through a stakeholder forum. RESULTS: The CLD illustrates six balancing and one reinforcing feedback loop in current healthcare coordination efforts within the EYS and health systems, respectively. Increasing EYS funding, building human resource capacity, strengthening inter and intra-systemic communication channels, and establishing strategic partnerships and formal referral pathways were identified among several other variables to be targeted to spiral positive change in healthcare coordination for YEH both within and between the EYS and health systems. CONCLUSIONS: The CLD provides a conceptual overview of the independent and integrated systems through which decision-makers can prioritize and guide interventions to strengthen healthcare coordination within and between the EYS and health systems. Overall, our research findings suggest that key variables such as streamlining communication and improving staff-youth relationships be prioritized, as each of these acts interdependently and influences YEH's access, quality and coordination of healthcare.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".