Tipping the balance: introducing the see-saw model of young adults unmet healthcare needs through a critical realist and patient-oriented approach
Bibliographic record
Abstract
• Examines how identity-based stigma shapes unmet healthcare needs (UHN) in young adults. • Challenges assumptions that low UHN rates reflect equitable access or meaningful care. • Introduces the See-Saw Model, highlighting identity validation in healthcare experiences. • Explores disparities in UHN tied to social identity factors like sexual orientation. • Advocates for policies addressing structural and cultural inequities in healthcare access. This study explores the associations between sociodemographic factors, unmet healthcare needs (UHN), and mental illness among Canadian young adults aged 18–30, employing a Critical Realist (CR) and patient-oriented research (POR) approach. Utilizing data from the 2017–2018 Canadian Community Health Survey, the analysis examines how structural, cultural, and agentic mechanisms influence self-reported UHN. Despite an unexpectedly low overall proportion of UHN (<5%), the results suggest significant disparities, with higher UHN likelihoods among equity-deserving subgroups, such as those experiencing food insecurity or identifying as non-heterosexual. The findings also indicate a difference from geographic disparities (e.g., where you are) and UHN to those tied to social identity (e.g., who you are) with mental illness, highlighting the role of mutable and immutable factors. The study introduces the See-Saw Model of young adults UHN, conceptualizing healthcare experiences as a dynamic balance between stabilizing forces (e.g., social networks) and destabilizing pressures (e.g., stigma). Central to this model is the distinction between “being saw” (utilization) and “being seen” (validation of identity and needs), emphasizing the critical role of person-centred care. The findings challenge assumptions that low UHN rates reflect system efficacy and underscore the need to rethink healthcare metrics and policies. By integrating CR’s emphasis on causative mechanisms and POR’s lived experience insights, the study provides actionable pathways for addressing inequities and improving healthcare access for young adults. This work calls for equity-focused interventions that prioritize structural reforms and culturally sensitive practices to bridge the gap between healthcare utilization and meaningful care.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".