Access to mental health services for people living with heart failure: a qualitative study
Bibliographic record
Abstract
OBJECTIVES: Amidst low recognition and treatment for mental health conditions among people living with heart failure (PLWHF), this study aimed to identify factors affecting access to mental health services for PLWHF. DESIGN: Semi-structured phone interviews were conducted with PLWHF (n=13) and clinicians and researchers (n=9). SETTING: Heart failure remote management programme at a large urban academic hospital in Ontario, Canada. RESULTS: Using inductive reflexive thematic analysis, 14 themes were created and mapped to Levesque's patient-centred access to care framework, revealing barriers at the system and patient levels. System-level barriers included service approachability (ie, difficulties detecting mental health concerns; unpreparedness for referral conversations), availability and accommodation (ie, limited mental health services; poorly timed services; inconsistent care pathways) and affordability (ie, limited human resources; lack of options for choice or finding fit; insufficiency of generic mental health services). Patient-level barriers included limitations in the ability to perceive mental health needs (ie, low mental health literacy), as well as seek (ie, stigma), reach (ie, inconvenience of in-person delivery) and pay (ie, lack of full insurance coverage and high cost of psychological services) for mental healthcare. CONCLUSIONS: The findings suggest enhancing the approachability, availability and appropriateness of mental health services and promoting the ability of PLWHF to recognise their mental health needs as potential interventional targets.
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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 | 0.010 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.009 | 0.006 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".