Understanding delays in care-seeking behavior in heart failure: a comprehensive scoping review
Bibliographic record
Abstract
BACKGROUND: Delayed care-seeking in heart failure patients is associated with adverse clinical outcomes, yet the factors contributing to such delays remain inconsistently defined and poorly understood. This scoping review aimed to systematically summarize existing evidence regarding definitions, durations, and influencing factors of delays in seeking medical care among heart failure patients, thereby providing a foundation for future intervention research. METHODS: A systematic search was conducted across eight electronic databases, including PubMed, Embase, Web of Science, Cochrane Library, China National Knowledge Infrastructure (CNKI), Wanfang, China Biomedical Literature Database (CBM), and VIP Database, from database inception to May 1, 2023. Additional studies were identified by manually screening reference lists. Articles were selected based on predefined inclusion and exclusion criteria. Thematic analysis was performed to extract and categorize definitions of delay, reported delay durations, and associated influencing factors. RESULTS: Fifteen studies, published between 1997 and 2021, comprising 7,303 patients with HF were identified as eligible. They were predominantly conducted in the United States (10/15), with the remainder from China, Canada, Japan, the Netherlands, and Sweden. The study designs included cross-sectional (n = 7), retrospective (n = 5), descriptive (n = 2), and prospective (n = 1) approaches. Definitions of delay varied, most commonly describing the interval from symptom onset or exacerbation to hospital arrival. The median delay time ranged from 2 to 168 h, while the average delay time spanned 13.3 to 392.2 h. Thematic analysis identified five major categories of influencing factors: (1) sociodemographic factors (e.g., age, sex, ethnicity); (2) environmental factors (e.g., geographic location, time of symptom onset); (3) psychological factors (e.g., depression, anxiety); (4) disease-related factors (e.g., comorbidities, symptom burden); and (5) symptom experience (e.g., perception, evaluation, and response to symptoms). Considerable variability in definitions of delay, measurement tools, and analytic methods contributed to inconsistencies across studies. CONCLUSION: Delays in seeking medical care are common among patients with HF and are shaped by multiple interacting factors. Future studies should adopt standardized definitions, apply validated assessment tools, and utilize longitudinal designs to clarify causal relationships. Interventions targeting symptom awareness, health literacy, and psychological support-particularly among older adults and those in rural areas-may help reduce avoidable delays and improve clinical outcomes.
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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 | 0.019 | 0.095 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.006 | 0.008 |
| Bibliometrics | 0.023 | 0.021 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".