The importance of interactions between patients and healthcare professionals for heart failure self-care: A systematic review of qualitative research into patient perspectives
Bibliographic record
Abstract
BACKGROUND: Effective heart failure (HF) self-care can improve clinical outcomes but is dependent on patients' undertaking a number of complex self-care behaviors. Research into the effectiveness of HF management programs demonstrates mixed results. There is a need to improve understanding of patient perspectives' of self-care need in order to enhance supportive interventions. AIM: This paper reports selected findings from a systematic review of qualitative research related to HF self-care need from the patients' perspective. The focus here is on those facets of patient-healthcare professional relationships perceived by patients to influence HF self-care. METHOD: We searched multiple healthcare databases to identify studies reporting qualitative findings with extractable data related to HF self-care need. Joanna Briggs Institute systematic review methods were employed and recognized meta-synthesis techniques were applied. Critical realist theory provided analytical direction to highlight how individual and contextual factors came together in complex ways to influence behavior and outcomes. RESULTS: Altogether 24 studies (1999-2012) containing data on patient-healthcare professional relationships and HF self-care were included. Interaction with healthcare professionals influenced self-care strongly but was notably mixed in terms of reported quality. Effective HF self-care was more evident when patients perceived that their healthcare professional was responsive, interested in their individual needs, and shared information. Poor communication and lack of continuity presented common barriers to HF self-care. CONCLUSION: Interactions and relationships with clinicians play a substantial role in patients' capacity for HF self-care. The way healthcare professionals interact with patients strongly influences patients' understanding about their condition and self-care behaviors.
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 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 | 0.011 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".