Experiences of informal caregivers taking care of heart surgery patients after discharge from hospital: a qualitative study
Bibliographic record
Abstract
Abstract Background/Introduction Open heart surgery is still the main treatment option for severe coronary and heart valve disease. After discharge from hospital, caregivers of heart surgery patients are given the main responsibility for care of their next of kin at home. There is a lack of studies on caregivers’ experiences with information from health care professionals regarding the discharge to home. Purpose To explore the informal caregivers' information and communication experiences with health care professionals following discharge to home after heart surgery Methods In-depth interviews using a semi-structured interview guide during videotelephony (Facetime), phone or face-to-face onsite interview. The settings were university hospitals in Norway and Denmark respectively and were carried out between November 2022 – January 2023. Data was analyzed in the NVivo software tool following Braun and Clarke`s 6-step thematic analysis process. Results Twelve informal caregivers (10 women, 2 men, mean age 65 years) were interviewed two to four weeks after the heart surgery patient had been discharged to home. Four main themes were identified: i) Lack of information ii) Insecurity, iii) Responsibility without knowledge and iv) Readmission to hospital is a challenge. Shortly after discharge the caregivers realized the consequences of lack of information and knowledge to facilitate for their next of kin` comfort, and how to manage if their symptoms worsened. Several caregivers were afraid, and especially if readmission to hospital due to serious complications were needed (Figure 1). Conclusion(s) Informal caregivers of heart surgery patients lack information from health care professionals, and communication with health care professionals at hospital discharge to gain knowledge, feel secured, and to be prepared for the responsibility for follow-up of their next of kin at home.Figure 1.Caregivers heart surgery pts.
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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 | 0.007 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.009 | 0.006 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| 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".