Development of an international research agenda for adult congenital heart disease nursing
Bibliographic record
Abstract
BACKGROUND: Since the population of adults with congenital heart disease (CHD) is growing, the role of nurse specialists is expanding. In order to advance ACHD nursing, the establishment of an international nursing research agenda is recommended. We aimed to investigate research priorities as perceived by nurse specialists and researchers in ACHD. METHODS: We applied a sequential quan-qual design. In the quantitative phase, a two-round Delphi study was conducted, in which 37 nurse specialists and nurse researchers in ACHD care participated. Respondents assessed the level of priority of 21 research topics using a 9-point rating scale (1 = no priority at all; 9 = very high priority). In the qualitative phase, semi-structured interviews were performed with six selected Delphi panelists, to scrutinize pending research questions. RESULTS: This study revealed that priority should be given to studies investigating knowledge and education of patients, outcomes of Advanced Practice Nursing, quality of life, transfer and transition, and illness experiences and psychosocial issues in adults with CHD. A low priority was given to post-operative pain, sexual functioning, transplantation in ACHD, and health care costs and utilization. Agreement about the level of priority was obtained for 14 out of 21 research topics. CONCLUSION: Based on this study, we could develop an international research agenda for ACHD. Researchers ought to focus on these areas of highest priority, in order to expand and strengthen the body of knowledge in ACHD nursing.
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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 | 0.156 | 0.079 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.009 | 0.007 |
| Scholarly communication | 0.015 | 0.018 |
| Open science | 0.003 | 0.021 |
| Research integrity | 0.011 | 0.010 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".