Identify decisions and decisional needs of adults with brain-heart conditions: An integrated knowledge translation systematic review
Bibliographic record
Abstract
Background: People affected with brain-heart conditions face difficult health decisions with limited evidence. To achieve quality decision-making and outcomes, people living with brain-heart conditions need effective decision support. According to the Ottawa Decision Support Framework, proper identification of unmet decisional needs can guide the provision of tailored decision support to achieve quality decisions and better decision-making processes. The purpose of this systematic review is to identify the common decisions, decisional needs, decision-making patterns and outcomes of people with combined brain-heart conditions from the perspectives of patients, caregivers, and clinicians. Methods: Using an integrated knowledge translation approach, our mixed methods systematic review will be guided by Cochrane methods. We will include peer reviewed quantitative, qualitative and mixed methods literature that report on the decisions, decisional needs, and decision-making patterns of people with select, predetermined heart-brain conditions selected by our team. We will perform inductive content analysis of decisional need “cases” extracted from the included articles, to first build a taxonomy of decisional needs of people with brain-heart conditions, and subsequently, to determine patterns of decision-making and possible outcomes. Cases are defined as a decisional need that involves: a) a decision (what), b) a person with combined brain-heart condition (who), c) role in decision-making, whether made independently or shared with a clinician (how), d) the physical place and time where the decision is made (where/when), e) the barriers and/or facilitators to communication and coordination (why), and f) the outcomes, such as actions taken, patient’s health and well-being, and decision quality and quality of the decision-making process. Relevance: As science evolves on the intimate connections between the heart and the brain, this systematic review will offer a patient-oriented view of the emerging decision-making needs people with combined brain-heart conditions must consider. Findings will be used to inform the tailoring, development, and use of decision support interventions for persons with combined brain-heart conditions.
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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 | 0.050 | 0.290 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.007 |
| Bibliometrics | 0.016 | 0.013 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.006 | 0.008 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.003 | 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".