Defining an enabling environment for those with chronic disease: an integrative review
Bibliographic record
Abstract
BACKGROUND: Health policies are currently being implemented to cope with the 37% of those affected by chronic disease and 63% of deaths worldwide. Among the proposals, there is accelerating support for greater autonomy for patients, which incorporates several concepts, including empowerment. To achieve this, develop an environment to increase an individual's capacity for action seems to be a fundamental step. The aim of this study is to characterize an enabling environment for patients in the context of chronic disease management. METHODS: An integrative review design was applied. Medline, CINAHL, and Web of Science databases were searched to identify relevant literature published between 2009 and 2019. Overall, the review process was guided by the PRISMA 2020 checklist. The Mixed Methods Appraisal Tool for quality evaluation was used. RESULTS: A total of 40 articles were analyzed, divided into 18 quantitative studies, 11 qualitative studies, two mixed studies, seven expert opinions, one theory and one conference report. The following characteristics defining an enabling environment were taken from the literature relating to those with a chronic condition: Needs assessment-adaptation of responses, supporting "take care", involvement in support, knowledge improvement, engagement with professionals, use of information and communication technologies, and organization of care. Beyond that, the interactions highlighted between these seven categories characterize an enabling environment. CONCLUSION: This review specifies the essential elements of an enabling environment for patients with chronic conditions. It encompasses the partnership between the healthcare professional, such as the advanced practice nurse, and the individual for whom interventions and care strategies must be devised.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 |
| 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".