A systematic review of interventions addressing limited health literacy to improve asthma self-management
Bibliographic record
Abstract
BACKGROUND: Supported asthma self-management improves health outcomes. However, people with limited health literacy, especially in lower-middle-income countries (LMICs), may need tailored interventions to enable them to realise the benefits. We aimed to assess the clinical effectiveness of asthma self-management interventions targeted at people with limited health literacy and to identify strategies associated with effective programmes. METHODS: Following Cochrane methodology, we searched ten databases (January 1990 - June 2018; updated October 2019), without language restriction. We included controlled experimental studies whose interventions targeted health literacy to improve asthma self-management. Selection of papers, extraction of data and quality assessment were done independently by two reviewers. The primary outcomes were clinical (asthma control) and implementation (adoption/adherence to intervention). Analysis was narrative. RESULTS: = 0.001); the other showed no effect. None reported uptake or adherence to the intervention. Behavioural change strategies typically focused on improving an individual's psychological and physical capacity to enact behaviour (eg, targeting asthma-related knowledge or comprehension). Only two interventions also targeted motivation; none sought to improve opportunity. Less than half of the interventions used specific self-management strategies (eg, written asthma action plan) with tailoring to limited health literacy status. Different approaches (eg, video-based and pictorial action plans) were used to provide education. CONCLUSIONS: The paucity of studies and diversity of the interventions to support people with limited health literacy to self-manage their asthma meant that the impact on health outcomes remains unclear. Given the proportion of the global population who have limited health literacy skills, this is a research priority. PROTOCOL REGISTRATION: PROSPERO CRD 42018118974.
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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 | 0.013 | 0.057 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.009 |
| Bibliometrics | 0.013 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".