Characterizing patient-oriented tools that could be packaged with guidelines to promote self-management and guideline adoption: a meta-review
Bibliographic record
Abstract
BACKGROUND: Self-management is an important component of care for patients or consumers (henceforth termed patients) with chronic conditions. Research shows that patients view guidelines as potential sources of self-management support. However, few guidelines provide such support. The primary purpose of this study was to characterize effective types of self-management interventions that could be packaged as resources in (i.e., appendices) or with guidelines (i.e., accompanying products). METHODS: We conducted a meta-review of systematic reviews that evaluated self-management interventions. MEDLINE, EMBASE, and the Cochrane Library were searched from 2005 to 2014 for English language systematic reviews. Data were extracted on study characteristics, intervention (content, delivery, duration, personnel, single or multifaceted), and outcomes. Interventions were characterized by the type of component for different domains (inform, activate, collaborate). Summary statistics were used to report the characteristics, frequency, and impact of the types of self-management components. A Measurement Tool to Assess Systematic Reviews (AMSTAR) was used to assess the methodological quality of included reviews. RESULTS: Seventy-seven studies were included (14 low, 44 moderate, 18 high risk of bias). Reviews addressed numerous clinical topics, most frequently diabetes (23, 30 %). Fifty-four focused on single (38 educational, 16 self-directed) and 21 on multifaceted interventions. Support for collaboration with providers was the least frequently used form of self-management. Most conditions featured multiple types of self-management components. The most frequently occurring type of self-management component across all studies was lifestyle advice (72 %), followed by psychological strategies (69 %), and information about the condition (49 %). In most reviews, the intervention both informed and activated patients (57, 76 %). Among the reviews that achieved positive results, 83 % of interventions involved activation alone, 94 % in combination with information, and 95 % in combination with information and collaboration. No trends in the characteristics and impact of self-management by condition were observed. CONCLUSIONS: This study revealed numerous opportunities for enhancing guidelines with resources for both patients and providers to support self-management. This includes single resources that provide information and/or prompt activation. Further research is needed to more firmly establish the statistical association between the characteristics of self-management support and outcomes; and to and optimize the design of self-management resources that are included in or with guidelines, in particular, resources that prompt collaboration with providers.
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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 | 0.026 | 0.073 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.017 | 0.035 |
| Bibliometrics | 0.013 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| 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".