Barriers and facilitators to implementing evidence-based guidelines in long-term care: a qualitative evidence synthesis
Bibliographic record
Abstract
BACKGROUND: The long-term care setting poses unique challenges and opportunities for effective knowledge translation. The objectives of this review are to (1) synthesize barriers and facilitators to implementing evidence-based guidelines in long-term care, as defined as a home where residents require 24-h nursing care, and 50% of the population is over the age of 65 years; and (2) map barriers and facilitators to the Behaviour Change Wheel framework to inform theory-guided knowledge translation strategies. METHODS: Following the guidance of the Cochrane Qualitative and Implementation Methods Group Guidance Series and the ENTREQ reporting guidelines, we systematically reviewed the reported experiences of long-term care staff on implementing evidence-based guidelines into practice. MEDLINE Pubmed, EMBASE Ovid, and CINAHL were searched from the earliest date available until May 2021. Two independent reviewers selected primary studies for inclusion if they were conducted in long-term care and reported the perspective or experiences of long-term care staff with implementing an evidence-based practice guideline about health conditions. Appraisal of the included studies was conducted using the Critical Appraisal Skills Programme Checklist and confidence in the findings with the GRADE-CERQual approach. FINDINGS: After screening 2680 abstracts, we retrieved 115 full-text articles; 33 of these articles met the inclusion criteria. Barriers included time constraints and inadequate staffing, cost and lack of resources, and lack of teamwork and organizational support. Facilitators included leadership and champions, well-designed strategies, protocols, and resources, and adequate services, resources, and time. The most frequent Behaviour Change Wheel components were physical and social opportunity and psychological capability. We concluded moderate or high confidence in all but one of our review findings. CONCLUSIONS: Future knowledge translation strategies to implement guidelines in long-term care should target physical and social opportunity and psychological capability, and include interventions such as environmental restructuring, training, and education.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gpt | no category Domain: not available · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Systematic review | high |
| grok | Meta-epidemiology (broad) Domain: not available · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Systematic review | high |
| opus | no category Domain: not available · Genre: Review About the Canadian research system: no · About a Canadian topic: no | Systematic review | high |
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 | 0.131 | 0.188 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.005 | 0.004 |
| Bibliometrics | 0.013 | 0.018 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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, unvalidatedLabeled directly by 3 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".