Evidence-based intervention sustainability strategies: a systematic review
Bibliographic record
Abstract
BACKGROUND: Sustainability of evidence-based interventions (EBI) remains a challenge for public health community-based institutions. The conceptual definition of sustainment is not universally agreed upon by researchers and practitioners, and strategies utilized to facilitate sustainment of EBI are not consistently reported in published literature. Given these limitations in the field, a systematic review was conducted to summarize the existing evidence supporting discrete sustainment strategies for public health EBIs and facilitating and hindering factors of sustainment. METHODS: We searched PsychINFO, Embase, ProQuest, PubMed, and Google Scholar. The initial search was run in March 2017 and an update was done in March 2019. Study eligibility criteria included (a) public health evidence-based interventions, (b) conducted in the community or community-based settings, and (c) reported outcomes related to EBI sustainment. Details characterizing the study setting, design, target population, and type of EBI sustained were extracted. RESULTS: A total of 26 articles published from 2004 to 2019 were eligible for data extraction. Overall, the importance of sustainability was acknowledged across all of the studies. However, only seven studies presented a conceptual definition of sustainment explicitly within the text. Six of the included studies reported specific sustainment strategies that were used to facilitate the sustainment of EBI. Only three of the studies reported their activities related to sustainment by referencing a sustainment framework. Multiple facilitators (i.e., adaptation/alignment, funding) and barriers (i.e., limited funding, limited resources) were identified as influencing EBI sustainment. The majority (n = 20) of the studies were conducted in high-income countries. Studies from low-income countries were mostly naturalistic. All of the studies from low-income countries reported lack of funding as a hindrance to sustainment. IMPLICATION FOR DISSEMINATION AND IMPLEMENTATION RESEARCH: Literature focused on sustainment of public health EBIs should present an explicit definition of the concept. Better reporting of the framework utilized, steps followed, and adaptations made to sustain the intervention might contribute to standardizing and developing the concept. Moreover, encouraging longitudinal dissemination and implementation (D&I) research especially in low-income countries might help strengthen D&I research capacity in public health settings.
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
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 | 0.029 | 0.109 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.013 | 0.014 |
| Bibliometrics | 0.023 | 0.017 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.005 | 0.004 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 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".