At a Juncture: Exploring Patterns and Trends in FASD Prevention Research from 2015 – 2021 Using the Four-Part Model of Prevention
Bibliographic record
Abstract
Background and objective Fetal Alcohol Spectrum Disorder (FASD) prevention efforts have grown in the last 25 years to go beyond the moral panic that guided the early public awareness campaigns and policy responses. In Canada, a four-part model of FASD prevention has been developed and used that describes a continuum of multisectoral efforts for women, girls, children, and their support networks, including broad awareness campaigns, safe and respectful conversations around pregnancy and alcohol use, and holistic and wraparound support services for pregnant and postpartum women with alcohol, and other health and social concerns. The purpose of this article is to describe the state of the evidence on FASD prevention from 2015 – 2021, including the prevalence and influences on alcohol use during pregnancy, interventions at each of the four levels of the fourpart model, as well as systemic, destigmatizing, and ethical considerations. Materials and methods Using EBSCO Host, seven academic databases were annually searched for articles related to FASD prevention from 2015 – 2021. English language articles were screened for relevance to alcohol use in pregnancy and FASD prevention. Using outlined procedures for thematic analysis, the findings were categorized within the following key themes: prevalence and influences on women's drinking; Level 1 prevention; Level 2 prevention; Level 3 prevention; Level 4 prevention; and systemic, destigmatizing, and ethical considerations. Results From January 2015 – December 2020, 532 (n = 532) articles were identified that addressed the prevalence and influences on alcohol use during pregnancy, interventions at each of the four levels, and systemic, destigmatizing, and ethical considerations. The most recent research on FASD prevention published in English was generated in the United States (US; n = 216, 40.6%), Canada (n = 91, 17.1%), United Kingdom (UK; n = 60, 11.3%), and Australia (n = 58, 10.9%). However, there was an increase in the studies published from other countries over the last six years. The literature heavily focused on the prevalence and influences on alcohol use during pregnancy (n = 182, 34.2%) with an increase in prevalence research from countries outside of Canada, the US, Australia, and the UK and on Level 2 prevention efforts (n = 174, 32.7%), specifically around the efficacy and implementation of brief interventions. Across Level 1 and Level 2 prevention efforts, there was an increase in literature published on the role of technology in supporting health promotion, education, screening, and brief interventions. Attention to Levels 3 and 4 demonstrated nuanced multiservice, traumainformed, relational, and holistic approaches to supporting women and their children. However, efforts are needed to address stigma, which acted as a systemic barrier to care across each level of prevention. Conclusion Research and practice of FASD prevention has continued to grow. Through our generated deductive themes, this review synthesized the findings and demonstrated how the work on FASD prevention has been amplified in the recent years and how efforts to support women and children's health are complex and interconnected. The findings highlight the opportunities for prevention through research and evidenceinformed policy and practice.
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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 | 0.034 | 0.078 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.026 | 0.032 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.007 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".