Screening in treatment programs for Fetal Alcohol Spectrum Disorders that could affect therapeutic progress
Bibliographic record
Abstract
Grant, T., Novick Brown, N., Graham, J., Whitney, N., Dubovsky, D. , & Nelson, L. (2013). Screening in treatment programs for Fetal Alcohol Spectrum Disorders that could affect therapeutic progress. The International Journal Of Alcohol And Drug Research, 2(3), 37-49. doi:10.7895/ijadr.v2i3.116 (http://dx.doi.org/10.7895/ijadr.v2i3.116)Aims: While structured intake interviews are the standard of care in substance abuse treatment programs, these interviews often do not screen for cognitive impairments, such as those found in fetal alcohol spectrum disorders (FASD) and other brain-based developmental disorders. The research reported here supports a brief interview protocol, the Life History Screen (LHS), that screens clients unobtrusively for adverse life-course outcomes typically found in FASD, so as to guide follow-up assessments and treatment planning.Design: Two-group observational study.Setting: A three-year case management intervention program in Washington State for high-risk women who abuse alcohol and/or drugs during pregnancy.Participants: Group 1: No prenatal alcohol exposure (N = 463); Group 2: Diagnosed with FASD (Fetal Alcohol Syndrome, Alcohol Related Neurodevelopmental Disorder, fetal alcohol effects, or static encephalopathy) by a qualified physician (N = 25), or suspected of having FASD (reported prenatal alcohol exposure and displayed behaviors consistent with a clinical diagnosis of FASD) (N = 61).Measures: The Addiction Severity Index (ASI) was administered to participants at intake. We analyzed eleven ASI items that corresponded to questions on the LHS in order to assess the potential of the LHS for identifying adults with possible FASD. The Life History Screen itself was not administered.Findings: Analysis of group differences between the diagnosed FASD and suspected FASD groups supported our decision to collapse the two groups for the main analysis. The Life History Screen shows promise as an efficient pre-treatment screen, in that core items are significantly associated with FASD group membership on factors involving childhood history, maternal drinking, education, substance use, employment, and psychiatric symptomatology.Conclusions: The Life History Screen may have utility as a self-report measure that can be used at the outset of treatment to identify clients with cognitive impairments and learning disabilities due to prenatal alcohol exposure.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".