Systematic review of clinical guidance documents for autism spectrum disorder diagnostic assessment in select regions
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Clinical guidance documents play an important role in ensuring access to high-quality autism spectrum disorder diagnostic assessment practices. The objective was to perform a systematic review of professional association and government clinical guidance documents for autism spectrum disorder diagnostic assessment, analyzing their quality and content. The government search was limited to English-speaking, single-payer, publicly funded health systems. A quality appraisal was conducted by two appraisers using the Appraisal of Guidelines Research and Evaluation, second edition tool. A content analysis was conducted for recommended clinical personnel and psychometric tools. The 11 documents demonstrated higher quality in Scope and Purpose (mean: 90.1, standard deviation: 7.4) and Clarity of Presentation (mean: 82.8, standard deviation: 9.4) and lower quality in Applicability (mean: 43.3, standard deviation: 23.8) and Rigor of Development (mean: 52, standard deviation: 21.9). All documents either recommended multidisciplinary team assessment or stated it was ideal. The documents varied substantially in their recommended tools and personnel for diagnostic assessment. There was little supporting evidence for team and personnel recommendations. Multiple guidance documents exist for autism spectrum disorder diagnostic assessments, with varying quality and recommendations. The substantial variation likely stems from insufficient evidence supporting assessment practices. Research is required to close the evidence gaps and inform high-quality clinical guidelines.
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.
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 | 0.005 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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 it