Introduction and methods of the evidence-based guidelines for the diagnosis and management of autism spectrum disorder by the Italian National Institute of Health
Bibliographic record
Abstract
BACKGROUND: Autism Spectrum Disorder (ASD) is a neuro-developmental disorder that affects communication and behavior with a prevalence of approximately 1% worldwide. Health outcomes of interventions for ASD are largely Participant Reported Outcomes (PROs). Specific guidelines can help support the best care for people with ASD to optimize these health outcomes but they have to adhere to standards for their development to be trustworthy. OBJECTIVE: The goal of this article is to describe the new methodological standards of the Italian National Institute of Health and novel aspects of this guideline development process. This article will serve as a reference standard for future guideline development in the Italian setting. METHODS: We applied the new standards of the Italian National Institute of Health to the two guidelines on diagnosis and management of children/adolescents and adults with ASD, with a focus on the scoping, panel composition, management of conflict of interest, generation and prioritization of research questions, early stakeholders' involvement, and PROs. Recommendations are based on the Grading of Recommendations Assessment, Development and Evaluation (GRADE) Evidence-to-Decision frameworks. RESULTS: Following a public application process, the ISS established two multidisciplinary panels including people with ASD and/or their caregivers. Seventy-nine research questions were identified as potentially relevant for the guideline on children and adolescents with ASD and 31 for the one on adults with ASD. Questions deemed to have the highest priority were selected for inclusion in the guidelines. Other stakeholders valued their early involvement in the process which will largely focus on PROs. The panels then successfully piloted the development of recommendations using the methodological standards and process set by the ISS with a focus on PROs. CONCLUSIONS: In this article, we describe the development of practice guidelines that focus on PROs for the diagnosis and management of ASD based on novel methods for question prioritization and stakeholder involvement. The recommendations allow for the adoption or adaptation to international settings.
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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 | 0.013 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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".