Medication use by adolescents and adults with fragile X syndrome
Bibliographic record
Abstract
BACKGROUND: The behavioural challenges and medical conditions associated with fragile X syndrome (FXS) can lead to increased need for medications. METHOD: This longitudinal study examined the use of prescription medications for psychotropic and non-psychotropic purposes by adolescents and adults with FXS drawn from a North American community sample (N = 105). Odds and probabilities of continuing or discontinuing medication were calculated. Predictors of medication use were calculated. RESULTS: More than two-thirds took psychotropic medication, and about one-quarter took non-psychotropic medication. Over a 3-year period, those who initially took prescription medications were considerably more likely to remain on medications than to stop. Individuals with more autism symptoms, more behavioural problems, a mental health diagnosis, and greater family income were significantly more likely to use psychotropic medication 3 years later. Individuals who had more health problems, a mental health diagnosis, and were female were more likely to use non-psychotropic medication over this time period. CONCLUSIONS: Findings highlight the elevated and ongoing use of medication by individuals with FXS. Implications for social and behavioural research on FXS are discussed.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".