Mechanisms of Mindfulness in Those with Higher and Lower Levels of Autism Traits
Bibliographic record
Abstract
The effects of brief mindfulness induction on a central trait of autism spectrum disorder (over-selective attention) were examined in order to assess whether different mechanisms act in those with lower and higher levels of autism traits, and determine which intervention may be most appropriate for individuals with different sets of symptoms. Two hundred and 24 volunteer participants (110 male; 114 female) were assessed for levels of autism traits (autism quotient; AQ), anxiety and depression (Hospital Anxiety and Depression Scales), and mindful awareness (Toronto Mindfulness Scale). They were randomly assigned to mindfulness, relaxation, or no-intervention groups. After three 10-min sessions, held on alternate days, participants underwent simultaneous discrimination training between two two-element compound stimuli (AB+ CD−), followed by an extinction test (AvC, AvD, BvC, BvD) to determine the amount of over-selectivity present. Levels of depression, anxiety, and mindfulness were re-assessed. Participants with greater autism traits demonstrated greater over-selectivity, than those with lower autism traits. Mindfulness reduced over-selectivity, and did so independently of the level of AQ displayed by the participants. For lower scoring AQ participants, mindfulness worked more effectively than relaxation. In contrast, for participants with higher AQ scores, there was little difference between the impact of mindfulness and relaxation. The latter group displayed no improvement in mindful awareness. Mindfulness induction can be effective, but may work through different mechanisms for those with higher and lower autism traits, and consideration should be given as to whether this intervention may be the most suitable in all cases where autism traits are present.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".