Affective and psychotic reactivity to daily-life stress in adults with 22q11DS: a study using the experience sampling method
Bibliographic record
Abstract
BACKGROUND: 22q11.2 deletion syndrome (22q11DS) is a genetic disorder associated with an increased risk of psychiatric disorders. Vulnerability for psychopathology has been related to an increased reactivity to stress. Here, we examined affective states, perceived stress, affective and psychotic reactivity to various sources of environmental stress using the experience sampling method (ESM), a structured diary technique allowing repeated assessments in the context of daily life. METHODS: Adults with 22q11DS (n = 31; age, 34.1 years) and matched healthy controls (HCs; n = 24; age, 39.9 years) were included. ESM was used to assess affective states, perceived stress, and stress reactivity. Data were analyzed using multilevel regression models. RESULTS: Adults with 22q11DS displayed overall higher levels of negative affect but comparable levels of positive affect compared to HCs. Higher levels of perceived stress were reported by individuals with 22q11DS. Comparable affective and psychotic reactivity in relation to all types of environmental stress was observed between the two groups. CONCLUSION: The results point toward higher levels of negative affect and differences in the perception of daily hassles in 22q11DS but no difference in affective or psychotic reactivity to stress. This study contributes to the growing literature regarding the impact of stress on the development of psychopathology in the 22q11DS population.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 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".