The pleasure expectancies scale (PLEX): A brief measure of expectancies for pleasure in schizophrenia
Bibliographic record
Abstract
A critical dysfunctional belief system implicated within the cognitive model of negative symptoms is low expectancies for pleasure, which refers to unhelpful beliefs characterized by generally negative expectations for one's likelihood of experiencing pleasure. In light of concerns regarding existing measures of anticipatory pleasure, the current study sought to examine the reliability and validity of a new brief self-report questionnaire, titled the Pleasure Expectancies Scale (PLEX). One hundred twenty five individuals with a diagnosis of schizophrenia-spectrum disorder (SSD) were administered the 8-item PLEX, along with a battery of other clinical and cognitive measures. The psychometric properties of the PLEX were evaluated. Cronbach's alpha was acceptable at baseline (α = 0.741) and good at the 6-month follow-up (α = 0.815, n = 75). Correlational analyses demonstrated good convergent and discriminant validity, as well as test-retest reliability at 6 months. Construct validity, as it pertains to the cognitive model of negative symptoms, was also established by way of significant correlations with negative symptoms, diminished motivation, and defeatist performance beliefs. Hierarchical regressions also revealed that the PLEX accounted for greater variance in negative symptoms beyond that of existing measures of anticipatory pleasure. Our findings suggest that the PLEX is a promising new measure of expectancies for pleasure in individuals with SSDs, with good indicators of reliability and validity. The PLEX lends itself well to both research and clinical settings, which may be particularly important given the hypothesized role of dysfunctional beliefs as mechanistic targets for treating negative symptoms using psychosocial interventions.
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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 | 0.000 | 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) | 0.002 | 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".