Conative Dysfunction in Schizophrenia:\tA New Empirically-Derived Framework
Bibliographic record
Abstract
Conative dysfunction, defined as deficits in performing motivated or volitional action leading to the functional outcome of reduced goal-directed activity (RGDA), is explored as a fundamental and highly impairing aspect of schizophrenia. It is proposed that conative dysfunction is multifaceted and may take different forms within different individuals. Although many such factors have already been studied in schizophrenia, this has been done in a piecemeal fashion, not permitting comparisons among multiple forms of conative dysfunction to determine which ones are most impacted by the disorder or which may cluster within individuals. Thus, the heterogeneity and interrelationships between these factors has not been adequately assessed. \n \nA broad range of motivational and volitional tests, representing aspects of conative functioning drawn from a variety of fields including personality, neuropsychology, motivational psychology and psychopathology are administered to a sample of schizophrenia outpatients. Several of these have not previously been examined in the context of schizophrenia. Three research questions are addressed, including; 1) whether distinct conative “types,” characterized by separable dysfunctions, exist; 2) whether some conative functions are more impacted than others in schizophrenia, and whether this depends upon the between-individual variability addressed in question one; and 3) which conative factors are most predictive of poor functional outcomes (i.e., RGDA) in schizophrenia. These questions are addressed via 1) cluster analysis, 2) a series of profile analyses, and 3) a series of regression analyses. \n \nFindings support the existence of two distinct patterns of conative dysfunction within schizophrenia, each associated with a set of specific characteristics. One cluster is characterized by difficulty energizing (an executive function subserved by the superior medial prefrontal cortex) and reduced reward sensitivity, while the other is characterized by increased punishment sensitivity, boredom proneness, and various self-reported cognitive, volitional and emotional pathologies, in the context of intact motivation. Distinct aspects of conative dysfunction in each cluster contribute significantly to RGDA, especially boredom propensity, reward sensitivity, intrinsic motivation, and various executive functions. Comparisons are drawn between each cluster and existing clinical typologies. Implications of each of these findings for future research, clinical assessment and intervention are discussed.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.010 |
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; both teacher heads agree on what is shown here.
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".