When Functional Capacity and Real-World Functioning Converge: The Role of Self-Efficacy
Bibliographic record
Abstract
Although functional capacity is typically diminished, there is substantial heterogeneity in functional outcomes in schizophrenia. Motivational factors likely play a significant role in bridging the capacity-to-functioning gap. Self-efficacy theory suggests that although some individuals may have the capacity to perform functional behaviors, they may or may not have confidence they can successfully perform these behaviors in real-world settings. We hypothesized that the relationship between functional capacity and real-world functioning would be moderated by the individual's self-efficacy in a sample of 97 middle-aged and older adults with schizophrenia (mean age = 50.9 ± 6.5 years). Functional capacity was measured using the Brief UCSD Performance-based Skills Assessment (UPSA-B), self-efficacy with the Revised Self-Efficacy Scale, and Daily Functioning via the Specific Level of Functioning (SLOF) scale and self-report measures. Results indicated that when self-efficacy was low, the relationship between UPSA-B and SLOF scores was not significant (P = .727). However, when self efficacy was high, UPSA-B scores were significantly related to SLOF scores (P = .020). Similar results were observed for self-reported social and work functioning. These results suggest that motivational processes (ie, self-efficacy) may aid in understanding why some individuals have the capacity to function well but do not translate this capacity into real-world functioning. Furthermore, while improvement in capacity may be necessary for improved functioning in this population, it may not be sufficient when motivation is absent.
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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 | 0.001 | 0.000 |
| 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 | 0.000 |
| 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 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".