Contributions of intrinsic and extrinsic reward sensitivity to apathy: Evidence from traumatic brain injury.
Bibliographic record
Abstract
OBJECTIVE: Apathy is a key feature of traumatic brain injury (TBI). However, mechanisms underlying apathy are poorly understood. Evidence suggests that changes in reward may be a crucial factor. Rewards can come from two important sources: extrinsic reward (e.g., money) and intrinsic reward (e.g., enjoyment). Here, we used an experimental paradigm to examine the contributions of intrinsic-extrinsic reward sensitivity to apathy post-TBI and neurocognitive processes associated with these reward processing components. METHOD: Fifty-seven patients with TBI (TBI with clinical/severe apathy [TBI + sA], TBI with subclinical/moderate apathy [TBI + mA] and TBI without apathy [TBI-A] groups), and 30 healthy individuals completed the "birthday-gift task." In the "intrinsic reward" condition, participants chose to "go" to collect the gift or "wait" for the same gift to be delivered. In the "extrinsic reward" condition, the task was identical, however, participants received monetary incentives when choosing "going" instead of "waiting." The Montreal Cognitive Assessment was utilized for cognitive examination. RESULTS: A smaller proportion of people in the TBI + sA group had high sensitivity to both intrinsic and extrinsic rewards than the TBI + mA, TBI-A and healthy comparison groups. The TBI+sA group also perceived the "go" option on the intrinsic reward condition as more effortful and made fewer "go" decisions on the extrinsic condition. Attention was the only predictor of intrinsic reward sensitivity, whereas executive functioning, attention and group predicted extrinsic reward. CONCLUSION: This study demonstrates the relationship between intrinsic-extrinsic reward hyposensitivity and apathy post-TBI. These results may be integrated into future trials to improve apathy in clinical practice. (PsycInfo Database Record (c) 2022 APA, all rights reserved).
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".