Positive affect predicts everyday problem-solving ability in older adults
Bibliographic record
Abstract
OBJECTIVES: Increased symptom endorsement on the short form of the Centre for Epidemiologic Studies Depression (CES-D) Scale has been previously associated with lower everyday problem-solving (EPS) ability in older adults. However, given the multifactorial and complex nature of depressive symptoms, it remains unclear whether certain symptoms/aspects of depression account for this relationship. We examined established factor scores on the full version of the CES-D to assess their utility as predictors of EPS in an older adult cohort. METHODS: Community-dwelling older adults (n = 103; age: 51-91) were administered the CES-D along with a measure of EPS ability assessing both social and practical EPS. Regression analyses were used to determine the relationships between variables. RESULTS: Analyses revealed that increased CES-D scores predicted worse EPS ability in older adults (β = -.17, p < .05) beyond the effects of age, gender, and education. Regression analyses examining each CES-D factor score revealed that decreased positive affect (loss of hope/enjoyment in life; β = -.21, p < .01) remained the only significant predictor of decreased overall EPS scores beyond demographic variables, while depressed affect, interpersonal, and somatic factors were not significant predictors. Positive affect predicted both practical, as well as social EPS scores. CONCLUSIONS: Current results extend previous findings by showing that the relationship between increased depressive symptoms and decreased EPS ability in older age may be primarily driven by anhedonia as opposed to other depressive symptoms.
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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 | 0.003 |
| 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 | 0.001 | 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 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".