The effect of age differences in motivation on mental health information processing and help-seeking attitudes and intentions in younger versus older adults
Bibliographic record
Abstract
Changes in motivation and goals over the lifespan as posited by Carstensen’s Socioemotional Selectivity Theory (1993) have shown to effect information processing and memory, such that motivation-consistent information is more likely to be remembered and evaluated more positively by young and older adults. The aim of this study was to examine the effect of motivation-consistent mental health information on memory for and evaluations of this information as well as attitudes towards mental health services and intentions to seek these services. An Internet-based sample of 160 younger (18-25) and 175 older adults (60+) were randomly assigned to read a mental health information pamphlet that emphasized motivations relevant to either early adulthood or late adulthood. Participants completed measures assessing memory for and subjective evaluation of the pamphlet, and attitudes towards and intentions to seek mental health services. There was no significant interaction between age group and pamphlet version on any of the variables measured; suggesting that designing and implementing motivation-consistent mental health information for different age groups confers little benefit with respect to information retention, as well as attitudes and intentions toward seeking professional psychological help.
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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 | 0.001 | 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".