Decreasing internalized ageism: development, feasibility, and effectiveness of a process-based intervention
Bibliographic record
Abstract
A lifetime of exposure to ageism may be internalized in older adults, and these ageist beliefs that are directed inwards can have severe consequences. Unfortunately, research on reducing internalized ageism is scarce. To address this, I designed and implemented a six-week process-based intervention to reduce internalized ageism. This intervention utilized education, acceptance and commitment therapy, and attributional retraining. I evaluated the feasibility and effectiveness of this intervention in reducing internalized ageism, and the mechanisms through which it achieved this reduction. A total of 81 participants consented to the feasibility portion of the study, and 78 consented to the effectiveness portion of the study. Regarding feasibility, the program was evaluated overwhelmingly positively. Most participants rated each session and the overall program as very useful and indicated that it changed their perspectives on ageism. The program also maintained impressive engagement, with only three participants dropping out of the program, and the majority completing the between-session activities. Participants also attributed a wide range of novel behaviours to this intervention. Regarding effectiveness, participants’ internalized ageism was substantially reduced following the intervention and this was maintained at a two-month follow up; improvements were associated with large effect sizes. Additionally, this reduction of internalized ageism was mediated by increases in psychological flexibility, mindfulness, and perceived control. Altogether, this study provides a promising foundation from which to advance research on interventions that address the problem of internalized ageism – a problem that has severe consequences on the health and well-being of growing numbers of older adults in every country around the world.
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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 | 0.007 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".