Suitability of the Attitudes to Aging Questionnaire Short Form for Use among Adults in Their 50s: A Cross-Sectional e-Survey Study
Bibliographic record
Abstract
This cross-sectional e-survey study examines the suitability (reliability and validity) of the 12-item Attitudes to Aging Questionnaire Short Form (AAQ-SF) for use among adults in their 50s. The AAQ-SF instrument was originally designed to capture subjective perceptions of physical change, psychosocial loss, and psychological growth by asking people aged 60 and beyond how they feel about growing older. Our sample comprised 517 people residing in three Canadian provinces. Respondents completed the Attitudes to Aging Questionnaire Short Form, the Rosenberg Self-Esteem Scale, and a short sociodemographic profile. Our findings replicate the original AAQ-SF structure for physical change, psychosocial loss, and psychological growth, with a promising internal consistency range for the third subscale. In our sample, psychological growth is best represented as 'Self' and 'Generativity', with a particularly greater capacity to explain variations in scores for item 18 and item 21. Physical change and psychosocial loss scores strongly differed based on perceived health and chronic illness presence. Psychosocial loss and psychological growth were moderately correlated with two aspects of self-esteem. We relate these patterns of findings within the context of prevailing growth and development theory and their perceived implications within the context of COVID-19 and post-pandemic life.
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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 | 0.006 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".