Development and Psychometric Validation of a Questionnaire Assessing the Impact of Memory Changes in Older Adults
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Many healthy older adults experience age-related memory changes that can impact their day-to-day functioning. Qualitative interviews have been useful in gaining insight into the experience of older adults who are facing memory difficulties. To enhance this insight, there is a need for a reliable and valid measure that quantifies the impact of normal memory changes on daily living. The primary objective of this study was to develop and validate a new instrument, the Memory Impact Questionnaire (MIQ). RESEARCH DESIGN AND METHODS: We examined the underlying component structure and psychometric properties of the MIQ in a sample of 205 community-dwelling older adults. RESULTS: Principal component analysis revealed three clusters: (a) Lifestyle Restrictions, (b) Positive Coping, and (c) Negative Emotion. Comparisons of the corresponding subscale scores with scores on other instruments revealed good convergent and discriminant validity. In addition, the MIQ subscales and the total score showed good test-retest reliability (rs = 0.65-0.91) and internal consistency (αs = 0.87-0.93). DISCUSSION AND IMPLICATIONS: This novel questionnaire can be used in both clinical and research settings to better understand the impact of memory changes on the day-to-day functioning of older adults and to monitor outcomes of support programs for this population.
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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 | 0.011 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".