The short-form Memory Impact Questionnaire: development and validation among community-dwelling middle-aged and older adults
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: As they age, many people experience memory changes that can impact their everyday functioning. The Memory Impact Questionnaire (MIQ) is a 51-item measure that assesses the negative impact of memory changes on one's lifestyle activities, negative appraisals of the self-due to memory changes, perceived negative appraisals from others due to memory changes, and coping approaches intended to compensate for memory changes. To improve the utility of this tool, we developed a short form version of the MIQ and investigated its psychometric properties. RESEARCH DESIGN AND METHODS: First, we established a 27-item version of the MIQ based on re-analysis of a previously collected sample of 205 adults (Mage = 71.8, SDage = 8.7) using a newly developed statistical tool for shortening existing measures (the Optimization App for Selecting Item Subsets). Next, we examined the psychometric properties of the short-form MIQ among an independent sample of 673 middle-aged and older adults (Mage = 73.1, SDage = 7.6). RESULTS: Our results revealed strong convergent (|rs| = 0.40-0.81) and discriminant validity (|r| = 0.19), test-retest reliability [intraclass correlation coefficient (ICC = 0.91)], and internal consistency (α=0.88) of the short-form MIQ. Factor structure and model fit were investigated and confirmed via exploratory and confirmatory factor analyses. Robust measurement invariance was demonstrated across gender, age and level of education. DISCUSSION AND IMPLICATIONS: Our findings demonstrate that the shortened MIQ retains the psychometric properties of the original scale while decreasing questionnaire length by ∼50%, thus improving its utility in both clinical and research settings.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".