Assessing one’s sense of normalcy: psychometric properties of the subjective normalcy inventory
Bibliographic record
Abstract
Objectives Individuals facing a personal challenge, such as age-related memory changes, may feel that their experiences are abnormal or pathological. Previous qualitative research on a group intervention that focuses on memory changes in older adulthood revealed that one of the greatest benefits derived by participants was the realization that their experience with memory changes was normal. In order to quantify this experience, we developed and validated a new measure, the 26-item Subjective Normalcy Inventory (SNI).Method Reliability and validity were assessed with a sample of 167 community-dwelling adults between the ages of 55 and 90. Questionnaire responsiveness was assessed with an additional sample of 29 older adults who completed a 5-session memory intervention program known to cultivate normalization.Results The SNI exhibited a two-factor structure, excellent test-retest reliability, ICC = .79, excellent internal consistency, Cronbach’s α = .91, and good convergent, |rs| = .46−.58, and discriminant, rs = .02–.06, validity. The measure was also responsive to change, as participants who completed the memory intervention program reported a greater sense of normalcy relative to nonintervention controls, η2p = 0.17.Conclusion The SNI has the potential to provide novel and useful outcome information for interventions designed to improve one’s sense of normalcy and may be applied in both clinical and research settings. The SNI can also be modified, validated, and used to assess subjective normalcy with respect to other personal challenges outside of memory and attention changes.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| 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".