Measuring Older Adult Loneliness Across Countries
Bibliographic record
Abstract
OBJECTIVES: The topic of older adult loneliness commands increasing media and policy attention around the world. Are surveys of aging equipped to measure it? We assess the measurement of loneliness in large-scale aging studies in 31 countries by describing the available measures, testing correlations between them, and documenting their construct validity. METHODS: We use data from several "sister studies" of aging adults around the world. In each country, we document available loneliness measures, test for measurement reliability by examining correlations between different measures of loneliness, and assess how these correlations differ by gender and age group. We then evaluate construct validity by estimating correlations between loneliness measures and theoretically hypothesized constructs related to loneliness: living alone and not having a spouse. RESULTS: There is substantial heterogeneity in available measures of loneliness across countries. Within countries with multiple measures, the correlations between measures are high (range 0.384-0.777, median 0.636). Although we find several statistically significant differences in these correlations by gender and age, the differences are small (gender: range -0.098 to 0.081, median -0.026; age group: range -0.194 to 0.092, median -0.003). Correlations between loneliness measures and living alone and being without a spouse are all positive, almost universally statistically significant, and similar in magnitude across countries, supporting construct validity. DISCUSSION: This article establishes that even single-item measures of loneliness contribute meaningful information in diverse settings. Similar to the measurement of self-rated health, there are nuances to the measurement of older adult loneliness in different contexts, but it has reliable and consistent measurement properties within many countries.
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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 | 0.001 |
| 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".