Measuring loneliness: a head-to-head psychometric comparison of the 3- and 20-item UCLA Loneliness Scales
Bibliographic record
Abstract
BACKGROUND: Despite the growing interest in the prevalence and consequences of loneliness, the way it is measured still raises a number of questions. In particular, few studies have directly compared the psychometric properties of very short measures of loneliness to standard measures. METHODS: = 1742) and performed a head-to-head comparison of the psychometric properties of the standard (20 items) and short version (3 items) of the UCLA Loneliness Scales (UCLA-LS). All participants completed the UCLA-LS-20, UCLA-LS-3, as well as other measures of mental health, including anxiety and depression. RESULTS: First, as predicted, we found that the two loneliness scales were strongly associated with each other. Second, when using the dimensional scores of the scales, we showed that the internal reliability, convergent-, discriminant-, and known-groups validities were high and of similar magnitude between the UCLA-LS-20 and the UCLA-LS-3. Third, when the scales were dichotomized, the results were more mixed. The sensitivity and/or specificity of the UCLA-LS-3 against the UCLA-LS-20 were systematically below acceptable thresholds, regardless of the dichotomizing process used. In addition, the prevalence of loneliness was strikingly variable as a function of the cut-offs used. CONCLUSIONS: Overall, we showed that the UCLA-LS-3 provided an adequate dimensional measure of loneliness that is very similar to the UCLA-LS-20. On the other hand, we were able to highlight more marked differences between the scales when their scores were dichotomized, which has important consequences for studies estimating, for example, the prevalence of loneliness.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 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".