Validation of the 6-item De Jong Gierveld loneliness scale in French and in English
Bibliographic record
Abstract
The 6-item De Jong Gierveld Loneliness Scale (DJGLS-6) has been previously validated in various languages, including Spanish and formal Chinese. However, some translations, although actively used, have yet to be validated. Although widely used, the English and French versions of this scale have not yet been validated. To validate this scale in both languages, samples were collected from French (N = 640) and English speaking (N = 767) multinational and independent samples in France, Canada, and the United States. The psychometric properties of the French (multinational) (Cronbach's alpha = .66, Item total Correlation (ITC) = .40, Inter Item Correlation (IIC) = .24, rs = .64) and English (multinational) (Cronbach's alpha = .72, ITC = .45, IIC = .28, rs = .72) translations of the DJGLS-6 were found to be acceptable at both the multinational and independent national levels. However, at the subscale level, the psychometrics of the emotional loneliness subscale were suboptimal in both languages compared to those of the social loneliness subscale. The confirmatory factor analysis (CFA) revealed a good fit according to the standardized root mean squared residual (SRMR) (=.02) and comparative fit index (CFI) (=.95) at the French multinational level. Similar results were obtained for the English multinational sample. Overall, these results indicate that the French and English translations of the DJGLS-6 are reliable and valid measures and may be used confidently, although the emotional loneliness subscale should be used with caution when considered independently
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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 | 0.009 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".