Measurement Properties and Cross-Cultural Adaptation of the De Jong Gierveld Loneliness Scale in Adults
Bibliographic record
Abstract
Abstract: This systematic review evaluated the measurement properties of the De Jong Gierveld Loneliness Scale (DJGLS) in adults. A systematic search of four electronic databases (PubMed, EMBASE, Scopus, and PsycINFO) was conducted from inception until December 2022. The COSMIN (Consensus-Based Standards for the Selection of Health Measurement Instruments) guidelines were used to assess the methodological quality and evidence synthesis of the included studies. Forty-six studies assessed the validity and reliability of the DJGLS-11 and its short version, the DJGLS-6. Very-low-quality evidence supported the content validity, moderate to high-quality evidence confirmed the structural validity and internal consistency, and low-quality evidence supported the construct validity of the two versions. Test-retest reliability was examined for the DJGLS-6 with low-quality evidence supporting excellent interclass coefficient values of 0.73–1.00. Both scales were cross-culturally adapted and translated into 18 languages across 12 countries. Although the structural validity and internal consistency of the DJGLS were supported by high-quality evidence, very-low to low-quality evidence was available for its other measurement properties. Future studies are needed to perform a more comprehensive assessment of the measurement properties of the DJGLS before fully recommending the scale to assess loneliness in adults.
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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 | 0.022 | 0.081 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.006 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".