Relationships among coping, loneliness, and depression in Chinese older patients with major depressive disorder: a case-control study
Bibliographic record
Abstract
OBJECTIVES: To investigate the relationships among loneliness, maladaptive coping, and depressive symptoms in Chinese older patients with major depressive disorder (MDD), and to compare differences in loneliness and coping between Chinese older individuals with and without depression. METHODS: Chinese patients aged ≥60 years who were diagnosed with MDD were approached in a randomised sequence during follow-up appointments at psychiatric outpatient clinics. Attendees of general outpatient clinics and elderly community centres matched for age, sex, and education level were recruited by convenience sampling as controls. Both groups completed a questionnaire that included the six-item De Jong Gierveld Loneliness Scale, the Brief Coping Orientation to Problem Experiences Inventory, the Social Readjustment Rating Scale, the Hamilton Depression Rating Scale, the Hong Kong version of the Montreal Cognitive Assessment, the Cumulative Illness Rating Scale-Geriatric, and the Lawton Instrumental Activities of Daily Living scale. Hierarchical multiple linear regression was performed to examine relationships among coping, loneliness, and depressive symptoms, followed by correlation and mediation analyses. RESULTS: In total, 100 cases and 100 matched controls were included in the analysis. Cases reported significantly greater overall, emotional, and social loneliness relative to controls. Among patients with MDD, emotional loneliness and avoidant coping were associated with depressive symptoms. Among controls, only emotional loneliness was associated with depressive symptoms. Among all participants, avoidant coping partially mediated the relationship between emotional loneliness and depressive symptoms. Depressive symptoms were positively correlated with overall, emotional, and social loneliness, and avoidant coping and negatively correlated with problem-focused coping. CONCLUSION: Loneliness and coping should be considered in comprehensive clinical assessments, psychiatric formulations, and individualised treatment plans for older patients with MDD. Targeted interventions addressing emotional loneliness and maladaptive coping strategies are warranted in MDD management.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".