Experiences of Social Disconnection in a Bereaved Community Sample from Ontario, Canada
Bibliographic record
Abstract
Lower perceived social support is a known risk factor for problematic grief reactions, but specific facets such as social disconnection may play a critical role in shaping grief responses. This study utilized the Oxford-Grief Social Disconnection Scale (OG-SD) to examine the demographic, loss-related, and psychological correlates of its three core dimensions, as identified in previous research: Negative Interpretation of Others’ Reactions to Grief Expression, Altered Social Self, and Safety in Solitude. Participants were a non-probability sample of N = 1171 bereaved adults living in Ontario, Canada. Confirmatory factor analysis (CFA) was used to confirm the three dimensions of grief-related social disconnection identified in previous research. Correlation and one-way ANOVA tests explored demographic and loss-related correlates of these dimensions, while associations with symptoms of Prolonged Grief Disorder (PGD), depression, and anxiety were assessed through correlational analyses. CFA results confirmed that the OG-SD was best reflected by a correlated three-factor model comprising Negative Interpretation of Others’ Reactions to Grief Expression, Altered Social Self, and Safety in Solitude latent variables. Distinct associations between the core dimensions of social disconnection and loss-related variables were identified, and significant associations between all three dimensions and scores on measures of PGD, depression, and anxiety were also observed. Findings from this study not only provide additional support for the validity and reliability of the OG-SD in a general population sample of Canadian adults, for the first time, but also identify demographic, loss-related, and psychological factors associated with social disconnection.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.008 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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".