Ethnic Identity, Perceived Social Support, and Posttraumatic Growth Following Loss: Quantitative and Qualitative Findings from a University Sample
Bibliographic record
Abstract
Individuals across cultures can experience both negative and positive outcomes following loss and trauma. Social support and group identity have been found to promote growth following trauma while reducing posttraumatic stress symptoms. Guided by Calhoun and Tedeschi's (2006) conceptualization of posttraumatic growth and the influence of one's ethnic group on growth, the present study aimed to expand previous research by examining the impact of ethnic identity and receiving social support from members of one's ethnic group on posttraumatic growth and posttraumatic stress symptoms following the loss of an important relationship. University students (N = 183) who had experienced a recent relationship loss completed self-report measures of posttraumatic growth, posttraumatic stress disorder, ethnic identity, and social support received separately from members of their ethnic group and their general social network. Additionally, participants commented on how their ethnic group helped and hindered their recovery following the loss. Initial results indicated that ethnic identity exploration and ethnic identity commitment were positively correlated with posttraumatic growth. When controlling for important covariates, such as ethnicity and type of loss, ethnic identity exploration remained a significant predictor of growth, but the influence of ethnic identity commitment was no longer significant. It was further hypothesized that social support from one's ethnic group would be a more important predictor of growth than general support. Findings did not support this hypothesis. Finally, as hypothesized, social support from one's ethnic group partially mediated the relation between ethnic identity commitment and posttraumatic growth following loss. Qualitative findings highlighted the primary role of ethnic group members in the recovery process through opportunities for communication, emotional processing, and gaining a sense of togetherness and belonging. Results suggest that ethnic identity and social support may have an impact on posttraumatic growth, but these were somewhat overshadowed by the relation of ethnicity to posttraumatic growth within the current sample. Further tests of these relations within more diverse populations would contribute greatly to research in this area. Results of the current study inform and guide research and clinical interventions in order to promote positive outcomes following loss and trauma for ethnically diverse individuals.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| 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".