Mitigating COVID-19 related stress: an exploration of the mediating effect of various forms of social support
Bibliographic record
Abstract
Background: The COVID-19 pandemic is an ongoing stressor that has severely affected people’s lives and mental health. Previous literature has revealed that prolonged measures implemented to slow the spread of the virus, as well as exposure to pandemic related stressors, have led to numerous psychopathologies, including and especially symptoms of trauma- and stressor-related (TSR) disorders. Social support is a well-established buffer of stress and a protective factor following trauma exposure. Some studies have shown its efficacy in dampening psychological problems linked to COVID-19 related stressors. However, only one study has examined the mediating role of social support in general, and no study has examined the role of specific sources of support in mediating the association between exposure to COVID-19 stressors and (TSR) symptoms. Objectives: The primary aim of the current study was to examine the mediating effect of social support in the relationship between COVID-19 stressors exposure and TSR symptoms. The secondary aim of this study was to assess the differential mediating effect of distinct sources of support (i.e., support from family, friends, a professional and via social media) in this association. Methods: 5 913 adults mostly from Canada, France, Italy, the U.S., China, completed a cross-sectional web-based survey on the psychosocial effects of the COVID-19 pandemic between April and May of 2020. TSR symptoms were measured using the 6-item abridged version of the Impact of Event Scale – Revised. Exposure to COVID-19 stressors was assessed using 19 self-reported yes/no questions and social support (SS) variables were assessed using four self-reported questions with a likert-like response format: help and emotional support from friends, family, a mental health professional and support via social media. Data Analysis: Simple and parallel mediation analysis were conducted to investigate mediation effects of social support variables (i.e., social support as a composite variable as well as distinct social support variables). Results: Social support in general did not mediate the effect of COVID-19 stressors on TSR symptoms (β =.001; 95% CI = .000 - .003) in our sample. In terms of specific sources of support, support from a professional and support via social media had statistically significant but negligible mediating effects (.003 ≤ βs ≤ .01). Support from friends and family did not mediate the relationship examined. Discussion: Social support variables had little to no buffering effect on TSR symptoms in this sample during the pandemic. Studies involving comprehensive social support scales and subscales (rather than single items) are needed to determine the actual role of social support – if any – in these relations. Alternate interpretations, methodological pitfalls, as well as the practical and clinical implications of this finding are addressed. Ways to address such methodological issues in the future are discussed
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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".