| Literature DB >> 35165674 |
Abstract
BACKGROUND: Adherence to anti-COVID-19 rules is important to slow down the pandemic spread. The present study investigated potential predictors of the adherence.Entities:
Keywords: Adherence to anti-COVID-19 rules; Psychological burden by COVID-19; Sense of control; Source of COVID-19 information
Year: 2022 PMID: 35165674 PMCID: PMC8828294 DOI: 10.1016/j.jadr.2022.100317
Source DB: PubMed Journal: J Affect Disord Rep ISSN: 2666-9153
Fig. 1Moderated mediation model with sense of control (predictor), burden by COVID-19 (mediator), COVID-19 information source (moderator) and adherence to anti-COVID-19 rules (outcome).
Descriptive statistics and correlations of sense of control, burden by COVID-19, adherence to anti-COVID-19 rules and sources of COVID-19 information.
| (2) | (3) | (4) | (5) | (6) | (7) | ||
|---|---|---|---|---|---|---|---|
| (1) Sense of Control | 3.19 (2.01) | 0.278** | −0.073** | −0.099** | −0.097* | −0.011 | 0.130** |
| (2) Burden by COVID-19 | 23.78 (7.12) | −0.130** | −0.028 | −0.013 | −0.043 | 0.228** | |
| (3) Adherence to rules | 4.20 (0.78) | 0.107** | 0.209** | 0.193** | −0.117** | ||
| (4) Newspaper | 2.05 (1.62) | 0.306** | 0.127** | −0.071* | |||
| (5) Television | 3.66 (2.12) | 0.114** | −0.072* | ||||
| (6) Official Sites | 3.98 (1.95) | 0.033 | |||||
| (7) Social Media | 3.79 (2.13) |
Notes. N = 1,247; M = Mean, SD = Standard Deviation; **p < .001, *p < .05.
Moderated Mediation Models (outcome: adherence to anti-COVID-19 rules).
| ß | SE | t | 95% | ||
|---|---|---|---|---|---|
| Moderator: | |||||
| Path | 0.982 | 0.104 | 9.441 | <0.001 | [0.778, 1.187] |
| Path | −0.012 | 0.004 | −3.501 | 0.001 | [−0.019, −0.005] |
| Interaction: Burden*Social Media → Adherence to rules | −0.005 | 0.002 | −3.082 | 0.002 | [−0.008, −0.007] |
| Path | −0.010 | 0.012 | −0.793 | 0.428 | [−0.033, 0.014] |
| Control → Burden → Adherence to rules | |||||
| Social Media: | |||||
| Low (one SD below mean = −2.127) | −0.002 | 0.004 | [−0.010, 0.006] | ||
| Medium (mean = 0) | −0.012 | 0.004 | [−0.020, −0.005] | ||
| High (one SD above mean = 2.127) | −0.022 | 0.006 | [−0.034, −0.011] | ||
| −0.005 | 0.002 | [−0.008, −0.002] | |||
| Moderator: | |||||
| Path | 0.982 | 0.104 | 9.441 | <0.001 | [0.778, 1.187] |
| Path | −0.015 | 0.003 | −4.456 | <0.001 | [−0.021, −0.008] |
| Interaction: Burden*Official Governmental Sites → Adherence to rules | 0.005 | 0.002 | 3.164 | 0.002 | [0.002, 0.008] |
| Path | −0.013 | 0.012 | −1.071 | 0.428 | [−0.036, 0.011] |
| Control → Burden → Adherence to rules | |||||
| Official Governmental Sites: | |||||
| Low (one SD below mean = −1.947) | −0.024 | 0.006 | [−0.037, −0.013] | ||
| Medium (mean = 0) | −0.015 | 0.004 | [−0.023, −0.008] | ||
| High (one SD above mean = 1.947) | −0.005 | 0.004 | [−0.013, 0.003] | ||
| 0.005 | 0.002 | [0.002, 0.009] | |||
| Moderator: | |||||
| Path | 0.982 | 0.104 | 9.441 | <0.001 | [0.778, 1.187] |
| Path | −0.014 | 0.003 | −4.232 | <0.001 | [−0.021, −0.008] |
| Interaction: Burden*Television Reports → Adherence to rules | 0.007 | 0.002 | 4.540 | <0.001 | [0.004, 0.010] |
| Path | −0.006 | 0.012 | −0.471 | 0.638 | [−0.028, 0.017] |
| Control → Burden → Adherence to rules | |||||
| Television Reports: | |||||
| Low (one SD below mean = −2.118) | −0.028 | 0.006 | [−0.041, −0.017] | ||
| Medium (mean = 0) | −0.014 | 0.004 | [−0.022, −0.007] | ||
| High (one SD above mean=2.118) | 0.001 | 0.004 | [−0.008, 0.008] | ||
| 0.007 | 0.002 | [0.004, 0.010] | |||
Notes. N = 1,247; covariates: age and gender; Control = Sense of Control; Burden = Burden by COVID-19; ß = Standardized Beta, SE = Standard Error, t = t-test, p = significance, CI = Confidence Interval.
Fig. 2Moderating effect of the source of COVID-19 information on the connection between burden by COVID-19 and adherence to anti-COVID-19 rules: a) moderator: social media use; b) moderator: use of official governmental sites; c) moderator: use of television reports.