| Literature DB >> 33945206 |
Shuhua Sun1, Stephen X Zhang2, Asghar Afshar Jahanshahi3, Mehdi Jahanshahi4.
Abstract
There is little research examining how individuals' daily experience during a pandemic affects their daily mental health status and work performance. To address this knowledge gap, we invoke conservation of resources theory to propose a resource-based framework explaining how individuals' daily COVID-19 intrusive experience affects their daily mental health status (depression and anxiety) and work performance via its effect on daily psychosocial resource loss and gain; We further examine whether their supervisors' daily visionary leadership behaviour alleviates the adverse impacts of daily COVID-19 intrusive experience. Results, based on daily diary data from 139 football players (or soccer players) at 15 professional football clubs over 5 days during the COVID-19 pandemic, provided support for our predictions. Our study extends the literature by providing previously undocumented evidence on daily within-person variations in mental health status and work performance during a pandemic and by offering theory-driven insights into the mediating and moderating mechanisms involved in within-person variations.Entities:
Keywords: conservation of resources theory; diary design; mental health; visionary leadership behaviour; work performance
Mesh:
Year: 2021 PMID: 33945206 PMCID: PMC8237014 DOI: 10.1002/smi.3059
Source DB: PubMed Journal: Stress Health ISSN: 1532-3005 Impact factor: 3.454
FIGURE 1Conceptual model
Descriptive statistics and within‐person correlations of the study variables
| Variables | Mean | SD | ICC1 | 1 | 2 | 3 | 4 | 5 | 6 | 7 | |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | Exposure to people with COVID‐19 | 0.02 | 0.14 | 0.00 | ‐‐‐ | ||||||
| 2 | COVID‐19 intrusive experience | 1.77 | 1.04 | 0.31 | 0.21** |
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| 3 | Visionary leadership behaviour | 5.02 | 1.71 | 0.37 | −0.09* | −0.47** |
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| 4 | Psychosocial resource loss | 0.48 | 0.48 | 0.22 | 0.10* | 0.55** | −0.39** |
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| 5 | Psychosocial resource gain | 0.85 | 0.49 | 0.21 | −0.08 | −0.38** | 0.38** | −0.37** |
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| 6 | Mental health status (PHQ‐4) | 1.71 | 0.74 | 0.23 | 0.13** | 0.63** | −0.48** | 0.57** | −0.43** |
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| 7 | Work performance | −0.09 | 0.76 | 0.39 | −0.04 | −0.27** | 0.41** | −0.28** | 0.33** | −0.36** |
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Note: N of observations = 569, N of participants = 139. All measures were repeatedly assessed daily. The bold values in the diagonal refer to reliability coefficients.
Abbreviations: ICC1, intraclass correlation; PHQ, patient health questionnaire; SD, standard deviation.
*p < 0.05; **p < 0.01.
Comparison of measurement models of key study variables with multilevel confirmatory factor analysis
| Model | Description | χ2 |
| CFI | TLI | RMSEA | Δ |
|---|---|---|---|---|---|---|---|
| 1 | Hypothesized six‐factor model | 679.04 | 285 | 0.94 | 0.93 | 0.04 | Baseline |
| 2 | Five‐factor model (psychosocial resource loss and gain were combined) | 951.63 | 290 | 0.90 | 0.89 | 0.06 | 272.59 (5) |
| 3 | Four‐factor model (psychosocial resource loss and gain were combined; COVID‐19 intrusive experience and mental health status were combined) | 1203.72 | 294 | 0.87 | 0.84 | 0.07 | 524.68 (9) |
| 4 | Three‐factor model (psychosocial resource loss, gain, COVID‐19 intrusive experience, and mental health status were combined) | 1373.94 | 297 | 0.84 | 0.82 | 0.08 | 694.9 (12) |
| 5 | Two‐factor model (work performance vs. the rest) | 2038.12 | 299 | 0.73 | 0.71 | 0.10 | 1359.08 (14) |
| 6 | One‐factor model | 2200.84 | 300 | 0.72 | 0.68 | 0.11 | 1521.8 (15) |
Note: The hypothesized six‐factor model served as the baseline model. All alternative models were compared to it. All Δχ 2 are significant at p < 0.01. We constructed parcels as composite indicators of the factors to achieve an optimal ratio of sample size to the number of estimated indicators (Little et al., 2013). Specifically, we created three parcels for scales with five items or more including psychosocial resource loss, and psychosocial resource gain, COVID‐19 intrusive experience, and work performance by randomly combining items. A value greater than 0.90 is needed for CFI and TLI and a value smaller than 0.07 to generally indicate an acceptable fit of the model (Hooper et al., 2008; Kline, 2005).
Abbreviations: CFI, comparative fit index; RMSEA = root mean squared error of approximation; TLI, Tucker‐Lewis index.
Hierarchical linear modeling for testing Hypotheses 1–4
| Model 1: | Model 2: | Model 3: | Model 4: | Model 5: | Model 6: | |||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Mental Health Status (PHQ‐4) | Psychosocial resource loss | Psychosocial resource gain | Mental health status (PHQ‐4) | Work performance ( | Work performance ( | |||||||
| Variables | γ | SE | γ | SE | γ | SE | γ | SE | γ | SE | γ | SE |
| Intercept | 1.79** | 0.11 | 0.52** | 0.07 | 0.87** | 0.08 | 1.79** | 0.11 | −0.20 | 0.14 | −0.20 | 0.14 |
| Control | ||||||||||||
| Exposure to people with COVID‐19 | 0.15 | 0.17 | 0.06 | 0.11 | −0.02 | 0.13 | 0.16 | 0.15 | −0.41 | 0.24 | −0.42 | 0.24 |
| Day | −0.03 | 0.01 | 0.00 | 0.01 | −0.01 | 0.01 | −0.03 | 0.01 | 0.03 | 0.03 | 0.03 | 0.03 |
| Age | 0.00 | 0.01 | 0.01* | 0.01 | 0.00 | 0.01 | 0.00 | 0.01 | 0.00 | 0.01 | 0.00 | 0.01 |
| Gender | −0.09 | 0.15 | −0.04 | 0.08 | 0.12 | 0.11 | −0.09 | 0.15 | 0.11 | 0.15 | 0.11 | 0.15 |
| Education | 0.01 | 0.03 | −0.01 | 0.02 | −0.01 | 0.02 | 0.01 | 0.03 | 0.02 | 0.04 | 0.02 | 0.04 |
| Main variables | ||||||||||||
| COVID‐19 intrusive experience | 0.46** | 0.03 | 0.27** | 0.02 | −0.19** | 0.02 | 0.30** | 0.03 | 0.01 | 0.05 | 0.00 | 0.06 |
| Psychosocial resource loss | 0.43** | 0.06 | 0.11 | 0.11 | ||||||||
| Psychosocial resource gain | −0.25** | 0.06 | −0.04 | 0.08 | ||||||||
| Mental health status (PHQ‐4) | −0.16* | 0.07 | −0.19* | 0.08 | ||||||||
| Variance (level 3 intercept) | 0.02 | 0.01 | 0.02 | 0.02 | 0.02 | 0.02 | ||||||
| Variance (level 2 intercept) | 0.13 | 0.05 | 0.04 | 0.14 | 0.21 | 0.21 | ||||||
| Variance (level 1 residual) | 0.26 | 0.13 | 0.17 | 0.22 | 0.26 | 0.26 | ||||||
| Deviance | 1011.34 | 574.19 | 690.93 | 938.16 | 665.81 | 664.50 | ||||||
|
| 0.38 | 0.29 | 0.14 | 0.16 | 0.06 | 0.03 | ||||||
Note: N = 569. *p < 0.05; **p < 0.01.
Abbreviations: PHQ, patient health questionnaire.
Hierarchical linear modeling for testing Hypotheses 5–7
| Model 7: | Model 8: | Model 9: | Model 10: | |||||
|---|---|---|---|---|---|---|---|---|
| Psychosocial resource loss | Psychosocial resource gain | Mental health status (PHQ‐4) | Mental health status (PHQ‐4) | |||||
| Variables | γ | SE | γ | SE | γ | SE | γ | SE |
| Intercept | 0.52** | 0.07 | 0.86** | 0.07 | 1.79** | 0.11 | 1.79** | 0.11 |
| Control | ||||||||
| Exposure to people with COVID‐19 | 0.02 | 0.11 | 0.01 | 0.13 | 0.11 | 0.16 | 0.40** | 0.16 |
| Day | −0.01 | 0.01 | 0.00 | 0.01 | −0.03* | 0.01 | −0.03* | 0.02 |
| Age | 0.01* | 0.01 | 0.00 | 0.01 | 0.00 | 0.01 | 0.00 | 0.01 |
| Gender | −0.06 | 0.08 | 0.13 | 0.11 | −0.11 | 0.15 | −0.10 | 0.15 |
| Education | −0.01 | 0.02 | −0.01 | 0.02 | 0.01 | 0.03 | 0.00 | 0.03 |
| Main variables | ||||||||
| COVID‐19 intrusive experience (IE) | 0.22** | 0.02 | −0.12** | 0.03 | 0.36** | 0.03 | ||
| Visionary leadership behaviour (VL) | −0.05** | 0.01 | 0.08** | 0.02 | −0.11** | 0.02 | ||
| IE × VL | −0.04** | 0.02 | 0.04* | 0.02 | −0.06** | 0.02 | ||
| Psychosocial resource loss (RL) | 0.68** | 0.06 | ||||||
| Psychosocial resource gain (RG) | −0.35** | 0.06 | ||||||
| RL × RG | −0.41** | 0.15 | ||||||
| Mental health status (PHQ‐4) | ||||||||
| Variance (level 3 intercept) | 0.01 | 0.01 | 0.02 | 0.02 | ||||
| Variance (level 2 intercept) | 0.05 | 0.04 | 0.13 | 0.12 | ||||
| Variance (level 1 residual) | 0.12 | 0.16 | 0.24 | 0.26 | ||||
| Deviance | 552.58 | 660.77 | 970.16 | 1007.31 | ||||
|
| 0.04 | 0.06 | 0.08 | 0.23 | ||||
Note: N = 569. *p < 0.05; **p < 0.01. We centred the predictor and moderator variables around their respective individual means to gain unbiased within‐person relationship estimates and the correct reparameterization of the interaction term (Gabriel et al., 2019; Raudenbush & Bryk, 2002; Zhang et al., 2009).
Abbreviations: PHQ, patient health questionnaire.
FIGURE 2Visionary leadership behaviour as a moderator of the relationship between COVID‐19 intrusive experience and psychosocial resource loss
FIGURE 3Visionary leadership behaviour as a moderator of the relationship between COVID‐19 intrusive experience and psychosocial resource gain
FIGURE 4Visionary leadership behaviour as a moderator of the relationship between COVID‐19 intrusive experience and mental health status patient health questionnaire (PHQ‐4)
FIGURE 5Psychosocial resource gain as a moderator of the relationship between psychosocial resource loss on mental health status patient health questionnaire (PHQ‐4)
FIGURE 6Psychosocial resource loss as a moderator of the relationship between psychosocial resource gain on mental health status patient health questionnaire (PHQ‐4)