| Literature DB >> 35990046 |
Jianmin Sun1, Hongzhou Shen1, Syed Ibn-Ul-Hassan2, Amir Riaz3, Aura Emanuela Domil4.
Abstract
The study aims to measure the mediating relationship of wellbeing at work between digitalization (IT infrastructure, IT business spanning, and IT proactive stance) and their effect on mental health. The study uses primary data collection techniques to gather data and used purposive sampling to analyze the data. The sample size of the study is 349 respondents. The research uses Smart PLS software to measure the relationship through bootstrapping and algorithms. The study finds a significant positive mediating role of wellbeing between digitalization (IT infrastructure, IT business spanning, and IT proactive stance) and their effect on mental health. The study outcomes are helpful for managers and policymakers.Entities:
Keywords: IT infrastructure; IT proactive stance; digital health; digitalization; job performance; mental health; well-being
Year: 2022 PMID: 35990046 PMCID: PMC9386346 DOI: 10.3389/fpsyt.2022.934357
Source DB: PubMed Journal: Front Psychiatry ISSN: 1664-0640 Impact factor: 5.435
Figure 1Conceptual framework.
Descriptive statistics.
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| Male | 161 | 46.1 |
| Female | 188 | 53.9 |
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| 19–30 | 44 | 12.6 |
| 31–40 | 95 | 27.2 |
| 41–50 | 84 | 24.1 |
| 51–60 | 76 | 21.8 |
| >60 | 50 | 14.3 |
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| Intermediate | 67 | 19.2 |
| Bachelor | 113 | 32.4 |
| Master | 124 | 35.5 |
| MPhil/Others | 45 | 12.9 |
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| Single | 59 | 16.9 |
| Married | 290 | 83.1 |
Reliability and validity results.
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| IT infrastructure | ITI_1 | 0.737 | 0.847 | 0.848 | 0.583 |
| ITI_2 | 0.703 | ||||
| ITI_3 | 0.779 | ||||
| ITI_4 | 0.830 | ||||
| IT business spanning | ITB_1 | 0.676 | 0.843 | 0.842 | 0.572 |
| ITB_2 | 0.779 | ||||
| ITB_3 | 0.733 | ||||
| ITB_4 | 0.830 | ||||
| IT proactive stance | ITP_1 | 0.704 | 0.836 | 0.836 | 0.560 |
| ITP_2 | 0.787 | ||||
| ITP_3 | 0.781 | ||||
| ITP_4 | 0.719 | ||||
| Well-being at work | WBW_1 | 0.784 | 0.929 | 0.929 | 0.592 |
| WBW_2 | 0.836 | ||||
| WBW_3 | 0.710 | ||||
| WBW_4 | 0.702 | ||||
| WBW_5 | 0.837 | ||||
| WBW_6 | 0.783 | ||||
| WBW_7 | 0.735 | ||||
| WBW_8 | 0.800 | ||||
| WBW_9 | 0.724 | ||||
| Mental health | MH_1 | 0.758 | 0.877 | 0.877 | 0.588 |
| MH_2 | 0.728 | ||||
| MH_3 | 0.731 | ||||
| MH_4 | 0.825 | ||||
| MH_5 | 0.787 |
Discriminant validity results.
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| 1. IT business spanning | 0.757 | 0.505 | 0.565 | 0.569 | 0.564 |
| 2. IT infrastructure | 0.507 | 0.763 | 0.568 | 0.547 | 0.547 |
| 3. IT proactive stance | 0.562 | 0.565 | 0.749 | 0.556 | 0.555 |
| 4. Mental health | 0.570 | 0.548 | 0.559 | 0.767 | 0.563 |
| 5. Well-being at work | 0.568 | 0.548 | 0.555 | 0.566 | 0.770 |
Figure 2Measurement model PLS-SEM diagram.
Results of direct effects.
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| H1 | ITI → MH | 0.202 | 0.066 | 3.079 |
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| H2 | ITB → MH | 0.239 | 0.076 | 3.158 |
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| H3 | ITP → MH | 0.192 | 0.073 | 2.642 |
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| H4 | ITI → WBW | 0.26 | 0.062 | 4.186 |
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| H5 | ITB → WBW | 0.302 | 0.069 | 4.390 |
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| H6 | ITP → WBW | 0.239 | 0.073 | 3.267 |
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| H7 | WBW → MH | 0.213 | 0.065 | 3.279 |
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p < 0.05,
p < 0.01,
p < 0.001.
Results of mediation effects.
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| H7a | ITI → WBW → MH | 0.055 | 0.025 | 2.224 |
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| H7b | ITB → WBW → MH | 0.064 | 0.026 | 2.481 |
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| H7c | ITP → WBW → MH | 0.051 | 0.024 | 2.133 |
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p < 0.05.
Figure 3Structural model PLS-SEM diagram.