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大流行期间软件专业人员的幸福感和生产力

丹尼尔·鲁索; 哈内尔(Paul); 塞拉菲那Altnickel; 尼尔斯·范·伯克尔


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{
  "publisher": "Zenodo", 
  "DOI": "10.5281 / zenodo.3959131", 
  "language": "eng", 
  "title": "大流行期间软件专业人员的幸福感和生产力", 
  "issued": {
    "date-parts": [
      [
        2020, 
        7, 
        24
      ]
    ]
  }, 
  "abstract": "<p>The 新冠肺炎 pandemic has forced governments worldwide to impose movement restrictions on their citizens. Although critical to reducing the virus&#39; reproduction rate, these restrictions come with far-reaching social and economic consequences. In this paper, we investigate the impact of these restrictions on an individual level among software engineers currently working from home. Although software professionals are accustomed to working with digital tools in their day-to-day work, the abrupt and enforced work-from-home context has resulted in an unprecedented scenario for the software engineering community. In a two-wave longitudinal study (N = 192), we covered over 50 psychological, social, situational, and physiological factors that have previously been associated with well-being or productivity. Examples include anxiety, distractions, psychological and physical needs, office set-up, stress, and work motivation. This design allowed us to identify those variables that explain unique variance in well-being and productivity.&nbsp;Results include (1) the quality of social contacts predicted positively, and stress predicted an individual&#39;s well-being negatively when controlling for other variables consistently across both waves; (2) boredom and distractions predicted productivity negatively; (3) productivity was less strongly associated with all predictor variables at time two compared to time one, suggesting that software engineers adapted to the lockdown situation over time; and (4) the longitudinal study did not provide evidence that any predictor variable causal explained variance in well-being and productivity. &nbsp;Our study can assess the effectiveness of current work-from-home and general well-being and productivity support guidelines and provide tailored insights for software professionals.</p>\n\n<p>&nbsp;</p>", 
  "author": [
    {
      "family": "Russo, Daniel"
    }, 
    {
      "family": "Hanel, Paul"
    }, 
    {
      "family": "Altnickel, Seraphina"
    }, 
    {
      "family": "Van Berkel, Niels"
    }
  ], 
  "version": "1.1", 
  "type": "dataset", 
  "id": "3959131"
}
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