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Information, Communication & Society ; 25(5):634-653, 2022.
Article in English | APA PsycInfo | ID: covidwho-20231846

ABSTRACT

While ride-hailing ridership declined in 2020 due to COVID-19 induced restrictions like stay-at-home orders, food/grocery delivery services became quasi-essential. This study investigates if and how public perceptions of gig work related to platform-based ride-hailing and food/grocery delivery services changed during the early stages of the pandemic. We collected a sample of 23,845 Twitter posts ('tweets') related to these platform-based services within two-week periods before and after the US COVID-19 emergency declaration. Sentiment analysis on tweets was conducted to investigate changes in public perception of gig work. Tweet content was analyzed by descriptively coding about 10% of the sample of tweets manually along ten different dimensions (e.g., personal experience, informative, and about driver);then we used thematic analysis to gain an understanding about the public's views towards gig work/workers. We tested supervised machine learning methods to explore their potential to classify the rest of the sample along the ten descriptive dimensions. The number of tweets increased by approximately 150% after the emergency declaration and became more positive in sentiment. Qualitative results indicate that tweets about negative personal experiences with drivers/companies decreased during COVID-19, while tweets exhibiting a sense of community (e.g., sharing information) and concern towards gig workers increased. Findings can inform policy and workforce changes regarding platform-based service companies. (PsycInfo Database Record (c) 2023 APA, all rights reserved)

2.
JMIR Aging ; 5(1): e32442, 2022 Jan 12.
Article in English | MEDLINE | ID: covidwho-1883822

ABSTRACT

BACKGROUND: The prevalence of COVID-19 in the United States led to mandated lockdowns for long-term care (LTC) facilities, resulting in loss of in-person contact with social ties for LTC residents. Though information and communication technologies (ICTs) can be used by LTC residents to support their socioemotional needs, residents must have access to ICTs to use them. OBJECTIVE: This study explored ICT access and use in LTC facilities and how LTC facilities adapted to try to enhance social connections for their residents during the COVID-19 pandemic. METHODS: LTC administrators in South Carolina (United States) were invited to complete a web-based survey exploring ICT access and use in LTC facilities and whether access and use changed as a result of the COVID-19 pandemic. RESULTS: LTC administrators (N=70, 12 nursing homes [NHs], and 58 assisted living facilities [ALFs]) completed the web-based survey. Since March 2020, a total of 53% (37/70) of the LTC facilities have purchased ICTs for residents' use. ICTs have mainly been used for videoconferencing with family members (31/36, 86%), friends (25/36, 69%), and health care providers (26/36, 72%). NHs were 10.23 times more likely to purchase ICTs for residents' use during the COVID-19 pandemic than ALFs (odds ratio 11.23, 95% CI 1.12-113.02; P=.04). Benefits of ICT use included residents feeling connected to their family members, friends, and other residents. Barriers to ICT use included staff not having time to assist residents with using the technology, nonfunctional technology, and residents who do not want to share technology. CONCLUSIONS: Our results suggest that over half of the LTC facilities in this study were able to acquire ICTs for their residents to use during the COVID-19 pandemic. Additional research is needed to explore how residents adapted to using the ICTs and whether LTC facilities developed and adopted technology integration plans, which could help them be prepared for future situations that may affect LTC residents' engagement and communication opportunities, such as another pandemic.

3.
American Behavioral Scientist ; : 00027642211066039, 2022.
Article in English | Sage | ID: covidwho-1714512

ABSTRACT

COVID-19 resulted in health and logistical challenges for many sectors of the American economy, including the trucking industry. This study examined how the pandemic impacted the trucking industry, focused on the pandemic?s impacts on company operations, health, and stress of trucking industry employees. Data were collected from three sources: surveys, focus groups, and social media posts. Individuals at multiple organizational levels of trucking companies (i.e., supervisors, upper-level management, and drivers) completed an online survey and participated in online focus groups. Data from focus groups were coded using a thematic analysis approach. Publicly available social media posts from Twitter were analyzed using a sentiment analysis framework to assess changes in public sentiment about the trucking industry pre- and during-COVID-19. Two themes emerged from the focus groups: (1) trucking company business strategies and adaptations and (2) truck driver experiences and workplace safety. Participants reported supply chain disruptions and new consumer buying trends as having larger industry-wide impacts. Company adaptability emerged due to freight variability, leading organizations to pivot business models and create solutions to reduce operational costs. Companies responded to COVID-19 by accommodating employees? concerns and implementing safety measures. Truck drivers noted an increase in positive public perception of truck drivers, but job quality factors worsened due to closed amenities and decreased social interaction. Social media sentiment analysis also illustrated an increase in positive public sentiment towards the trucking industry during COVID-19. The pandemic resulted in multi-level economic, health, and social impacts on the trucking industry, which included economic impacts on companies and economic, social and health impacts on employees within the industry levels. Further research can expand on this study to provide an understanding of the long-term impacts of the pandemic on the trucking industry companies within the industry and segments of the trucking industry workforce.

4.
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