Dependence and Precarity in the Gig Economy: A Longitudinal Analysis of Platform Work and Mental Distress

While there is a growing body of literature examining platform dependence and its implications for mental health, much of the research has focused on gig workers with small sample sizes. The lack of large-scale quantitative research, particularly using longitudinal representative data, limits a comprehensive understanding of the dynamic relationship between platform dependence and mental distress. This study uses nationally representative data from the UK and fixed effects models to explore the heterogeneity of gig work, specifically examining differences in mental distress between high-dependence workers (those solely engaged in gig work) and low-dependence workers (those also employed in other jobs). The findings reveal that high-dependence gig workers have greater mental distress compared to low-dependence and full-time workers, with their mental well-being similar to those with no paid work. Low-dependence gig workers have lower mental distress than those without paid work. Financial precarity and loneliness partly explain these differences, with the impact stronger for highly educated high-dependence workers and less educated low-dependence workers. These findings highlight the significance of recognizing the heterogeneity of gig work in addressing future well-being challenges in a post-pandemic economy, as well as broadening the scope of the latent deprivation model to encompass the unique dynamics of gig work.

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Publication Details

Journal
British Journal of Sociology
Published
2025-09-08
DOI
https://doi.org/10.1111/1468-4446.70028
Primary Topic
Digital Economy and Work Transformation
Type
article
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article

Dependence and Precarity in the Gig Economy: A Longitudinal Analysis of Platform Work and Mental Distress

Ya Guo, Senhu Wang, Zhuofei Lu, Shiyue Cui
British Journal of Sociology
Digital Economy and Work Transformation
article

Dependence and Precarity in the Gig Economy: A Longitudinal Analysis of Platform Work and Mental Distress

Ya Guo, Senhu Wang, Zhuofei Lu, Shiyue Cui
article en

Abstract

While there is a growing body of literature examining platform dependence and its implications for mental health, much of the research has focused on gig workers with small sample sizes. The lack of large-scale quantitative research, particularly using longitudinal representative data, limits a comprehensive understanding of the dynamic relationship between platform dependence and mental distress. This study uses nationally representative data from the UK and fixed effects models to explore the heterogeneity of gig work, specifically examining differences in mental distress between high-dependence workers (those solely engaged in gig work) and low-dependence workers (those also employed in other jobs). The findings reveal that high-dependence gig workers have greater mental distress compared to low-dependence and full-time workers, with their mental well-being similar to those with no paid work. Low-dependence gig workers have lower mental distress than those without paid work. Financial precarity and loneliness partly explain these differences, with the impact stronger for highly educated high-dependence workers and less educated low-dependence workers. These findings highlight the significance of recognizing the heterogeneity of gig work in addressing future well-being challenges in a post-pandemic economy, as well as broadening the scope of the latent deprivation model to encompass the unique dynamics of gig work.

British Journal of SociologyVol. 76(5)
National University of Singapore (SG), University of Macau (MO), University of Oxford (GB)
Openalex Percentile: Top 68%
Digital Economy and Work Transformation
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Dependence and Precarity in the Gig Economy: A Longitudinal Analysis of Platform Work and Mental Distress — Ya Guo, Senhu Wang, et al. · British Journal of Sociology (2025) | TGRS Research Map | TGRS