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LETTERS TO THE EDITOR

Acute Musculoskeletal Pain Reported Among Rideshare Drivers in the Health/Safety Investigation Among Non-Standard Workers in the Gig Economy (H.I.N.G.E.) Pilot Study

Caban-Martinez, Alberto J. DO, PhD, MPH; Santiago, Katerina M. MPH; Louzado Feliciano, Paola MS; Ogunsina, Kemi MBBS; Kling, Hannah MPH; Griffin, Kevin BS; Schaefer Solle, Natasha PhD, RN

Author Information
Journal of Occupational and Environmental Medicine: May 2020 - Volume 62 - Issue 5 - p e236-e239
doi: 10.1097/JOM.0000000000001849
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To the Editor:

In the United States, on-demand employment, also known as the “gig economy” is on the rise.1–3 The proportion of individuals employed as gig workers, that is, individuals who provide contracted, freelance work on a short-term basis via digital platform technologies is growing rapidly.4 Gig workers can include individuals who are employed as delivery-personnel, personal assistants, drivers, handymen, cleaners, cooks, dog-sitters, and babysitters, but increasingly are also more specialized professionals, including tutors, teachers, programmers, nurses, doctors, freelance writers, and lawyers.4 It is estimated that the rideshare industry alone has nearly half a million drivers in its fleet.5,6 Despite the growth of this gig industry, little is known about the health and safety concerns of individuals who engage in non-standard work arrangements, particularly where traditional organizational-levels policies, benefits, and resources do not exist (ie, health insurance, retirement benefits, workers compensation).

The rideshare business (ie, Uber/Lyft) is a type of gig economy that allows individuals to contract or provide freelance car transportation services on a short-term basis via digital platform technologies.7 Some rideshare companies refer to their drivers as “partners” as a way to emphasize they are not company employees and lack certain work-related benefits.8 Non-standard work arrangements among rideshare drivers can give rise to precarious working conditions such as limited health insurance options, wage volatility, job insecurity due to rating systems, and costly car maintenance expenditures.9,10 These challenging working conditions can have a negative impact on the driver's health. Despite the growth and popularity of ride share services in US economy, little is known of the musculoskeletal health of this rather nomadic worker population that share many attributes to professions who drive for a living, such as taxicab drivers, chauffeurs, and truckers. In the present pilot study, we use the quantitative data collected as part of the “Health/Safety Investigation Among Non-standard Workers in the Gig Economy (H.I.N.G.E.) Pilot Study” to characterize and describe the acute (7-day) musculoskeletal pain reported by US rideshare drivers. We hypothesize that their self-reported acute muscle and joint pain would be similar to those reported by other professional drivers.

MATERIALS AND METHODS

Study Design and Participant Recruitment

A cross-sectional study design was used to collect qualitative and quantitative data from a non-probabilistic sample of rideshare drivers across the United States between September/October 2019. Team members requested a ride using the rideshare digital platform. Prior to the start of the ride, the researcher described the study to the driver and obtained consent. During the ride, the researcher verbally asked the participant to respond to a one-page closed-ended sociodemographic and work-related survey. Following the brief survey administration, the researcher used an interview script to assess information about the rideshare job experience and occupational health and safety concerns. The interview was audio recorded with expressed permission from the study participant. Drivers were compensated a $10 incentive for participating in the pilot study. All components (ie, survey or interview) of the pilot study were voluntary and could be skipped by the driver participant. Data from the survey component are present in this analysis. Thirty-six drivers were recruited during the data collection phase of which 35 completed both the survey and interview (response rate = 35/36 = 97.2%).

Survey Measures and Administration

Following the study description and verbal consent process, the researcher administered a one-page, 24-item survey instrument. Questions were read to the driver, and responses were recorded on paper by the research team. The survey instrument was comprised of standard questions assessing socio-demographic and work-related characteristics obtained and adapted from the US National Health Interview Survey and the NHIS Occupational Health Supplement.11 Measures on muscle and joint pain were obtained from the Nordic questionnaire,12 where drivers indicated on a anatomic diagram the site-specific pain (ie, lower back, shoulder, wrist/forearm, knee, neck, or ankle/feet) felt in the prior 7-days (acute pain) to survey administration.

Data Analysis

Continuous data are presented as mean ± standard deviation (SD). Kolmogorov–Smirnov Z test was used to determine the normal distribution of all continuous variables; age, hours worked on rideshare, and hours between breaks. Independent-samples t test and chi-square test were used to compare continuous and categorical variables, respectively, between rideshare drivers with and without musculoskeletal pain. For non-normally distributed continuous variables, the Mann–Whitney U test was used. Analysis of variance (ANOVA) was then conducted to empirically assess if the worker groups (those drivers with and without joint pain) significantly differed in their average hours per week working in rideshare, the average continuous hours without break from working on a rideshare shift, and the average number of months worked in rideshare. Two-way ANOVA was used to assess a potential effect of the interaction of musculoskeletal pain (joint pain vs no joint pain) on work hours and job tenure characteristics. A Bonferonni adjustment was applied to guard against Type 1 error, and the corrected P-values are reported. Prior to conducting the analysis, assumptions of independent observations, multivariate normality, and homogeneity of variance/covariance matrices across groups were examined and met. Statistical analyses were performed using SAS (version 9.3, SAS Institute Inc, Cary, NC). Data collection methods used in this study were reviewed and approved by the University Institutional Review Board (#20190676).

RESULTS

A total of 35 rideshare drivers participated in the pilot study of which 77.1% were men, 51.4% Caucasian, 82.9% Hispanic, 37.1% college graduates, 44.1% were married or member of an unmarried couple, 65.7% has some type of health insurance, 57.1% rated their health as very good/good and had a group mean age of 43.1 ± 11.2 years standard deviation (minimum 21 and maximum age 68; Table 1). Over 37% of drivers reported muscle or joint pain over the past 7-days since survey administration, of which the top two most frequently reported areas included the low back (34.3%) and neck (11.4%, Fig. 1).

TABLE 1
TABLE 1:
Sociodemographic and Work-Related Characteristics Among Rideshare Drivers Participating in the Health/Safety Investigation Among Non-Standard Workers in the Gig Economy (H.I.N.G.E.) Pilot (n = 35)
FIGURE 1
FIGURE 1:
Self-reported (7-day) acute musculoskeletal joint pain by anatomic location among Uber/Lyft rideshare drivers.

Compared with drivers with no musculoskeletal pain, drivers with musculoskeletal pain had significantly greater proportions of drivers that considered rideshare their primary job (84.6% vs 45.5%; P = 0.022), worked more hours per week (56.4% vs 42.2% hours; P = 0.021), and rated the overall health as fair/poor (15.4% vs 0.0%; P = 0.008). Among drivers with a second job, the most frequently reported second jobs were realtor (22.2%) and drivers (ie, delivery service or ambulance, 16.7%).

DISCUSSION

We found approximately a third of rideshare drivers surveyed in this pilot sample had experienced acute musculoskeletal pain (in the prior 7-days to survey administration) of which low back and neck were the most frequently reported anatomic sites. Similar findings have been reported in international epidemiological studies of taxi drivers in both Japan and Taiwan that found taxi drivers had an elevated risk for knee pain, low back pain, and musculoskeletal system disorders when compared with the general population.13–15 More recently a mixed-methods study of US taxi drivers, found 74.7% reported recurrent musculoskeletal pain with low back, knee/leg, and shoulder/upper arm.16 These musculoskeletal pain estimates documented in US taxi drivers did not differ much from our sample of rideshare drivers who had similar anatomic locations of frequently reported acute musculoskeletal pain, albeit taxi drivers worked more hours than those rideshare drivers in this pilot study.

Length of time spent driving as a rideshare driver per week was associated with acute musculoskeletal pain. In our sample, rideshare drivers with acute musculoskeletal pain spent 14.4 more hours per week in rideshare driving activity than those without joint pain. This raises the idea that perhaps frequent breaks between rides or spreading rideshare hours per week more uniformly (as opposed to many hours in a shift) could reduce acute joint pain. Nonetheless, there is a need to better understand the risk factors that precipitate or cause acute musculoskeletal pain in this growing industry that receives very little training and education in ergonomics.

This pilot study is not without limitations. Recruitment was limited to a small number of rideshare drivers that directly impacts the external generalizability of the study results to a broader rideshare workforce. Our pilot study's musculoskeletal pain measures assessed a one-time acute (7-day) assessment of muscle or joint pain that could be related to their second job or some other type of injury not associated to rideshare activity. Despite these limitations this is the first study of US rideshare drivers examining musculoskeletal disorders. Collecting survey and interview data was feasible and well accepted by the driver participants. Among all recruited drivers, only one recruited driver who elected not to participate in the pilot cited a lack of interest in the study.

The recent passage of the California gig-economy bill, or AB5 in January 2020 has ushered a new State statue requiring employers to classify their workers as employees.17 This new law represents a paradigm shift for employers and particularly workers who depend on digital apps to secure on-demand gigs. The statue could have a major impact on gig worker minimum wage, sick leave policy, and unemployment and workers’ compensation benefits traditionally not available to independent contractors. While other states such as Illinois, New Jersey, and New York work towards similar statues to protect gig economy workers, the future of gig workers as it relates to the protection of their health and safety while ridesharing remains unclear. Future studies should consider longitudinal follow-up to better understand repeated measures of physical and mental exposure experienced by the drivers. Researchers should consider documenting exposures encountered by the drivers during their routes using digital technologies. As the digital economy gives way to growing avenues of non-standard work arrangements, such as those of rideshare drivers, occupational health and safety research is needed to further document the health protection and health promotion facilitators and barriers of workers who are not tethered to a physical location, have ad-hoc work tasks, and/or function in dynamic work environments like rideshare drivers.

Acknowledgments

The authors thank all the rideshare drivers that participate in this pilot study.

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