ArticleFrontiers in public health2026
From algorithmic efficiency to cascading health burdens: a text-mining study of online food delivery riders in the platform economy.
Article in Frontiers in public health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Algorithmic management has markedly improved operational efficiency in the platform economy, yet its consequences for the occupational health of platform workers remain insufficiently understood. This study therefore examines how efficiency-driven algorithmic pressures produce occupational health burdens among online food delivery (OFD) riders in China. The analysis drew on 10,103 valid rider comments from a major Chinese social media platform, and it combined Latent Dirichlet Allocation topic modeling with co-occurrence network analysis and sentiment intensity assessment. Semi-structured interviews with 32 OFD riders were added to corroborate these computational findings and to reduce reliance on a single data source. Expert review identified five core health burden dimensions: physical exhaustion, social devaluation, disciplinary distress, injury vulnerability, and health-protection deficit. Network analysis showed that these dimensions form a tightly interconnected structure with physical exhaustion as the central hub, and that pressure cascades from operational demands into punitive mechanisms and then into injury risk and social protection deficits. A clear gap emerged between structural prominence and emotional intensity. Riders discussed time pressure most widely and largely accepted it as routine, while punitive mechanisms and health-protection deficits drew the strongest negative responses. The study contributes an integrated text-mining framework for occupational health research. It reframes rider health as a cascading system of mutually reinforcing burdens rather than a set of isolated risks, and it shows that the most central burden is not the one felt most acutely. These insights point to concrete measures for governments, platforms, rider organizations, and industry associations such as portable occupational-injury insurance, algorithmic transparency, fairer timing and rating rules, and accessible grievance channels.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.