Author(s)
Subharun Pal, Dr. Richa Gupta
- ISSN (P): 3139-8464
- Manuscript ID: 141231
- Volume: 2
- Issue: 10
- Pages: 963–973
Subject Area: Psychology and Behavioural Science
Abstract
Background: Digital labour platforms create psychological demands in gig workers by automating management processes such as allocation, surveillance, pricing and performance evaluation. These gig workers are flexible and can work across platforms, locations and times. Flexibility requires a high level of worker control to accomplish tasks. Published studies synthesizing algorithmic management and gig workers’ mental health remain limited. This paper defines the field and presents a step-by-step reproducible method of science mapping of gig-worker research from 2015–2026 using Scopus. Studies on gig workers indicate that control and precariousness contribute to adverse mental health outcomes, although negative effects are not absolute. A new bibliometric corpus and compatible effect-size dataset were not provided; therefore, a pooled effect estimate was not reported. The paper introduces the Algorithmic Control–Distress Pathways Framework, outlines what will be required for future reviews, and identifies key policy gaps.
Evidence boundaries and disaggregated outcomes are explicitly documented to prevent false precision in quantitative claims.