Work

Platform-specific digital media use and psychological distress among Turkish adults: evidence from a nationally representative, cross-sectional survey

Year: 2026

Type: article

Abstract: Digital media’s mental-health signature may depend on which platform a population uses, yet nationally representative evidence that distinguishes platforms is scarce, especially for upper-middle-income, Muslim-majority, non-Arab settings. We examined platform-specific associations between digital media use and psychological distress in the Turkish adult population, and whether age moderates them, using the 2024 Turkish General Social Survey, a probability-based, nationally representative survey of adults aged 18 and over ( N = 2,615; analytical N = 1,478 after listwise deletion). Psychological distress was measured with a nine-item past-week negative-affect index informed by the Center for Epidemiologic Studies Depression Scale (CES-D), and unweighted hierarchical ordinary least squares regression with heteroskedasticity-consistent (HC3) robust standard errors modeled demographic, aggregate-exposure, platform-specific, age-interaction, and loneliness blocks, with a Johnson–Neyman procedure characterizing age moderation. Instagram use ( β = +.066, p = .011) was associated with higher psychological distress and WhatsApp use ( β = -.073, p = .007) with lower distress, whereas total internet time, TikTok, and YouTube showed no detectable association. Overall social-media time was likewise positively associated with distress ( β = +.088, p = .016), but the platform contrasts, not aggregate exposure, survived the most demanding clustering and exposure-scale checks. The positive Instagram association declined with age and was statistically indistinguishable from zero by the early forties, a secondary finding that turned on whether loneliness entered the model (age-by-Instagram β = -.069, p = .014 with loneliness, β = -.060, p = .059 without). Adding loneliness — an affective covariate overlapping the outcome battery — raised explained variance to R 2 = .359 (largely shared variance) while the platform and aggregate coefficients remained significant. In this national sample the platform types diverged: algorithm-driven image-platform use (Instagram) showed a small positive association with distress, interpersonal-messaging use (WhatsApp) a small inverse (protective-direction) one. The headline effect sizes were below Cohen’s small-effect benchmark and estimated at the limit of what this design could detect, and the cross-sectional data require longitudinal confirmation of the platform contrasts. Whether distinguishing platform types, rather than treating screen time as uniform, improves population-level digital well-being efforts remains a hypothesis for longitudinal and experimental testing.

Source: Frontiers in Public Health

DOI: 10.3389/fpubh.2026.1941229

Authors: Aydın Aktay, Muhammed Veysel Bilici, Mehmet Veysel Karataş, Abdullah Yıldırmaz

Institutions: Sakarya University, Kırklareli University, Siirt Üniversitesi, Batman University

Language: English

Topic: Impact of Technology on Adolescents

Subfield: Sociology and Political Science

Field: Social Sciences

Domain: Social Sciences

SDG: Good health and well-being

Open Access status: gold

Estimated APC paid: $3,801