Digitalization: Flexibility and Overload

Aline Rappo

23 May 2026 / 2 min read

Note. Illustration generated using OpenAI ChatGPT. The illustration visualizes the tension between digital flexibility and overload in the everyday lives of working Social Work students, highlighting the role of digital demands, constant connectivity, and supportive resources within increasingly digitalized study and work environments.

Topic

This master’s thesis examines how digital demands and digital-related resources influence exhaustion and subjective well-being among working Social Work students at the Bern University of Applied Sciences (BFH). The study focuses on increasingly digitalized study and work environments shaped by platforms such as Moodle, MS Teams, and AI-based applications. Using the Job Demands Resources (JD-R) model, the research explores both strain-inducing and supportive aspects of digitalization, including technostress, organizational support, affinity for technology interaction (ATI), and boundary management.

Relevance

Digitalization has fundamentally changed higher education and the everyday lives of students. Many Social Work students combine studying with employment and private responsibilities while simultaneously navigating increasingly digitalized environments. This creates a “triple burden” in which constant connectivity, digital communication, and platform-based learning may contribute to stress and exhaustion. Understanding how students experience digital demands is highly relevant for higher education institutions, as it provides insights into how digital systems, support structures, and study conditions can be designed in healthier and more sustainable ways.

Results

The findings show that technological complexity was the only digital demand significantly associated with exhaustion, but contrary to expectations, the relationship was negative. Students perceiving higher complexity reported lower exhaustion levels, suggesting that digital complexity may sometimes function as a motivating “challenge demand” rather than a purely negative stressor. At the same time, the study confirms a strong negative relationship between exhaustion and well-being (ρ = −0.46). Organizational support was positively related to well-being, although it did not significantly buffer the effects of digital demands on exhaustion.

Implications for Practitioners

Design digital platforms and study environments as intuitively and transparently as possible.
Provide accessible technical support and structured onboarding for digital tools.
Promote digital literacy and confidence in dealing with complex systems.
Recognize the multiple-role demands experienced by working students.
Develop healthier digital study environments that support recovery and boundary management.

Methods

The study applies a two-wave time-lagged survey design based on the JD-R model. Data are collected approximately four weeks apart from Bachelor students in Social Work at BFH who combine studying with employment. At Time 1 (T1), participants report digital demands, organizational resources, ATI, and boundary management variables. At Time 2 (T2), exhaustion, disengagement, and subjective well-being are assessed. The final matched sample consists of 100 participants. Data are analyzed in R using descriptive statistics, reliability analyses, Spearman correlations, regression analyses, and moderation analyses.