Unpacking expectancy in digital interventions for mental well-being

Wruk, Aleksandra (2026) Unpacking expectancy in digital interventions for mental well-being. PhD thesis, University of Glasgow.

Abstract

Although there are many digital interventions specifically designed for Mental Well-Being (MWB) support, low engagement and high dropout rates are commonly reported (Borghouts et al. 2021; Baumel et al. 2019). As people often bypass specialized tools in favour of general-purpose technologies for MWB, this thesis draws on expectancy as a lens to understand what impedes their uptake and use in practice, and to inform new design interventions. Across three empirical studies and an exploration of a design prototype, the thesis explores how expectancy shapes whether, in MWB contexts, digital technologies feel approachable or burdensome, relevant or misaligned and therefore frustrating. This thesis uncovers that expectancy narrows or broadens with MWB states and mediates how users interpret digital technology through effort and performance expectancy. Rather than creating new specialised applications from scratch, through the design prototype Chatty, the thesis also demonstrates how scaffolding by adding a lightweight mediating layer, can help better align general-purpose technologies with users’ needs and expectancies. By foregrounding expectancy as a mediating mechanism and a design principle, the thesis contributes both theoretical and practical insights and offers some crucial design implications.

• Item Type: Thesis (PhD)
• Qualification Level: Doctoral
• Additional Information: Supported by funding from the UKRI centre for Doctoral Training in Socially Intelligent Artificial Agents, Grant Number EP/S02266X/1.
• Subjects: B Philosophy. Psychology. Religion > BF Psychology; R Medicine > RC Internal medicine > RC0321 Neuroscience. Biological psychiatry. Neuropsychiatry; T Technology > T Technology (General)
• Colleges/Schools: College of Science and Engineering
• Funder's Name: Engineering and Physical Sciences Research Council (EPSRC)
• Supervisor's Name: Ding, Dr. Sharon and Dix, Dr. Sophie
• Date of Award: 2026
• Depositing User: Theses Team
• Unique ID: glathesis:2026-85743
• Copyright: Copyright of this thesis is held by the author.
• Date Deposited: 05 Feb 2026 09:44
• Last Modified: 05 Feb 2026 09:44
• Thesis DOI: 10.5525/gla.thesis.85743
• URI: https://theses.gla.ac.uk/id/eprint/85743

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