Development and Evaluation of the Mobile Tech Support Questionnaire for Older Adults
Hasti Sharifi, Joseph E Michaelis, Debaleena Chattopadhyay · 2024 · ASSETS '24: Proceedings of the 26th International ACM SIGACCESS Conference on Computers and Accessibility · doi:10.1145/3663548.3675661
Summary
This paper develops and validates the Mobile Tech Support Questionnaire (MTSQ), a standardised instrument for measuring older adults' preferences for and perceived quality of technology support during ongoing mobile device use. While mobile device ownership among older adults has risen dramatically, sustained use is often hampered by a lack of adequate support for learning new features, troubleshooting problems, and adapting to updates. The research followed a rigorous scale development methodology across two phases. Phase 1 involved semi-structured interviews with 23 older adults (aged 65+) to identify the types of tech support they use and value, generating an initial pool of questionnaire items. These covered a wide range of support sources including online tutorials, YouTube videos, built-in help features, manufacturer support lines, family and friends, community classes, and in-store assistance. Phase 2 deployed the refined questionnaire as an online survey with 259 older adults and used exploratory factor analysis (EFA) to identify the underlying structure of tech support preferences. The analysis revealed two clear dimensions: self-reliant support (resources used independently, such as online search, video tutorials, built-in device help, and trial-and-error) and social support (help from other people, including family, friends, tech-savvy acquaintances, formal classes, and professional support staff). The researchers then used partial least squares structural equation modeling (PLS-SEM) to examine how preference for and perceived quality of each support type related to frequency of use and perceived ease of use.
Key findings
The exploratory factor analysis yielded a clean two-factor solution — self-reliant and social support — with strong internal consistency (Cronbach's alpha above 0.8 for both dimensions). The structural equation modeling revealed that both preference for and perceived quality of a support type positively predicted how frequently older adults used that type and how easy they found it to use. Importantly, quality had a stronger effect than preference alone — even if an older adult preferred social support, they would use it less frequently if the quality was poor (e.g., family members being impatient or unavailable). Self-reliant support was used more frequently overall than social support, contrary to the stereotype that older adults primarily rely on family for tech help. However, social support was rated as higher quality when available, particularly for complex troubleshooting tasks. The interviews revealed nuanced dynamics: many older adults felt reluctant to ask family members repeatedly for help ("I don't want to be a burden"), driving them toward self-reliant strategies even when social support would be more effective. YouTube tutorials emerged as the most commonly cited self-reliant resource, though participants noted that tutorials often assumed higher baseline knowledge than they possessed. The questionnaire also identified a gap in professional tech support — manufacturer help lines were rated as low quality due to long wait times, scripted responses, and difficulty understanding accented English, while in-store support was valued but geographically inaccessible for many.
Relevance
The MTSQ fills a methodological gap in ageing and accessibility research by providing a validated instrument specifically designed to measure tech support experiences of older adults. Previously, researchers studying older adults' technology adoption relied on general technology acceptance models (like TAM or UTAUT) that do not capture the support dimension. For accessibility practitioners and organisations serving older adults, the two-factor structure offers a clear framework: interventions should strengthen both self-reliant resources (better tutorials, more intuitive help systems, age-appropriate learning materials) and social support (community tech help programmes, peer mentoring, family education about effective support). The finding that older adults prefer self-reliance but are often forced into it by inadequate social support challenges patronising assumptions and suggests that the real barrier is not willingness to learn but the quality and availability of learning resources. For technology designers, the implications are direct: built-in help features need to be dramatically better, onboarding should account for varying baseline knowledge, and update communications should explain changes in plain language rather than assuming users will figure it out.
Tags: older adults · mobile technology · tech support · questionnaire development · digital literacy · ageing · scale development · self-reliant support · social support