Generative AI, autonomy and healthy ageing: a reflexive thematic analysis of urban older adults through an integrated SST–SDT lens

Purpose This paper aims to offer a worked methodological demonstration of an integrated socioemotional selectivity theory (SST)–self-determination theory (SDT) reflexive thematic analysis (RTA), examining how urban, community-dwelling older adults in India are illustrated as using and emotionally experiencing generative AI and how this relates to autonomy, competence, relatedness and healthy ageing. Design/methodology/approach An RTA, organised using a Gioia-style structure, was conducted on an illustrative data set of 16 urban older adults (aged 61–83, mean 70.6) across 10 Indian cities: 5 full transcripts and 11 condensed summaries. As the data set was constructed for teaching purposes rather than collected under ethics-approved fieldwork, findings are a hypothesis-generating exercise rather than generalisable evidence. Findings Six aggregate dimensions were derived: everyday instrumental and cognitive integration; emotional relief primarily through reduction of uncertainty rather than direct companionship; differentiated relational meaning ranging from simulated companionship to explicitly non-relational, intellectual partnership; autonomy and competence gained through self-directed problem-solving; a near-universal positioning of AI as bounded against human relationships; and countercurrents of privacy unease, calibrated trust, literacy barriers and fear of overdependence. The integrated SST–SDT chain fit unevenly: several accounts were better explained by an informational, cognitive-appraisal pathway than an emotional one, and relatedness, unlike autonomy and competence, was not consistently reported. Originality/value This paper provides a transparent, reflexive worked example of applying an integrated SST–SDT framework with Gioia-structured RTA to a novel, under-researched population, and specifies what a genuine empirical study in this domain would require.