Personalising persuasive technologies for behaviour change: a scoping review and research agenda

Elena Minucci et al.

Interacting with Computers2026https://doi.org/10.1093/iwc/iwag006article
AJG 2ABDC B
Weight
0.50

Abstract

Persuasive technologies help users meet various types of behavioural goals, and are becoming increasingly personalised to individual users’ needs. Research has been siloed into single domains of behaviour change, such as health or environmental behaviours, leaving open questions on how users across domains respond to personalised interventions. To fill this gap, we reviewed 56 publications between 2013 and 2024, which developed personalised persuasive technologies. We analysed how the technologies were designed and how users evaluated them. We found that persuasive technologies build user profiles that are either static or dynamic, and use this information to deliver three types of personalised interventions: personalised goals, personalised messages, or personalised timing of reminders. Personalised technologies were more effective than one-size-fits-all and utilised a combination of behaviour change techniques. Users not only evaluated personalisation positively, but wanted to know how it was achieved. In addition, users preferred goals that were easy to meet, and appreciated empathetic support from persuasive technology when a goal was not met. Based on these findings, we discuss methodological, theoretical, and practical implications, as well as future research directions for personalised persuasive technologies.

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https://doi.org/https://doi.org/10.1093/iwc/iwag006

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@article{elena2026,
  title        = {{Personalising persuasive technologies for behaviour change: a scoping review and research agenda}},
  author       = {Elena Minucci et al.},
  journal      = {Interacting with Computers},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1093/iwc/iwag006},
}

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

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