Profiles and Predictors of Smart Home Technology Adoption by Older Adults.
Sajay Arthanat, John Wilcox, Mackenzie Macuch
PMID 30477397WHAT IT FOUND
Older adults mostly own basic safety devices like alarms and thermostats but reject complex automation like voice assistants or remote monitoring.
Being female, younger, or having mobility issues predicts higher adoption, but these factors explain very little of the variance, so no single profile guarantees success.
Key findings
01Participants reported high ownership of simple safety devices like carbon monoxide alarms and thermostats, but low interest in complex features like remote home monitoring and voice-activated assistants.
02Women, individuals aged 60 to 70, and those with mobility or balance impairments were significantly more likely to be 'brisk adopters' of smart home technology than men, older adults, or those without impairments.
03Statistical models showed that demographic and health factors only explained 8% of the variance in current ownership and 6% in readiness to adopt, indicating these predictors are weak.
STILL TO COME
How it was doneWhat they foundWhat it means for OTs
Read the rest of this summary
You get three full summaries a month, free, and we do not ask for a card. Search, the TL;DRs and your library stay unlimited either way.
What it does not show
The sample was limited to New England and may not generalize to other regions or populations. The study relied on self-reported ownership and attitudes, which may not reflect actual usage patterns. The analytical framework for defining 'adopters' was arbitrary and may not be consistent with other studies. The low variance explained by the models (6-8%) suggests that unmeasured factors, such as technology anxiety or specific needs, play a larger role in adoption decisions than the demographic and health variables studied.
Declared interests
The authors declared no potential conflicts of interest.
The easy way to misread this
Do not assume that a client's demographic profile, such as being female or having a mobility impairment, guarantees they will adopt smart home technology. The study found these factors explain very little of the variance, meaning individual attitudes and prior technology experience are far more important than these broad categories.