JMIR Publications

ABSTRACT

Background:

Older adults often express positive attitudes toward digital-health technologies in surveys, yet adoption remains low. Self-report measures may not capture automatic affective reactions such as anxiety or distrust. Implicit paradigms like the Affect Misattribution Procedure (AMP) can reveal these automatic attitudes, but parameters optimized for younger adults may not suit older populations because of age-related slowing and changes in visual processing.

Objective:

This study aimed to adapt and evaluate an Influence-Aware Affect Misattribution Procedure (IA-AMP) for measuring older adults’ implicit attitudes toward digital-health technologies and to identify an age-appropriate prime duration that balances affect-transfer strength with minimal conscious awareness.

Methods:

A two-phase methodological adaptation and feasibility study was conducted with older adults (≥60 years). Phase 1 (N=40) developed and validated age-relevant synthetic images depicting older adults using digital-health tools. Images were evaluated on valence, arousal, thematic relevance, and low-level perceptual features. Phase 2 (N=56) implemented an IA-AMP with three prime durations (75 ms, 350 ms, 425 ms) across two sequential cohorts. The first cohort (Batch 2A, n=29) used the initial awareness probe; a second cohort (Batch 2B, n=27) used a simplified awareness interface. The core IA-AMP target judgment task was unchanged across batches. The primary inferential outcome was the binary trial-level target judgment, coded as pleasant versus unpleasant. Trial-level responses were analyzed using binomial logistic mixed-effects models with Prime Valence, Prime Duration, their interaction, and Batch as fixed effects, with random intercepts for participant and prime image. Awareness analyses were restricted to Batch 2B.

Results:

The primary GLMM showed a significant prime valence × prime duration interaction, χ²(2)=38.1, P<.001. Positive primes increased the odds of pleasant target judgments relative to negative primes at all durations: OR=11.2 at 75 ms, OR=31.9 at 350 ms, and OR=45.6 at 425 ms, all Holm-adjusted P<.001. The positive-negative contrast was smaller at 75 ms than at 350 ms and 425 ms, whereas the 350-ms and 425-ms contrasts did not significantly differ. Batch sensitivity analyses showed stronger overall priming in Batch 2B, but the Prime Valence × Prime Duration × Batch interaction was not significant, χ²(2)=0.76, P=.683.

Conclusions:

The IA-AMP offers a promising approach for assessing older adults’ affective responses to digital-health technologies beyond self-report. A prime duration of approximately 350 ms appears to be a practical calibration point for older-adult AMP studies, producing strong affect-transfer effects while avoiding the longest exposure duration. Because reported influence awareness was common, AMP effects should be interpreted alongside awareness measures rather than as awareness-free implicit attitudes. AMP-based affective measures may complement usability and adoption research by identifying emotional responses that users may not readily articulate, supporting more inclusive and evidence-informed digital-health development, evaluation, and implementation for aging populations. Clinical Trial: Not applicable