Background: The technology acceptance model (TAM) and the unified theory of acceptance and use of technology (UTAUT) are widely used to examine health care technology acceptance among older adults. However, existing literature exhibits considerable heterogeneity, making it difficult to determine consistent predictors of acceptance and behavior. Objective: We aimed to (1) determine the influence of perceived usefulness (PU), perceived ease of use (PEOU), and social influence (SI) on the behavioral intention (BI) to use health care technology among older adults and (2) assess the moderating effects of age, gender, geographic region, type of health care technology, and presence of visual demonstrations. Methods: A systematic search was conducted across Google Scholar, Web of Science, Scopus, IEEE Xplore, and ProQuest databases on March 15, 2024, following PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. Of the 1167 initially identified studies, 41 studies (11,574 participants; mean age 67.58, SD 4.76 years; and female:male ratio=2.00) met the inclusion criteria. The studies comprised 12 mobile health, 12 online or telemedicine, 9 wearable, and 8 home or institution hardware investigations, with 23 studies from Asia, 7 from Europe, 7 from African-Islamic regions, and 4 from the United States. Studies were eligible if they used the TAM or UTAUT, examined health care technology adoption among older adults, and reported zero-order correlations. Two independent reviewers screened studies, extracted data, and assessed methodological quality using the Newcastle-Ottawa Scale, evaluating selection, comparability, and outcome assessment with 34% (14/41) of studies rated as good quality and 66% (27/41) as satisfactory. Results: Random-effects meta-analysis revealed significant positive correlations for PU-BI (r=0.607, 95% CI 0.543-0.665; P<.001), PEOU-BI (r=0.525, 95% CI 0.462-0.583; P<.001), and SI-BI (r=0.551, 95% CI 0.468-0.624; P<.001). High heterogeneity was observed across studies (I²=95.9%, 93.6%, and 95.3% for PU-BI, PEOU-BI, and SI-BI, respectively). Moderator analyses revealed significant differences based on geographic region for PEOU-BI (Q=8.27; P=.04), with strongest effects in Europe (r=0.628) and weakest in African-Islamic regions (r=0.480). Technology type significantly moderated PU-BI (Q=8.08; P=.04) and SI-BI (Q=14.75; P=.002), with home or institutional hardware showing the strongest effects (PU-BI: r=0.736; SI-BI: r=0.690). Visual demonstrations significantly enhanced PU-BI (r=0.706 vs r=0.554; Q=4.24; P=.04) and SI-BI relationships (r=0.670 vs r=0.492; Q=4.38; P=.04). Age and gender showed no significant moderating effects. Conclusions: The findings indicate that PU, PEOU, and SI significantly impact the acceptance of health care technology among older adults, with heterogeneity influenced by geographic region, type of technology, and presence of visual demonstrations. This suggests that tailored strategies for different types of technology and the use of visual demonstrations are important for enhancing adoption rates. Limitations include varying definitions of older adults across studies and the use of correlation coefficients rather than controlled effect sizes. Results should therefore be interpreted within specific contexts and populations.

The combined effects of color temperature and illuminance in a small office on visual response and mood under various lighting conditions were examined in this study. Visual annoyance tests were conducted using a sample of 20 subjects in a full-scale mock-up test space. Computer and paper-based reading tasks were conducted for 500 lx and 750 lx illuminance levels under 3,000 K, 4,000 K and 6,500 K conditions. Two hypotheses were considered for the test in this study. The primary hypothesis was that visual perception is affected by the color temperatures of light sources. The secondary hypothesis was that better moods, such as relaxed and cozy feelings, are associated with low color temperatures given equal illuminance levels. The visual environment under the 3,000 K condition was characterized by glare and brightness, resulting in visual discomfort when target illuminance was higher than 500 lx. Occupants preferred 500 lx under the 6,500 K condition, and 500 lx and 750 lx under the 4,000 K condition, reporting better visual satisfaction when performing office tasks. Prediction models for visual comfort suggest that the less that subjects are visually bothered by light during tasks, the more visual comfort they feel. User satisfaction with light source color is critical for the prediction of visual comfort under different lighting conditions. Visual comfort was the most influential factor on mood. Lower color temperature was associated with better mood at lower illuminance levels, while higher color temperature was preferred at higher illuminance levels.

This study examined which accompanying information elements were noticed by visitors while they were looking at artworks, using eye-tracking experiments. First, we conducted an online survey to grasp the types of information that visitors wanted to know, and five elements were obtained. Second, we collected information on these five elements through interviews with one artist. Third, eye-tracking experiments were performed with semi-structured interviews. We set the information delivery media as follows: wall and mobile texts as commonly used in art museums. The results showed that patterns of eye movement of visitors were different according to the information delivery media. Also, we found that there was a correlation between the results of the eye-tracking experiment and visitor interest. This study has limitations in that it is an experiment limited to small sample size and artwork genre; however, it is meaningful in that it was able to grasp the information needs of visitors through eye-tracking.