Mindfulness Intervention for Health Information Avoidance in Older Adults: Mixed Methods Study.
Chenyu Gu, Liquan Qian, Xiaojie Zhuo
JMIR public health and surveillance January 28, 2025 DOI: 10.2196/69554 (opens in new tab)
Study at a glance
AI-extracted from the abstract| Characteristics | Mixed methods study (cross-sectional survey plus randomized controlled intervention) Qualitative Peer reviewed |
|---|---|
| Sample size | 330 |
| Population | Older adults |
| Intervention | Mindfulness meditation |
| Duration | 4-week mindfulness meditation intervention; cross-sectional survey |
| Topics | Meditation |
| Keywords | Cyberchondria Elderly Health information avoidance Self-determination theory |
| Key findings | Cyberchondria mediated the effects of positive metacognition, health self-efficacy, and health information similarity on health information avoidance in older adults, while subjective norms showed no significant association. A 4-week mindfulness meditation intervention raised mindfulness levels but did not reduce cyberchondria; the authors report a significant interaction suggesting mindfulness weakened the link between cyberchondria and avoidance behavior. |
Abstract
The global aging population and rapid development of digital technology have made health management among older adults an urgent public health issue. The complexity of online health information often leads to psychological challenges, such as cyberchondria, exacerbating health information avoidance behaviors. These behaviors hinder effective health management; yet, little research examines their mechanisms or intervention strategies. This study investigates the mechanisms influencing health information avoidance among older adults, emphasizing the mediating role of cyberchondria. In addition, it evaluates the effectiveness of mindfulness meditation as an intervention strategy to mitigate these behaviors. A mixed methods approach was used, combining quantitative and qualitative methodologies. Substudy 1 developed a theoretical model based on self-determination theory to explore internal (positive metacognition and health self-efficacy) and external (subjective norms and health information similarity) factors influencing health information avoidance, with cyberchondria as a mediator. A cross-sectional survey (N=236) was conducted to test the proposed model. Substudy 2 involved a 4-week mindfulness meditation intervention (N=94) to assess its impact on reducing health information avoidance behaviors. Study 1 showed that positive metacognition (β=.26, P=.002), health self-efficacy (β=.25, P<.001), and health information similarity (β=.29, P<.001) significantly predicted health information avoidance among older adults. Cyberchondria mediated these effects: positive metacognition (effect=0.106, 95% CI 0.035-0.189), health self-efficacy (effect=0.103, 95% CI 0.043-0.185), and health information similarity (effect=0.120, 95% CI 0.063-0.191). Subjective norms did not significantly predict health information avoidance (β=‒.11, P=.13), and cyberchondria did not mediate this relationship (effect=‒0.045, 95% CI ‒0.102 to 0.016). Study 2 found that after the 4-week mindfulness intervention, the intervention group (group 1: n=46) exhibited significantly higher mindfulness levels than the control group (group 2: n=48; Mgroup1=4.122, Mgroup2=3.606, P<.001) and higher levels compared with preintervention (Mt2=4.122, Mt1=3.502, P<.001, where t1=preintervention and t2=postintervention). However, cyberchondria levels did not change significantly (Mt1=2.848, Mt2=2.685, P=.18). Nevertheless, the results revealed a significant interaction effect between mindfulness and cyberchondria on health information avoidance (effect=‒0.357, P=.002, 95% CI ‒0.580 to ‒0.131), suggesting that mindfulness intervention effectively inhibited the transformation of cyberchondria into health information avoidance behavior. This study reveals the role of cyberchondria in health information avoidance and validates mindfulness meditation as an effective intervention for mitigating such behaviors. Findings offer practical recommendations for improving digital health information delivery and health management strategies for older adults.