Men with prostate cancer often need social support to help them cope with illness-related physiological and psychosocial challenges. Whether those needs are met depends on receiving support optimally matched to their needs. This study examined relationships between perceived stress, prostate cancer-related stigma, weak-tie support preference, and online community use for social support in a survey of online prostate cancer community participants (n = 149). Findings revealed a positive relationship between stigma and perceived stress. This relationship, however, was moderated by weak-tie support preference and online community use for social support. Specifically, stigma was positively related to perceived stress when weak-tie support was preferred. Analyses also showed a positive relationship between stigma and perceived stress in those who used their online community for advice or emotional support. Health communication scholars should work collaboratively with diagnosed men, clinicians, and online community administrators to develop online interventions that optimally match social support needs.

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BackgroundMen with prostate cancer require ample information and support along the continuum of care, and eHealth is one way to meet such critical information and support needs. Currently, evidence about how age influences use and perceptions about prostate cancer eHealth information and support is lacking.ObjectiveThe aim of this paper is to explore use and perceptions about eHealth among men living with prostate cancer. Specifically, we aimed to analyze men with prostate cancer by age-specific cohorts to identify potential age-related differences in use and perceptions about prostate cancer eHealth information.MethodsWe used survey methodology to examine how men under 65 years old with prostate cancer differ from those aged 65 years old or older in use and perceptions about prostate cancer eHealth information and support (n=289).ResultsWe found that men in the younger cohort used the Internet more often to be informed about treatment options (P=.04) and to learn more about staging/grading (P=.01) than men in the older cohort. Results also showed comparatively greater use of online prostate cancer information for emotional support and encouragement by the younger as compared to the older cohort (P=.001). Furthermore, the older cohort reported more negative psychosocial effects of eHealth (eg, more anxious, depressed) than younger men (P=.002). We also found that as a result of more frequent Internet use, younger men experienced more positive psychosocial effects (eg, more informed, in control) from accessing information about prostate cancer through eHealth channels (b=-0.10, 95% CI -0.28 to 0).ConclusionsMen with prostate cancer have different information and support needs; our findings suggest that these needs might vary by age. Future research is needed to unravel age-related factors underlying these differences to be better able to tailor prostate cancer eHealth information to men’s information and support needs.

BackgroundWomen are concerned about reducing their breast cancer risk, particularly if they have daughters. Social media platforms, such as blogs written by mothers, are increasingly being recognized as a channel that women use to make personal and family health–related decisions. Government initiatives (eg, Interagency Breast Cancer and Environmental Research Coordinating Committee) and researchers have called for scientists and the community to partner and disseminate scientifically and community-informed environmental risk information.ObjectiveWe developed and evaluated a blog intervention to disseminate breast cancer and environmental risk information to mothers. We teamed with mommy bloggers to disseminate a message that we developed and tailored for mothers and daughters based on scientific evidence from the Breast Cancer and the Environment Research Program (BCERP). We posited that the intervention would influence women’s exposure to, acceptance of, and beliefs about environmental risks while promoting their intention to adopt risk-reducing behaviors.MethodsUsing a quasi-experimental design, we recruited 75 mommy bloggers to disseminate the breast cancer risk message on their respective blogs and examined the impact of the intervention on (1) readers exposed to the intervention (n=445) and (2) readers not exposed to the intervention (comparison group; n=353).ResultsFollowing the intervention, blog reader scores indicating exposure to the breast cancer risk and prevention information were greater than scores of blog readers who were not exposed (or did not recall seeing the message; mean 3.92, SD 0.85 and mean 3.45, SD 0.92, respectively; P<.001). Readers who recalled the intervention messages also had higher breast cancer risk and prevention information satisfaction scores compared with readers who did not see (or recall) the messages (mean 3.97, SD 0.75 and mean 3.57, SD 0.94, respectively; P<.001). Blog readers who recalled seeing the intervention messages were significantly more likely to share the breast cancer risk and prevention information they read, with their daughters specifically, than readers who did not recall seeing them (χ21=8.1; P=.004). Those who recalled seeing the intervention messages reported significantly higher breast cancer risk and prevention information influence scores, indicative of behavioral intentions, than participants who did not recall seeing them (mean 11.22, SD 2.93 and mean 10.14, SD 3.24, respectively; P=.003). Most women ranked Facebook as their first choice for receiving breast cancer risk information.ConclusionsResults indicated that blog readers who were exposed to (and specifically recalled) the BCERP-adapted intervention messages from mommy bloggers had higher breast cancer risk and prevention information exposure scores and higher breast cancer risk and prevention information satisfaction and influence scores than those who did not see (or recall) them. Mommy bloggers may be important opinion leaders for some women and key to enhancing the messaging, delivery, an...

Background Multiple types of mobile health (mHealth) technologies are available, such as smartphone health apps, fitness trackers, and digital medical devices. However, despite their availability, some individuals do not own, do not realize they own, or own but do not use these technologies. Others may use mHealth devices, but their use varies in tracking health, behaviors, and goals. Examining patterns of mHealth use at the population level can advance our understanding of technology use for health and behavioral tracking. Moreover, investigating sociodemographic and health-related correlates of these patterns can provide direction to researchers about how to target mHealth interventions for diverse audiences. Objective The aim of this study was to identify patterns of mHealth use for health and behavioral tracking in the US adult population and to characterize the population according to those patterns. Methods We combined data from the 2017 and 2018 National Cancer Institute Health Information National Trends Survey (N=6789) to characterize respondents according to 5 mutually exclusive reported patterns of mHealth use for health and behavioral tracking: (1) mHealth nonowners and nonusers report not owning or using devices to track health, behaviors, or goals; (2) supertrackers track health or behaviors and goals using a smartphone or tablet plus other devices (eg, Fitbit); (3) app trackers use only a smartphone or tablet; (4) device trackers use only nonsmartphone or nontablet devices and do not track goals; and (5) nontrackers report having smartphone or tablet health apps but do not track health, behaviors, or goals. Results Being in the mHealth nonowners and nonusers category (vs all mHealth owners and users) is associated with males, older age, lower income, and not being a health information seeker. Among mHealth owners and users, characteristics of device trackers and supertrackers were most distinctive. Compared with supertrackers, device trackers have higher odds of being male (odds ratio [OR] 2.22, 95% CI 1.55-3.19), older age (vs 18-34 years; 50-64 years: OR 2.83, 95% CI 1.52-5.30; 65+ years: OR 6.28, 95% CI 3.35-11.79), have an annual household income of US $20,000 to US $49,999 (vs US $75,000+: OR 2.31, 95% CI 1.36-3.91), and have a chronic condition (OR 1.69, 95% CI 1.14-2.49). Device trackers also have higher odds of not being health information seekers than supertrackers (OR 2.98, 95% CI 1.66-5.33). Conclusions Findings revealed distinctive sociodemographic and health-related characteristics of the population by pattern of mHealth use, with notable contrasts between those who do and do not use devices to track goals. Several characteristics of individuals who track health or behaviors but not goals (device trackers) are similar to those of mHealth nonowners and nonusers. Our results suggest patterns of mHealth use may inform how to target mHealth interventions to enhance reach and facilitate healthy behaviors.