Martin Emily C, Basen-Engquist Karen, Cox Matthew G, Lyons Elizabeth J, Carmack Cindy L, Blalock Janice A, Demark-Wahnefried Wendy
University of Texas MD Anderson Cancer Center, Department of Behavioral Science, Houston, TX, United States.
The University of Texas Medical Branch, Department of Nutrition and Metabolism, Galveston, TX, United States.
JMIR Cancer. 2016 Feb 11;2(1):e1. doi: 10.2196/cancer.5247.
Effective, broad-reaching channels are important for the delivery of health behavior interventions in order to meet the needs of the growing population of cancer survivors in the United States. New technology presents opportunities to increase the reach of health behavior change interventions and therefore their overall impact. However, evidence suggests that older adults may be slower in their adoption of these technologies than the general population. Survivors' interest for more traditional channels of delivery (eg, clinic) versus new technology-based channels (eg, smartphones) may depend on a variety of factors, including demographics, current health status, and the behavior requiring intervention.
The aim of this study was to determine the factors that predict cancer survivors' interest in new technology-based health behavior intervention modalities versus traditional modalities.
Surveys were mailed to 1871 survivors of breast, prostate, and colorectal cancer. Participants' demographics, diet and physical activity behaviors, interest in health behavior interventions, and interest in intervention delivery modalities were collected. Using path analysis, we explored the relationship between four intervention modality variables (ie, clinic, telephone, computer, and smartphone) and potential predictors of modality interest.
In total, 1053 respondents to the survey (56.3% response rate); 847 provided complete data for this analysis. Delivery channel interest was highest for computer-based interventions (236/847, 27.9% very/extremely interested) and lowest for smartphone-based interventions (73/847, 8.6%), with interest in clinic-based (147/847, 17.3%) and telephone-delivered (143/847, 16.9%) falling in between. Use of other technology platforms, such as Web cameras and social networking sites, was positively predictive of interest in technology-based delivery channels. Older survivors were less likely to report interest in smartphone-based diet interventions. Physical activity, fruit and vegetable consumption, weight status, and age moderated relationships between interest in targeted intervention behavior and modality.
This study identified several predictors of survivor interest in various health behavior intervention delivery modalities. Overall, computer-based interventions were found to be most acceptable, while smartphones were the least. Factors related to survivors' current technology use and health status play a role in their interest for technology-based intervention versus more traditional delivery channels. Future health behavior change research in this population should consider participants' demographic, clinical, and lifestyle characteristics when selecting a delivery channel. Furthermore, current health behavior interventions for older cancer survivors may be best delivered over the Internet. Smartphone interventions may be feasible in the future following further adoption and familiarization by this particular population.
有效的、广泛覆盖的渠道对于提供健康行为干预措施很重要，以便满足美国不断增长的癌症幸存者群体的需求。新技术为扩大健康行为改变干预措施的覆盖范围以及提升其总体影响提供了机遇。然而，有证据表明，老年人采用这些技术的速度可能比普通人群慢。幸存者对更传统的传播渠道（如诊所）与基于新技术的渠道（如智能手机）的兴趣可能取决于多种因素，包括人口统计学特征、当前健康状况以及需要干预的行为。
本研究的目的是确定预测癌症幸存者对基于新技术的健康行为干预方式与传统方式的兴趣的因素。
向1871名乳腺癌、前列腺癌和结直肠癌幸存者邮寄了调查问卷。收集了参与者的人口统计学特征、饮食和身体活动行为、对健康行为干预的兴趣以及对干预传播方式的兴趣。使用路径分析，我们探讨了四种干预方式变量（即诊所、电话、计算机和智能手机）与方式兴趣的潜在预测因素之间的关系。
共有1053名受访者回复了调查问卷（回复率为56.3%）；847人提供了完整数据用于本分析。基于计算机的干预措施的传播渠道兴趣最高（236/847，27.9%非常/极其感兴趣），基于智能手机的干预措施的兴趣最低（73/847，8.6%），基于诊所的（147/847，17.3%）和电话传播的（143/847，16.9%）兴趣介于两者之间。使用其他技术平台，如网络摄像头和社交网站，对基于技术的传播渠道的兴趣具有正向预测作用。年龄较大的幸存者对基于智能手机的饮食干预措施表示感兴趣的可能性较小。身体活动、水果和蔬菜消费、体重状况以及年龄调节了目标干预行为兴趣与方式之间的关系。
本研究确定了幸存者对各种健康行为干预传播方式兴趣的几个预测因素。总体而言，发现基于计算机的干预措施最易被接受，而智能手机的接受度最低。与幸存者当前技术使用和健康状况相关的因素在他们对基于技术的干预措施与更传统传播渠道的兴趣方面发挥了作用。未来针对该人群的健康行为改变研究在选择传播渠道时应考虑参与者的人口统计学、临床和生活方式特征。此外，目前针对老年癌症幸存者的健康行为干预措施可能最好通过互联网提供。在这一特定人群进一步采用和熟悉之后，智能手机干预措施未来可能是可行的。
