背景:研究已经确定了恋爱关系对个体发病率和死亡率的影响。然而,关系运作之间的相互作用,情感过程,健康行为研究相对不足。在COVID-19大流行期间,关系过程可能会影响新的健康行为,如社交距离和掩蔽。
目的:我们描述了设计,招募,以及关系的方法,风险认知,以及COVID-19大流行研究期间与癌症相关的行为。这项研究旨在了解关系和情感过程如何影响浪漫伴侣参与癌症预防行为以及COVID-19大流行引入或加剧的健康行为。
方法:关系,风险认知,在COVID-19大流行研究期间,癌症相关行为使用在线调查方法招募和招募2组参与同居浪漫关系的个体,包括1组成组(n=223)和1组癌症幸存者(n=443)。调查评估在平均间隔5.57(SD3.14)周的2个时间点完成。评估的健康行为包括COVID-19疫苗接种和社交距离,身体活动,饮食,睡眠,酒精使用,和吸烟行为。我们还检查了关系因素,心理困扰,家庭混乱。
结果:数据收集发生在2021年10月至2022年8月之间。在此期间,共有926名参与者参加,其中约三分之二来自英国(n=622,67.8%),三分之一来自美国(n=296,32.2%);约三分之二已婚(n=608,66.2%),三分之一是未婚夫妇(n=294,32%).在队列1和2中,平均年龄分别约为34岁和50岁。在队列1的478名参与者中,有19名(4%)被确定为西班牙裔或拉丁裔/a,79(17%)为非西班牙裔亚洲人,40(9%)是非西班牙裔黑人或非裔美国人,和306(64%)为非西班牙裔白人;62(13%)参与者确定他们的性取向为双性恋或泛性,359(75.1%)为异性恋或异性恋,和53(11%)为同性恋。在队列2中,在440名参与者中,13(3%)被确定为西班牙裔或拉丁裔/a,8(2%)为非西班牙裔亚洲人,5(1%)是非西班牙裔黑人或非裔美国人,和398(90.5%)为非西班牙裔白人;41(9%)参与者确定他们的性取向为双性恋或泛性,384(87.3%)为异性恋或异性恋,13(3%)是同性恋。个人的总体入学率为66.14%,总体完成率为80.08%。
结论:我们讨论了收集在线调查数据的最佳实践,用于研究人际关系和健康,与COVID-19大流行有关的挑战,招募代表性不足的人口,和二元组的注册。建议包括进行试点研究,为边缘化或服务不足的人群提供额外的数据收集时间,盈余筛选,以说明二元组合内的预期减员,以及计划dyad特定的数据质量检查。
■DERR1-10.2196/48516。
BACKGROUND: Research has established the effects of romantic relationships on individuals\' morbidity and mortality. However, the interplay between relationship functioning, affective processes, and health behaviors has been relatively understudied. During the COVID-19 pandemic, relational processes may influence novel health behaviors such as social distancing and masking.
OBJECTIVE: We describe the design, recruitment, and methods of the relationships, risk perceptions, and cancer-related behaviors during the COVID-19 pandemic study. This study was developed to understand how relational and affective processes influence romantic partners\' engagement in cancer prevention behaviors as well as health behaviors introduced or exacerbated by the COVID-19 pandemic.
METHODS: The relationships, risk perceptions, and cancer-related behaviors during the COVID-19 pandemic study used online survey methods to recruit and enroll 2 cohorts of individuals involved in cohabiting romantic relationships, including 1 cohort of dyads (n=223) and 1 cohort of cancer survivors (n=443). Survey assessments were completed over 2 time points that were 5.57 (SD 3.14) weeks apart on average. Health behaviors assessed included COVID-19 vaccination and social distancing, physical activity, diet, sleep, alcohol use, and smoking behavior. We also examined relationship factors, psychological distress, and household chaos.
RESULTS: Data collection occurred between October 2021 and August 2022. During that time, a total of 926 participants were enrolled, of which about two-thirds were from the United Kingdom (n=622, 67.8%) and one-third were from the United States (n=296, 32.2%); about two-thirds were married (n=608, 66.2%) and one-third were members of unmarried couples (n=294, 32%). In cohorts 1 and 2, the mean age was about 34 and 50, respectively. Out of 478 participants in cohort 1, 19 (4%) identified as Hispanic or Latino/a, 79 (17%) as non-Hispanic Asian, 40 (9%) as non-Hispanic Black or African American, and 306 (64%) as non-Hispanic White; 62 (13%) participants identified their sexual orientation as bisexual or pansexual, 359 (75.1%) as heterosexual or straight, and 53 (11%) as gay or lesbian. In cohort 2, out of 440 participants, 13 (3%) identified as Hispanic or Latino/a, 8 (2%) as non-Hispanic Asian, 5 (1%) as non-Hispanic Black or African American, and 398 (90.5%) as non-Hispanic White; 41 (9%) participants identified their sexual orientation as bisexual or pansexual, 384 (87.3%) as heterosexual or straight, and 13 (3%) as gay or lesbian. The overall enrollment rate for individuals was 66.14% and the overall completion rate was 80.08%.
CONCLUSIONS: We discuss best practices for collecting online survey data for studies examining relationships and health, challenges related to the COVID-19 pandemic, recruitment of underrepresented populations, and enrollment of dyads. Recommendations include conducting pilot studies, allowing for extra time in the data collection timeline for marginalized or underserved populations, surplus screening to account for expected attrition within dyads, as well as planning dyad-specific data quality checks.
UNASSIGNED: DERR1-10.2196/48516.