Laura Pathak, Rosa Hernandez-Ramos, Karina Rosales, Jose Miramontes-Gomez, Faviola Garcia, Vivian Yip, Suchitra Sudarshan, Anupama Gunshekar Cemballi, Courtney Lyles, Adrian Aguilera
{"title":"利用社交媒体招募不同样本的参与者进行移动健康(mHealth)干预以增加身体活动:探索性研究。","authors":"Laura Pathak, Rosa Hernandez-Ramos, Karina Rosales, Jose Miramontes-Gomez, Faviola Garcia, Vivian Yip, Suchitra Sudarshan, Anupama Gunshekar Cemballi, Courtney Lyles, Adrian Aguilera","doi":"10.2196/56329","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Recruitment of demographically diverse samples in clinical research is often challenging and even more so during the COVID-19 pandemic when traditional in-person recruitment methods could not be implemented. Social media platforms offer an alternative approach for recruiting diverse samples of participants for clinical trials, including those testing digital health interventions. This approach allowed for a quicker recruitment process without the physical constraints associated with traditional in-person methods.</p><p><strong>Objective: </strong>This study aimed to detail the online and social media campaigns used to recruit participants for \"Diabetes and Mental Health Adaptive Notification Tracking and Evaluation\" (DIAMANTE), a randomized controlled trial testing a smartphone-based intervention (a text messaging system that uses machine learning to personalize content) to increase physical activity for patients with diabetes and depression. In describing the recruitment process, we seek to offer insights to the research community on recruitment through online and social media advertisements for diverse communities.</p><p><strong>Methods: </strong>This study sought to recruit demographically diverse individuals in the United States through social media, including paid advertisements on Craigslist and Facebook (Meta). For the DIAMANTE project recruitment, we created 18 personas that mapped into the population's target demographics using a user-centered design methodology. We deployed targeted English and Spanish ads on Craigslist and Facebook in 78 cities based on county-level demographics and diabetes prevalence data to target diverse individuals aged 18-75 years old, who had been diagnosed with diabetes and had documented depressive symptoms.</p><p><strong>Results: </strong>A total of 1379 individuals completed the study's initial screening survey. Of those, 71 respondents on Facebook and 508 on Craigslist were interested in enrolling in our study. In total, 26 out of 58 (45%) eligible respondents from Facebook and 50 out of 235 (21.3%) eligible respondents from Craigslist were eventually recruited in the randomized controlled trial. In all, both platforms showed poor performance in recruiting Spanish speakers, with Facebook advertisements accounting for 0 and Craigslist for 4 (5.3%) of such participants. When it came to English speakers, Craigslist proved to be the better performing platform compared to Facebook, both in terms of reach (579 vs 71) and cost-effectiveness (US $67.61 in average cost per recruited participant vs US $80.16). While Craigslist ads reached more people, resulting in more completed screening surveys than Facebook ads, there was a higher number of ineligible and incomplete enrollment from Craigslist compared with Facebook, leading to a relatively lower conversion rate (9.4% vs 36.6%). Importantly, participants recruited through Craigslist were more ethnically and racially diverse than those recruited from Facebook.</p><p><strong>Conclusions: </strong>Results from this study revealed that it is possible to recruit diverse sample sets using social media and online advertisements. However, despite targeted recruitment efforts, social media recruitment of Spanish speakers proved especially challenging and costly. Further research is needed to determine systematic, online methods for recruiting marginalized communities.</p>","PeriodicalId":14756,"journal":{"name":"JMIR mHealth and uHealth","volume":"13 ","pages":"e56329"},"PeriodicalIF":5.4000,"publicationDate":"2025-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12052219/pdf/","citationCount":"0","resultStr":"{\"title\":\"Using Social Media to Recruit a Diverse Sample of Participants for a Mobile Health (mHealth) Intervention to Increase Physical Activity: Exploratory Study.\",\"authors\":\"Laura Pathak, Rosa Hernandez-Ramos, Karina Rosales, Jose Miramontes-Gomez, Faviola Garcia, Vivian Yip, Suchitra Sudarshan, Anupama Gunshekar Cemballi, Courtney Lyles, Adrian Aguilera\",\"doi\":\"10.2196/56329\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Recruitment of demographically diverse samples in clinical research is often challenging and even more so during the COVID-19 pandemic when traditional in-person recruitment methods could not be implemented. Social media platforms offer an alternative approach for recruiting diverse samples of participants for clinical trials, including those testing digital health interventions. This approach allowed for a quicker recruitment process without the physical constraints associated with traditional in-person methods.</p><p><strong>Objective: </strong>This study aimed to detail the online and social media campaigns used to recruit participants for \\\"Diabetes and Mental Health Adaptive Notification Tracking and Evaluation\\\" (DIAMANTE), a randomized controlled trial testing a smartphone-based intervention (a text messaging system that uses machine learning to personalize content) to increase physical activity for patients with diabetes and depression. In describing the recruitment process, we seek to offer insights to the research community on recruitment through online and social media advertisements for diverse communities.</p><p><strong>Methods: </strong>This study sought to recruit demographically diverse individuals in the United States through social media, including paid advertisements on Craigslist and Facebook (Meta). For the DIAMANTE project recruitment, we created 18 personas that mapped into the population's target demographics using a user-centered design methodology. We deployed targeted English and Spanish ads on Craigslist and Facebook in 78 cities based on county-level demographics and diabetes prevalence data to target diverse individuals aged 18-75 years old, who had been diagnosed with diabetes and had documented depressive symptoms.</p><p><strong>Results: </strong>A total of 1379 individuals completed the study's initial screening survey. Of those, 71 respondents on Facebook and 508 on Craigslist were interested in enrolling in our study. In total, 26 out of 58 (45%) eligible respondents from Facebook and 50 out of 235 (21.3%) eligible respondents from Craigslist were eventually recruited in the randomized controlled trial. In all, both platforms showed poor performance in recruiting Spanish speakers, with Facebook advertisements accounting for 0 and Craigslist for 4 (5.3%) of such participants. When it came to English speakers, Craigslist proved to be the better performing platform compared to Facebook, both in terms of reach (579 vs 71) and cost-effectiveness (US $67.61 in average cost per recruited participant vs US $80.16). While Craigslist ads reached more people, resulting in more completed screening surveys than Facebook ads, there was a higher number of ineligible and incomplete enrollment from Craigslist compared with Facebook, leading to a relatively lower conversion rate (9.4% vs 36.6%). Importantly, participants recruited through Craigslist were more ethnically and racially diverse than those recruited from Facebook.</p><p><strong>Conclusions: </strong>Results from this study revealed that it is possible to recruit diverse sample sets using social media and online advertisements. However, despite targeted recruitment efforts, social media recruitment of Spanish speakers proved especially challenging and costly. 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Using Social Media to Recruit a Diverse Sample of Participants for a Mobile Health (mHealth) Intervention to Increase Physical Activity: Exploratory Study.
Background: Recruitment of demographically diverse samples in clinical research is often challenging and even more so during the COVID-19 pandemic when traditional in-person recruitment methods could not be implemented. Social media platforms offer an alternative approach for recruiting diverse samples of participants for clinical trials, including those testing digital health interventions. This approach allowed for a quicker recruitment process without the physical constraints associated with traditional in-person methods.
Objective: This study aimed to detail the online and social media campaigns used to recruit participants for "Diabetes and Mental Health Adaptive Notification Tracking and Evaluation" (DIAMANTE), a randomized controlled trial testing a smartphone-based intervention (a text messaging system that uses machine learning to personalize content) to increase physical activity for patients with diabetes and depression. In describing the recruitment process, we seek to offer insights to the research community on recruitment through online and social media advertisements for diverse communities.
Methods: This study sought to recruit demographically diverse individuals in the United States through social media, including paid advertisements on Craigslist and Facebook (Meta). For the DIAMANTE project recruitment, we created 18 personas that mapped into the population's target demographics using a user-centered design methodology. We deployed targeted English and Spanish ads on Craigslist and Facebook in 78 cities based on county-level demographics and diabetes prevalence data to target diverse individuals aged 18-75 years old, who had been diagnosed with diabetes and had documented depressive symptoms.
Results: A total of 1379 individuals completed the study's initial screening survey. Of those, 71 respondents on Facebook and 508 on Craigslist were interested in enrolling in our study. In total, 26 out of 58 (45%) eligible respondents from Facebook and 50 out of 235 (21.3%) eligible respondents from Craigslist were eventually recruited in the randomized controlled trial. In all, both platforms showed poor performance in recruiting Spanish speakers, with Facebook advertisements accounting for 0 and Craigslist for 4 (5.3%) of such participants. When it came to English speakers, Craigslist proved to be the better performing platform compared to Facebook, both in terms of reach (579 vs 71) and cost-effectiveness (US $67.61 in average cost per recruited participant vs US $80.16). While Craigslist ads reached more people, resulting in more completed screening surveys than Facebook ads, there was a higher number of ineligible and incomplete enrollment from Craigslist compared with Facebook, leading to a relatively lower conversion rate (9.4% vs 36.6%). Importantly, participants recruited through Craigslist were more ethnically and racially diverse than those recruited from Facebook.
Conclusions: Results from this study revealed that it is possible to recruit diverse sample sets using social media and online advertisements. However, despite targeted recruitment efforts, social media recruitment of Spanish speakers proved especially challenging and costly. Further research is needed to determine systematic, online methods for recruiting marginalized communities.
期刊介绍:
JMIR mHealth and uHealth (JMU, ISSN 2291-5222) is a spin-off journal of JMIR, the leading eHealth journal (Impact Factor 2016: 5.175). JMIR mHealth and uHealth is indexed in PubMed, PubMed Central, and Science Citation Index Expanded (SCIE), and in June 2017 received a stunning inaugural Impact Factor of 4.636.
The journal focusses on health and biomedical applications in mobile and tablet computing, pervasive and ubiquitous computing, wearable computing and domotics.
JMIR mHealth and uHealth publishes since 2013 and was the first mhealth journal in Pubmed. It publishes even faster and has a broader scope with including papers which are more technical or more formative/developmental than what would be published in the Journal of Medical Internet Research.