Recruiting Young People for Digital Mental Health Research: Lessons From an AI-Driven Adaptive Trial
BackgroundWith increasing adoption of remote clinical trials in digital mental health, identifying cost-effective and time-efficient recruitment methodologies is crucial for the success of such trials. Evidence on whether web-based recruitment methods are more effective than...
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| Format: | Article |
| Language: | English |
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JMIR Publications
2025-01-01
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| Series: | Journal of Medical Internet Research |
| Online Access: | https://www.jmir.org/2025/1/e60413 |
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| author | Wu Yi Zheng Artur Shvetcov Aimy Slade Zoe Jenkins Leonard Hoon Alexis Whitton Rena Logothetis Smrithi Ravindra Stefanus Kurniawan Sunil Gupta Kit Huckvale Eileen Stech Akash Agarwal Joost Funke Kupper Stuart Cameron Jodie Rosenberg Nicholas Manoglou Manisha Senadeera Svetha Venkatesh Kon Mouzakis Rajesh Vasa Helen Christensen Jill M Newby |
| author_facet | Wu Yi Zheng Artur Shvetcov Aimy Slade Zoe Jenkins Leonard Hoon Alexis Whitton Rena Logothetis Smrithi Ravindra Stefanus Kurniawan Sunil Gupta Kit Huckvale Eileen Stech Akash Agarwal Joost Funke Kupper Stuart Cameron Jodie Rosenberg Nicholas Manoglou Manisha Senadeera Svetha Venkatesh Kon Mouzakis Rajesh Vasa Helen Christensen Jill M Newby |
| author_sort | Wu Yi Zheng |
| collection | DOAJ |
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BackgroundWith increasing adoption of remote clinical trials in digital mental health, identifying cost-effective and time-efficient recruitment methodologies is crucial for the success of such trials. Evidence on whether web-based recruitment methods are more effective than traditional methods such as newspapers, media, or flyers is inconsistent. Here we present insights from our experience recruiting tertiary education students for a digital mental health artificial intelligence–driven adaptive trial—Vibe Up.
ObjectiveWe evaluated the effectiveness of recruitment via Facebook and Instagram compared to traditional methods for a treatment trial and compared different recruitment methods’ retention rates. With recruitment coinciding with COVID-19 lockdowns across Australia, we also compared the cost-effectiveness of social media recruitment during and after lockdowns.
MethodsRecruitment was completed for 2 pilot trials and 6 minitrials from June 2021 to May 2022. To recruit participants, paid social media advertising on Facebook and Instagram was used, alongside mailing lists of university networks and student organizations or services, media releases, announcements during classes and events, study posters or flyers on university campuses, and health professional networks. Recruitment data, including engagement metrics collected by Meta (Facebook and Instagram), advertising costs, and Qualtrics data on recruitment methods and survey completion rates, were analyzed using RStudio with R (version 3.6.3; R Foundation for Statistical Computing).
ResultsIn total, 1314 eligible participants (aged 22.79, SD 4.71 years; 1079, 82.1% female) were recruited to 2 pilot trials and 6 minitrials. The vast majority were recruited via Facebook and Instagram advertising (n=1203; 92%). Pairwise comparisons revealed that the lead institution’s website was more effective in recruiting eligible participants than Facebook (z=3.47; P=.003) and Instagram (z=4.23; P<.001). No differences were found between recruitment methods in retaining participants at baseline, at midpoint, and at study completion. Wilcoxon tests found significant differences between lockdown (pilot 1 and pilot 2) and postlockdown (minitrials 1-6) on costs incurred per link click (lockdown: median Aus $0.35 [US $0.22], IQR Aus $0.27-$0.47 [US $0.17-$0.29]; postlockdown: median Aus $1.00 [US $0.62], IQR Aus $0.70-$1.47 [US $0.44-$0.92]; W=9087; P<.001) and the amount spent per hour to reach the target sample size (lockdown: median Aus $4.75 [US $2.95], IQR Aus $1.94-6.34 [US $1.22-$3.97]; postlockdown: median Aus $13.29 [US $8.26], IQR Aus $4.70-25.31 [US $2.95-$15.87]; W=16044; P<.001).
ConclusionsSocial media advertising via Facebook and Instagram was the most successful strategy for recruiting distressed tertiary students into this artificial intelligence–driven adaptive trial, providing evidence for the use of this recruitment method for this type of trial in digital mental health research. No recruitment method stood out in terms of participant retention. Perhaps a reflection of the added distress experienced by young people, social media recruitment during the COVID-19 lockdown period was more cost-effective.
Trial RegistrationAustralian New Zealand Clinical Trials Registry ACTRN12621001092886; https://tinyurl.com/39f2pdmd; Australian New Zealand Clinical Trials Registry ACTRN12621001223820; https://tinyurl.com/bdhkvucv |
| format | Article |
| id | doaj-art-ef69108ab9ef42e38524ed69a77e8f65 |
| institution | Kabale University |
| issn | 1438-8871 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | JMIR Publications |
| record_format | Article |
| series | Journal of Medical Internet Research |
| spelling | doaj-art-ef69108ab9ef42e38524ed69a77e8f652025-01-14T21:30:32ZengJMIR PublicationsJournal of Medical Internet Research1438-88712025-01-0127e6041310.2196/60413Recruiting Young People for Digital Mental Health Research: Lessons From an AI-Driven Adaptive TrialWu Yi Zhenghttps://orcid.org/0000-0002-1159-4700Artur Shvetcovhttps://orcid.org/0000-0003-0592-984XAimy Sladehttps://orcid.org/0000-0001-5368-1792Zoe Jenkinshttps://orcid.org/0009-0002-8749-7939Leonard Hoonhttps://orcid.org/0000-0003-0428-7240Alexis Whittonhttps://orcid.org/0000-0002-7944-2172Rena Logothetishttps://orcid.org/0000-0003-0143-3812Smrithi Ravindrahttps://orcid.org/0000-0001-7551-8179Stefanus Kurniawanhttps://orcid.org/0009-0001-4469-1056Sunil Guptahttps://orcid.org/0000-0002-3308-1930Kit Huckvalehttps://orcid.org/0000-0001-9088-6682Eileen Stechhttps://orcid.org/0000-0003-0151-9026Akash Agarwalhttps://orcid.org/0009-0009-2333-8366Joost Funke Kupperhttps://orcid.org/0009-0009-6067-1782Stuart Cameronhttps://orcid.org/0000-0002-7862-3051Jodie Rosenberghttps://orcid.org/0000-0002-8738-3467Nicholas Manoglouhttps://orcid.org/0009-0004-2225-149XManisha Senadeerahttps://orcid.org/0000-0002-5923-6857Svetha Venkateshhttps://orcid.org/0000-0001-8675-6631Kon Mouzakishttps://orcid.org/0000-0003-4447-5166Rajesh Vasahttps://orcid.org/0000-0003-4805-1467Helen Christensenhttps://orcid.org/0000-0003-0435-2065Jill M Newbyhttps://orcid.org/0000-0002-6473-9811 BackgroundWith increasing adoption of remote clinical trials in digital mental health, identifying cost-effective and time-efficient recruitment methodologies is crucial for the success of such trials. Evidence on whether web-based recruitment methods are more effective than traditional methods such as newspapers, media, or flyers is inconsistent. Here we present insights from our experience recruiting tertiary education students for a digital mental health artificial intelligence–driven adaptive trial—Vibe Up. ObjectiveWe evaluated the effectiveness of recruitment via Facebook and Instagram compared to traditional methods for a treatment trial and compared different recruitment methods’ retention rates. With recruitment coinciding with COVID-19 lockdowns across Australia, we also compared the cost-effectiveness of social media recruitment during and after lockdowns. MethodsRecruitment was completed for 2 pilot trials and 6 minitrials from June 2021 to May 2022. To recruit participants, paid social media advertising on Facebook and Instagram was used, alongside mailing lists of university networks and student organizations or services, media releases, announcements during classes and events, study posters or flyers on university campuses, and health professional networks. Recruitment data, including engagement metrics collected by Meta (Facebook and Instagram), advertising costs, and Qualtrics data on recruitment methods and survey completion rates, were analyzed using RStudio with R (version 3.6.3; R Foundation for Statistical Computing). ResultsIn total, 1314 eligible participants (aged 22.79, SD 4.71 years; 1079, 82.1% female) were recruited to 2 pilot trials and 6 minitrials. The vast majority were recruited via Facebook and Instagram advertising (n=1203; 92%). Pairwise comparisons revealed that the lead institution’s website was more effective in recruiting eligible participants than Facebook (z=3.47; P=.003) and Instagram (z=4.23; P<.001). No differences were found between recruitment methods in retaining participants at baseline, at midpoint, and at study completion. Wilcoxon tests found significant differences between lockdown (pilot 1 and pilot 2) and postlockdown (minitrials 1-6) on costs incurred per link click (lockdown: median Aus $0.35 [US $0.22], IQR Aus $0.27-$0.47 [US $0.17-$0.29]; postlockdown: median Aus $1.00 [US $0.62], IQR Aus $0.70-$1.47 [US $0.44-$0.92]; W=9087; P<.001) and the amount spent per hour to reach the target sample size (lockdown: median Aus $4.75 [US $2.95], IQR Aus $1.94-6.34 [US $1.22-$3.97]; postlockdown: median Aus $13.29 [US $8.26], IQR Aus $4.70-25.31 [US $2.95-$15.87]; W=16044; P<.001). ConclusionsSocial media advertising via Facebook and Instagram was the most successful strategy for recruiting distressed tertiary students into this artificial intelligence–driven adaptive trial, providing evidence for the use of this recruitment method for this type of trial in digital mental health research. No recruitment method stood out in terms of participant retention. Perhaps a reflection of the added distress experienced by young people, social media recruitment during the COVID-19 lockdown period was more cost-effective. Trial RegistrationAustralian New Zealand Clinical Trials Registry ACTRN12621001092886; https://tinyurl.com/39f2pdmd; Australian New Zealand Clinical Trials Registry ACTRN12621001223820; https://tinyurl.com/bdhkvucvhttps://www.jmir.org/2025/1/e60413 |
| spellingShingle | Wu Yi Zheng Artur Shvetcov Aimy Slade Zoe Jenkins Leonard Hoon Alexis Whitton Rena Logothetis Smrithi Ravindra Stefanus Kurniawan Sunil Gupta Kit Huckvale Eileen Stech Akash Agarwal Joost Funke Kupper Stuart Cameron Jodie Rosenberg Nicholas Manoglou Manisha Senadeera Svetha Venkatesh Kon Mouzakis Rajesh Vasa Helen Christensen Jill M Newby Recruiting Young People for Digital Mental Health Research: Lessons From an AI-Driven Adaptive Trial Journal of Medical Internet Research |
| title | Recruiting Young People for Digital Mental Health Research: Lessons From an AI-Driven Adaptive Trial |
| title_full | Recruiting Young People for Digital Mental Health Research: Lessons From an AI-Driven Adaptive Trial |
| title_fullStr | Recruiting Young People for Digital Mental Health Research: Lessons From an AI-Driven Adaptive Trial |
| title_full_unstemmed | Recruiting Young People for Digital Mental Health Research: Lessons From an AI-Driven Adaptive Trial |
| title_short | Recruiting Young People for Digital Mental Health Research: Lessons From an AI-Driven Adaptive Trial |
| title_sort | recruiting young people for digital mental health research lessons from an ai driven adaptive trial |
| url | https://www.jmir.org/2025/1/e60413 |
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