scholarly journals A Peer-Led Social Media Intervention to Improve Interest in Research Careers Among Urban Youth: Mixed Methods Study

10.2196/16392 ◽  
2020 ◽  
Vol 6 (1) ◽  
pp. e16392
Author(s):  
Christianah Ogunleye ◽  
Jeanne M Farnan ◽  
Shannon K Martin ◽  
Audrey Tanksley ◽  
Samantha Ngooi ◽  
...  

Background Novel methods to boost interest in scientific research careers among minority youth are largely unexplored. Social media offers a unique avenue toward influencing teen behavior and attitudes, and can therefore be utilized to stimulate interest in clinical research. Objective The aim of this study was to engage high-achieving minority youth enrolled in a science pipeline program to develop a targeted social media marketing campaign for boosting interest in clinical research careers among their peers. Methods Students enrolled in the Training Early Achievers for Careers in Health program conducted focus groups in their communities to inform themes that best promote clinical research. They then scripted, storyboarded, and filmed a short video to share on social media with a campaign hashtag. Additionally, each student enrolled peers from their social circle to be subjects of the study. Subjects were sent a Career Orientation Survey at baseline to assess preliminary interest in clinical research careers and again after the campaign to assess how they saw the video, their perceptions of the video, and interest in clinical research careers after watching the video. Subjects who did not see the video through the online campaign were invited to watch the video via a link on the postsurvey. Interest change scores were calculated using differences in Likert-scale responses to the question “how interested are you in a career in clinical research?” An ordinal logistic regression model was used to test the association between watching a peer-shared video, perception of entertainment, and interest change score controlling for underrepresented minorities in medicine status (Black, American Indian/Alaska Native, Native Hawaiian, or Pacific Islander), gender, and baseline interest in medical or clinical research careers. Results From 2014 to 2017, 325 subjects were enrolled as part of 4 distinct campaigns: #WhereScienceMeetsReality, #RedefiningResearch, #DoYourResearch, and #LifeWithoutResearch. Over half (n=180) of the subjects watched the video via the campaign, 227/295 (76.9%) found the video entertaining, and 92/325 (28.3%) demonstrated baseline interest in clinical research. The ordinal logistic regression model showed that subjects who viewed the video from a peer (odds ratio [OR] 1.56, 95% CI 1.00-2.44, P=.05) or found the video entertaining (OR 1.36, 95% CI 1.01-1.82, P=.04) had greater odds of increasing interest in a clinical research career. Subjects with a higher baseline interest in medicine (OR 1.55, 95% CI 1.28-1.87, P<.001) also had greater odds of increasing their interest in clinical research. Conclusions The spread of authentic and relevant peer-created messages via social media can increase interest in clinical research careers among diverse teens. Peer-driven social media campaigns should be explored as a way to effectively recruit minority youth into scientific research careers.

2019 ◽  
Author(s):  
Christianah Ogunleye ◽  
Jeanne M Farnan ◽  
Shannon K Martin ◽  
Audrey Tanksley ◽  
Samantha Ngooi ◽  
...  

BACKGROUND Novel methods to boost interest in scientific research careers among minority youth are largely unexplored. Social media offers a unique avenue toward influencing teen behavior and attitudes, and can therefore be utilized to stimulate interest in clinical research. OBJECTIVE The aim of this study was to engage high-achieving minority youth enrolled in a science pipeline program to develop a targeted social media marketing campaign for boosting interest in clinical research careers among their peers. METHODS Students enrolled in the Training Early Achievers for Careers in Health program conducted focus groups in their communities to inform themes that best promote clinical research. They then scripted, storyboarded, and filmed a short video to share on social media with a campaign hashtag. Additionally, each student enrolled peers from their social circle to be subjects of the study. Subjects were sent a Career Orientation Survey at baseline to assess preliminary interest in clinical research careers and again after the campaign to assess how they saw the video, their perceptions of the video, and interest in clinical research careers after watching the video. Subjects who did not see the video through the online campaign were invited to watch the video via a link on the postsurvey. Interest change scores were calculated using differences in Likert-scale responses to the question “how interested are you in a career in clinical research?” An ordinal logistic regression model was used to test the association between watching a peer-shared video, perception of entertainment, and interest change score controlling for underrepresented minorities in medicine status (Black, American Indian/Alaska Native, Native Hawaiian, or Pacific Islander), gender, and baseline interest in medical or clinical research careers. RESULTS From 2014 to 2017, 325 subjects were enrolled as part of 4 distinct campaigns: #WhereScienceMeetsReality, #RedefiningResearch, #DoYourResearch, and #LifeWithoutResearch. Over half (n=180) of the subjects watched the video via the campaign, 227/295 (76.9%) found the video entertaining, and 92/325 (28.3%) demonstrated baseline interest in clinical research. The ordinal logistic regression model showed that subjects who viewed the video from a peer (odds ratio [OR] 1.56, 95% CI 1.00-2.44, <i>P</i>=.05) or found the video entertaining (OR 1.36, 95% CI 1.01-1.82, <i>P</i>=.04) had greater odds of increasing interest in a clinical research career. Subjects with a higher baseline interest in medicine (OR 1.55, 95% CI 1.28-1.87, <i>P</i>&lt;.001) also had greater odds of increasing their interest in clinical research. CONCLUSIONS The spread of authentic and relevant peer-created messages via social media can increase interest in clinical research careers among diverse teens. Peer-driven social media campaigns should be explored as a way to effectively recruit minority youth into scientific research careers.


2012 ◽  
Vol 460 ◽  
pp. 393-397 ◽  
Author(s):  
Peng Fei Mu ◽  
Dong Ling Zhang ◽  
Xiao Mei Xu ◽  
Yang Liu

It presents a proposed method for the development of quality evaluation and classification for material products, and shows the application of the ordinal logistic regression model and its advantages. It involved several steps: applying the linguistic information processing method, building the ordinal logistic regression model, differentiating and analyzing the quality evaluation to reach the quality classification result


2020 ◽  
Vol 12 (8) ◽  
pp. 3076
Author(s):  
Ting Xu ◽  
Yanjun Hao ◽  
Shichao Cui ◽  
Xingqi Wu ◽  
Zhishun Zhang ◽  
...  

The focus of this paper is the crash risk assessment of off-ramps in Xi’an. The time-to-collision (TTC) is used for the measurement and cross-comparison of the crash risk of each location. Five sites from the urban expressway in Xi’an were selected to explore the TTC distribution. An unmanned aerial vehicle and a camera were used to collect traffic flow data for 20 min at each site. The parameters, including speed, deceleration rate, truck percentage, traffic volume, and vehicle trajectories, were extracted from video images. The TTCs were calculated for each vehicle. The Gaussian mixture model (GMM) was proposed to predict the TTC probability density functions (PDFs) and cumulative density functions (CDFs) for five sites. The Kolmogorov–Smirnov (K-S) test indicated that the samples followed the estimated GMM distribution. The relationship between the crash risk level and influencing factors was studied by an ordinal logistic regression model and a naive Bayesian model. The results showed that the naive Bayesian model had an accuracy of 86.71%, while the ordinal logistic regression model had an accuracy of 84.81%. The naive Bayesian model outperformed the ordinal logistic regression model, and it could be applied to the real-time collision warning system.


Sign in / Sign up

Export Citation Format

Share Document