BackgroundAnalysing public opinions on HPV vaccines on social media using machine learning based approaches will help us understand the reasons behind the low vaccine coverage and come up with corresponding strategies to improve vaccine uptake.ObjectiveTo propose a machine learning system that is able to extract comprehensive public sentiment on HPV vaccines on Twitter with satisfying performance.MethodWe collected and manually annotated 6,000 HPV vaccines related tweets as a gold standard. SVM model was chosen and a hierarchical classification method was proposed and evaluated. Additional feature sets evaluation and model parameters optimization was done to maximize the machine learning model performance.ResultsA hierarchical classification scheme that contains 10 categories was built to access public opinions toward HPV vaccines comprehensively. A 6,000 annotated tweets gold corpus with Kappa annotation agreement at 0.851 was created and made public available. The hierarchical classification model with optimized feature sets and model parameters has increased the micro-averaging and macro-averaging F score from 0.6732 and 0.3967 to 0.7442 and 0.5883 respectively, compared with baseline model.ConclusionsOur work provides a systematical way to improve the machine learning model performance on the highly unbalanced HPV vaccines related tweets corpus. Our system can be further applied on a large tweets corpus to extract large-scale public opinion towards HPV vaccines.Electronic supplementary materialThe online version of this article (doi:10.1186/s13326-017-0120-6) contains supplementary material, which is available to authorized users.
Background: To learn from errors, electronic patient safety event reporting systems (e-reporting systems) have been widely adopted to collect medical incidents from the frontline practitioners in US hospitals. However, two issues of underreporting and low-quality of reports pervade and thus the system effectiveness remains dubious.
Background
Early adolescent unintended pregnancy and sexually transmitted infection prevention are significant public health challenges in the United States. Parental influence can help adolescents make responsible and informed sexual health decisions toward delayed sexual debut; yet parents often feel ill equipped to communicate about sex-related topics. Intergenerational games offer a potential strategy to provide life skills training to young adolescents (aged 11-14 years) while engaging them and their parents in communication about sexual health.
Objective
This study aims to describe the development of a web-based online sexual health intergenerational adventure game, the Secret of Seven Stones (SSS), using an intervention mapping (IM) approach for developing theory- and evidence-based interventions.
Methods
We followed the IM development steps to describe a theoretical and empirical model for young adolescent sexual health behavior, define target behaviors and change objectives, identify theory-based methods and practical applications to inform design and function, develop and test a prototype of 2 game levels to assess feasibility before developing the complete 18-level game, draft an implementation plan that includes a commercial dissemination strategy, and draft an evaluation plan including a study design for a randomized controlled trial efficacy trial of SSS.
Results
SSS comprised an adventure game for young adolescent skills training delivered via a desktop computer, a text-based notification system to provide progress updates for parents and cues to initiate dialogue with their 11- to 14-year-old child, and a website for parent skills training and progress monitoring. Formative prototype testing demonstrated feasibility for in-home use and positive usability ratings.
Conclusions
The SSS intergenerational game provides a unique addition to the limited cadre of home-based programs that facilitate parent involvement in influencing young adolescent behaviors and reducing adolescent sexual risk taking. The IM framework provided a logical and thorough approach to development and testing, attentive to the need for theoretical and empirical foundations in serious games for health.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.