Journal of medical Internet research
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J. Med. Internet Res. · Nov 2017
Using Facebook to Recruit Young Australian Men Into a Cross-Sectional Human Papillomavirus Study.
Young men can be difficult to engage in health research using traditional methods of recruitment. Social networking sites are increasingly being used to recruit participants into health research, due to their cost effectiveness, overall generalizability, and wide reach. ⋯ Using Facebook is a feasible and efficient strategy for the recruitment of men from across Australia for HPV testing. This method could be used for monitoring the impact of HPV vaccination. Additional targeting may achieve a sample that is broadly demographically representative of the Australian population. Future research should explore how the sexual risk behavior characteristics of populations recruited through Facebook compare with those of traditional recruitment methods.
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J. Med. Internet Res. · Nov 2017
Review Meta AnalysisTailored Web-Based Interventions for Pain: Systematic Review and Meta-Analysis.
Efforts have multiplied in the past decade to underline the importance of pain management. For both acute and chronic pain management, various barriers generate considerable treatment accessibility issues, thereby providing an opportunity for alternative intervention formats to be implemented. Several systematic reviews on Web-based interventions with a large emphasis on chronic pain and cognitive behavioral therapy have been recently conducted to explore the influence of these interventions on pain management However, to our knowledge, the specific contribution of tailored Web-based interventions for pain management has not been described and their effect on pain has not been evaluated. ⋯ Tailored Web-based interventions did not prove to be more efficacious than standardized Web-based interventions in terms of pain intensity, pain-related disability, anxiety, and depression. An interesting finding was that some efficacy was shown on pain catastrophizing compared with active control interventions. Considering the diversity of approaches used in tailored Web-based interventions for chronic pain management, their efficacy is yet to be explored. Moreover, their contribution to acute pain management is embryonic.
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J. Med. Internet Res. · Nov 2017
Artificial Intelligence Learning Semantics via External Resources for Classifying Diagnosis Codes in Discharge Notes.
Automated disease code classification using free-text medical information is important for public health surveillance. However, traditional natural language processing (NLP) pipelines are limited, so we propose a method combining word embedding with a convolutional neural network (CNN). ⋯ Word embedding combined with a CNN showed outstanding performance compared with traditional methods, needing very little data preprocessing. This shows that future studies will not be limited by incomplete dictionaries. A large amount of unstructured information from free-text medical writing will be extracted by automated approaches in the future, and we believe that the health care field is about to enter the age of big data.
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J. Med. Internet Res. · Nov 2017
Beyond Adoption: A New Framework for Theorizing and Evaluating Nonadoption, Abandonment, and Challenges to the Scale-Up, Spread, and Sustainability of Health and Care Technologies.
Many promising technological innovations in health and social care are characterized by nonadoption or abandonment by individuals or by failed attempts to scale up locally, spread distantly, or sustain the innovation long term at the organization or system level. ⋯ Subject to further empirical testing, NASSS could be applied across a range of technological innovations in health and social care. It has several potential uses: (1) to inform the design of a new technology; (2) to identify technological solutions that (perhaps despite policy or industry enthusiasm) have a limited chance of achieving large-scale, sustained adoption; (3) to plan the implementation, scale-up, or rollout of a technology program; and (4) to explain and learn from program failures.