Crowdsourcing Treatments for Low Back Pain (bibtex)
by Hosio, Simo, Karppinen, Jaro, Takala, Esa-Pekka, Takatalo, Jani, Goncalves, Jorge, van Berkel, Niels, Konomi, Shin'ichi and Kostakos, Vassilis
Abstract:
Low back pain (LBP) is a globally common condition with no silver bullet solutions. Further, the lack of therapeutic consensus causes challenges in choosing suitable solutions to try. In this work, we crowdsourced knowledge bases on LBP treatments. The knowledge bases were used to rank and offer best-matching LBP treatments to end users. We collected two knowledge bases: one from clinical professionals and one from non-professionals. Our quantitative analysis revealed that non-professional end users perceived the best treatments by both groups as equally good. However, the worst treatments by non-professionals were clearly seen as inferior to the lowest ranking treatments by professionals. Certain treatments by professionals were also perceived significantly differently by non-professionals and professionals themselves. Professionals found our system handy for self-reflection and for educating new patients, while non-professionals appreciated the reliable decision support that also respected the non-professional opinion.
Reference:
S. Hosio, J. Karppinen, E. Takala, J. Takatalo, J. Goncalves, N. van Berkel, S. Konomi, V. Kostakos, "Crowdsourcing Treatments for Low Back Pain", in Proceedings of the ACM SIGCHI Conference on Human Factors in Computing Systems (CHI'18), 2018, 276:1-276:12.
Bibtex Entry:
@inproceedings{Hosio2018CrowdsourcingTreatments,
	Abstract = {Low back pain (LBP) is a globally common condition with no silver bullet solutions. Further, the lack of therapeutic consensus causes challenges in choosing suitable solutions to try. In this work, we crowdsourced knowledge bases on LBP treatments. The knowledge bases were used to rank and offer best-matching LBP treatments to end users. We collected two knowledge bases: one from clinical professionals and one from non-professionals. Our quantitative analysis revealed that non-professional end users perceived the best treatments by both groups as equally good. However, the worst treatments by non-professionals were clearly seen as inferior to the lowest ranking treatments by professionals. Certain treatments by professionals were also perceived significantly differently by non-professionals and professionals themselves. Professionals found our system handy for self-reflection and for educating new patients, while non-professionals appreciated the reliable decision support that also respected the non-professional opinion.},
	Author = {Hosio, Simo and Karppinen, Jaro and Takala, Esa-Pekka and Takatalo, Jani and Goncalves, Jorge and van Berkel, Niels and Konomi, Shin'ichi and Kostakos, Vassilis},
	Booktitle = {Proceedings of the ACM SIGCHI Conference on Human Factors in Computing Systems},
	Doi = {10.1145/3173574.3173850},
	Location = {CHI'18},
	Pages = {276:1-276:12},
	Title = {Crowdsourcing Treatments for Low Back Pain},
	Type = {Conference Paper},
	Url = {https://nielsvanberkel.com/files/publications/chi2018a.pdf},
	Year = {2018}}
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