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      Applying Sparse Machine Learning Methods to Twitter: Analysis of the 2012 Change in Pap Smear Guidelines. A Sequential Mixed-Methods Study

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          Abstract

          Background

          It is difficult to synthesize the vast amount of textual data available from social media websites. Capturing real-world discussions via social media could provide insights into individuals’ opinions and the decision-making process.

          Objective

          We conducted a sequential mixed methods study to determine the utility of sparse machine learning techniques in summarizing Twitter dialogues. We chose a narrowly defined topic for this approach: cervical cancer discussions over a 6-month time period surrounding a change in Pap smear screening guidelines.

          Methods

          We applied statistical methodologies, known as sparse machine learning algorithms, to summarize Twitter messages about cervical cancer before and after the 2012 change in Pap smear screening guidelines by the US Preventive Services Task Force (USPSTF). All messages containing the search terms “cervical cancer,” “Pap smear,” and “Pap test” were analyzed during: (1) January 1–March 13, 2012, and (2) March 14–June 30, 2012. Topic modeling was used to discern the most common topics from each time period, and determine the singular value criterion for each topic. The results were then qualitatively coded from top 10 relevant topics to determine the efficiency of clustering method in grouping distinct ideas, and how the discussion differed before vs. after the change in guidelines .

          Results

          This machine learning method was effective in grouping the relevant discussion topics about cervical cancer during the respective time periods (~20% overall irrelevant content in both time periods). Qualitative analysis determined that a significant portion of the top discussion topics in the second time period directly reflected the USPSTF guideline change (eg, “New Screening Guidelines for Cervical Cancer”), and many topics in both time periods were addressing basic screening promotion and education (eg, “It is Cervical Cancer Awareness Month! Click the link to see where you can receive a free or low cost Pap test.”)

          Conclusions

          It was demonstrated that machine learning tools can be useful in cervical cancer prevention and screening discussions on Twitter. This method allowed us to prove that there is publicly available significant information about cervical cancer screening on social media sites. Moreover, we observed a direct impact of the guideline change within the Twitter messages.

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          Most cited references19

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          Reaching the parts other methods cannot reach: an introduction to qualitative methods in health and health services research.

          C Pope, N Mays (1995)
          Qualitative research methods have a long history in the social sciences and deserve to be an essential component in health and health services research. Qualitative and quantitative approaches to research tend to be portrayed as antithetical; the aim of this series of papers is to show the value of a range of qualitative techniques and how they can complement quantitative research.
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            Social Media Use in the United States: Implications for Health Communication

            Background Given the rapid changes in the communication landscape brought about by participative Internet use and social media, it is important to develop a better understanding of these technologies and their impact on health communication. The first step in this effort is to identify the characteristics of current social media users. Up-to-date reporting of current social media use will help monitor the growth of social media and inform health promotion/communication efforts aiming to effectively utilize social media. Objective The purpose of the study is to identify the sociodemographic and health-related factors associated with current adult social media users in the United States. Methods Data came from the 2007 iteration of the Health Information National Trends Study (HINTS, N = 7674). HINTS is a nationally representative cross-sectional survey on health-related communication trends and practices. Survey respondents who reported having accessed the Internet (N = 5078) were asked whether, over the past year, they had (1) participated in an online support group, (2) written in a blog, (3) visited a social networking site. Bivariate and multivariate logistic regression analyses were conducted to identify predictors of each type of social media use. Results Approximately 69% of US adults reported having access to the Internet in 2007. Among Internet users, 5% participated in an online support group, 7% reported blogging, and 23% used a social networking site. Multivariate analysis found that younger age was the only significant predictor of blogging and social networking site participation; a statistically significant linear relationship was observed, with younger categories reporting more frequent use. Younger age, poorer subjective health, and a personal cancer experience predicted support group participation. In general, social media are penetrating the US population independent of education, race/ethnicity, or health care access. Conclusions Recent growth of social media is not uniformly distributed across age groups; therefore, health communication programs utilizing social media must first consider the age of the targeted population to help ensure that messages reach the intended audience. While racial/ethnic and health status–related disparities exist in Internet access, among those with Internet access, these characteristics do not affect social media use. This finding suggests that the new technologies, represented by social media, may be changing the communication pattern throughout the United States.
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              Screening for cervical cancer: U.S. Preventive Services Task Force recommendation statement.

              Update of the 2003 U.S. Preventive Services Task Force (USPSTF) recommendation statement on screening for cervical cancer. The USPSTF reviewed new evidence on the comparative test performance of liquid-based cytology and the benefits and harms of human papillomavirus (HPV) testing as a stand-alone test or in combination with cytology. In addition to the systematic evidence review, the USPSTF commissioned a decision analysis to help clarify the age at which to begin and end screening, the optimal interval for screening, and the relative benefits and harms of different strategies for screening (such as cytology and co-testing). This recommendation statement applies to women who have a cervix, regardless of sexual history. This recommendation statement does not apply to women who have received a diagnosis of a high-grade precancerous cervical lesion or cervical cancer, women with in utero exposure to diethylstilbestrol, or women who are immunocompromised (such as those who are HIV positive).The USPSTF recommends screening for cervical cancer in women aged 21 to 65 years with cytology (Papanicolaou smear) every 3 years or, for women aged 30 to 65 years who want to lengthen the screening interval, screening with a combination of cytology and HPV testing every 5 years. See the Clinical Considerations for discussion of cytology method, HPV testing, and screening interval (A recommendation).The USPSTF recommends against screening for cervical cancer in women younger than age 21 years (D recommendation).The USPSTF recommends against screening for cervical cancer in women older than age 65 years who have had adequate prior screening and are not otherwise at high risk for cervical cancer. See the Clinical Considerations for discussion of adequacy of prior screening and risk factors (D recommendation).The USPSTF recommends against screening for cervical cancer in women who have had a hysterectomy with removal of the cervix and who do not have a history of a high-grade precancerous lesion (cervical intraepithelial neoplasia grade 2 or 3) or cervical cancer (D recommendation).The USPSTF recommends against screening for cervical cancer with HPV testing, alone or in combination with cytology, in women younger than age 30 years (D recommendation).
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                Author and article information

                Contributors
                Journal
                JMIR Public Health Surveill
                JMIR Public Health Surveill
                JPH
                JMIR Public Health and Surveillance
                Gunther Eysenbach (JMIR Publications Inc., Toronto, Canada )
                2369-2960
                Jan-Jun 2016
                10 June 2016
                : 2
                : 1
                : e21
                Affiliations
                [1] 1Center for Vulnerable Populations & Division of General Internal Medicine at the Zuckerberg San Francisco General Hospital Department of Medicine University of California San Francisco San Francisco, CAUnited States
                [2] 2Department of Electrical Engineering and Computer Science University of California Berkeley Berkeley, CAUnited States
                Author notes
                Corresponding Author: Courtney Rees Lyles courtney.lyles@ 123456ucsf.edu
                Author information
                http://orcid.org/0000-0002-1111-8595
                Article
                v2i1e21
                10.2196/publichealth.5308
                4920957
                27288093
                d8a08a52-c128-4925-a193-47a7e41d9bee
                ©Courtney Rees Lyles, Andrew Godbehere, Gem Le, Laurent El Ghaoui, Urmimala Sarkar. Originally published in JMIR Public Health and Surveillance (http://publichealth.jmir.org), 10.06.2016.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Public Health and Surveillance, is properly cited. The complete bibliographic information, a link to the original publication on http://publichealth.jmir.org, as well as this copyright and license information must be included.

                History
                : 30 October 2015
                : 24 January 2016
                : 18 February 2016
                : 28 March 2016
                Categories
                Original Paper
                Original Paper

                twitter,machine learning,social media,cervical cancer,qualitative research

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