How Much Is Enough? New Recommendations for Using Constructed Week Sampling in Newspaper Content Analysis of Health Stories

Luke, Douglas A.; Caburnay, Charlene; Cohen, Edward P.

doi:10.1080/19312458.2010.547823

Cited by 77 publications

(51 citation statements)

References 18 publications

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“…Because the City A and City B mainstream newspapers were published daily, we used a constructed week sampling approach to select a manageable but representative number of newspaper issues for coders to read: one constructed 7-day week (which included a randomly selected Sunday, Monday, etc.) was generated per month across the 12-month period (7×12, thus N =84 issues in each community) (38, 39). In contrast, since both communities' ethnic newspapers were published weekly, we used a census approach to select newspaper issues for coding ( N =52 issues in each community).…”

Section: Methodsmentioning

confidence: 99%

Prevalence and Framing of Health Disparities in Local Print News: Implications for Multilevel Interventions to Address Cancer Inequalities

Nagler

Bigman

Ramanadhan

et al. 2016

Cancer Epidemiology, Biomarkers &Amp; Prevention

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Background Americans remain under-informed about cancer and other health disparities and the social determinants of health (SDH). The news media may be contributing to this knowledge deficit, whether by discussing these issues narrowly or ignoring them altogether. Because local media are particularly important in influencing public opinion and support for public policies, this study examines the prevalence and framing of disparities/SDH in local mainstream and ethnic print news. Methods We conducted a multi-method content analysis of local mainstream (English-language) and ethnic (Spanish-language) print news in two lower-income cities in New England with substantial racial/ethnic minority populations. After establishing inter-coder reliability (kappa=0.63–0.88), coders reviewed the primary English- and Spanish-language newspaper in each city, identifying both disparities and non-disparities health stories published between February 2010 and January 2011. Results Local print news coverage of cancer and other health disparities was rare. Of 650 health stories published across four newspapers during the one-year study period, only 21 (3.2%) discussed disparities/SDH. Although some stories identified causes of and solutions for disparities, these were often framed in individual (e.g., poor dietary habits) rather than social contextual terms (e.g., lack of food availability/affordability). Cancer and other health stories routinely missed opportunities to discuss disparities/SDH. Conclusion Local mainstream and ethnic media may be ideal targets for multilevel interventions designed to address cancer and other health inequalities. Impact By increasing media attention to and framing of health disparities, we may observe important downstream effects on public opinion and support for structural solutions to disparities, particularly at the local level.

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Section: Methodsmentioning

confidence: 99%

Prevalence and Framing of Health Disparities in Local Print News: Implications for Multilevel Interventions to Address Cancer Inequalities

Nagler

Bigman

Ramanadhan

et al. 2016

Cancer Epidemiology, Biomarkers &Amp; Prevention

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“…To account for this variation, we used a constructed week sampling procedure (23). Specifically, we selected 1 week of randomly selected days (eg, 1 randomly selected Monday, 1 Tuesday) from May and June 2014.…”

Section: Methodsmentioning

confidence: 99%

Diabetes Topics Associated With Engagement on Twitter

Harris¹,

Mart²,

Moreland-Russell³

et al. 2015

Prev. Chronic Dis.

Self Cite

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IntroductionSocial media are widely used by the general public and by public health and health care professionals. Emerging evidence suggests engagement with public health information on social media may influence health behavior. However, the volume of data accumulating daily on Twitter and other social media is a challenge for researchers with limited resources to further examine how social media influence health. To address this challenge, we used crowdsourcing to facilitate the examination of topics associated with engagement with diabetes information on Twitter.MethodsWe took a random sample of 100 tweets that included the hashtag “#diabetes” from each day during a constructed week in May and June 2014. Crowdsourcing through Amazon’s Mechanical Turk platform was used to classify tweets into 9 topic categories and their senders into 3 Twitter user categories. Descriptive statistics and Tweedie regression were used to identify tweet and Twitter user characteristics associated with 2 measures of engagement, “favoriting” and “retweeting.”ResultsClassification was reliable for tweet topics and Twitter user type. The most common tweet topics were medical and nonmedical resources for diabetes. Tweets that included information about diabetes-related health problems were positively and significantly associated with engagement. Tweets about diabetes prevalence, nonmedical resources for diabetes, and jokes or sarcasm about diabetes were significantly negatively associated with engagement.ConclusionCrowdsourcing is a reliable, quick, and economical option for classifying tweets. Public health practitioners aiming to engage constituents around diabetes may want to focus on topics positively associated with engagement.

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“…1 Hallym University, Republic of Korea 2 University of South Carolina, USA technique should consider or control for such cyclical variations (Luke, Caburnay, & Cohen, 2011;Riffe et al, 1993).…”

Section: Research-article20182018mentioning

confidence: 99%

Evaluating Sampling Methods for Content Analysis of Twitter Data

Kim

Jang

Kim

et al. 2018

Social Media + Society

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Despite the existing evaluation of the sampling options for periodical media content, only a few empirical studies have examined whether probability sampling methods can be applicable to social media content other than simple random sampling. This article tests the efficiency of simple random sampling and constructed week sampling, by varying the sample size of Twitter content related to the 2014 South Carolina gubernatorial election. We examine how many weeks were needed to adequately represent 5 months of tweets. Our findings show that a simple random sampling is more efficient than a constructed week sampling in terms of obtaining a more efficient and representative sample of Twitter data. This study also suggests that it is necessary to produce a sufficient sample size when analyzing social media content.

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How Much Is Enough? New Recommendations for Using Constructed Week Sampling in Newspaper Content Analysis of Health Stories

Cited by 77 publications

References 18 publications

Prevalence and Framing of Health Disparities in Local Print News: Implications for Multilevel Interventions to Address Cancer Inequalities

Prevalence and Framing of Health Disparities in Local Print News: Implications for Multilevel Interventions to Address Cancer Inequalities

Diabetes Topics Associated With Engagement on Twitter

Evaluating Sampling Methods for Content Analysis of Twitter Data

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