Background The coronavirus disease (COVID-19) pandemic led to substantial public discussion. Understanding these discussions can help institutions, governments, and individuals navigate the pandemic. Objective The aim of this study is to analyze discussions on Twitter related to COVID-19 and to investigate the sentiments toward COVID-19. Methods This study applied machine learning methods in the field of artificial intelligence to analyze data collected from Twitter. Using tweets originating exclusively in the United States and written in English during the 1-month period from March 20 to April 19, 2020, the study examined COVID-19–related discussions. Social network and sentiment analyses were also conducted to determine the social network of dominant topics and whether the tweets expressed positive, neutral, or negative sentiments. Geographic analysis of the tweets was also conducted. Results There were a total of 14,180,603 likes, 863,411 replies, 3,087,812 retweets, and 641,381 mentions in tweets during the study timeframe. Out of 902,138 tweets analyzed, sentiment analysis classified 434,254 (48.2%) tweets as having a positive sentiment, 187,042 (20.7%) as neutral, and 280,842 (31.1%) as negative. The study identified 5 dominant themes among COVID-19–related tweets: health care environment, emotional support, business economy, social change, and psychological stress. Alaska, Wyoming, New Mexico, Pennsylvania, and Florida were the states expressing the most negative sentiment while Vermont, North Dakota, Utah, Colorado, Tennessee, and North Carolina conveyed the most positive sentiment. Conclusions This study identified 5 prevalent themes of COVID-19 discussion with sentiments ranging from positive to negative. These themes and sentiments can clarify the public’s response to COVID-19 and help officials navigate the pandemic.

Level I, prospective comparative outcome study.

2.

No abstract

Objective: Relatives of colorectal cancer (CRC) patients are at increased risk for the disease, yet screening rates still remain low. Guided by the Extended Parallel Process Model, we examined the impact of a personalized, remote risk communication intervention on behavioral intention and colonoscopy uptake in relatives of CRC patients, assessing the original additive model and an alternative model in which each theoretical construct contributes uniquely.Methods: We collected intention-to-screen and medical record-verified colonoscopy information on 218 individuals who received the personalized intervention.Results: Structural equation modeling showed poor main model fit (root mean square error of approximation (RMSEA) = 0.109; standardized root mean residual (SRMR) = 0.134; comparative fit index (CFI) = 0.797; Akaike information criterion (AIC) = 11,601; Bayesian information criterion (BIC) = 11,884). However, the alternative model (RMSEA = 0.070; SRMR = 0.105; CFI = 0.918; AIC = 11,186; BIC = 11,498) showed good fit. Cancer susceptibility (B = 0.319, p < 0.001) and colonoscopy self-efficacy (B = 0.364, p < 0.001) perceptions predicted intention to screen, which was significantly associated with colonoscopy uptake (B = 0.539, p < 0.001).Conclusions: Our findings provide support of the utility of Extended Parallel Process Model for designing effective interventions to motivate CRC screening in persons at increased risk when individual elements of the model are considered. Copyright © 2015 John Wiley & Sons, Ltd. Average lifetime risk for developing colorectal cancer (CRC) is approximately 5%; having a first-degree relative (FDR) with CRC increases risk twofold to eightfold [1,2]. Colonoscopy has the potential to reduce both CRC incidence and mortality through early detection and removal of precancerous polyps. The American Cancer Society and the National Comprehensive Cancer Network recommend individuals with an intermediate risk of familial CRC (i.e., CRC diagnosis in an FDR

Level I, diagnostic study.

No abstract

Background:The applicability and validity of many patient-reported outcome measures in the high-functioning population are not well understood.Purpose:To compare the psychometric properties of the modified Harris Hip Score (mHHS), the Hip Outcome Score activities of daily living subscale (HOS-ADL) and sports (HOS-sports), and the Lower Extremity Computerized Adaptive Test (LE CAT). The hypotheses was that all instruments would perform well but that the LE CAT would show superiority psychometrically because a combination of CAT and a large item bank allows for a high degree of measurement precision.Study Design:Cohort study (diagnosis); Level of evidence, 2.Methods:Data were collected from 472 advanced-age, active participants from the Huntsman World Senior Games in 2012. Validity evidences were examined through item fit, dimensionality, monotonicity, local independence, differential item functioning, person raw score to measure correlation, and instrument coverage (ie, ceiling and floor effects), and reliability evidences were examined through Cronbach alpha and person separation index.Results:All instruments demonstrated good item fit, unidimensionality, monotonicity, local independence, and person raw score to measure correlations. The HOS-ADL had high ceiling effects of 36.02%, and the mHHS had ceiling effects of 27.54%. The LE CAT had ceiling effects of 8.47%, and the HOS-sports had no ceiling effects. None of the instruments had any floor effects. The mHHS had a very low Cronbach alpha of 0.41 and an extremely low person separation index of 0.08. Reliabilities for the LE CAT were excellent and for the HOS-ADL and HOS-sports were good.Conclusion:The LE CAT showed better psychometric properties overall than the HOS-ADL, HOS-sports, and mHHS for the senior population. The mHHS demonstrated pronounced ceiling effects and poor reliabilities that should be of concern. The high ceiling effects for the HOS-ADL were also of concern. The LE CAT was superior in all psychometric aspects examined in this study. Future research should investigate the LE CAT for wider use in different populations.