BackgroundIncreasing the reach of messages disseminated through Twitter promotes the success of Twitter-based health education campaigns.ObjectiveThis study aimed to identify factors associated with reach in a dental Twitter network (1) initially and (2) sustainably at individual and network levels.MethodsWe used instructors’ and students’ Twitter usernames from a Saudi dental school in 2016-2017 and applied Gephi (a social network analysis tool) and social media analytics to calculate user and network metrics. Content analysis was performed to identify users disseminating oral health information. The study outcomes were reach at baseline and sustainably over 1.5 years. The explanatory variables were indicators of popularity (number of followers, likes, tweets retweeted by others), communication pattern (number of tweets, retweets, replies, tweeting/ retweeting oral health information or not). Multiple logistic regression models were used to investigate associations.ResultsAmong dental users, 31.8% had reach at baseline and 62.9% at the end of the study, reaching a total of 749,923 and dropping to 37,169 users at the end. At an individual level, reach was associated with the number of followers (baseline: odds ratio, OR=1.003, 95% CI=1.001-1.005 and sustainability: OR=1.002, 95% CI=1.0001-1.003), likes (baseline: OR=1.001, 95% CI=1.0001-1.002 and sustainability: OR=1.0031, 95% CI=1.0003-1.002), and replies (baseline: OR=1.02, 95% CI=1.005-1.04 and sustainability: OR=1.02, 95% CI=1.004-1.03). At the network level, users with the least followers, tweets, retweets, and replies had the greatest reach.ConclusionsReach was reduced by time. Factors increasing reach at the user level had different impact at the network level. More than one strategy is needed to maximize reach.

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Background, inappropriate administration of inotropic medications can lead to devastating and harmful effects to critically ill patients and nurses have a great responsibility for administration of these medications, this study aimed to assess nurses' performance regarding administration of inotropic medications for critically ill patients. Design: A descriptive research design was used in the study. Setting: the present study was carried out at Critical Care Units affiliated to the Suez Canal University Hospital and General Hospital in Ismailia city. Sample: A convenient sample of all staff nurses (90 nurses) included the pilot study who were working at the previously mentioned settings. Tools of data collection: The data were collected using three tools (nurses' Knowledge Assessment Questionnaire, Nurses' observational checklist and Nurses' Attitude Questionnaire. Results: The majority of nurses had an unsatisfactory level of knowledge and the majority of studied nurses had unsatisfactory total practice with nearly most of studied nurses had a positive attitude toward administering inotropic medications. Conclusion: there was a highly positive correlation between nurses' practice and nurses' knowledge and there was a positive correlation between the nurses' attitude and their knowledge and practice. Recommendations: Provide educational and training program and upgrading courses supported with evidence based practices and guidelines for appropriate administration of inotropic medications.

Dental public health is concerned with preventing oral disease, promoting oral health, and improving the quality of life through the organized efforts of society. Oral diseases including dental caries, periodontal disease, oral neoplasms, and dentofacial trauma are common, have a significant impact on individuals and wider society, and are largely preventable. While the prevalence and severity of these most common and costly dental diseases have fallen in most developed countries, oral health inequalities exist in relation to socioeconomic status, ethnicity, or region. The links between oral and general health indicate that strategies to improve both sets of problems and reduce inequalities should be integrated within the framework advocated by the Commission for the Social Determinants of Health. Of particular relevance to oral health are increasing the availability of fluoride and ensuring universal access to quality dental services. Factors influencing oral health in the future include tighter financial pressures, changes in disease prevalence, the deprofessionalization of dentistry, the role of consumerism in oral health, and the need for a better evidence base.

BACKGROUND Increasing the reach of messages disseminated through Twitter promotes the success of Twitter-based health education campaigns. OBJECTIVE This study aimed to identify factors associated with reach in a dental Twitter network (1) initially and (2) sustainably at individual and network levels. METHODS We used instructors’ and students’ Twitter usernames from a Saudi dental school in 2016-2017 and applied Gephi (a social network analysis tool) and social media analytics to calculate user and network metrics. Content analysis was performed to identify users disseminating oral health information. The study outcomes were reach at baseline and sustainably over 1.5 years. The explanatory variables were indicators of popularity (number of followers, likes, tweets retweeted by others), communication pattern (number of tweets, retweets, replies, tweeting/ retweeting oral health information or not). Multiple logistic regression models were used to investigate associations. RESULTS Among dental users, 31.8% had reach at baseline and 62.9% at the end of the study, reaching a total of 749,923 and dropping to 37,169 users at the end. At an individual level, reach was associated with the number of followers (baseline: odds ratio, OR=1.003, 95% CI=1.001-1.005 and sustainability: OR=1.002, 95% CI=1.0001-1.003), likes (baseline: OR=1.001, 95% CI=1.0001-1.002 and sustainability: OR=1.0031, 95% CI=1.0003-1.002), and replies (baseline: OR=1.02, 95% CI=1.005-1.04 and sustainability: OR=1.02, 95% CI=1.004-1.03). At the network level, users with the least followers, tweets, retweets, and replies had the greatest reach. CONCLUSIONS Reach was reduced by time. Factors increasing reach at the user level had different impact at the network level. More than one strategy is needed to maximize reach.