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BackgroundPublic health agencies are actively using social media, including Twitter. In the public health and nonprofit sectors, Twitter has been limited to one-way communication. Two-way, interactive communication on Twitter has the potential to enhance organizational relationships with followers and help organizations achieve their goals by increasing communication and dialog between the organization and its followers. Research shows that nonprofit organizations use Twitter for three main functions: information sharing, community building, and action. ObjectiveIt is not known whether state health departments are using Twitter primarily for one-way information sharing or if they are trying to engage followers to build relationships and promote action. The purpose of this research was to discover what the primary function of Twitter use is among state health departments in the United States and whether this is similar to or different from nonprofit organizations. MethodsA complete list of “tweets” made by each state health department account was obtained using the Twitter application programming interface. We randomly sampled 10% of each state health department’s tweets. Four research assistants hand-coded the tweets’ primary focus (organization centric or personal health information centric) and then the subcategories of information dissemination, engagement, or action. Research assistants coded each tweet for interactivity, sophistication, and redirects to another website. Data were analyzed using SPSS version 20. ResultsThere were 4221 tweets from 39 state health departments. There was no statistically significant difference in the number of tweets made by a state health department and the state population density (P=.25). The majority of tweets focused on personal health topics (69.37%, 2928/4221) while one-third were tweets about the organization (29.14% , 1230/4221). The main function of organization-based tweets was engagement through conversations to build community (65.77%, 809/1236). These engagement-related tweets were primarily recognition of other organizations’ events (43.6%, 353/809) and giving thanks and recognition (21.4%, 173/809). Nearly all of the personal health information-centric tweets involved general public health information (92.10%, 1399/1519) and 79.03% (3336/4221) of tweets directed followers to another link for more information. ConclusionsThis is the first study to assess the purpose of public health tweets among state health departments. State health departments are using Twitter as a one-way communication tool, with tweets focused primarily on personal health. A state health department Twitter account may not be the primary health information source for individuals. Therefore, state health departments should reconsider their focus on personal health tweets and envision how they can use Twitter to develop relationships with community agencies and partners. In order to realize the potential of Twitter to establish relationships and develop connections, more two-way communication and interaction are essential.

BackgroundPrescription drug abuse has become a major public health problem. Relationships and social context are important contributing factors. Social media provides online channels for people to build relationships that may influence attitudes and behaviors. ObjectiveTo determine whether people who show signs of prescription drug abuse connect online with others who reinforce this behavior, and to observe the conversation and engagement of these networks with regard to prescription drug abuse. MethodsTwitter statuses mentioning prescription drugs were collected from November 2011 to November 2012. From this set, 25 Twitter users were selected who discussed topics indicative of prescription drug abuse. Social circles of 100 people were discovered around each of these Twitter users; the tweets of the Twitter users in these networks were collected and analyzed according to prescription drug abuse discussion and interaction with other users about the topic. ResultsFrom November 2011 to November 2012, 3,389,771 mentions of prescription drug terms were observed. For the 25 social circles (n=100 for each circle), on average 53.96% (SD 24.3) of the Twitter users used prescription drug terms at least once in their posts, and 37.76% (SD 20.8) mentioned another Twitter user by name in a post with a prescription drug term. Strong correlation was found between the kinds of drugs mentioned by the index user and his or her network (mean r=0.73), and between the amount of interaction about prescription drugs and a level of abusiveness shown by the network (r=0.85, P

BackgroundSocial media offers unprecedented opportunities for public health to engage audiences in conversations and collaboration that could potentially lead to improved health conditions. While there is some evidence that local health departments (LHDs) are using social media and Twitter in particular, little is known about how Twitter is used by LHDs and how they use it to engage followers versus disseminating one-way information. ObjectiveTo examine how LHDs use Twitter to share information, engage with followers, and promote action, as well as to discover differences in Twitter use among LHDs by size of population served. MethodsThe Twitter accounts for 210 LHDs were stratified into three groups based on size of population served (n=69 for less than 100,000; n=89 for 100,000-499,999; n=52 for 500,000 or greater). A sample of 1000 tweets was obtained for each stratum and coded as being either about the organization or about personal-health topics. Subcategories for organization included information, engagement, and action. Subcategories for personal health included information and action. ResultsOf all LHD tweets (n=3000), 56.1% (1682/3000) related to personal health compared with 39.5% (1186/3000) that were about the organization. Of the personal-health tweets, 58.5% (984/1682) involved factual information and 41.4% (697/1682) encouraged action. Of the organization-related tweets, 51.9% (615/1186) represented one-way communication about the organization and its events and services, 35.0% (416/1186) tried to engage followers in conversation, and 13.3% (158/1186) encouraged action to benefit the organization (eg, attend events). Compared with large LHDs, small LHDs were more likely to post tweets about their organization (Cramer’s V=0.06) but were less likely to acknowledge events and accomplishments of other organizations (χ2=12.83, P=.02, Cramer’s V=0.18). Small LHDs were also less likely to post personal health-related tweets (Cramer’s V=0.08) and were less likely to post tweets containing suggestions to take action to modify their lifestyle. While large LHDs were more likely to post engagement-related tweets about the organization (Cramer’s V=0.12), they were less likely to ask followers to take action that would benefit the organization (χ2=7.59, P=.02. Cramer’s V=0.08). While certain associations were statistically significant, the Cramer’s V statistic revealed weak associations. ConclusionsTwitter is being adopted by LHDs, but its primary use involves one-way communication on personal-health topics as well as organization-related information. There is also evidence that LHDs are starting to use Twitter to engage their audiences in conversations. As public health transitions to more dialogic conversation and engagement, Twitter’s potential to help form partnerships with audiences and involve them as program participants may lead to action for improved health.

BackgroundAdderall is the most commonly abused prescription stimulant among college students. Social media provides a real-time avenue for monitoring public health, specifically for this population. ObjectiveThis study explores discussion of Adderall on Twitter to identify variations in volume around college exam periods, differences across sets of colleges and universities, and commonly mentioned side effects and co-ingested substances. MethodsPublic-facing Twitter status messages containing the term “Adderall” were monitored from November 2011 to May 2012. Tweets were examined for mention of side effects and other commonly abused substances. Tweets from likely students containing GPS data were identified with clusters of nearby colleges and universities for regional comparison. Results213,633 tweets from 132,099 unique user accounts mentioned “Adderall.” The number of Adderall tweets peaked during traditional college and university final exam periods. Rates of Adderall tweeters were highest among college and university clusters in the northeast and south regions of the United States. 27,473 (12.9%) mentioned an alternative motive (eg, study aid) in the same tweet. The most common substances mentioned with Adderall were alcohol (4.8%) and stimulants (4.7%), and the most common side effects were sleep deprivation (5.0%) and loss of appetite (2.6%). ConclusionsTwitter posts confirm the use of Adderall as a study aid among college students. Adderall discussions through social media such as Twitter may contribute to normative behavior regarding its abuse.

BackgroundTwitter provides various types of location data, including exact Global Positioning System (GPS) coordinates, which could be used for infoveillance and infodemiology (ie, the study and monitoring of online health information), health communication, and interventions. Despite its potential, Twitter location information is not well understood or well documented, limiting its public health utility. ObjectiveThe objective of this study was to document and describe the various types of location information available in Twitter. The different types of location data that can be ascertained from Twitter users are described. This information is key to informing future research on the availability, usability, and limitations of such location data. MethodsLocation data was gathered directly from Twitter using its application programming interface (API). The maximum tweets allowed by Twitter were gathered (1% of the total tweets) over 2 separate weeks in October and November 2011. The final dataset consisted of 23.8 million tweets from 9.5 million unique users. Frequencies for each of the location options were calculated to determine the prevalence of the various location data options by region of the world, time zone, and state within the United States. Data from the US Census Bureau were also compiled to determine population proportions in each state, and Pearson correlation coefficients were used to compare each state’s population with the number of Twitter users who enable the GPS location option. ResultsThe GPS location data could be ascertained for 2.02% of tweets and 2.70% of unique users. Using a simple text-matching approach, 17.13% of user profiles in the 4 continental US time zones were able to be used to determine the user’s city and state. Agreement between GPS data and data from the text-matching approach was high (87.69%). Furthermore, there was a significant correlation between the number of Twitter users per state and the 2010 US Census state populations (r ≥ 0.97, P

Minimally invasive delivery of peptide and protein molecules represents a significant opportunity for product differentiation and value creation versus standard injectable routes of administration. One such technology utilizes microneedle (MN) patches and it has made considerable clinical advances in systemic delivery of potent macromolecules and vaccines. A sub-class of this technology has focused on preparation of solid dense MN arrays followed by precision formulation coating on the tips of the MN. The objective of this study was to develop a drug product using the MN technology that has similar bioperformance when compared to subcutaneous route of delivery and can provide improved stability under storage. Therapeutic peptide (Peptide A, Merck & Co., Inc., Kenilworth, NJ, USA) is being developed as a subcutaneous injection for chronic dosing with a submilligram estimated therapeutic dose. Peptide A has chemical and physical stability challenges in solution and this led to exploration of a viable drug product which could provide therapeutic dosages while overcoming the stability issues seen with the compound. This work focused on developing a coated solid microstructure transdermal system (sMTS) for Peptide A followed by detailed in vitro and preclinical evaluation for two different coating formulations. Based on initial assessment, ~250 μg of Peptide A could be coated with precision on a 1.27cm2 patch which contained 316 MN's. The delivery from these systems was achieved with absolute bioavailability being similar to the subcutaneous delivery (88% and 74% for coated sMTS 1 & 2 and 75% for subcutaneous delivery). Stability of Peptide A was also found to be significantly improved when coated on the sMTS system with minimal degradation recorded at room temperature storage as compared to the subcutaneous liquid formulation. Additionally, skin irritation (on pig skin) was also measured in this study and it was found to be minimal and self-resolving. This evaluation provided a viable option for developing a drug product with improved stability and successful delivery of the investigated molecule. [ABSTRACT FROM AUTHOR]

The maintenance of the high-quality regional water supply to the growing Inland Empire of California through the desalting of groundwater at the treatment plants of the Chino Desalters Project is described.

We examine the problem of identifying social circles, or sets of cohesive and mutually aware nodes surrounding an initial query set, in directed graphs where the complete graph is not known beforehand. This problem differs from local community mining, in that the query set defines the circle of interest. We explicitly handle edge direction, as in many cases relationships are not symmetric, and focus on the local context because many real-world graphs cannot be feasibly known. We outline several issues that are unique to this context, introduce a quality function to measure the value of including a particular node in an emerging social circle, and describe a greedy social circle discovery algorithm. We demonstrate the effectiveness of this approach on artificial benchmarks, large networks with topical community labels, and several real-world case studies. [ABSTRACT FROM AUTHOR]

Traditional association rule mining algorithms often have difficulty handling questions that are implicitly related, producing rules that are very accurate but are so obvious as to be completely useless to researchers. This problem is compounded by the fact that standard objective measures for interestingness often capture the wrong information and are maximized by these obvious rules. We propose an enhancement to standard association rule mining that uses clustering to identify related questions to pre-prune rules involving similar questions, which are less likely to be subjectively interesting. This enhancement reduces the search space of rules, improving the algorithm's efficiency. In addition, the resulting rule list has a higher concentration of diverse rules, more likely to be useful to researchers. We demonstrate this improvement relative to existing algorithms on two real-world, public health questionnaires. [ABSTRACT FROM AUTHOR]