Online Healthcare Communities Research Articles

The Hidden Cost of Transitioning to a Paid Service: The Effect of Unexpected Revealing of New Patient Prospects on Physicians’ Service Quality in Online Healthcare Communities

In this research, we seek to understand how physicians would respond to a policy change, i.e. promoting paid consultations over free services, on an online platform. We found that, contrary to general expectations, physicians’ service quality increased for free consultations and decreased for paid consultations. Our findings have important theoretical and practical implications.

Identifying the Underlying Factors Associated With Patients' Attitudes Toward Antidepressants: Qualitative and Quantitative Analysis of Patient Drug Reviews.

BackgroundNonadherence to antidepressants is a major obstacle to deriving antidepressants’ therapeutic benefits, resulting in significant burdens on the individuals and the health care system. Several studies have shown that nonadherence is weakly associated with personal and clinical variables but strongly associated with patients’ beliefs and attitudes toward medications. Patients’ drug review posts in online health care communities might provide a significant insight into patients’ attitude toward antidepressants and could be used to address the challenges of self-report methods such as patients’ recruitment.ObjectiveThe aim of this study was to use patient-generated data to identify factors affecting the patient’s attitude toward 4 antidepressants drugs (sertraline [Zoloft], escitalopram [Lexapro], duloxetine [Cymbalta], and venlafaxine [Effexor XR]), which in turn, is a strong determinant of treatment nonadherence. We hypothesized that clinical variables (drug effectiveness; adverse drug reactions, ADRs; perceived distress from ADRs, ADR-PD; and duration of treatment) and personal variables (age, gender, and patients’ knowledge about medications) are associated with patients’ attitude toward antidepressants, and experience of ADRs and drug ineffectiveness are strongly associated with negative attitude.MethodsWe used both qualitative and quantitative methods to analyze the dataset. Patients’ drug reviews were randomly selected from a health care forum called askapatient. The Framework method was used to build the analytical framework containing the themes for developing structured data from the qualitative drug reviews. Then, 4 annotators coded the drug reviews at the sentence level using the analytical framework. After managing missing values, we used chi-square and ordinal logistic regression to test and model the association between variables and attitude.ResultsA total of 892 reviews posted between February 2001 and September 2016 were analyzed. Most of the patients were females (680/892, 76.2%) and aged less than 40 years (540/892, 60.5%). Patient attitude was significantly (P<.001) associated with experience of ADRs, ADR-PD, drug effectiveness, perceived lack of knowledge, experience of withdrawal, and duration of usage, whereas oth age (F4,874=0.72, P=.58) and gender (χ24=2.7, P=.21) were not found to be associated with patient attitudes. Moreover, modeling the relationship between variables and attitudes showed that drug effectiveness and perceived distress from adverse drug reactions were the 2 most significant factors affecting patients’ attitude toward antidepressants.ConclusionsPatients’ self-report experiences of medications in online health care communities can provide a direct insight into the underlying factors associated with patients’ perceptions and attitudes toward antidepressants. However, it cannot be used as a replacement for self-report methods because of the lack of information for some of the variables, colloquial language, and the unstructured format of the reports.

Value co‐creation in online healthcare communities: The impact of patients’ reference frames on cure and care

AbstractThe gradual transition of health care toward businesses during the past 50 years has converted passive patients into active customers. In our digital society, patients increasingly use online health communities to satisfy complex needs that healthcare professionals leave unmet, including the creation of cure‐oriented (i.e., functional) and care‐oriented (i.e., emotion) value. This research investigates patients’ reference frames (self versus other) as an information processing mechanism and their impact on value creation in online communities. The analysis of 1,687 online postings of a leading healthcare platform shows that self‐referencing is typical for information obtained through an individualistic, patient–doctor encounter; other‐referencing emerges when patients focus on the needs of their peers. Information gathered through the patient–doctor encounter and processed with a self‐referencing frame accordingly enhances cure‐related value, but limits care‐oriented value co‐creation. Other‐referencing does exactly the opposite: it creates a barrier to cure‐related value, but stimulates care‐related value. A patient's experience with the community largely moderates the impact of both self‐ and other‐referencing on cure‐ and care‐related value. These findings show that online health communities can identify and address unmet patient needs, but healthcare professionals still play a critical role in terms of ensuring information quality in online health communities.

Patient Continued Use of Online Health Care Communities: Web Mining of Patient-Doctor Communication.

BackgroundIn practice, online health communities have passed the adoption stage and reached the diffusion phase of development. In this phase, patients equipped with knowledge regarding the issues involved in health care are capable of switching between different communities to maximize their online health community activities. Online health communities employ doctors to answer patient questions, and high quality online health communities are more likely to be acknowledged by patients. Therefore, the factors that motivate patients to maintain ongoing relationships with online health communities must be addressed. However, this has received limited scholarly attention.ObjectiveThe purpose of this study was to identify the factors that drive patients to continue their use of online health communities where doctor-patient communication occurs. This was achieved by integrating the information system success model with online health community features.MethodsA Web spider was used to download and extract data from one of the most authoritative Chinese online health communities in which communication occurs between doctors and patients. The time span analyzed in this study was from January 2017 to March 2017. A sample of 469 valid anonymous patients with 9667 posts was obtained (the equivalent of 469 respondents in survey research). A combination of Web mining and structural equation modeling was then conducted to test the research hypotheses.ResultsThe results show that the research framework for integrating the information system success model and online health community features contributes to our understanding of the factors that drive patients' relationships with online health communities. The primary findings are as follows: (1) perceived usefulness is found to be significantly determined by three exogenous variables (ie, social support, information quality, and service quality; R2=0.88). These variables explain 87.6% of the variance in perceived usefulness of online health communities; (2) similarly, patient satisfaction was found to be significantly determined by the three variables listed above (R2=0.69). These variables explain 69.3% of the variance seen in patient satisfaction; (3) continuance use (dependent variable) is significantly influenced by perceived usefulness and patient satisfaction (R2=0.93). That is, the combined effects of perceived usefulness and patient satisfaction explain 93.4% of the variance seen in continuance use; and (4) unexpectedly, individual literacy had no influence on perceived usefulness and satisfaction of patients using online health communities.ConclusionsFirst, this study contributes to the existing literature on the continuance use of online health communities using an empirical approach. Second, an appropriate metric was developed to assess constructs related to the proposed research model. Additionally, a Web spider enabled us to acquire objective data relatively easily and frequently, thereby overcoming a major limitation of survey techniques.

Understanding a Nonlinear Causal Relationship Between Rewards and Physicians' Contributions in Online Health Care Communities: Longitudinal Study.

BackgroundThe online health care community is not just a place for the public to share physician reviews or medical knowledge, but also a physician-patient communication platform. The medical resources of developing countries are relatively inadequate, and the online health care community is a potential solution to alleviate the phenomenon of long hospital queues and the lack of medical resources in rural areas. However, the success of the online health care community depends on online contributions by physicians.ObjectiveThe aim of this study is to examine the effect of incentive mechanisms on physician’s online contribution behavior in the online health community. We addressed the following questions: (1) from which specialty area are physicians more likely to participate in online health care community activities, (2) what are the factors affecting physician online contributions, and (3) do incentive mechanisms, including psychological and material rewards, result in differences of physician online contributions?MethodsWe designed a longitudinal study involving a data sample in three waves. All data were collected from the Good Doctor website, which is the largest online health care community in China. We first used descriptive statistics to investigate the physician online contribution behavior in its entirety. Then multiple linear and quadratic regression models were applied to verify the causal relationship between rewards and physician online contribution.ResultsOur sample included 40,300 physicians from 3607 different hospitals, 10 different major specialty areas, and 31 different provinces or municipalities. Based on the multiple quadratic regression model, we found that the coefficients of the control variables, past physician online contributions, doctor review rating, clinic title, hospital level, and city level, were .415, .189, –.099, –.106, and –.143, respectively. For the psychological (or material) rewards, the standardized coefficient of the main effect was 0.261 (or 0.688) and the standardized coefficient of the quadratic effect was –0.015 (or –0.049). All estimates were statistically significant (P<.001).ConclusionsPhysicians with more past physician online contribution, with higher review ratings, coming from lower level clinics, not coming from tertiary hospitals, and not coming from big cities were more willing to participate in online health care community activities. To promote physician online contribution, it is necessary to establish an appropriate incentive mechanism including psychological and material rewards. Finally, our findings suggest two guidelines for designing a useful incentive mechanism to facilitate physician online contribution. First, material reward is more useful than psychological reward. Second, as indicated by the concave-down-increasing causal relationship between rewards and physician online contribution, although an appropriate reward is effective in encouraging willingness on the part of physicians to contribute to the online health care community, the effect of additional rewards is limited.

Information Seeking in Online Healthcare Communities: The Dual Influence From Social Self and Personal Self

The use of online healthcare communities to acquire health-related information and reduce uncertainty over illnesses is currently hampered by the lack of understanding of how health information-seeking behavior can be stimulated in such environments. By drawing upon the theoretical notion of social self and personal self, and conducting a field survey among 101 online healthcare community users, this study investigates how social identity in online healthcare communities and individual users’ perceived disease severity jointly influence the health information-seeking propensity. This study contributes to the literature on health information seeking by investigating the influence of social self (social identity), personal self (perceived disease severity), and their interplay in online communities. The findings can guide healthcare providers and community managers in formulating strategic plans for promoting health information-seeking behavior.

Modeling Physicianss Dynamic Behaviors in an Online Healthcare Community: An Empirical Study Using a Vector Autoregression Approach

Physicians’ participation in online healthcare platforms serves to integrate online healthcare resources with the offline medical system. This integration brings opportunities for reshaping healthcare delivery systems. Although, in the field of telemedicine, there has been extensive discussion about physician participation, little is known about how physicians actually participate in online healthcare platforms and offline medical systems. Understanding physicians’ participation dynamics between online and offline channels is of great importance to academic researchers, practitioners, and policymakers. Such an understanding can reveal insights into how healthcare is actually delivered to patients through both channels, how to contribute to quantifying the social impacts of online healthcare services, and how to improve healthcare delivery systems. Thus, in this study, we investigate physicians’ online-offline behavior dynamics. We collected data from both online and offline channels to conduct our analysis. As physicians’ online and offline activities are highly endogenous, we deploy a time-series technique and develop a structural vector autoregression (SVAR) model to examine such behavior dynamics. We find that physicians’ online activities can lead to a higher service quantity in offline channels, whereas offline activities may reduce physicians’ online services due to resource constraints. Our results also show that the more offline patients physicians serve, the more articles the physicians will likely share online. These findings are robust to various econometric specifications and estimation methods. Our paper contributes to the advocacy of Health 2.0 and provides evidence of the value of online healthcare communities and the policies that support them.

An Empirical Study on the Effectiveness of Perceived and Received Support in Online Healthcare Communities

Social media-based online communities are becoming increasingly popular for various social interactions, including those for healthcare and health-related activities. The benefits from these activities, however, are constrained by how a platform is designed, as a platform’s design defines what activities can be done and how individuals can engage and interact on the platform. In this study, we focus on weight-loss communities and social tools that facilitate social communication and establish a variety of relationships between users. In particular, we examine the effectiveness of one-way and two-way social relationships on individuals’ weight-loss management. Drawing from theories of social support, social reciprocity, and social indebtedness, we use two-way friendship relationships to proxy perceived support and one-way commenting relationships to proxy received support and conjecture that they work through different pathways. We find, through empirical analysis, that both types of social relationships as well as self-monitoring are effective in promoting weight loss, but perceived and received support have different impacts. Whereas both perceived and received support are positively related to weight-loss outcomes, the effect of received support is found to be higher than that of perceived support and the difference is statistically significant. Moreover, we find that received support is positively associated with self-monitoring behaviors, whereas perceived support is not. These findings provide insights for platform providers to improve the social design aspect of online services and for healthcare providers and practitioners in their efforts to advise individuals on weight self-management. Our results also can be used to design and implement more effective online interventions.

How Doctors Gain Social and Economic Returns in Online Health-Care Communities: A Professional Capital Perspective

An online health-care community (OHC) is a novel channel through which doctors share medical or health-care knowledge with patients. While the sustainable development of an OHC relies on doctors’ participation, we have limited information on how doctors can gain benefits from OHCs. In attempting to close this knowledge gap, we examine the determinants of social and economic returns of doctors at OHCs by extending the social exchange theory into the professional domain. The notion of professional capital, as a set of renewable resources for social professionals developed by good education within a territory of social practice, is introduced to understand the unique resources available to doctors for social exchange. Specifically, we examine the effects of status capital and decisional capital (two dimensions of professional capital) on doctors’ social and economic returns. Moreover, we explore how such effects differ across different doctor groups. The results show that, in addition to the widespread pursuit of celebrity doctors (who can be recognized by their high status capital) offline, the doctor’s decisional capital is also an important professional component in maintaining exchange returns at OHCs. This study provides empirical evidence of the relationship between professional capital and the exchange returns, and extends prior research on OHCs through a professional capital perspective with implications for theory and practice.

Doctor–patient relationship strength’s impact in an online healthcare community

ABSTRACTDoctor–patient (D–P) interaction currently faces a set of challenges owing to a dearth in medical resources and related communication reasons. Healthcare information technology and associated systems, such as those supporting online healthcare communities (OHCs) that provide new platforms for information exchange and online communication, are expected to alter traditional D–P relationship models. Despite significant results from extant research indicating patient benefits, empirical research on OHC returns for physicians is lacking. This exploratory study examines the strength of the D–P relationship and its impacts on physicians’ individual outcomes in an OHC. Guided by the social capital and social ties theories, and using a structural equation modeling (SEM) approach to study 339,010 instances of doctor–patient communication from 1430 physicians at The Good Doctor (www.Haodf.com), which is one of the largest Chinese OHCs, we found that weak ties can result in economic and social returns for doctors. However, further analysis has indicated that strong ties mediate the effect of weak ties, thus encouraging doctors to convert weak ties into strong ties by mobilizing their website settings to strengthen their relationships and, subsequently, to be better rewarded. Implications for research and practice on the development of healthcare information technology and associated systems are discussed.

The Consensus Effect in Online Health-Care Communities

Online health-care communities have become increasingly popular among patients, enabling them to connect to a large population of patients who suffer from similar health problems and to access massive amounts of health-related information. We are interested in investigating how other patients’ consensus on treatment experiences affects patients’ perceived treatment effectiveness. In this regard, we use the cue diagnosticity framework to examine patients’ shared treatment reviews. By controlling individual heterogeneity and the inhomogeneous weighting function of social influence on patients, we find that consensus has a positive impact on patients’ perceived treatment effectiveness. This positive effect, however, is negatively moderated by the characteristics of the shared information, including volume and patients’ precommitment and social connectedness. Overall, we find that perceived treatment effectiveness is closely related to community participants’ perceptions about the treatment. These findings can be used to help health-care practitioners incorporate patients’ experiences into health-care systems and develop effective interventions to help patients better engage in their disease management.

Online Healthcare Community Interaction Dynamics

With the increasing dilemma of the rapid global demand for healthcare services (often in the presence of limited resources), how to creatively allocate and use healthcare resources across a widespread population has become a salient issue. Online healthcare communities (OHCs) are regarded as a potential ICT-based partial solution. In contrast to traditional healthcare, online doctor-patient interaction is unlimited in terms of time and space limitations while an OHC is exposed to the whole community. These characteristics are key to achieving synergistic doctor-patient interaction and community development in the longer term. In order to explore the nature of doctor-patient interaction dynamics in an OHC, we systematically investigate doctor-patient interaction dynamics from the dual perspectives of doctor and patient. Our doctor-patient interaction dual-cycle model has been built based on six doctor-patient interaction processes (i.e., searching, choosing, knowledge sharing, providing, receiving and balancing). According to our dual-cycle model, four key managerial issues in OHC (information asymmetry, incentive mechanisms, service delivery processes and interaction mechanisms) have been identified as examples. Discussion and directions for future research, with challenges as well as opportunities, have been elaborated. A broad view with fruitful research potential is ensured and new theories and methods ultimately provide implications for effectively and efficiently allocating scarce healthcare resources to a broader population.

The Impact of Individual and Organizational Reputation on Physicians’ Appointments Online

ABSTRACTInsufficient research exists on the impact of reputation in online health-care market communities, especially from the multilevel and cross-level perspectives. Based on prior research on individual and organizational reputation, we hypothesize multilevel and cross-level reputation determinants of physicians’ performance in online health-care market communities. Using hierarchical linear modeling, we analyzed the data of 47,182 physicians from 660 hospitals in a Chinese online health-care market community to test our hypotheses. Our results suggest that the number of physicians’ appointments is positively associated with their individual offline and online reputations, as well as the offline and online reputation of the hospital in which the physicians work. We also find that organizational reputation moderates the relationship between an individual’s reputation and a physician’s performance, in such a way that the hospital’s offline reputation increases the importance of physicians’ online reputation in promoting the number of physicians’ appointments. However, the hospital’s online reputation enhances the relationship between physicians’ offline reputation and the number of appointments. Our study contributes to existing theories of reputation and the signaling theory, and also provides physicians with guidelines that support them in effectively improving their performance.

Improving customer well-being through two-way online social support

Purpose – The purpose of this paper is to explore the dynamics of online health care communities and the impact of two-way online social support on customers’ well-being and patients’ quality of life, at different social exclusion levels. Design/methodology/approach – An online survey in China’s Anti-Hepatitis B Online Community includes 326 respondents. A combined hierarchical regression analysis and structural equation model test the hypotheses. Findings – Both receiving and giving online social support, as reciprocal altruism behaviors, enhance patients’ well-being. Receiving online social support influences psychological well-being most; giving has the largest impact on existential domains. Social exclusion boosts the benefits of giving online social support but attenuates the benefits of receiving it. Research limitations/implications – This research focusses on the effects of online social support among socially excluded patients. Extensions could rely on objective instead of subjective measures and alternative methodologies to test the underlying processes. Additional insights could derive from a bidirectional perspective. Practical implications – Medical treatment institutions should leverage customer resources; health care providers should prioritize patients who feel socially excluded as effective online support providers. Health care community administrators can use several means to convince patients to contribute to communities. Originality/value – Social support in online health care communities is a collaborative service that uses customers as service resources. This study explains the collaborative service and how customers feel about their bidirectional roles. It also extends reciprocal altruism research to a health information technology realm by systematically exploring how giving, vs receiving, online social support affects customers’ well-being.

How users adopt healthcare information: An empirical study of an online Q&A community

ObjectivesThe emergence of social media technology has led to the creation of many online healthcare communities, where patients can easily share and look for healthcare-related information from peers who have experienced a similar problem. However, with increased user-generated content, there is a need to constantly analyse which content should be trusted as one sifts through enormous amounts of healthcare information. This study aims to explore patients’ healthcare information seeking behavior in online communities. MethodsBased on dual-process theory and the knowledge adoption model, we proposed a healthcare information adoption model for online communities. This model highlights that information quality, emotional support, and source credibility are antecedent variables of adoption likelihood of healthcare information, and competition among repliers and involvement of recipients moderate the relationship between the antecedent variables and adoption likelihood. Empirical data were collected from the healthcare module of China’s biggest Q&A community—Baidu Knows. Text mining techniques were adopted to calculate the information quality and emotional support contained in each reply text. A binary logistics regression model and hierarchical regression approach were employed to test the proposed conceptual model. ResultsInformation quality, emotional support, and source credibility have significant and positive impact on healthcare information adoption likelihood, and among these factors, information quality has the biggest impact on a patient’s adoption decision. In addition, competition among repliers and involvement of recipients were tested as moderating effects between these antecedent factors and the adoption likelihood. Results indicate competition among repliers positively moderates the relationship between source credibility and adoption likelihood, and recipients’ involvement positively moderates the relationship between information quality, source credibility, and adoption decision. ConclusionsIn addition to information quality and source credibility, emotional support has significant positive impact on individuals’ healthcare information adoption decisions. Moreover, the relationships between information quality, source credibility, emotional support, and adoption decision are moderated by competition among repliers and involvement of recipients.

The development of online doctor reviews in China: an analysis of the largest online doctor review website in China.

BackgroundSince the time of Web 2.0, more and more consumers have used online doctor reviews to rate their doctors or to look for a doctor. This phenomenon has received health care researchers’ attention worldwide, and many studies have been conducted on online doctor reviews in the United States and Europe. But no study has yet been done in China. Also, in China, without a mature primary care physician recommendation system, more and more Chinese consumers seek online doctor reviews to look for a good doctor for their health care concerns.ObjectiveThis study sought to examine the online doctor review practice in China, including addressing the following questions: (1) How many doctors and specialty areas are available for online review? (2) How many online reviews are there on those doctors? (3) What specialty area doctors are more likely to be reviewed or receive more reviews? (4) Are those reviews positive or negative?MethodsThis study explores an empirical dataset from Good Doctor website, haodf.com—the earliest and largest online doctor review and online health care community website in China—from 2006 to 2014, to examine the stated research questions by using descriptive statistics, binary logistic regression, and multivariate linear regression.ResultsThe dataset from the Good Doctor website contained 314,624 doctors across China and among them, 112,873 doctors received 731,543 quantitative reviews and 772,979 qualitative reviews as of April 11, 2014. On average, 37% of the doctors had been reviewed on the Good Doctor website. Gynecology-obstetrics-pediatrics doctors were most likely to be reviewed, with an odds ratio (OR) of 1.497 (95% CI 1.461-1.535), and internal medicine doctors were less likely to be reviewed, with an OR of 0.94 (95% CI 0.921-0.960), relative to the combined small specialty areas. Both traditional Chinese medicine doctors and surgeons were more likely to be reviewed than the combined small specialty areas, with an OR of 1.483 (95% CI 1.442-1.525) and an OR of 1.366 (95% CI 1.337-1.395), respectively. Quantitatively, traditional Chinese medicine doctors (P<.001) and gynecology-obstetrics-pediatrics doctors (P<.001) received more reviews than the combined small specialty areas. But internal medicine doctors received fewer reviews than the combined small specialty areas (P<.001). Also, the majority of quantitative reviews were positive—about 88% were positive for the doctors' treatment effect measure and 91% were positive for the bedside manner measure. This was the case for the four major specialty areas, which had the most number of doctors—internal medicine, gynecology-obstetrics-pediatrics, surgery, and traditional Chinese medicine.ConclusionsLike consumers in the United States and Europe, Chinese consumers have started to use online doctor reviews. Similar to previous research on other countries’ online doctor reviews, the online reviews in China covered almost every medical specialty, and most of the reviews were positive even though all of the reviewing procedures and the final available information were anonymous. The average number of reviews per rated doctor received in this dataset was 6, which was higher than that for doctors in the United States or Germany, probably because this dataset covered a longer time period than did the US or German dataset. But this number is still very small compared to any doctor’s real patient population, and it cannot represent the reality of that population. Also, since all the data used for analysis were from one single website, the data might be biased and might not be a representative national sample of China.

The Impact of Online Social Support on Patients’ Quality of Life and the Moderating Role of Social Exclusion

Social support is critical for improving patients’ health outcomes. People living with chronic diseases are often socially excluded and thus face many challenges in their lives. The type and amount of social support they receive from online health care communities can potentially enhance their quality of life. This research verifies emotional support, informational support, companionship, and relatedness as four categories of online social support pertinent in health care communities. In examining the detailed effects of multidimensional online social support on physical, psychological, and existential quality of life, this research finds that the impact of emotional support on psychological quality of life is most effective. An empirical survey of 349 participants finds that the influential outcomes of online social support on quality of life depend on stigmatized patients’ perceptions of their level of social exclusion. In general, stigmatized patients with high levels of social exclusion seek a variety of online social support and attain a more improved quality of life than those patients with lower levels of social exclusion. This research recommends that the health care sector emphasize patients’ synergies and develop online customer resources to extend the limited medical support available.

The Consensus Effect on Shared Treatment Experience in Online Healthcare Communities

Online healthcare communities have become increasingly popular among patients, enabling them to access massive health-related information and to connect to a large population of patients who suffer from similar health problems. Extant research has demonstrated the important role that others’ shared opinions play in the decision-making process of individuals. In this paper, we are therefore interested in investigating how other patients’ inconsistency of treatment experience affects patients’ perceived treatment effectiveness. By viewing consensus as the exploratory cost for patients to find diversified health information and by controlling individual heterogeneity and the inhomogeneous weighting function of social influence on patients, we find that consensus has a positive impact on patients’ perceived treatment effectiveness. We also find that this effect is moderated by the discussion volume, the scope of discussed issues, and patients’ social connectedness. Because perceived treatment effectiveness is closely related to patients’ medical decisions about treatments, we provide a discussion of the implications of these findings on pharmaceutical marketing and public policies.

Modelling liking networks in an online healthcare community: An exponential random graph model analysis approach

The value and role of the Like button in social media have gained increased attention/focus, yet we know little about how liking relations form between Likers and Likeds. We study this problem in an online healthcare context from a social network perspective. Taking into account the effects of both the network structures and the attributes of Likers and Likeds, we utilize a theory-grounded statistical modelling approach, Exponential Random Graph Models (ERGMs), to model the liking network in an online healthcare community. The results of ERGM analysis reveal that, while network degree exhibits a big effect in the liking process, individual attributes like the level of past involvement and degree of activity also positively influence members’ future liking behaviour and performance. The evaluation indicates that our model is an effective method to identify the formation of liking networks. The findings extend the understanding of online liking behaviour and provide insights into harnessing the power of liking.

Change is in the air: APhA awarded HRSA contract

Out with the old and in with the new. To meet the evolving needs of today's health care initiatives, the U.S. Department of Health and Human Services Health Resources and Services Administration (HRSA) has awarded APhA a contract to help safety net providers deliver high quality pharmacy services. This new contract replaces the Pharmacy Services Support Center (PSSC) brand, which was retired upon the initiation of the new contract.