The Experts below are selected from a list of 14982 Experts worldwide ranked by ideXlab platform
Rahul Katarya - One of the best experts on this subject based on the ideXlab platform.
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Opinion Leader detection using whale optimization algorithm in online social network
Expert Systems With Applications, 2020Co-Authors: Lokesh Jain, Rahul Katarya, Shelly SachdevaAbstract:Abstract In the current digital era, optimization is one of the most significant problems in the social network. Most of the issues related to optimization are NP-complete and not possible to solve them in polynomial time. Detection of Opinion Leader based on their optimized centrality measure is a critical issue. The Opinion Leaders have a non-trivial influence on the other user's decision-making process and can solve various problems related to the diffusion of new products and innovations in the real world. In this paper, we proposed a new Social Network-based Whale Optimization Algorithm (SNWOA) to find the top-N Opinion Leaders by measuring the reputation of the user using various standard optimization function in the network. The proposed algorithm is advantageous to determine the Opinion Leaders because it based on the bubble-net hunting behavior of humpback whales. The algorithm found the best possible solution as the number of users raises progressively in the network; therefore, the general complexity of the algorithm remains unchanged. Besides, we also proposed a new approach to categorize the communities based on the similarity index comprising neighbor similarity and clustering coefficient as the significant components. Initially, we computed the objective function of each user by using their centralities and deployed the proposed algorithm with different optimization functions to identify the local and universal Opinion Leaders. We implemented the proposed algorithm on the real and synthesized datasets and compared the result based on the accuracy, precision, recall, and F1-score. The result indicates that the proposed algorithms give a better result as compared to the other standard Social Network Analysis (SNA) measures. We also concluded that the community partitioning algorithm is even better than the other community detection algorithms based on different parameters and computational time.
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Opinion Leader discovery based on text analysis in online social network
International Conference on Information Systems, 2019Co-Authors: Lokesh Jain, Rahul Katarya, Shelly SachdevaAbstract:The amalgamation of technology, social media, and innovation has a significant influence on human life. Most of us spend their time on social networking sites for their decision making. An Opinion Leader has enormous significance for human's decision-making process. In this paper, we addressed an inventive and novel approach to discovering the Opinion Leader based tweets posted by the user on the respond of the query posed by another user in the social network. We used the sentiment analysis based model to classify the tweets/ reviews on a particular topic in the data set. We calculated the positive, negative, and neutral score and measured the polarity of each statement using the NLTK python package. Next, we calculated the total polarity cost and ranked the user based on the total polarity cost. The user has a higher polarity cost considered as an Opinion Leader. In this paper, we have implemented the proposed model on Amazon Fine Foods reviews data set having around 568,454 reviews posted by 256,059 users. For validating the proposed model, we compared the results with the other standard classifier and found that the proposed model is better than another classifier in terms of accuracy, precision, recall, and F1-score.
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discover Opinion Leader in online social network using firefly algorithm
Expert Systems With Applications, 2019Co-Authors: Lokesh Jain, Rahul KataryaAbstract:Abstract Nowadays, with the widespread access to web 2.0, the social network plays an unbelievable role in knowledge sharing and diffusion of new products. People can share their views and can visit other's Opinion about the particular material, news, products, artifacts and, trends, etc. anywhere, anytime, and anywhere. An Opinion Leader is a critical person who can change, modify and transform other's view by their knowledge and proficiency. In this article, an innovative approach is proposed to discover the top-N local and global Opinion Leader within the community and social network respectively. Initially, we identified the community structure within the social network using the modified Louvain method and next identified the Opinion Leader using a modified firefly algorithm in each community. We also determined the global Opinion Leader within the same social network using the same firefly algorithm. The proposed approach is exceptionally supportive to expert and intelligent system because it competently discovered the local optimum concurrently in each subgroup of the social network. All the users can update its attractiveness value without any supposition, and as soon as the distance among the user's increases, the other users can automatically create another subgroup in the network and form the local community. In addition, as the population size in the network increases, the entire users measure their prominence simultaneously. Therefore, there is no consequence on computational time and accuracy of the algorithm. Thus, the proposed algorithm is superlative suitable for discovering the Opinion Leader in the local community and globally in the social network. For legalized the proposed approach, we implemented our proposed method on synthesized as well as on real dataset. Finally, we concluded that both the recommended procedures are much better concerning the accuracy, precision, recall, and F1-score with the widely used standard Social Network Analysis (SNA) measures.
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Survey on Opinion Leader in Social Network using Data Mining
2019 5th International Conference on Advanced Computing & Communication Systems (ICACCS), 2019Co-Authors: Rahul Katarya, Diksha GautamAbstract:Online Social Network (OSN) is an online virtual community which helps people from anywhere to connect, share their views, ideas with each other and express themselves without any restrictions on social networks. Sometimes, in such kind of network one person's view or idea can make an impact on another person. Hence OSNs plays a significant role in the behavior and decision making of a person. The person that can make an impact, help or influence another person in any kind of issue is we call an Opinion Leader (OL). It has become essential to identify an Opinion Leader for different benefits among society. In this paper, we have shown the need and features of an Opinion Leader. This study also shows the different methods to identify an Opinion Leader in and some recent research in the area of data mining techniques to find an Opinion Leader in the OSN.
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Role of Opinion Leader for the diffusion of products using Epidemic model in Online Social Network
2019 Twelfth International Conference on Contemporary Computing (IC3), 2019Co-Authors: Lokesh Jain, Rahul Katarya, Shelly SachdevaAbstract:In the emergent web period, an Opinion Leader plays a very significant job for the diffusion of new products in the realworld via the online social network. Various epidemic models are used for the diffusion of new products, but it is very challenging to validate the model mathematically due to network heterogeneity. In this paper, we presented a novel model that indicated how Opinion Leader is supportive for the diffusion of new products via Bayesian network considering the epidemic models in the online social network. In the proposed model, first, we discovered the Opinion Leader based on various centrality measures used for social network analysis. Next, we used the Bayesian network that depicted the joint probability distribution on a set of random users involved in the diffusion process. Finally, we implemented the proposed algorithm on real data set and evaluated the results. We observed that the obtained results are much more effective as compared to the previously developed models in concern of accuracy, precision, recall, F1-score as well. The diffusion rate of the proposed model is also lesser than the basic epidemic models.
Finlay A Mcalister - One of the best experts on this subject based on the ideXlab platform.
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impact of Opinion Leader endorsed evidence summaries on the quality of prescribing for patients with cardiovascular disease a randomized controlled trial
American Heart Journal, 2007Co-Authors: Sumit R Majumdar, Ross T Tsuyuki, Finlay A McalisterAbstract:Background Local Opinion Leaders are educationally and socially influential physicians. Although they can accelerate the adoption of new evidence in hospitals, their impact on the quality of prescribing for outpatients has only been examined by a few studies. We hypothesized that an intervention consisting of patient-specific one-page evidence summaries, generated and endorsed by local Opinion Leaders, would improve prescribing of angiotensin-converting enzyme (ACE) inhibitors or angiotensin receptor blockers (ARBs) in heart failure (HF) and that of statins in ischemic heart disease (IHD). Methods We conducted a community-based randomized controlled trial in patients with HF (not receiving ACE inhibitors or ARBs) and those with IHD (not receiving statins) who were recruited from 40 pharmacies and allocated either to the Opinion Leader intervention or to usual care based on randomization of their primary care physician. The primary outcome was an increase in the use of efficacious therapies (ACE inhibitors or ARBs in HF and statins in IHD) within 6 months; the secondary outcomes were prescribing changes for HF or IHD. Results A total of 171 patients participated in the study; 87 were allocated to the intervention, whereas 84 were assigned to the control group. The median age of the participants was 75 years; 103 (60%) were female, 54 (32%) had HF, and 117 (68%) had IHD. Overall, 21 (24%) intervention patients started receiving an efficacious medication within 6 months, as compared with 15 (18%) control subjects (relative risk of improvement 1.32, 95% CI 0.73-2.40, P = .31). In the HF subgroup, 38% of the intervention patients started receiving an ACE inhibitor or ARB therapy, as compared with 20% of control subjects (relative risk of improvement 1.90, 95% CI 0.76-4.72, P = .15). In the IHD subgroup, 17% of the intervention patients and 17% of the control subjects started receiving statin therapy ( P = .97). Conclusions The influence of local Opinion Leaders may be useful for improving the quality of cardiovascular prescribing in the community, but the benefits are likely modest and may be disease specific. Further studies on this method are warranted.
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a randomized trial to assess the impact of Opinion Leader endorsed evidence summaries on the use of secondary prevention strategies in patients with coronary artery disease the esp cad trial protocol nct00175240
Implementation Science, 2006Co-Authors: Finlay A Mcalister, Miriam Fradette, Michelle M Graham, Sumit R Majumdar, William A Ghali, Randall Williams, Ross T Tsuyuki, James Mcmeekin, Jeremy M Grimshaw, Merril L KnudtsonAbstract:Although numerous therapies have been shown to be beneficial in the prevention of myocardial infarction and/or death in patients with coronary disease, these therapies are under-used and this gap contributes to sub-optimal patient outcomes. To increase the uptake of proven efficacious therapies in patients with coronary disease, we designed a multifaceted quality improvement intervention employing patient-specific reminders delivered at the point-of-care, with one-page treatment guidelines endorsed by local Opinion Leaders ("Local Opinion Leader Statement"). This trial is designed to evaluate the impact of these Local Opinion Leader Statements on the practices of primary care physicians caring for patients with coronary disease. In order to isolate the effects of the messenger (the local Opinion Leader) from the message, we will also test an identical quality improvement intervention that is not signed by a local Opinion Leader ("Unsigned Evidence Statement") in this trial. Randomized trial testing three different interventions in patients with coronary disease: (1) usual care versus (2) Local Opinion Leader Statement versus (3) Unsigned Evidence Statement. Patients diagnosed with coronary artery disease after cardiac catheterization (but without acute coronary syndromes) will be randomly allocated to one of the three interventions by cluster randomization (at the level of their primary care physician), if they are not on optimal statin therapy at baseline. The primary outcome is the proportion of patients demonstrating improvement in their statin management in the first six months post-catheterization. Secondary outcomes include examinations of the use of ACE inhibitors, anti-platelet agents, beta-blockers, non-statin lipid lowering drugs, and provision of smoking cessation advice in the first six months post-catheterization in the three treatment arms. Although randomization will be clustered at the level of the primary care physician, the design effect is anticipated to be negligible and the unit of analysis will be the patient. If either the Local Opinion Leader Statement or the Unsigned Evidence Statement improves secondary prevention in patients with coronary disease, they can be easily modified and applied in other communities and for other target conditions.
Lokesh Jain - One of the best experts on this subject based on the ideXlab platform.
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Opinion Leader detection using whale optimization algorithm in online social network
Expert Systems With Applications, 2020Co-Authors: Lokesh Jain, Rahul Katarya, Shelly SachdevaAbstract:Abstract In the current digital era, optimization is one of the most significant problems in the social network. Most of the issues related to optimization are NP-complete and not possible to solve them in polynomial time. Detection of Opinion Leader based on their optimized centrality measure is a critical issue. The Opinion Leaders have a non-trivial influence on the other user's decision-making process and can solve various problems related to the diffusion of new products and innovations in the real world. In this paper, we proposed a new Social Network-based Whale Optimization Algorithm (SNWOA) to find the top-N Opinion Leaders by measuring the reputation of the user using various standard optimization function in the network. The proposed algorithm is advantageous to determine the Opinion Leaders because it based on the bubble-net hunting behavior of humpback whales. The algorithm found the best possible solution as the number of users raises progressively in the network; therefore, the general complexity of the algorithm remains unchanged. Besides, we also proposed a new approach to categorize the communities based on the similarity index comprising neighbor similarity and clustering coefficient as the significant components. Initially, we computed the objective function of each user by using their centralities and deployed the proposed algorithm with different optimization functions to identify the local and universal Opinion Leaders. We implemented the proposed algorithm on the real and synthesized datasets and compared the result based on the accuracy, precision, recall, and F1-score. The result indicates that the proposed algorithms give a better result as compared to the other standard Social Network Analysis (SNA) measures. We also concluded that the community partitioning algorithm is even better than the other community detection algorithms based on different parameters and computational time.
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Opinion Leader discovery based on text analysis in online social network
International Conference on Information Systems, 2019Co-Authors: Lokesh Jain, Rahul Katarya, Shelly SachdevaAbstract:The amalgamation of technology, social media, and innovation has a significant influence on human life. Most of us spend their time on social networking sites for their decision making. An Opinion Leader has enormous significance for human's decision-making process. In this paper, we addressed an inventive and novel approach to discovering the Opinion Leader based tweets posted by the user on the respond of the query posed by another user in the social network. We used the sentiment analysis based model to classify the tweets/ reviews on a particular topic in the data set. We calculated the positive, negative, and neutral score and measured the polarity of each statement using the NLTK python package. Next, we calculated the total polarity cost and ranked the user based on the total polarity cost. The user has a higher polarity cost considered as an Opinion Leader. In this paper, we have implemented the proposed model on Amazon Fine Foods reviews data set having around 568,454 reviews posted by 256,059 users. For validating the proposed model, we compared the results with the other standard classifier and found that the proposed model is better than another classifier in terms of accuracy, precision, recall, and F1-score.
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discover Opinion Leader in online social network using firefly algorithm
Expert Systems With Applications, 2019Co-Authors: Lokesh Jain, Rahul KataryaAbstract:Abstract Nowadays, with the widespread access to web 2.0, the social network plays an unbelievable role in knowledge sharing and diffusion of new products. People can share their views and can visit other's Opinion about the particular material, news, products, artifacts and, trends, etc. anywhere, anytime, and anywhere. An Opinion Leader is a critical person who can change, modify and transform other's view by their knowledge and proficiency. In this article, an innovative approach is proposed to discover the top-N local and global Opinion Leader within the community and social network respectively. Initially, we identified the community structure within the social network using the modified Louvain method and next identified the Opinion Leader using a modified firefly algorithm in each community. We also determined the global Opinion Leader within the same social network using the same firefly algorithm. The proposed approach is exceptionally supportive to expert and intelligent system because it competently discovered the local optimum concurrently in each subgroup of the social network. All the users can update its attractiveness value without any supposition, and as soon as the distance among the user's increases, the other users can automatically create another subgroup in the network and form the local community. In addition, as the population size in the network increases, the entire users measure their prominence simultaneously. Therefore, there is no consequence on computational time and accuracy of the algorithm. Thus, the proposed algorithm is superlative suitable for discovering the Opinion Leader in the local community and globally in the social network. For legalized the proposed approach, we implemented our proposed method on synthesized as well as on real dataset. Finally, we concluded that both the recommended procedures are much better concerning the accuracy, precision, recall, and F1-score with the widely used standard Social Network Analysis (SNA) measures.
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Role of Opinion Leader for the diffusion of products using Epidemic model in Online Social Network
2019 Twelfth International Conference on Contemporary Computing (IC3), 2019Co-Authors: Lokesh Jain, Rahul Katarya, Shelly SachdevaAbstract:In the emergent web period, an Opinion Leader plays a very significant job for the diffusion of new products in the realworld via the online social network. Various epidemic models are used for the diffusion of new products, but it is very challenging to validate the model mathematically due to network heterogeneity. In this paper, we presented a novel model that indicated how Opinion Leader is supportive for the diffusion of new products via Bayesian network considering the epidemic models in the online social network. In the proposed model, first, we discovered the Opinion Leader based on various centrality measures used for social network analysis. Next, we used the Bayesian network that depicted the joint probability distribution on a set of random users involved in the diffusion process. Finally, we implemented the proposed algorithm on real data set and evaluated the results. We observed that the obtained results are much more effective as compared to the previously developed models in concern of accuracy, precision, recall, F1-score as well. The diffusion rate of the proposed model is also lesser than the basic epidemic models.
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identification of Opinion Leader in online social network using fuzzy trust system
IEEE International Advance Computing Conference, 2018Co-Authors: Lokesh Jain, Rahul KataryaAbstract:In today human life, a social network plays a significant role in the user’s decision-making. In the social network, an Opinion Leader is a critical person who influences the behavior of the person with their own knowledge and skills. The major contribution of this paper is to recommend an advance approach to discover the Opinion Leader in the social network using fuzzy logic and trust generation model. In the first step, we evaluate the fuzzy trust rules based on the user’s trust. In the next step, these fuzzy trust rules apply to the online social network and then the de-fuzzification process applied to find out the trust value for each user and at last, identify the top-N user according to their prominence value that directly used to obtain their trust value for each user. We demonstrate our approach on the synthesized dataset and show the result that is better than the standard Social network analysis measures with respect to accuracy, precision, F1-score, and recall.
Xia Lin - One of the best experts on this subject based on the ideXlab platform.
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networking groups Opinion Leader identification algorithms based on sentiment analysis
Computer Science, 2012Co-Authors: Xia LinAbstract:Opinion Leaders are core users in online communities,which can guide the direction of public Opinion.We proposed a method to find the interest group based on topic content analysis,which combines the advantages of clustering and classification algorithms.Then we used the method of sentiment analysis to define the authority value as the weight of the link between users.On this basis,an algorithm named LeaderRank was proposed to identify the Opinion Leaders in BBS,and experiments indicate that LeaderRank algorithm can effectively improve the accuracy of Leaders mining.
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A Feature Analysis of the Opinion Leader in On-Line Communities
Computer Engineering and Science, 2011Co-Authors: Xia LinAbstract:We use a method of social network analysis to indentify Opinion Leaders in social networks.First of all we analyze the characteristics of the social networks of on-line communities,consider the difference between BBS,blogosphere and QA network,and propose that undirected weighted network models will enhance the identification accuracy of Opinion Leaders.Then,we analyze the features of social networks.We validate that BBS is small-world and scale-free,and we make a quantitative analysis of the social background of Opinion Leaders.We also propose a PageRank algorithm based on undirected weighted networks,and test several algorithms proposed before our experiment.We use four years' data from a BBS,and test these algorithms.Finally,we make a profound analysis and find the relationship between Opinion Leaders and boards,and the result shows that we can find a majority of Opinion Leaders from covering few boards.
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algorithms of bbs Opinion Leader mining based on sentiment analysis
Web Information Systems Modeling, 2010Co-Authors: Xu Wei, Xia LinAbstract:Opinion Leaders play a crucial role in online communities, which can guide the direction of public Opinion. Most proposed algorithms on Opinion Leaders mining in internet social network are based on network structure and usually omit the fact that Opinion Leaders are field-limited and the Opinion sentiment orientation analysis is the vital factor of one's authority. We propose a method to find the interest group based on topic content analysis, which combine the advantages of clustering and classification algorithms. Then we use the method of sentiment analysis to define the authority value as the weight of the link between users. On this basis, an algorithm named LeaderRank is proposed to identify the Opinion Leaders in BBS, and experiments indicate that Leader-Rank algorithm can effectively improve the accuracy of Leaders mining.
Sumit R Majumdar - One of the best experts on this subject based on the ideXlab platform.
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engaging patients and primary care providers in the design of novel Opinion Leader based interventions for acute asthma in the emergency department a mixed methods study
BMC Health Services Research, 2018Co-Authors: Cristina Villaroel, Sumit R Majumdar, Maria B Ospina, S Couperthwaite, Erin Rawe, Taylor Nikel, Brian H RoweAbstract:Multifaceted interventions driven by the needs of patients and providers can help move evidence into practice more rapidly. This study engaged both patients and primary care providers (PCPs) to help design novel Opinion Leader (OL)-based interventions for patients with acute asthma seen in emergency departments (EDs). A mixed methods design was employed. In phase I, we invited convenience samples of patients with asthma presenting to the ED and PCPs to participate in a survey. Perceptions with respect to: a) an ideal OL-profile for asthma guidance; and b) content, style and delivery methods of OL-based interventions in acute asthma directed from the ED were collected. In phase II, we conducted focus groups to further explore preferences and expectations for such interventions with attention to barriers and facilitators for implementation. Overall, 54 patients completed the survey; 39% preferred receiving guidance from a respirologist, 44% during their ED visit and 56% through individual discussions. In addition, 55% expressed interest in having PCP follow-up within a week of ED discharge. A respirologist was identified as the ideal OL-profile by 59% of the 39 responding PCPs. All expressed interest in receiving notification of their patients’ ED presentation, most within a week and including diagnosis and ED/post ED-treatment. Personalized, guideline-based, recommendations were considered to be the ideal content by the majority; 39% requested this guidance through a pamphlet faxed to their offices. In the focus groups, patients and PCPs recognized the importance of health professional liaisons in transitions in care; patient anxiety and PCP time constraints were identified as potential barriers for ED-educational information uptake and proper post-ED follow-up, respectively. Engaging patients and PCPs yielded actionable information to tailor OL-based multifaceted interventions for acute asthma in the ED. We identified potential facilitators for the implementation of such interventions (e.g., patient interaction with alternative health care professionals who could facilitate transitions in asthma care between the ED and the primary care setting), and for the provision of post discharge self-management education (e.g., consideration of the first week of ED discharge as a practical time frame for this intervention). Prioritization of identified barriers (e.g., lack of PCP involvement) could be addressed by the identification of potential early adopters in practice environments (e.g., clinicians with special interest in asthma).
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impact of Opinion Leader endorsed evidence summaries on the quality of prescribing for patients with cardiovascular disease a randomized controlled trial
American Heart Journal, 2007Co-Authors: Sumit R Majumdar, Ross T Tsuyuki, Finlay A McalisterAbstract:Background Local Opinion Leaders are educationally and socially influential physicians. Although they can accelerate the adoption of new evidence in hospitals, their impact on the quality of prescribing for outpatients has only been examined by a few studies. We hypothesized that an intervention consisting of patient-specific one-page evidence summaries, generated and endorsed by local Opinion Leaders, would improve prescribing of angiotensin-converting enzyme (ACE) inhibitors or angiotensin receptor blockers (ARBs) in heart failure (HF) and that of statins in ischemic heart disease (IHD). Methods We conducted a community-based randomized controlled trial in patients with HF (not receiving ACE inhibitors or ARBs) and those with IHD (not receiving statins) who were recruited from 40 pharmacies and allocated either to the Opinion Leader intervention or to usual care based on randomization of their primary care physician. The primary outcome was an increase in the use of efficacious therapies (ACE inhibitors or ARBs in HF and statins in IHD) within 6 months; the secondary outcomes were prescribing changes for HF or IHD. Results A total of 171 patients participated in the study; 87 were allocated to the intervention, whereas 84 were assigned to the control group. The median age of the participants was 75 years; 103 (60%) were female, 54 (32%) had HF, and 117 (68%) had IHD. Overall, 21 (24%) intervention patients started receiving an efficacious medication within 6 months, as compared with 15 (18%) control subjects (relative risk of improvement 1.32, 95% CI 0.73-2.40, P = .31). In the HF subgroup, 38% of the intervention patients started receiving an ACE inhibitor or ARB therapy, as compared with 20% of control subjects (relative risk of improvement 1.90, 95% CI 0.76-4.72, P = .15). In the IHD subgroup, 17% of the intervention patients and 17% of the control subjects started receiving statin therapy ( P = .97). Conclusions The influence of local Opinion Leaders may be useful for improving the quality of cardiovascular prescribing in the community, but the benefits are likely modest and may be disease specific. Further studies on this method are warranted.
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a randomized trial to assess the impact of Opinion Leader endorsed evidence summaries on the use of secondary prevention strategies in patients with coronary artery disease the esp cad trial protocol nct00175240
Implementation Science, 2006Co-Authors: Finlay A Mcalister, Miriam Fradette, Michelle M Graham, Sumit R Majumdar, William A Ghali, Randall Williams, Ross T Tsuyuki, James Mcmeekin, Jeremy M Grimshaw, Merril L KnudtsonAbstract:Although numerous therapies have been shown to be beneficial in the prevention of myocardial infarction and/or death in patients with coronary disease, these therapies are under-used and this gap contributes to sub-optimal patient outcomes. To increase the uptake of proven efficacious therapies in patients with coronary disease, we designed a multifaceted quality improvement intervention employing patient-specific reminders delivered at the point-of-care, with one-page treatment guidelines endorsed by local Opinion Leaders ("Local Opinion Leader Statement"). This trial is designed to evaluate the impact of these Local Opinion Leader Statements on the practices of primary care physicians caring for patients with coronary disease. In order to isolate the effects of the messenger (the local Opinion Leader) from the message, we will also test an identical quality improvement intervention that is not signed by a local Opinion Leader ("Unsigned Evidence Statement") in this trial. Randomized trial testing three different interventions in patients with coronary disease: (1) usual care versus (2) Local Opinion Leader Statement versus (3) Unsigned Evidence Statement. Patients diagnosed with coronary artery disease after cardiac catheterization (but without acute coronary syndromes) will be randomly allocated to one of the three interventions by cluster randomization (at the level of their primary care physician), if they are not on optimal statin therapy at baseline. The primary outcome is the proportion of patients demonstrating improvement in their statin management in the first six months post-catheterization. Secondary outcomes include examinations of the use of ACE inhibitors, anti-platelet agents, beta-blockers, non-statin lipid lowering drugs, and provision of smoking cessation advice in the first six months post-catheterization in the three treatment arms. Although randomization will be clustered at the level of the primary care physician, the design effect is anticipated to be negligible and the unit of analysis will be the patient. If either the Local Opinion Leader Statement or the Unsigned Evidence Statement improves secondary prevention in patients with coronary disease, they can be easily modified and applied in other communities and for other target conditions.
