Brief report Special Issues

The top 100 Twitter influencers in cardiology

Running title: Cardiology influencers on Twitter
  • Importance 

    Twitter represents a growing aspect of the social media experience and is a widely used tool for public education in the 21st century. In the last few years, there has been concern about the dissemination of false health information on social media. It is therefore important that we assess the influencers of this health information in the field of cardiology.

    Objective 

    We sought to identify the top 100 Twitter influencers within cardiology, characterize them, and examine the relationship between their social media activity and academic influence.

    Design 

    Twitter topic scores for the topic search “cardiology” were queried on May 01, 2020 using the Right Relevance application programming interface (API). Based on their scores, the top 100 influencers were identified. Among the cardiologists, their academic h-indices were acquired from Scopus and these scores were compared to the Twitter topic scores.

    Result 

    We found out that 88/100 (88%) of the top 100 social media influencers on Twitter were cardiologists. Of these, 63/88 (72%) were males and they practiced mostly in the United States with 50/87 (57%) practicing primarily in an academic hospital. There was a moderately positive correlation between the h-index and the Twitter topic score, r = +0.32 (p-value 0.002).

    Conclusion 

    Our study highlights that the top ranked cardiology social media influencers on Twitter are board-certified male cardiologists practicing in academic settings in the US. The most influential on Twitter have a moderate influence in academia. Further research should evaluate the relationship between other academic indices and social media influence.

    Citation: Onoriode Kesiena, Henry K Onyeaka, Setri Fugar, Alexis K Okoh, Annabelle Santos Volgman. The top 100 Twitter influencers in cardiology[J]. AIMS Public Health, 2021, 8(4): 743-753. doi: 10.3934/publichealth.2021058

    Related Papers:

    [1] Josephine Y Chau, Lina Engelen, Sarah Burks-Young, Michelle Daley, Jen-Kui Maxwell, Karen Milton, Adrian Bauman . Perspectives on a ‘Sit Less, Move More’ Intervention in Australian Emergency Call Centres. AIMS Public Health, 2016, 3(2): 288-297. doi: 10.3934/publichealth.2016.2.288
    [2] Bronwyn Sudholz, Anna Timperio, Nicola D. Ridgers, David W. Dunstan, Rick Baldock, Bernie Holland, Jo Salmon . The Impact and Feasibility of Introducing Height-Adjustable Desks on Adolescents’ Sitting in a Secondary School Classroom. AIMS Public Health, 2016, 3(2): 274-287. doi: 10.3934/publichealth.2016.2.274
    [3] P. Dean Cooley, Casey P. Mainsbridge, Vaughan Cruickshank, Hongwei Guan, Anjia Ye, Scott J. Pedersen . Peer champions responses to nudge-based strategies designed to reduce prolonged sitting behaviour: Lessons learnt and implications from lived experiences of non-compliant participants. AIMS Public Health, 2022, 9(3): 574-588. doi: 10.3934/publichealth.2022040
    [4] Justine Leavy, Jonine Jancey . Stand by Me: Qualitative Insights into the Ease of Use of Adjustable Workstations. AIMS Public Health, 2016, 3(3): 644-662. doi: 10.3934/publichealth.2016.3.644
    [5] Genevieve N Healy, Ana Goode, Diane Schultz, Donna Lee, Bell Leahy, David W Dunstan, Nicholas D Gilson, Elizabeth G Eakin. . The BeUpstanding ProgramTM: Scaling up the Stand Up Australia Workplace Intervention for Translation into Practice. AIMS Public Health, 2016, 3(2): 341-347. doi: 10.3934/publichealth.2016.2.341
    [6] Alison Kirk, Ann-Marie Gibson, Katie Laverty, David Muggeridge, Louise Kelly, Adrienne Hughes . Patterns of Sedentary Behaviour in Female Office Workers. AIMS Public Health, 2016, 3(3): 423-431. doi: 10.3934/publichealth.2016.3.423
    [7] Calum F Leask, Marlene Sandlund, Dawn A Skelton, Emmanuelle Tulle, Sebastien FM Chastin . Modifying Older Adults’ Daily Sedentary Behaviour Using an Asset-based Solution: Views from Older Adults. AIMS Public Health, 2016, 3(3): 542-554. doi: 10.3934/publichealth.2016.3.542
    [8] Heini Wennman, Tommi Vasankari, Katja Borodulin . Where to Sit? Type of Sitting Matters for the Framingham Cardiovascular Risk Score. AIMS Public Health, 2016, 3(3): 577-591. doi: 10.3934/publichealth.2016.3.577
    [9] Francesco Marcatto, Donatella Ferrante, Mateusz Paliga, Edanur Kanbur, Nicola Magnavita . Behavioral dysregulation at work: A moderated mediation analysis of sleep impairment, work-related stress, and substance use. AIMS Public Health, 2025, 12(2): 290-309. doi: 10.3934/publichealth.2025018
    [10] Lynda M. Hegarty, Jacqueline L. Mair, Karen Kirby, Elaine Murtagh, Marie H. Murphy . School-based Interventions to Reduce Sedentary Behaviour in Children: A Systematic Review. AIMS Public Health, 2016, 3(3): 520-541. doi: 10.3934/publichealth.2016.3.520
  • Importance 

    Twitter represents a growing aspect of the social media experience and is a widely used tool for public education in the 21st century. In the last few years, there has been concern about the dissemination of false health information on social media. It is therefore important that we assess the influencers of this health information in the field of cardiology.

    Objective 

    We sought to identify the top 100 Twitter influencers within cardiology, characterize them, and examine the relationship between their social media activity and academic influence.

    Design 

    Twitter topic scores for the topic search “cardiology” were queried on May 01, 2020 using the Right Relevance application programming interface (API). Based on their scores, the top 100 influencers were identified. Among the cardiologists, their academic h-indices were acquired from Scopus and these scores were compared to the Twitter topic scores.

    Result 

    We found out that 88/100 (88%) of the top 100 social media influencers on Twitter were cardiologists. Of these, 63/88 (72%) were males and they practiced mostly in the United States with 50/87 (57%) practicing primarily in an academic hospital. There was a moderately positive correlation between the h-index and the Twitter topic score, r = +0.32 (p-value 0.002).

    Conclusion 

    Our study highlights that the top ranked cardiology social media influencers on Twitter are board-certified male cardiologists practicing in academic settings in the US. The most influential on Twitter have a moderate influence in academia. Further research should evaluate the relationship between other academic indices and social media influence.



    1. Introduction

    In the last decades, the world energy dem and has significantly raised. With the decay of fossil resources, renewable energy sources are facing a growing dem and . Among them, ocean wave energy is one of the most promising alternatives regarding the production of electricity [1]. This renewable energy source provides a high power density when compared, for instance, with solar and wind energies. Additionally it is more reliable than most of the other renewable energy sources, since wave power availability can surpass 90 percent of the time while solar and wind availability only reach 20 to 30 percent of the time [2]. This allows the high utilization of wave power plants over the year, as well as their customization through engineering solutions that match those devices to different ocean climates [3]. Although in an early stage of development when compared with more mature renewable energy sources, different countries with exploitable wave power resources started considering wave energy as a possible source of power supply. However, devices suitable to harness this kind of renewable energy source and convert it into electricity are not yet commercially competitive [1] when compared with more mature renewable energies, such as wind and solar. Currently there are numerous concepts of wave energy converters (WEC) being developed and tested around the world which require a great deal of investigation. Some of them have already been submitted to real ocean conditions and a few full-scale devices have been operating under a more or less continuous basis [4].

    This paper is focused on the development of a WEC 3D CAD numerical model suitable to be applied under different combinations of buoy positions and resultant hydrodynamic forces acting upon the buoy, function of specific sea wave parameters found on the deployment site. The sizing of the floating buoy and the materials selected to build the components of the WEC can be optimized and customized to each specific site conditions, leading thus to an improved WEC performance at lower costs.

    The selection and analysis of different types of elastic materials and their influence on the structural behavior of a near shore floating point absorber WEC was analyzed. Although the FEA is widespread throughout several engineering domains, it is not so exploited in wave energy domain. Resorting to FEA, the influence of several characteristics such as the dimensions, different wave parameters, hydrodynamic forces and elastic material properties on the structural behavior of a given floating point absorber wave energy converter WEC can be revealed. In order to do this, after a brief characterization of the device, a 3D CAD numerical model was built and several FEA were performed through a commercial finite element code. Among other parameters, the magnitude of the resultant hydrodynamic forces acting upon each buoy is needed. This input data is supplied by the WEC time domain simulator (TDS) implemented in Matlab/Simulink software and based on the WEC dynamic model previously developed [5].

    2. WEC working principle, model and simulator

    This section briefly describes the working principle of a small scaled WEC equipped with a hydraulic power take-off (PTO) as well as the corresponding dynamic model. This model was used as a basis to develop a TDS, built using Matlab/Simulink software. The TDS was therefore used to obtain the force values used as inputs in the commercial finite element code.

    The general WEC architecture is depicted in Figure 1 [5]. It belongs to the point absorber category, since its characteristic dimension has a negligible size when compared to the ocean wavelength [6]. Additionally, this device can also be classified as a near-shore WEC since it should be deployed at intermediate water depth, according with the relative depth criterion [7]. The components of the hydraulic PTO system should be enclosed in a sealed waterproof concrete mooring foundation placed at the seabed. For a detailed description of a hydraulic PTO see [8,9,10] .

    Figure 1. 3D CAD model of the WEC.






    The main components are a spherical buoy with 200 mm radius, which floats with the sea waves, connected to a double effect hydraulic cylinder by supporting cables. A cardan joint connects the piston rod of the hydraulic cylinder to the concrete mooring. Although three modes of motion are possible (heave, roll and pitch) due to the cardan joint, for simplicity reasons the floating buoy is assumed to oscillate with the sea waves only in heave mode. When submitted to the sea waves the buoy floats and moves upwards under the influence of a wave crest and moves downwards under the effect of a wave trough. Other hydraulic PTO components are four non-returnable valves, an oil tank, a hydraulic accumulator and a hydraulic motor mechanically coupled to an electric generator. The force acting upon the buoy is transmitted through the hydraulic PTO. As a consequence the hydraulic cylinder pumps oil from the tank to the hydraulic accumulator and the fluid returns to the tank through the hydraulic motor. The alternating oil flow is rectified by the non-returnable valves and is smoothed by the hydraulic accumulator which could also be used as energy storage. The goal is to deliver a reasonable smooth electrical output. The continuous oil flow through the hydraulic motor will be converted into rotary motion and will drive an electric generator.

    A more detailed description of the entire WEC used here can be found in [11].

    A previously developed WEC dynamic model [5] describes the buoy heave motion with respect to its acceleration. It is based on the second Newton's law and assumes that the buoy heave motion is excited by the sea waves. Due to the model nonlinearities, a simulator in time domain is preferable instead of a simulator in frequency domain. The corresponding WEC TDS was built using Matlab/Simulink software. It intends to simulate the dynamic behavior of the WEC buoy due to the action of sea waves. All equations from the mathematical model were grouped in a dynamic model block under individual subsystems. Another block simulates the sea wave equation. This is shown in Figure 2a) . More details about this subject can be found in [5]. Several inputs such as buoy and wave data, among others are needed to run the simulation. Figure 2b) exemplifies a 50 s detail of the evolution with time of the total hydrodynamic force acting on the spherical buoy. Different results can be obtained if input parameters are changed in the TDS.

    Figure 2. a) TDS dynamic model block and b) Total force [N] acting on buoy vs. time [s].

    3. WEC finite element model

    The WEC 3D CAD numerical model was initially built using SolidWorksÒ software [11]. The Simulation tool of this software was used to perform FEA in order to simulate different sea conditions and to evaluate the influence of dimensions and material properties of the WEC components on its structural behavior.

    Figure 3a) shows the 3D CAD model that was developed, as well as the boundary and load conditions considered. It can be observed that the inferior half of the cardan joint, represented by green arrows, is rigidly fixed. Therefore, constraints of no displacements and rotations are applied to simulate the WEC mooring system. Based on data retrieved from Figure 2b) , it was assumed a maximum resultant hydrodynamic force of 50 x 103 N (peak to peak amplitude) , which corresponds to a pressure of 8 × 10-5 Nm-2. This pressure, represented in Figure 3a) by the pink arrows, is applied to the surface elements. Its direction is a function of the position of the hydraulic cylinder piston rod and changes if the retracted or the advanced position is simulated.

    Figure 3.a) 3D CAD model with boundary and applied load conditions, retracted position of hydraulic cylinder piston rod and b) Mesh geometry of finite element model.

    Regarding the finite element model, a relatively fine mesh of triangular tetrahedral solid elements was applied, as depicted in Figure 3b) . A meshing sensitivity study was previously conducted to guarantee that the resultant solid mesh has the required accuracy. In all FEA simulations carried out in this work the whole WEC numerical model was always analyzed, no axis symmetric solutions were used.

    Figures 3a) and 3b) represent both the retracted position of the hydraulic cylinder piston rod, corresponding to the wave through. The wave crest situation corresponds to the opposite stroke position. From a structural point of view, the advanced position of the hydraulic cylinder piston rod leads to a higher magnitude of stresses when compared with the retracted position of the hydraulic cylinder piston rod [5]. Therefore the results presented in the following section only reflect the advanced position of the hydraulic cylinder piston rod.

    Additionally, only the condition corresponding to the buoy partially submerged was considered in this analysis. When compared with the other two conditions — buoy at the surface and totally submerged buoy — the partially submerged buoy condition leads to a considerable increase on both maximum stress and displacements values. This corresponds to the critical position of the buoy [5]. Furthermore, the partially submerged buoy condition is the most expected position when the spherical buoy heaves due to the action of the sea waves.

    In what concerns the buoy dimensions it was also demonstrated that, regardless of the buoy dimensions and the considered WEC components size, the increase of the dimensions leads, for the same level of applied load, to the increase on both stress and displacements values. This is an expected behavior since the area submitted to the pressure resulting from the resultant hydrodynamic forces acting on the buoy is greater [5]. However this is not a desirable situation and can be avoided with the resizing of the WEC.

    4. Results and discussion

    Several simulations were performed using SolidWorksÒ software in order to evaluate the structural response of the WEC when submitted to specific loading conditions. The objective was to demonstrate that the developed WEC numerical model is able enough to be optimized in terms of dimensions and materials of the WEC components. Therefore, several materials or combinations between different materials were simulated to demonstrate which lead to the lowest level of stress concentration as well as displacements, when the spherical buoy is submitted to a resultant hydrodynamic force. The magnitude of this resultant hydrodynamic force depends of the specific sea wave parameters found on the deployment site.

    Materials such as polyethylene, nylon 6/10 and silicone were considered for both buoy core and shell. Although most of the buoys commercially available have a polyurethane core and a high density polyethylene shell, in this work the same solid material was considered for core and shell. Materials such as AISI 316 stainless steel (SS) , aluminum alloy 6063 T6 (AA) and high strength steel (HSS) were selected for the supporting cables, hydraulic cylinder and cardan joint. Table 1 resumes their relevant elastic material properties: Young’s modulus, Poisson coefficient, yield strength and density.

    Table 1. Selected elastic material properties for the WEC main components.
    Material Young’s modulus (Nmm-2) Poisson coefficient Yield strength (Nmm-2) Density (kgm-3)
    Polyethylene 1860 × 10-6 0.39 30 940
    Nylon 6/10 8300 0.28 139 1400
    Silicone 112000 0.28 120 2330
    AISI 316 SS 193000 0.27 172 8000
    AA 6063 T6 69000 0.33 215 2700
    HSS 21000 0.28 620 7700
     | Show Table
    DownLoad: CSV

    Figure 4 shows the Von Mises stress gradient for a polyethylene spherical buoy partially submerged with a radius of 200 mm, considering the advanced position of the hydraulic cylinder piston rod and assuming that the hydraulic cylinder and cardan joint are both made of SS, AA and HSS, respectively.

    Figure 4. Von Mises Stress field for 200 mm radius polyethylene spherical buoy partially submerged assuming remaining WEC components made of: a) SS, b) AA and c) HSS.

    The analysis based on the finite element method provides not only an insight into the stress concentration magnitude and location as well as the maximum value of the displacement and their corresponding location, as shown in Figure 4.

    For the polyethylene buoy, results reveal that maximum stress (given by the red color in Figure 4) exceeded the yield strength of the material. This means that plastic deformation is reached and , consequently, the collapse of the structure. It should be highlighted that plastic deformation only occurs at the supporting cables within a restricted location when the HSS material is chosen. Otherwise, for the other two materials considered (SS and AA) the maximum stress largely exceeds the yield strength of material at the hydraulic cylinder piston rod and at the cardan joint.

    Concerning the displacement fields, it is clear that AA leads to maximum values than those obtained for SS or HSS, where similar values are observed, as depicted in Figure 5. It can be concluded that AA seems to be unsuitable due to the higher stresses and displacements attained for the buoy dimensions and the applied load level considered in this study. This behavior is not surprising if elastic material properties, in particular the Young’s modulus of AA, are compared with those of SS or HSS. The lower AA Young’s modulus corresponds to a low stiffness, which means that the deformation expected will be greater, according with the results presented, namely in Figure 5. However a low stiffness can represent an advantage for the supporting cables since an overdue life can be expected due to the load cycles they are submitted.

    Figure 5. Displacement field for 200 mm radius polyethylene spherical buoy partially submerged assuming remaining WEC components made of: a) SS, b) AA and c) HSS.

    It should be highlighted that an extremely high hydrodynamic force value was considered during the simulation process, which justifies the results obtained.

    Another simulation was done assuming again a polyethylene spherical buoy and considering that both the hydraulic cylinder and cardan joint are made of HSS. Only the material of the supporting cables was changed: cables made of SS, AA and HSS are analyzed. Figures 6 and 7 show the corresponding Von Mises stress and displacement fields for the described simulation conditions.

    Figure 6. Von Mises stress field for supporting cables made of: a) SS, b) AA and c) HSS assuming polyethylene spherical buoy and remaining WEC components made of HSS.
    Figure 7. Displacement field for supporting cables made of: a) SS, b) AA and c) HSS assuming polyethylene spherical buoy and remaining WEC components made of HSS.

    As expected once again, the areas of higher stress concentration are located in the hydraulic cylinder piston rod and in the supporting cables. Regarding maximum stress distribution, no significant differences were observed between the supporting cables made of SS or AA. However, for the AA cables is observed a slight increase of the stress values on the hydraulic cylinder. The poor mechanical behavior achieved for the AA material is confirmed by the higher displacements obtained, as shown in Figure 7. Thus, materials with a low Young’s modulus seem to be unsuitable.

    In order to analyze the influence of different buoy materials on the mechanical behavior, all the WEC main components are assumed to be made of HSS. Materials such as nylon and silicone were considered for the buoy. Simulation results revealed that, regardless of the material considered for the buoy, no relevant differences are observed in maximum stress, as illustrated in Figure 8. A significant increase in displacement values is observed at the buoy itself when polyethylene is considered, as demonstrated in Figure 9. Once again, among the several buoy materials, polyethylene is the one that presents the lowest Young’s modulus.

    Figure 8. Von Mises Stress field assuming WEC main components made of HSS and spherical buoy made of: a) Silicone, b) Nylon and c) Polyethylene.
    Figure 9. Displacement field assuming WEC main components made of HSS and spherical buoy made of: a) Silicone, b) Nylon and c) Polyethylene.

    It is important to quantify in what manner the level of the applied load can induce the plastic deformation of the structure. Thus, half of the original resultant hydrodynamic force applied corresponding to a pressure of 4 × 10-5 Nm-2, was considered.

    Figure 10 presents the influence of the resultant hydrodynamic force on the structural behavior of the WEC, considering a polyethylene spherical buoy and all the main components of the WEC made of HSS. Comparing Figure 10a) , Figure 4c) and Figure 6c) for stresses and Figure 10b) , Figure 5c) and Figure 7c) for displacement fields, it can be concluded that plastic deformation can be avoided with the decrease of the resultant hydrodynamic force, as it was demonstrated in Figure 10, where half of the original values for stresses and displacements are achieved. It is also important to analyze the influence of the size of the components, function of the material properties. The influence of the increased diameters of the supporting cables and hydraulic cylinder piston rod was calculated using the original pressure value (8 × 10-5 Nm-2) , a polyethylene spherical buoy and assuming that the WEC main components are made of SS and HSS. An increase of 5 mm on both supporting cables and hydraulic cylinder piston rod diameters was considered.

    Figure 10. a) Von Mises Stress field and b) displacement field assuming polyethylene spherical buoy, WEC components made of HSS, 25 kN resultant hydrodynamic force.

    Figures 11 and 12 depict the simulation results for the conditions described in the last paragraph, in terms of maximum stress and displacement values, respectively.

    Figure 11. Von Mises Stress field assuming polyethylene spherical buoy, 50 kN resultant hydrodynamic force and : a) WEC main components made of SS and 20 mm diameter supporting cables; b) WEC main components made of SS, 20 mm diameter supporting cables and 25 mm hydraulic cylinder piston rod diameter and c) WEC main components made of HSS, 20 mm diameter supporting cables and 25 mm hydraulic cylinder piston rod diameter.
    Figure 12. Displacement field assuming polyethylene spherical buoy50 kN resultant hydrodynamic force and : a) WEC main components made of SS and 20 mm diameter supporting cables; b) WEC main components made of SS, 20 mm diameter supporting cables and 25 mm hydraulic cylinder piston rod diameter and c) WEC main components made of HSS, 20 mm diameter supporting cables and 25 mm hydraulic cylinder piston rod diameter.

    As expected, from the comparison between Figure 4a) and Figure 11a) as well as between Figure 5a) and Figure 12a) , for SS material and for the increased diameter of the supporting cables, is obtained a significant reduction of stress and displacement values, but only at the supporting cables. For the hydraulic cylinder piston rod, even with the increase on its diameter, the maximum value for the Von Mises Stress is around 200 × 106 Pa, as shown in Figure 11b) .

    With the applied load level and since SS has a yield strength of 172 × 106 Pa, plastic deformation is undoubtedly reached, although relatively low displacement values are attained, as depicted in Figure 12b) . Moreover, no relevant differences on displacement field values are obtained with the increase of the diameter of the hydraulic cylinder piston rod. However, the scenario is quite different if HSS is considered. This material leads to the lowest magnitude of stresses and displacements achieved, in particular when the supporting cables and hydraulic cylinder piston rod are resized. This is demonstrated by the comparison between Figure 5c) and Figure 11c) for stress values and Figure 6c) and Figure 12c) for displacement values. Plastic deformation is never attained because the yield strength of the material is not reached even if a higher level of load is applied.

    5. Conclusion

    The purpose of this work was to provide a WEC 3D CAD numerical model able enough to be customized, depending on different combinations of buoy position and resultant hydrodynamic forces acting upon the WEC floating buoy, function of specific sea wave parameters found on the deployment site. To demonstrate its robustness, several materials or combinations between different materials and sizing of WEC components, as well as loading magnitudes were simulated, using FEA, and their influence on the WEC structural performance was analyzed. For the conditions simulated, it was demonstrated that materials with low stiffness and low strength lead to a structural collapse, for the load level applied and sizes considered. For this kind of materials, even when the dimensions of the main WEC components are increased, plastic deformation tends to occur. Furthermore, the developed model proved that it can be very useful in order to easily test the structural behavior of the main WEC components when different buoy positions are assumed. Regarding the dimensions and materials of the WEC main components, it is possible to optimize the model, according with the applied load level, which is a function of the resultant hydrodynamic forces acting upon the buoy.

    Conflict of Interest

    All authors declare no conflicts of interest in this paper.



    Conflict of interest



    The authors have no conflict of interest to declare.

    [1] Lokot T, Diakopoulos N (2016) News Bots: Automating news and information dissemination on Twitter. Digit Journal 4: 682-699.
    [2] Arora A, Bansal S, Kandpal C, et al. (2019) Measuring social media influencer index- insights from facebook, Twitter and Instagram. J Retail Consum Serv 49: 86-101. doi: 10.1016/j.jretconser.2019.03.012
    [3] Lou C, Yuan S (2019) Influencer Marketing: How Message Value and Credibility Affect Consumer Trust of Branded Content on Social Media. J Interact Advert 19: 58-73. doi: 10.1080/15252019.2018.1533501
    [4] Featherstone JD, Ruiz JB, Barnett GA, et al. (2020) Exploring childhood vaccination themes and public opinions on Twitter: A semantic network analysis. Telemat Inform 54: 101474. doi: 10.1016/j.tele.2020.101474
    [5] McNeill A, Harris PR, Briggs P (2016) Twitter influence on UK vaccination and antiviral uptake during the 2009 H1N1 pandemic. Front Public Health 4: 26. doi: 10.3389/fpubh.2016.00026
    [6] Borgmann H, Loeb S, Salem J, et al. (2016) Activity, content, contributors, and influencers of the twitter discussion on urologic oncology. Urol Oncol 34: 377-383. doi: 10.1016/j.urolonc.2016.02.021
    [7] Waszak PM, Kasprzycka-Waszak W, Kubanek A (2018) The spread of medical fake news in social media – The pilot quantitative study. Health Policy Technol 7: 115-118. doi: 10.1016/j.hlpt.2018.03.002
    [8] Yusuf S, Rangarajan S, Teo K, et al. (2014) Cardiovascular Risk and Events in 17 Low-, Middle-, and High-Income Countries. N Engl J Med 371: 818-827. doi: 10.1056/NEJMoa1311890
    [9] Xu WW, Chiu IH, Chen Y, et al. (2015) Twitter hashtags for health: applying network and content analyses to understand the health knowledge sharing in a Twitter-based community of practice. Qual Quant 49: 1361-1380. doi: 10.1007/s11135-014-0051-6
    [10] Park H, Reber BH, Chon MG (2016) Tweeting as Health Communication: Health Organizations' Use of Twitter for Health Promotion and Public Engagement. J Health Commun 21: 188-198. doi: 10.1080/10810730.2015.1058435
    [11] Bornmann L, Daniel HD (2005) Does the h-index for ranking of scientists really work? Scientometrics 65: 391-392. doi: 10.1007/s11192-005-0281-4
    [12] Chandawarkar AA, Gould DJ, Grant Stevens W (2018) The Top 100 Social Media Influencers in Plastic Surgery on Twitter: Who Should You Be Following? Aesthet Surg J 38: 913-917. doi: 10.1093/asj/sjy024
    [13] Varady NH, Chandawarkar AA, Kernkamp WA, et al. (2019) Who should you be following? The top 100 social media influencers in orthopaedic surgery. World J Orthop 10: 327-338. doi: 10.5312/wjo.v10.i9.327
    [14] Pulido CM, Villarejo-Carballido B, Redondo-Sama G, et al. (2020) COVID-19 infodemic: More retweets for science-based information on coronavirus than for false information. Int Sociol 35: 377-392. doi: 10.1177/0268580920914755
    [15] Chou WYS, Oh A, Klein WMP (2018) Addressing Health-Related Misinformation on Social Media. JAMA 320: 2417-2418. doi: 10.1001/jama.2018.16865
    [16] Mehta LS, Fisher K, Rzeszut AK, et al. (2019) Current Demographic Status of Cardiologists in the United States. JAMA Cardiol 4: 1029-1033. doi: 10.1001/jamacardio.2019.3247
    [17] Mehta LS, Fisher K, Rzeszut AK, et al. (2019) Current Demographic Status of Cardiologists in the United States. JAMA Cardiol 4: 1029-1033. doi: 10.1001/jamacardio.2019.3247
    [18] Panhwar MS, Kalra A (2019) Breaking Down the Hierarchy of Medicine. Eur Heart J 40: 1482-1483. doi: 10.1093/eurheartj/ehz264
    [19] Aaltonen S, Kakderi C, Hausmann V, et al. (2013) Social media in Europe: Lessons from an online survey. Proceedings of the 18th UKAIS Conference Available from: http://usir.salford.ac.uk/id/eprint/28500/.
    [20] Java A, Song X, Finin T, et al. (2007) Why we twitter: understanding microblogging usage and communities. Proceedings of the 9th WebKDD and 1st SNA-KDD 2007 Workshop on Web Mining and Social Network Analysis - WebKDD/SNA-KDD '07 ACM Press, 56-65. doi: 10.1145/1348549.1348556
    [21] Moreno A, Navarro C, Tench R, et al. (2015) Does social media usage matter? An analysis of online practices and digital media perceptions of communication practitioners in Europe. Public Relat Rev 41: 242-253. doi: 10.1016/j.pubrev.2014.12.006
    [22] Bert F, Zeegers Paget D, Scaioli G (2016) A social way to experience a scientific event: Twitter use at the 7th European Public Health Conference. Scand J Public Health 44: 130-133. doi: 10.1177/1403494815612932
    [23] Hudson S, Mackenzie G (2019) ‘Not your daughter's Facebook’: Twitter use at the European Society of Cardiology Conference 2018. Heart 105: 169-170. doi: 10.1136/heartjnl-2018-314163
    [24] Uhl A, Kolleck N, Schiebel E (2017) Twitter data analysis as contribution to strategic foresight-The case of the EU Research Project “Foresight and Modelling for European Health Policy and Regulations” (FRESHER). Eur J Futur Res 5: 1. doi: 10.1007/s40309-016-0102-4
    [25] Kapoor R, Sachdeva S, Zacks JS (2015) An Analysis of Global Research Trends in Cardiology Over the Last two Decades. J Clin Diagn Res JCDR 9: OC06-OC09.
    [26] Tanoue MT, Chatterjee D, Nguyen HL, et al. (2018) Tweeting the Meeting: Rapid Growth in the Use of Social Media at Major Cardiovascular Scientific Sessions from 2014–2016. Circ Cardiovasc Qual Outcomes 11: e005018. doi: 10.1161/CIRCOUTCOMES.118.005018
    [27] Tanoue M, Nguyen H, Sekimura T, et al. (2018) To Tweet or Not to Tweet: Rapid Growth in the Use of Social Media at Major Cardiovascular Meetings. J Am Coll Cardiol 71: A2633. d. doi: 10.1016/S0735-1097(18)33174-7
    [28] Lee G, Choi AD, Michos ED (2019) Social Media as a Means to Disseminate and Advocate Cardiovascular Research: Why, How, and Best Practices. Curr Cardiol Rev 15.
    [29] Ladeiras-Lopes R, Clarke S, Vidal-Perez R, et al. (2020) Twitter promotion predicts citation rates of cardiovascular articles: a preliminary analysis from the ESC Journals Randomized Study. Eur Heart J 41: 3222-3225. doi: 10.1093/eurheartj/ehaa211
    [30] Bornmann L, Mutz R, Hug SE, et al. (2011) A multilevel meta-analysis of studies reporting correlations between the h index and 37 different h index variants. J Informetr 5: 346-359. doi: 10.1016/j.joi.2011.01.006
  • This article has been cited by:

    1. Teneale McGuckin, Rebecca Sealey, Fiona Barnett, Peter Walla, The use and evaluation of a theory-informed, multi-component intervention to reduce sedentary behaviour in the workplace, 2017, 4, 2331-1908, 1411038, 10.1080/23311908.2017.1411038
    2. Nyssa T. Hadgraft, Elisabeth A. H. Winkler, Genevieve N. Healy, Brigid M. Lynch, Maike Neuhaus, Elizabeth G. Eakin, David W. Dunstan, Neville Owen, Brianna S. Fjeldsoe, Intervening to reduce workplace sitting: mediating role of social-cognitive constructs during a cluster randomised controlled trial, 2017, 14, 1479-5868, 10.1186/s12966-017-0483-1
    3. Birgit Wallmann-Sperlich, Josephine Y. Chau, Ingo Froboese, Self-reported actual and desired proportion of sitting, standing, walking and physically demanding tasks of office employees in the workplace setting: do they fit together?, 2017, 10, 1756-0500, 10.1186/s13104-017-2829-9
    4. Niels van Berkel, Jorge Goncalves, Peter Koval, Simo Hosio, Tilman Dingler, Denzil Ferreira, Vassilis Kostakos, 2019, Context-Informed Scheduling and Analysis, 9781450359702, 1, 10.1145/3290605.3300281
    5. Stuart J.H. Biddle, Jason Bennie, Editorial for Special Issue: Advances in Sedentary Behavior Research and Translation, 2017, 4, 2327-8994, 33, 10.3934/publichealth.2017.1.33
    6. Natalie M. Golaszewski, Andrea Z. LaCroix, Steven P. Hooker, John B. Bartholomew, Group exercise membership is associated with forms of social support, exercise identity, and amount of physical activity, 2021, 1612-197X, 1, 10.1080/1612197X.2021.1891121
    7. Amanda H. Wilkerson, Shristi Bhochhibhoya, Adriana Dragicevic, “It Feels Unhealthy to be Sitting for 40 hours a Week”, 2021, 63, 1076-2752, 322, 10.1097/JOM.0000000000002128
    8. Hana Alkhalidy, Aliaa Orabi, Tamara Alzboun, Khadeejah Alnaser, Islam Al-Shami, Nahla Al-Bayyari, Health-Risk Behaviors and Dietary Patterns Among Jordanian College Students: A Pilot Study, 2021, 8, 2296-861X, 10.3389/fnut.2021.632035
    9. Siriporn Dankachatarn, Anongnard Boonpak, Nattakarn Worrasan, Busma Kama, Donrawee Waeyeng, Mujalin Intaramuean, Junjira Mahaboon, Effects of safety interventions toward workers’ behaviors using the theory of planned behavior in the rubber wood processing industry, 2022, 1080-3548, 1, 10.1080/10803548.2022.2127244
    10. Byron A. Foster, Kylie Seeley, Melinda Davis, Janne Boone-Heinonen, Positive deviance in health and medical research on individual level outcomes – a review of methodology, 2022, 69, 10472797, 48, 10.1016/j.annepidem.2021.12.001
    11. Amanda H. Wilkerson, Nuha Abutalib, Ny’Nika T. McFadden, Shristi Bhochhibhoya, Adriana Dragicevic, Bushra R. Salous, Vinayak K. Nahar, A Social Cognitive Assessment of Workplace Sedentary Behavior among a Sample of University Employees, 2023, 20, 1660-4601, 6476, 10.3390/ijerph20156476
  • Reader Comments
  • © 2021 the Author(s), licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0)
通讯作者: 陈斌, bchen63@163.com
  • 1. 

    沈阳化工大学材料科学与工程学院 沈阳 110142

  1. 本站搜索
  2. 百度学术搜索
  3. 万方数据库搜索
  4. CNKI搜索

Metrics

Article views(20865) PDF downloads(317) Cited by(14)

Article outline

Figures and Tables

Figures(2)  /  Tables(2)

/

DownLoad:  Full-Size Img  PowerPoint
Return
Return

Catalog