scholarly journals Development and Evaluation of the Canteen Connect Online Health Community: Using a Participatory Design Approach in Meeting the Needs of Young People Impacted by Cancer

Cancers ◽  
2021 ◽  
Vol 14 (1) ◽  
pp. 50
Author(s):  
Jennifer Cohen ◽  
Pandora Patterson ◽  
Melissa Noke ◽  
Kristina Clarke ◽  
Olga Husson
Keyword(s):  
Participatory Design ◽  
Positive Impact ◽  
Familial Cancer ◽  
Online Health Communities ◽  
Implementation Evaluation ◽  
Online Health Community ◽  
Health Community ◽  
Health Related ◽  
Adolescent And Young Adults ◽  
Health Communities

Adolescent and young adults (AYAs) impacted by their own or familial cancer require information and peer support throughout the cancer journey to ameliorate feelings of isolation. Online Health Communities (OHC) provide social networks, support, and health-related content to people united by a shared health experience. Using a participatory design (PD) process, Canteen developed Canteen Connect (CC), an OHC for AYAs impacted by cancer. This manuscript outlines the process used to develop CC: (1) A mixed-methods implementation evaluation of Version I of CC (CCv.1); (2) Qualitative workshops utilizing strengths-based approaches of PD and appreciative inquiry to inform the development of CC Version 2 (CCv.2); quantitative implementation evaluation to assess the appropriateness, acceptability, and effectiveness of CCv.2. Through several iterations designed and tested in collaboration with AYAs, CCv.2 had improvements in the user experience, such as the ability to send a private message to other users and the site becoming mobile responsive. Results from the evaluation showed CCv.2 was appropriate for connecting with other AYAs. Most AYAs reported satisfaction with CCv.2 and a positive impact on their feelings of sadness, worry, and/or anxiety. CCv.2 fills an important service provision gap in providing an appropriate and acceptable OHC for AYAs impacted by cancer, with initial promising psychological outcomes.

scholarly journals Social exchange approach in knowledge sharing of online communities – A Case of online health communities at Ho Chi Minh City

2017 ◽  
Vol 1 (Q4) ◽  
pp. 13-24
Author(s):  
Phong Thanh Nguyen ◽  
Tuan Manh Nguyen
Keyword(s):  
Social Exchange ◽  
Positive Impact ◽  
Sense Of Self ◽  
Online Health Communities ◽  
Online Health Community ◽  
Writing Group ◽  
Health Community ◽  
Self Worth ◽  
Face Concern ◽  
Health Communities

The demand to look for information and share information in nowaday society are a huge needed, especially in the internet revolution are developing more and more. The studies proposed the model that includes the benefit factors (sense of self-worth, face concern, reputation and social support) and cost factors (executional costs, cognitive costs) with the points of view of Social Exchange Theory that influences to knowledge donating behavior, knowledge collecting behavior and community promotion among members. The studies will be verified in health care member of the online health communities in Ho Chi Minh City. Quantitative research also was conducted 336 samples were used to evaluate and test the research. The results of the Structural Equation Modeling (SEM) show that the theoretical models are suited the market data and hypotheses of the research model are supported. In particular, factors of the benifit group (sense of self-worth, face concern, reputation and social support) have a positive impact on the knowledge donating behavior and knowledge collecting behavior. In addition, factors of the cost group (executional costs, cognitive costs) have a negative impact the knowledge donating behavior and knowledge collecting behavior. Knowledge donating behavior and knowledge collecting behavior have a positive impact on community promotion to the online health community. In addition, the results of multi-group analysis that there is no difference between knowledge sharing’s writing group and no knowledge sharing’s writing group. The results may be usefull for online health community, hospitals, doctors, individuals and businesses.

scholarly journals Impact of Patient Crowdvotes Aggregated Service Diversity on Doctors� Service Sales in Online Health Community: a Retrospective Study (Preprint)

2018 ◽  
Author(s):  
Hai-Yan Yu ◽  
Jying-Nan Wang ◽  
Ya-Ling Chiu ◽  
Hang Qiu ◽  
Ling Xiao
Keyword(s):  
Retrospective Study ◽  
Good Doctor ◽  
Lorenz Curves ◽  
Online Health Communities ◽  
Online Health Community ◽  
Health Community ◽  
Main Effect ◽  
Health Communities ◽  
Log Linear ◽  
Disease Understanding

BACKGROUND An increasing number of people visit online health communities to esquire health information with doctors. In the online health community (OHC), patient crowds tended to label and vote the doctors’ specialties with encountered disease. Understanding how patients’ online labels can help us understand the service diversity for patients in online health communities and provide constructive suggestions for doctors serving more patients online. OBJECTIVE Our goal was to understand: (1) what kind of patterns are the labels of patient crowdvotes aggregated service diversity, including encountered disease labels and online votes, in a OHC? (2) wheather the patient crowdvotes aggregated service diversity make doctors’ service sales difference in OHC? (3) how can managers in OHC perform to improve doctors’ service sales with the feedback of crowdvotes aggregated service diversity? METHODS We designed a retrospective study with data collected from the largest OHC (Good Doctor website) in China. We first used descriptive statistics to investigate the patient crowdvotes aggregated service diversity. Then a multiple log-linear relationship was adapted to investigate the main and the interaction impact of service diversity on doctors’ service sales. RESULTS Our sample consists of 9,841 doctors from 1,255 different hospitals widely distributed in China. 18,997,018 patients had been serviced by these doctors since they became members of the study OHC. 704,467 votes of doctors’ clinical specialties were labeled by patient crowds in recent two years (Aug.26, 2015-Aug. 25, 2017). Gini coefficient of serviced patients is very high, 0.626, followed by the volume of votes (0.562). Based on the regression model, we found that the coefficients of the control variables, doctor review rating and clinic title, were 0.810(0.041), and 1.735 (0.027), respectively. For the breadth of voted specialties, volume of votes and degree of voted diversity, the standardized coefficient of the main effect were 0.309 (0.038), 0.745 (0.014) and 0.073 (0.018), respectively. All of the estimates are statistically significant at a 0.1% level. CONCLUSIONS Our study provided empirical evidence that the patterns of both the labels of patient crowdvotes aggregated service diversity and doctors’ service sales were of inequality (as illustrated in Lorenz curves) in the distribution of its size of serviced patients in a OHC. Patient crowds’ online labels also leaded to differences in the doctors’ service sales online. The treads of the doctors’ service sales kept increasing as the patient crowdvotes aggregated service diversity increased. Finally, our findings suggested that the higher breadth of voted specialties and degree of voted diversity displayed a greater service sales with a higher review rating, deploying less inequality of Doctors’ service sales.

scholarly journals Study on the Evolution of Information Sharing Strategy for Users of Medical Cloud

2019 ◽  
Author(s):  
Panpan Zhu ◽  
Jiang Shen ◽  
Man Xu
Keyword(s):  
Information Sharing ◽  
Scale Free ◽  
Online Health Communities ◽  
Online Health Community ◽  
Health Community ◽  
Community Information ◽  
Free Network ◽  
Health Communities ◽  
Sharing Behavior ◽  
Community Patients

Abstract Technological advances are driving the growth of online health communities. However, there are some problems such as low user participation and insignificant social benefits in online health communities. This paper discusses the evolution law of information sharing behavior of members of online health community to study the influence of different behaviors on health information sharing results and explore the ways to improve the level of community information sharing. Based on BA scale-free network (Albert-László Barabás and Réka Albert scale-free network) , this paper established an information sharing behavior model for members of online health community with the evolutionary game theory method, and discussed the influence of different game parameters and initial conditions on the evolution results of information sharing behavior of community patients with the method of numerical experiment.Results: It is found that the key to improve the level of community information sharing is to improve the benefit of patients' information sharing, the proportion of patients sharing information at the initial moment, the degree of network nodes, and reduce the sharing cost. Community managers should improve the information conversion ability and information absorption ability of community patients through offline activities, professional guidance and other forms. At the same time, it can reduce the difficulty and risk of information sharing and strengthen the connection among members, thus comprehensively enhancing the value of the community.

scholarly journals Consequences of Gift Giving in Online Health Communities on Physician Service Quality: Empirical Text Mining Study

10.2196/18569 ◽  
2020 ◽  
Vol 22 (7) ◽  
pp. e18569
Author(s):  
Li Peng ◽  
Yanan Wang ◽  
Jing Chen
Keyword(s):  
Health Care ◽  
Service Quality ◽  
Physician Service ◽  
Gift Giving ◽  
Online Health Communities ◽  
Online Health Community ◽  
Interaction Processes ◽  
Health Community ◽  
Health Communities ◽  
Physician Patient

Background Gift giving, which has been a heavily debated topic in health care for many years, is considered as a way of expressing gratitude and to be beneficial for the physician-patient relationship within a reasonable range. However, not much work has been done to examine the influence of gift giving on physicians’ service quality, especially in the online health care environment. Objective This study addressed the consequences of gift giving by mining and analyzing the dynamic physician-patient interaction processes in an online health community. Specifically, gift types (affective or instrumental) based on the motivations and physician-patient tie strength were carefully considered to account for differences in physicians’ service quality. Methods The dynamic interaction processes (involving 3154 gifts) between 267 physicians and 14,187 patients from a well-known online health community in China (haodf.com) were analyzed to obtain empirical results. Results Our results reveal that patient gift giving inspires physicians to improve their service quality as measured by physicians’ more detailed responses and improved bedside manner, and the degree of influence varied according to the strength of the physician-patient tie. Moreover, affective gifts and instrumental gifts had different effects in improving physicians’ service quality online. Conclusions This study is among the first to explore gift giving in online health communities providing both important theoretical and practical contributions. All of our results suggest that gift giving online is of great significance to promoting effective physician-patient communication and is conducive to the relief of physician-patient conflicts.

scholarly journals Converting Visitors of Physicians’ Personal Websites to Customers in Online Health Communities: Longitudinal Study

10.2196/20623 ◽  
2020 ◽  
Vol 22 (8) ◽  
pp. e20623
Author(s):  
Qin Chen ◽  
Xiangbin Yan ◽  
Tingting Zhang
Keyword(s):  
Longitudinal Study ◽  
Panel Data ◽  
Empirical Study ◽  
Conversion Rate ◽  
Online Health Communities ◽  
Online Health Community ◽  
Health Community ◽  
Community Information ◽  
Time Periods ◽  
Health Communities

Background With the dramatic development of Web 2.0, increasing numbers of patients and physicians are actively involved in online health communities. Despite extensive research on online health communities, the conversion rate from visitor to customer and its driving factors have not been discussed. Objective The aim of this study was to analyze the conversion rate of online health communities and to explore the effects of multisource online health community information, including physician-generated information, patient-generated information, and system-generated information. Methods An empirical study was conducted to examine the effects of physician-generated, patient-generated, and system-generated information on the conversion rate of physicians’ personal websites by analyzing short panel data from 2112 physicians over five time periods in a Chinese online health community. Results Multisource online health community information (ie, physician-generated, patient-generated, and system-generated information) positively affected the conversion rate. Physician-generated and patient-generated information showed a substitute relationship rather than a complementary relationship. In addition, the usage time of a personal website positively moderated patient-generated information, but negatively moderated physician-generated information. Conclusions This study contributes to the electronic health literature by investigating the conversion rate of online health communities and the effect of multisource online health community information. This study also contributes to understanding the drivers of conversion rate on service websites, which can help to successfully improve the efficiency of online health communities.

scholarly journals Consequences of Gift Giving in Online Health Communities on Physician Service Quality: Empirical Text Mining Study (Preprint)

2020 ◽  
Author(s):  
Li Peng ◽  
Yanan Wang ◽  
Jing Chen
Keyword(s):  
Health Care ◽  
Service Quality ◽  
Physician Service ◽  
Gift Giving ◽  
Online Health Communities ◽  
Online Health Community ◽  
Interaction Processes ◽  
Health Community ◽  
Health Communities ◽  
Physician Patient

BACKGROUND Gift giving, which has been a heavily debated topic in health care for many years, is considered as a way of expressing gratitude and to be beneficial for the physician-patient relationship within a reasonable range. However, not much work has been done to examine the influence of gift giving on physicians’ service quality, especially in the online health care environment. OBJECTIVE This study addressed the consequences of gift giving by mining and analyzing the dynamic physician-patient interaction processes in an online health community. Specifically, gift types (affective or instrumental) based on the motivations and physician-patient tie strength were carefully considered to account for differences in physicians’ service quality. METHODS The dynamic interaction processes (involving 3154 gifts) between 267 physicians and 14,187 patients from a well-known online health community in China (haodf.com) were analyzed to obtain empirical results. RESULTS Our results reveal that patient gift giving inspires physicians to improve their service quality as measured by physicians’ more detailed responses and improved bedside manner, and the degree of influence varied according to the strength of the physician-patient tie. Moreover, affective gifts and instrumental gifts had different effects in improving physicians’ service quality online. CONCLUSIONS This study is among the first to explore gift giving in online health communities providing both important theoretical and practical contributions. All of our results suggest that gift giving online is of great significance to promoting effective physician-patient communication and is conducive to the relief of physician-patient conflicts.

scholarly journals Patient Continued Use of Online Health Care Communities: Web Mining of Patient-Doctor Communication (Preprint)

2017 ◽  
Author(s):  
Bing Wu
Keyword(s):  
Patient Satisfaction ◽  
Web Mining ◽  
Perceived Usefulness ◽  
Online Health Communities ◽  
Information System Success ◽  
Online Health Community ◽  
Web Spider ◽  
Health Community ◽  
Information System Success Model ◽  
Health Communities

BACKGROUND In 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. OBJECTIVE The 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. METHODS A 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. RESULTS The 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. CONCLUSIONS First, 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.

scholarly journals IoT Based Health—Related Topic Recognition from Emerging Online Health Community (Med Help) Using Machine Learning Technique

Electronics ◽  
2020 ◽  
Vol 9 (9) ◽  
pp. 1469 ◽  
Author(s):  
Pradeepa Sampath ◽  
Gayathiri Packiriswamy ◽  
Nishmitha Pradeep Kumar ◽  
Vimal Shanmuganathan ◽  
Oh-Young Song ◽  
...  
Keyword(s):  
Machine Learning ◽  
Language Processing ◽  
Learning Algorithm ◽  
Vital Role ◽  
Online Health Communities ◽  
Health Community ◽  
Chi Squared ◽  
Health Related ◽  
Health Communities ◽  
Processing Techniques

The unprompted patient’s and inimitable physician’s experience shared on online health communities (OHCs) contain a wealth of unexploited knowledge. Med Help and eHealth are some of the online health communities offering new insights and solutions to all health issues. Diabetes mellitus (DM), thyroid disorders and tuberculosis (TB) are chronic diseases increasing rapidly every year. As part of the project described in this article comments related to the diseases from Med Help were collected. The comments contain the patient and doctor discussions in an unstructured format. The sematic vision of the internet of things (IoT) plays a vital role in organizing the collected data. We pre-processed the data using standard natural language processing techniques and extracted the essential features of the words using the chi-squared test. After preprocessing the documents, we clustered them using the K-means++ algorithm, which is a popular centroid-based unsupervised iterative machine learning algorithm. A generative probabilistic model (LDA) was used to identify the essential topic in each cluster. This type of framework will empower the patients and doctors to identify the similarity and dissimilarity about the various diseases and important keywords among the diseases in the form of symptoms, medical tests and habits.

Exploring the collective knowledge curation process of online health communities

2016 ◽  
Author(s):  
◽  
Wanli Xing
Keyword(s):  
Social Support ◽  
Information Flow ◽  
Flow Patterns ◽  
University Of Missouri ◽  
Online Health Communities ◽  
Health Community ◽  
Health Related ◽  
Health Communities ◽  
The University ◽  
Relationship Of

[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT AUTHOR'S REQUEST.] More and more people turn to online health communities for social support to satisfy their health-related needs. Previous studies on social support and online health communities in general have focused on the content of social support and the relationship of social support with other entities using traditional social science methods. Little is known about how social support facilitate the knowledge curation process in an online health community. Moreover, the presence of misinformation in online health communities also calls for research into the knowledge curation process in order to reduce the risk of misinformation. This study uses data mining technologies to analyze around one million posts across 23 online health communities. It aims to reveal how information, through social support, flows between the community users working as a whole to dynamically curate knowledge and further interacts with information accuracy. This data-centric research in online health communities 1) discovered that xperiphery users instead of core users dominate the quantitative and content information flow; 2) identified three temporal information flow patterns for the knowledge curation process -- each with distinct characteristics; 3) found that information accuracy differed significantly over the identified information flow patterns and time and the information accuracy variation trends with each information flow pattern was identified as well. These findings not only have important implications for social support use, delivery and social support research methodologies but also can inform future online health platform design.

q-Rung orthopair fuzzy TOPSIS method and the application to information service quality evaluation in online health community

2021 ◽  
pp. 1-18
Author(s):  
Aihui Ye ◽  
Runtong Zhang ◽  
Pei Wu ◽  
Yuping Xing
Keyword(s):  
Information Quality ◽  
Quality Evaluation ◽  
Evaluation Criteria ◽  
Information Service ◽  
Topsis Method ◽  
Online Health Communities ◽  
Online Health Community ◽  
Health Community ◽  
Pca Method ◽  
Health Communities

Since the information quality in the online health community is very important for users to obtain valuable health information, information quality evaluation is a necessary research that involves a multi-attribute decision-making (MADM) problem. However, few researches have been done to address both the construction of evaluation criteria and the expression and processing of fuzzy information, especially in online health community. This manuscript proposes a novel evaluation framework of information service quality combined principal component analysis (PCA) method with the TOPSIS method under q-rung orthopair fuzzy set (q-ROFS) environment. An accurate evaluation criteria system is optimized by the PCA method, and the q-ROF TOPSIS method is proposed to process larger space of fuzzy evaluation information and overcome information loss and information distortion, in which a new distance measure between q-ROFSs is defined and an entropy weight model is initiated to determine the unknown weight of attribute. Moreover, a numerical example is performed to prove the practicability and superiority of the method through comparative analysis, which gives clear results of information quality evaluation of four online health communities. This research ends with fuzzy decision-making theory and application, and provides references for standardizing and improving the information quality of online health communities.

Sign in / Sign up

Export Citation Format

Share Document