Privacy Concern of Health Information Disclosure in mHealth: The Moderate Effect of Social Support (Preprint)

2020 ◽  
Author(s):  
Yuanyuan Dang ◽  
Shanshan Guo ◽  
Xitong Guo
Keyword(s):  
Social Support ◽  
Health Information ◽  
Emotional Support ◽  
Information Disclosure ◽  
Perceived Health ◽  
Privacy Concern ◽  
Informational Support ◽  
Privacy Concerns ◽  
Information Sensitivity ◽  
Moderate Effect

BACKGROUND The mobile health (mHealth) provides a new opportunity for patients’ disease prediction and health self-management. At the same time, privacy problems in mHealth have brought forth significant attention concerning patients' online health information disclosure and hindered mHealth development. OBJECTIVE Privacy calculus theory (PCT) has been widely used to understand personal information disclosure behaviors with the basic assumption of a national and linear decision-making process. However, people’s cognitive behavior processes are complex and mutual. In attempting to close this knowledge gap, we further optimize the information disclosure model of patients based on PCT by identifying the mutual relationship between costs (privacy concerns) and benefits. Social support, which has been proved to be a distinct and significant disclosure benefit of mHealth, was chosen to be the representative benefit of information disclosure in mHealth. METHODS From an individual perspective, a structural equation model with privacy concerns, health information disclosure intention in mHealth, and social support from mHealth has been examined. RESULTS 253 randomly selected participants provided validated questionnaire. The result indicated that perceived health information sensitivity positively enhances the privacy concern (0.505, p<0.01), and higher privacy concern levels will decrease the health information disclosure intention (-0.338, p<0.01). Various aspects of individual characters influence perceived health information sensitivity in different ways. The informational support has a negatively moderate on reduce the positive effect between perceived health information sensitivity and privacy concerns (-0.171, p<0.1) and will decrease the negative effect between privacy concerns and health information disclosure intention(-0.105, p<0.1). However, emotional support has no directly moderate effect on both privacy concerns and health information disclosure intention. CONCLUSIONS The results indicate that social support can be regarded as a disutility reducer, that is, on the one hand, it reduces the privacy concerns of patients; on the other hand, it also reduces the negative impact of privacy concerns on information disclosure intention. Moreover, the moderate effect of social support is partially supported. Informational support, one demission of social support, is significant, while the other demission, emotional support, is not significant in mHealth. Furthermore, the results are different among patients with different individual characteristics. This study also provides specific theoretical and practical implications to enhance the development of mHealth.

scholarly journals The Association of Sources of Support, Types of Support and Satisfaction with Support Received on Perceived Stress and Quality of Life of Cancer Patients

2021 ◽  
Vol 20 ◽  
pp. 153473542199490
Author(s):  
Iván Ruiz-Rodríguez ◽  
Isabel Hombrados-Mendieta ◽  
Anabel Melguizo-Garín ◽  
Mª José Martos-Méndez
Keyword(s):  
Quality Of Life ◽  
Social Support ◽  
Cancer Patients ◽  
Perceived Stress ◽  
Emotional Support ◽  
Multidimensional Analysis ◽  
Informational Support ◽  
Cancer Data ◽  
The Family

Introduction: The aim of the present study is to carry out a multidimensional analysis of the relationship of social support with quality of life and the stress perceived by cancer patients. Methods: The participants were 200 patients with cancer. Data was gathered on sociodemographic characteristics, health, quality of life, social support and perceived stress. Results: Frequency of and satisfaction with different sources and types of support are related positively with improvement of quality of life and negatively with perceived stress. The emotional support from the partner and the emotional and informational support from the family are significant predictors of quality of life. Emotional support from the family reduces patients’ perceived stress. Satisfaction with emotional support from the partner and with the informational support from friends and family increases quality of life. Satisfaction with emotional support from the family and with informational support from friends decreases patients’ perceived stress. Instrumental support and support provided by health professionals are not good predictors of quality of life and perceived stress. Satisfaction with the support received is more significantly related with quality of life and stress than the frequency with which the sources provide support. Conclusions: These results have important practical implications to improve cancer patients’ quality of life and reduce their perceived stress through social support. Designing intervention strategies to improve satisfaction with the support provided to patients by their closest networks results in a global benefit for the patient’s quality of life.

Social Support and Happiness in Immigrant Women in Spain

2012 ◽  
Vol 110 (3) ◽  
pp. 977-990 ◽  
Author(s):  
Juan Manuel Dominguez-Fuentes ◽  
María Isabel Hombrados-Mendieta
Keyword(s):  
Social Support ◽  
Social Services ◽  
Emotional Support ◽  
Indigenous Population ◽  
Immigrant Women ◽  
Instrumental Support ◽  
Informational Support ◽  
The Social ◽  
The Family ◽  
Sources Of Support

The association between perceived social support and happiness was investigated in women who are members of various associations in Malaga (Spain) that work with immigrant women. Based on the Social Convoy model, the association between sources of support, frequency of support, satisfaction with support, and happiness reported by women were examined. The main social support predictor of happiness was satisfaction with the support received. Thus, the best predictors of happiness were emotional support from the family and instrumental support from the indigenous population and associations. The best predictor of frequency of support was the frequency of informational support received from social services. These results may prove useful for developing lines of action or interventions centred on the social network and the functions that social support can fulfil among immigrant women.

Understanding social influence on mobile social networking sites: A social support perspective

2017 ◽  
Vol 35 (2) ◽  
pp. 220-229 ◽  
Author(s):  
Tao Zhou
Keyword(s):  
Social Support ◽  
Social Influence ◽  
Social Networking ◽  
Emotional Support ◽  
Social Networking Sites ◽  
Service Providers ◽  
Informational Support ◽  
Mobile Social Networking ◽  
The Social ◽  
Mobile Sns

Due to the social networking relationship, users’ continuance of social networking sites (SNS) may receive social influence from their peers and referents. This research identified the effect of social support on social influence in mobile SNS. Social support consists of both informational support and emotional support. Social influence is reflected by three factors: subjective norm, social identity and group norm. The results suggested that social support has a significant effect on social influence. The results imply that service providers need to build a supportive climate in order to facilitate social influence and users’ continuance usage.

scholarly journals Antecedents and consequences of the perceived usefulness of smoking cessation online health communities

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Chenglong Li ◽  
Hongxiu Li ◽  
Reima Suomi
Keyword(s):  
Social Support ◽  
Smoking Cessation ◽  
Knowledge Sharing ◽  
Emotional Support ◽  
Perceived Usefulness ◽  
Informational Support ◽  
Continuance Intention ◽  
Content Type ◽  
Online Health Communities ◽  
Health Communities

PurposeAn empirical study investigated the antecedents to perceived usefulness (PU) and its consequences in the context of smoking cessation online health communities (OHCs).Design/methodology/approachTo validate a research model for perceived informational support, perceived emotional support and perceived esteem support, the authors conducted a partial-least-squares analysis of empirical data from an online survey (N = 173) of users of two smoking cessation OHCs. The proposed model articulates these as antecedents to PU from a social support perspective, and knowledge sharing and continuance intention are expressed as consequences of PU.FindingsThe empirical study identified that the PU of smoking cessation OHCs is influenced by perceived emotional support and perceived esteem support, and perceived informational support indirectly affects PU via these factors. In turn, PU exerts a positive influence on both knowledge sharing and continuance intention. Also, knowledge sharing positively affects continuance intention.Originality/valueThe study contributes to scholarship on users' postadoption behavior in the context of smoking cessation OHCs by disentangling the antecedents to PU from a social support perspective and pinpointing some important consequences of PU. The research also has practical implications for managing smoking cessation OHCs.

scholarly journals CEPTM: A Cross-Edge Model for Diverse Personalization Service and Topic Migration in MEC

2018 ◽  
Vol 2018 ◽  
pp. 1-12 ◽  
Author(s):  
Hongchen Wu ◽  
Huaxiang Zhang ◽  
Lizhen Cui ◽  
Xinjun Wang
Keyword(s):  
Information Disclosure ◽  
Management Strategies ◽  
Mobile User ◽  
High Rate ◽  
Privacy Concern ◽  
Self Disclosure ◽  
Privacy Concerns ◽  
Individual Privacy ◽  
Computing Paradigm ◽  
User Data

For several reasons, the cloud computing paradigm, e.g., mobile edge computing (MEC), is suffering from the problem of privacy issues. MEC servers provide personalization services to mobile users for better QoE qualities, but the ongoing migrated data from the source edge server to the destination edge server cause users to have privacy concerns and unwillingness of self-disclosure, which further leads to a sparsity problem. As a result, personalization services ignore valuable user profiles across edges where users have accounts in and tend to predict users’ potential purchases with insufficient sources, thereby limiting further improvement of QoE through personalization of the contents. This paper proposes a novel model, called CEPTM, which (1) collects mobile user data across multiple MEC edge servers, (2) improves the users’ experience in personalization services by loading collected diverse data, and (3) lowers their privacy concern with the improved personalization. This model also reveals that famous topics in one edge server can migrate into several other edge servers with users’ favorite content tags and that the diverse types of items could increase the possibility of users accepting the personalization service. In the experiment section, we use exploratory factor analysis to mathematically evaluate the correlations among those factors that influence users’ information disclosure in the MEC network, and the results indicate that CEPTM (1) achieves a high rate of personalization acceptance due to the availability of more data as input and highly diverse personalization as output and (2) gains the users’ trust because it collects user data while respecting individual privacy concerns and providing better personalization. It outperforms a traditional personalization service that runs on a single-edge server. This paper provides new insights into MEC diverse personalization services and privacy problems, and researchers and personalization providers can apply this model to merge popular users’ like trends throughout the MEC edge servers and generate better data management strategies.

scholarly journals How Could Peers in Online Health Community Help Improve Health Behavior

2020 ◽  
Vol 17 (9) ◽  
pp. 2995
Author(s):  
Yumei Li ◽  
Xiangbin Yan
Keyword(s):  
Social Support ◽  
Health Behavior ◽  
Social Integration ◽  
Social Relationships ◽  
Support Group ◽  
Emotional Support ◽  
Informational Support ◽  
Mutual Support ◽  
Descriptive Norms ◽  
The Social

Human behavior is the largest source of variance in health-related outcomes, and the increasingly popular online health communities (OHC) can be used to promote healthy behavior and outcomes. We explored how the social influence (social integration, descriptive norms and social support) exerted by online social relationships does affect the health behavior of users. Based on an OHC, we considered the effect of three types of social relationships (friendship, mutual support group and competing group) in the OHC. We found that social integration, descriptive norms and social support (information and emotional support) from the OHC had a positive effect on dietary and exercise behavior. Comparing the effects of different social relationships, we found that the stronger social relationship—friendship—had a stronger effect on health behavior than the mutual support group and competing group. Emotional support had a stronger effect on health behavior than informational support. We also found that the effects of social integration and informational support became stronger as membership duration increased, but the effects of the descriptive norms and emotional support became smaller. This study extended the research on health behavior to the online social environment and explored how the social influence exerted by various social relationships in an OHC affected health behavior. The results could be used for guiding users to make use of online social relationships for changing and maintaining healthy behavior, and helping healthcare websites improve their services.

scholarly journals Investigating Privacy and Information Disclosure Behavior in Social Electronic Commerce

2019 ◽  
Vol 11 (12) ◽  
pp. 3311 ◽  
Author(s):  
Yuan Sun ◽  
Shuyue Fang ◽  
Yujong Hwang
Keyword(s):  
Information Disclosure ◽  
Current Trend ◽  
Perceived Benefits ◽  
Privacy Concern ◽  
Privacy Concerns ◽  
Group Buying ◽  
Internet Users ◽  
Privacy Calculus ◽  
Negative Impacts ◽  
A Current

Social e-commerce has steadily emerged as a current trend for an enormous amount of Internet users. Despite the popularity and prevalence of social e-commerce, many users hesitate to disclose their information due to privacy concerns. This resistance from users impedes the development of social e-commerce enterprises. In order to help enterprises collect more user information and establish better development strategies, this research builds on the Privacy Antecedent-Privacy Concern-Outcomes (APCO) model and the theory of privacy calculus. This research investigates how the privacy antecedents of hot topic interactivity and group buying experience influence users’ privacy concerns and perceived benefits as well as how to further influence users’ information disclosure behavior. The results from 406 questionnaire responses indicate that hot topic interactivity and group buying experience have significant negative impacts on privacy concerns and significant positive impacts on perceived benefits. Privacy concerns negatively influence the behavior of information disclosure while perceived benefits positively influence the behavior of information disclosure. Based on these results, social e-commerce enterprises should promote users’ behaviors of hot topic interactivity and group buying to stimulate users’ information disclosure behavior.

The Provision of Social Support to Injured Athletes: A Qualitative Analysis

1998 ◽  
Vol 7 (4) ◽  
pp. 267-284 ◽  
Author(s):  
Lynne Halley Johnston ◽  
Douglas Carroll
Keyword(s):  
Social Support ◽  
Emotional Support ◽  
Injury Severity ◽  
Medical Knowledge ◽  
Sports Performance ◽  
Informational Support ◽  
Data Indexing ◽  
Personal Assistance ◽  
Practical Support ◽  
Injured Athletes

Twelve seriously injured athletes were asked to describe the provision of eight functional types of support during their rehabilitation. NUD*IST (Nonnumerical Unstructured Data Indexing Searching and Theorizing) was used to organize the data. Overall, the provision of social support largely matched demand. Emotional and practical forms of support decreased with time, while varieties of informational support were increasingly received and preferred over time. The provision of informational and emotional support appeared to be dictated by four temporally sequential appraisals: injury severity, rehabilitation progress, recovery/readiness to return, and sports performance. Practical support in the form of personal assistance greatly depended upon the visibility of the injury and the mobility of the injured athlete. Physiotherapists, doctors, and other currently or previously injured athletes were most likely to provide informational support requiring expert medical knowledge, whereas coaches provided informational support requiring sport-specific expertise. Friends and family were the main source of emotional and practical support. The situational and temporal context of the provision of support is represented diagrammatically.

scholarly journals Development of Social Support Networks by Patients With Depression Through Online Health Communities: Social Network Analysis

10.2196/24618 ◽  
2021 ◽  
Vol 9 (1) ◽  
pp. e24618
Author(s):  
Yingjie Lu ◽  
Shuwen Luo ◽  
Xuan Liu
Keyword(s):  
Social Support ◽  
Social Networks ◽  
Social Network ◽  
Emotional Support ◽  
Mental Health Problems ◽  
Support Networks ◽  
Support Network ◽  
Social Support Networks ◽  
Informational Support ◽  
To Receive

Background In recent years, people with mental health problems are increasingly using online social networks to receive social support. For example, in online depression communities, patients can share their experiences, exchange valuable information, and receive emotional support to help them cope with their disease. Therefore, it is critical to understand how patients with depression develop online social support networks to exchange informational and emotional support. Objective Our aim in this study was to investigate which user attributes have significant effects on the formation of informational and emotional support networks in online depression communities and to further examine whether there is an association between the two social networks. Methods We used social network theory and constructed exponential random graph models to help understand the informational and emotional support networks in online depression communities. A total of 74,986 original posts were retrieved from 1077 members in an online depression community in China from April 2003 to September 2017 and the available data were extracted. An informational support network of 1077 participant nodes and 6557 arcs and an emotional support network of 1077 participant nodes and 6430 arcs were constructed to examine the endogenous (purely structural) effects and exogenous (actor-relation) effects on each support network separately, as well as the cross-network effects between the two networks. Results We found significant effects of two important structural features, reciprocity and transitivity, on the formation of both the informational support network (r=3.6247, P<.001, and r=1.6232, P<.001, respectively) and the emotional support network (r=4.4111, P<.001, and r=0.0177, P<.001, respectively). The results also showed significant effects of some individual factors on the formation of the two networks. No significant effects of homophily were found for gender (r=0.0783, P=.20, and r=0.1122, P=.25, respectively) in the informational or emotional support networks. There was no tendency for users who had great influence (r=0.3253, P=.05) or wrote more posts (r=0.3896, P=.07) or newcomers (r=–0.0452, P=.66) to form informational support ties more easily. However, users who spent more time online (r=0.6680, P<.001) or provided more replies to other posts (r=0.5026, P<.001) were more likely to form informational support ties. Users who had a big influence (r=0.8325, P<.001), spent more time online (r=0.5839, P<.001), wrote more posts (r=2.4025, P<.001), or provided more replies to other posts (r=0.2259, P<.001) were more likely to form emotional support ties, and newcomers (r=–0.4224, P<.001) were less likely than old-timers to receive emotional support. In addition, we found that there was a significant entrainment effect (r=0.7834, P<.001) and a nonsignificant exchange effect (r=–0.2757, P=.32) between the two networks. Conclusions This study makes several important theoretical contributions to the research on online depression communities and has important practical implications for the managers of online depression communities and the users involved in these communities.

Sign in / Sign up

Export Citation Format

Share Document