Monitoring your weight-loss process online: prior weight-loss experiences, online social support and subsequent weight-loss success (Preprint)

2021 ◽  
Author(s):  
Lun Li ◽  
Qiuju Yin ◽  
Zhijun Yan
Keyword(s):  
Social Support ◽  
Weight Loss ◽  
Self Monitoring ◽  
Online Social Support ◽  
Moderation Effect ◽  
Negative Effect ◽  
Successful Weight Loss ◽  
Weight Loss Success ◽  
Failed Weight Loss ◽  
The Relationship

BACKGROUND Online weight-loss communities (OWCs) have been becoming increasingly popular for weight management, which enable individuals to monitor (i.e. self-monitoring) and discuss (i.e. social interaction) their weight-loss experiences. However, there has been limited understanding of the role of individuals’ prior weight-loss experiences in subsequent weight-loss success, especially in online settings. OBJECTIVE To address the significant literature gap, this study investigates the relationship between prior weight-loss experiences (success or failure), online social support and subsequent weight-loss success in the contexts of OWCs based on self-determination theory. METHODS The data of 1650 users from one popular OWC is collected using a python crawler procedure, including individuals’ characteristics (e.g. gender, age, friends, posts, membership duration) and weight-loss diary information. Two logit regression models are deployed to estimate the effects of prior weight-loss experiences and social support on subsequent weight-loss success, as well as the moderation effect of social support. RESULTS The results reveal that prior successful weight-loss experiences are positively related to subsequent weight-loss success (β=0.376,p<0.01) while the relationship between prior failed weight-loss experiences and subsequent weight-loss success is negative (β=-0.225,p<0.05). Meanwhile, online social support can not only influence positively subsequent weight-loss success directly (β=0.441,p<0.01) but also undermine the negative effect of prior failed weight-loss experiences (β=0.025,p<). Nevertheless, social support has no significant moderating effect on the relationship between prior successful weight-loss experiences and subsequent weight-loss success (β=0.104,p>0.1). CONCLUSIONS This study contributes to literature on prior experiences and online social support in the context of OWCs, and provides valuable insights for OWCs’ designs to improve users’ engagement and their weight-loss success.

Pesten op het werk: de relatie met lichamelijke gezondheidsklachten en de invloed van sociale steun

2012 ◽  
Vol 25 (4) ◽  
Author(s):  
Tessa Haesevoets ◽  
Francine Dehue ◽  
Mieneke Pouwelse
Keyword(s):  
Social Support ◽  
Physical Health ◽  
Hierarchical Regression ◽  
Health Complaints ◽  
Moderation Effect ◽  
Work Related ◽  
Sociale Steun ◽  
Received Social Support ◽  
Being Bullied ◽  
The Relationship

Bullying at work: The relation with physical health complaints and the influence of social support Bullying at work: The relation with physical health complaints and the influence of social support This survey among Belgian employees (N = 497) investigated, starting from the Michigan Stress Model, the relationships among the amount of and satisfaction with social support, being bullied in the workplace, and physical health complaints. Hierarchical regression analyses confirmed that both person-related and work-related bullying influenced perceived health of victimized employees negatively. There was some evidence for a moderation effect of satisfaction with social support: victims of work-related bullying, who experienced a lack of social support from colleagues, reported more health problems. In addition, it was found that satisfaction with received social support from supervisors affected the relationship between being bullied and health complaints indirectly (i.e., mediation). No effects were found for the amount of received support. These results emphasize the need for future studies investigating the influence of satisfaction with received social support on victimized employees.

scholarly journals Internal R&D and Acquisition Performance of Chinese Pharmaceutical Firms: Moderation Effect of Acquisition Motive and Corporate Ownership

Processes ◽  
2019 ◽  
Vol 7 (5) ◽  
pp. 292 ◽  
Author(s):  
Qi Yue ◽  
Xing Hua ◽  
Jianyuan Li
Keyword(s):  
Path Dependence ◽  
Corporate Ownership ◽  
Acquisition Performance ◽  
Moderation Effect ◽  
Pharmaceutical Firms ◽  
Key Factor ◽  
Negative Effect ◽  
The Impact ◽  
The Relationship

Although corporate capability has been recognized as a key factor affecting corporate acquisition performance, the role of R&D capability in acquisition performance has not been fully explained. The aim of this paper was to research the impact of internal R&D on acquisition performance according to a sample of 215 acquisitions of Chinese listed pharmaceutical companies from 2012 to 2016. First, it was found that R&D has a significant negative effect on acquisition performance. Furthermore, it was confirmed that the acquisition motive and the ownership of the acquiring firm have a moderating effect on the relationship between R&D and acquisition performance. Compared to non-technical acquisitions, the negative effect of internal R&D on acquisition performance was reduced for technical acquisitions. Compared with non-state-owned-enterprise acquisition, the negative effect of internal R&D on the acquisition performance of state-owned enterprises was weakened. Our study enriches the research of the path dependence theory on the acquisition performance of enterprises and also the interpretation of acquisition performance on the basis of internal and external innovation and the institutional theory.

scholarly journals Consistent Self-monitoring of Weight: A Key Component of Successful Weight Loss Maintenance**

Obesity ◽  
2007 ◽  
Vol 15 (12) ◽  
pp. 3091-3096 ◽  
Author(s):  
Meghan L. Butryn ◽  
Suzanne Phelan ◽  
James O. Hill ◽  
Rena R. Wing
Keyword(s):  
Weight Loss ◽  
Weight Loss Maintenance ◽  
Self Monitoring ◽  
Successful Weight Loss

scholarly journals Using Social Network Analysis to Understand the Effects of a Social Media-based Weight Loss Intervention Targeting Low-SES Adults (Preprint)

2020 ◽  
Author(s):  
Ran Xu ◽  
David Cavallo
Keyword(s):  
Social Support ◽  
Social Media ◽  
Weight Loss ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Self Efficacy ◽  
Network Characteristics ◽  
Using Data ◽  
The Relationship

BACKGROUND Obesity is a known risk factor for cardiovascular disease (CVD) risk factors including hypertension and type II diabetes. Although numerous weight-loss interventions have demonstrated efficacy, there is considerably less evidence about the theoretical mechanisms through which they work. Delivering lifestyle behavior change interventions via social media provides unique opportunities for understanding mechanisms of intervention effects. Server data collected directly from online platforms can provide detailed, real-time behavioral information over the course of intervention programs that can be used to understand how interventions work. OBJECTIVE The objective of this study was to demonstrate how social network analysis can facilitate our understanding of the mechanisms underlying a social-media based weight loss intervention. METHODS This study performed secondary analysis using data from a pilot study that delivered a dietary and physical activity intervention to a group of low-SES participants via Facebook. We mapped out participants’ interaction networks over the 12-week intervention period, and linked participants’ network characteristics (e.g. in-degree, out-degree and network constraint) to participants’ changes in theoretical mediators (i.e. dietary knowledge, perceived social support, self-efficacy) and weight loss using regression analysis. This study also performed mediation analyses to explore how the effects of social network measures on weight loss could be mediated by the aforementioned theoretical mediators. RESULTS 47 participants from two waves completed the study and were included in the analysis. We found that participants creating posts, comments and reactions predicted weight-loss (β=-.94, P=.042); receiving comments positively predicted changes in self-efficacy (β=7.81, P=.009); the degree to which one’s network neighbors are tightly connected with each other weakly predicted changes in perceived social support (β=7.70, P=.08). In addition, change in self-efficacy mediated the relationship between receiving comments and weight-loss (Indirect effect=-.89, P=.017). CONCLUSIONS Our analyses using data from this pilot study have linked participants’ network characteristics with changes in several important study outcomes of interest, such as self-efficacy, social support and weight. Our results point to the potential of using social network analysis to understand the social processes and mechanisms through which online behavioral interventions affects participants’ psychological and behavioral outcomes. Future studies are warranted to validate our results and further explore the relationship between network dynamics and study outcomes in similar and larger trials.

scholarly journals Unemployment, Personality Traits, and the Use of Facebook

2021 ◽  
Vol 13 (1) ◽  
pp. 56-72
Author(s):  
Dandison C. Ukpabi ◽  
Olayemi Olawumi ◽  
Oluwafemi Samson Balogun ◽  
Chijioke E. Nwachukwu ◽  
Sunday Adewale Olaleye ◽  
...  
Keyword(s):  
Social Support ◽  
Social Media ◽  
Regression Model ◽  
Personality Traits ◽  
Social Economic ◽  
Online Social Support ◽  
Unemployment Data ◽  
The Relationship ◽  
Practical Implications ◽  
The Way

Different personality traits respond differently to unfavourable life situations. Unemployment can have several negative social, economic, and domestic consequences. Many people use social media for a variety of reasons. The aim of this study is to examine the way different personality traits respond to Facebook in the period of unemployment. Data was obtained from 3,002 unemployed respondents in Nigeria. The study used regression model to analyse the data. Among the five personality traits, results indicated that the relationship between neuroticism and online social support was negative. However, the relationship between online social support and satisfaction was positive. The study highlights several theoretical and practical implications.

scholarly journals Feasibility of a social media-based weight loss intervention designed for low-SES adults

2020 ◽  
Author(s):  
David N Cavallo ◽  
Rogelio Martinez ◽  
Monica Webb Hooper ◽  
Susan Flocke
Keyword(s):  
Social Support ◽  
Social Media ◽  
Weight Loss ◽  
Low Socioeconomic Status ◽  
Low Ses ◽  
Weight Loss Intervention ◽  
Self Monitoring ◽  
Intervention Delivery ◽  
Group 2 ◽  
Pilot Intervention

Abstract Low-socioeconomic status (SES) individuals have higher rates of obesity. Social media platforms are used frequently by low-SES individuals and facilitate important weight loss program components including social support. Very few social media-based weight loss interventions, however, have enrolled or been tailored to low-SES participants. The purpose of this article is to examine the feasibility of a social media-based weight loss intervention among low-SES adults. We conducted a one-group pretest post-test pilot intervention study with two groups (group 1, n = 39, group 2, n = 16) of low-SES overweight/obese adults who were enrolled in a 12-week social media-based weight loss intervention including self-monitoring via Fitbits and participation in a private Facebook group. A moderator provided educational content and encouraged social support via Facebook. Descriptive statistics were used to assess intervention acceptability and engagement. Exploratory analyses were conducted to examine changes in study outcomes and engagement patterns. The study had good retention (86%). Among 55 total participants enrolled, there were 9,175 participant interactions within the Facebook group. Among completers (n = 47), 96% indicated they would recommend the intervention to a friend. Mean weight loss was 1.07 kg (SD = 3.96, p = .0498), and participants reported increases in positive dietary social support (mean = 2.47, SD = 5.09, p = .0007). Engagement in this social media-based pilot intervention was high and exceeded results from previous studies using similar formats. Participants evaluated the intervention favorably. Changes in weight loss and several theoretical mediators were in the desired direction. Overall, our results indicate social media groups as a platform for weight loss intervention delivery among low-SES adults are feasible and should be studied in larger randomized trials.

On the Relationship between Online Social Support and Users' ontinuance Intention

2015 ◽  
pp. 140-152 ◽  
Author(s):  
Xiaolin Lin ◽  
Dawei Zhang ◽  
Yibai Li
Keyword(s):  
Social Support ◽  
Social Networking ◽  
User Satisfaction ◽  
Social Networking Sites ◽  
Well Being ◽  
Continuance Intention ◽  
Online Social Support ◽  
Managerial Implications ◽  
The Relationship

This chapter discusses the online social support in the context of social networking sites (SNSs). The pervasive adoption of social networking sites has profound influence on society and enables a new way to provide social support. Social support has been considered a key social value that online users can obtain from social networking sites. Research has shown that social support may reduce stress and promote well-being among diverse populations. Despite its significance to society, the online social support in the context of SNSs has been surprisingly under-investigated. Some fundamental questions—such as (1) What are the dimensions of online social support on SNSs? and (2) How does online social support influence other factors such as the users' satisfaction and continuance intention to SNSs?—have not been answered. This chapter attempts to answer those questions. Specifically, this chapter aims to first identify the definitional dimensions of online social support on SNSs through an extensive review of the literature. Second, this chapter uses these dimensions to model online social support and test its effects on other SNS factors: user satisfaction and continuance intention. Eventually, the results support all proposed hypotheses. The theoretical contributions and managerial implications of the results are discussed at the end of this chapter. 1

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