Opposition to Early Dental Visit by Dentists: A Qualitative Study on Mothers’ Social Networks

2021 ◽  
pp. 238008442110590
Author(s):  
J.M. Burgette ◽  
Z.T. Dahl ◽  
R.J. Weyant ◽  
D.W. McNeil ◽  
B. Foxman ◽  
...  
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Qualitative Study ◽  
Qualitative Data ◽  
Comparative Method ◽  
Dental Visit ◽  
Professional Relationship ◽  
Cross Sectional ◽  
Dental Visits ◽  
The Impact

Objectives: To examine whether information that mothers received from dentists in their social network was consistent with professional recommendations for the first dental visit at age 1 y. Methods: We performed a cross-sectional qualitative study on mothers in Pennsylvania and West Virginia from 2018 to 2020 to explore how their social networks influence their children’s dental service utilization. In-person, semistructured interviews were conducted with 126 mothers of children ages 3 to 5 y. Qualitative data were transcribed, coded, and analyzed using NVivo 12. Two investigators analyzed data using grounded theory and the constant comparative method. Results: Over half of mothers reported a professional relationship with a dentist as part of their social network on children’s oral health. Mothers described the following themes: 1) mothers contacted dentists in their social network for child dental information and to schedule their child’s first dental visit, 2) mothers described dentists’ justifications for the timing of the first dental visit older than age 1 y, 3) mothers described the impact of the dentist declining to see her child, and 4) after the dentist declined to see her child, some mothers did not comply with the dentist’s recommendation of delayed child dental visits because they were given alternative information that encouraged early dental visits. Conclusions: Our findings indicate a need for dentists to reinforce mothers’ dental-seeking behavior for young children and adhere to recommendations on the age 1 dental visit. Knowledge Transfer Statement: Qualitative data on mothers’ social networks show that dentists play a key role in access to early dental visits, particularly when dentists decline to see the mother’s child for visits.

The impact of organizational social networks on salespeople’s negative headquarters stereotypes

2020 ◽  
Vol 35 (12) ◽  
pp. 1901-1913
Author(s):  
Babak Hayati ◽  
Sandeep Puri
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Sales Performance ◽  
Sales Managers ◽  
Cross Sectional ◽  
Data Set ◽  
Content Type ◽  
Network Patterns ◽  
The Impact ◽  
Sales Forces

Purpose Extant sales management literature shows that holding negative headquarters stereotypes (NHS) by salespeople is harmful to their sales performance. However, there is a lack of research on how managers can leverage organizational structures to minimize NHS in sales forces. This study aims to know how social network patterns influence the flow of NHS among salespeople and sales managers in a large B2B sales organization. Design/methodology/approach The authors hypothesize and test whether patterns of social networks among salespeople and sales managers determine the stereotypical attitudes of salespeople toward corporate directors and, eventually, impact their sales performance. The authors analyzed a multi-level data set from the B2B sales forces of a large US-based media company. Findings The authors found that organizational social network properties including the sales manager’s team centrality, sales team’s network density and sales team’s external connectivity moderate the flow of NHS from sales managers and peer salespeople to a focal salesperson. Research limitations/implications First, the data was cross-sectional and did not allow the authors to examine the dynamics of social network patterns and their impact on NHS. Second, The authors only focused on advice-seeking social networks and did not examine other types of social networks such as friendship and trust networks. Third, the context was limited to one company in the media industry. Practical implications The authors provide recommendations to sales managers on how to leverage and influence social networks to minimize the development and flow of NHS in sales forces. Originality/value The findings advance existing knowledge on how NHS gets shared and transferred in sales organizations. Moreover, this study provides crucial managerial insights with regard to controlling and managing NHS in sales forces.

scholarly journals Sexual health norms and communication patterns within the close social networks of men who have sex with men and transgender women in Lima, Peru: a 2017 cross-sectional study

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Amrita Ayer ◽  
Eddy R. Segura ◽  
Amaya Perez-Brumer ◽  
Susan Chavez-Gomez ◽  
Rosario Fernandez ◽  
...  
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Sexual Health ◽  
Cross Sectional Study ◽  
Sectional Study ◽  
Cross Sectional ◽  
Sti Prevention ◽  
Sti Testing ◽  
Trans Women ◽  
Sex With Men

Abstract Background Social networks, norms, and discussions about sexual health may inform sexual practices, influencing risk of human immunodeficiency virus (HIV) or sexually transmitted infection (STI) acquisition. To better understand social networks of Peruvian men who have sex with men (MSM) and transgender women (trans women), we examined key social network members (SNMs), participant perceptions of these network members’ opinions toward sexual health behaviors, and associations between network member characteristics and condomless anal intercourse (CAI). Methods In a 2017 cross-sectional study, a convenience sample of 565 MSM and trans women with HIV-negative or unknown serostatus was asked to identify three close SNMs; describe discussions about HIV and STI prevention with each; and report perceived opinions of condom use, HIV/STI testing, and partner notification of STIs. Generalized estimating equations evaluated relationships between SNM characteristics, opinions, and discussions and participant-reported CAI. Results Among participants who identified as MSM, 42.3% of key SNMs were perceived to identify as gay. MSM “never” discussed HIV and STI prevention concerns with 42.4% of heterosexual SNMs, but discussed them “at least once weekly” with 16.9 and 16.6% of gay- and bisexual- identifying SNMs, respectively. Among participants who identified as trans women, 28.2% of key SNMs were perceived as heterosexual; 25.9%, as bisexual; 24.7%, as transgender; and 21.2%, as gay. Trans women discussed HIV/STI prevention least with cis-gender heterosexual network members (40.2% “never”) and most with transgender network members (27.1% “at least once weekly”). Participants perceived most of their close social network to be completely in favor of condom use (71.2% MSM SNMs, 61.5% trans women SNMs) and HIV/STI testing (73.1% MSM SNMs, 75.6% trans women SNMs), but described less support for partner STI notification (33.4% MSM SNMs, 37.4% trans women SNMs). Most participants reported CAI with at least one of their past three sexual partners (77.5% MSM, 62.8% trans women). SNM characteristics were not significantly associated with participant-reported frequency of CAI. Conclusions Findings compare social support, perceived social norms, and discussion patterns of Peruvian MSM and trans women, offering insight into social contexts and sexual behaviors. Trial registration The parent study from which this analysis was derived was registered at ClinicalTrials.gov (Identifier: NCT03010020) on January 4, 2017.

Enabling social networks in an R&D organization

2006 ◽  
Vol 25 (4) ◽  
pp. 237-246
Author(s):  
Tomas Hellström
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Qualitative Study ◽  
Network Formation ◽  
Higher Order ◽  
Practical Significance ◽  
Administrative Unit ◽  
High Level ◽  
Social Network Formation

This paper presents a qualitative study of mechanisms enabling social network formation in the R&D unit of a large technology-based organization. Drawing on interviews with 37 high-level technical and administrative unit members, a number of social network enablers could be discerned, which related to the need for effective location mechanisms, special “enrolment spaces”, and mechanisms for forging contacts. It was also possible to identify a number of higher-order factors for facilitation of network formation, namely hierarchical enablers and communicative and assimilative factors. Based on these results, the paper makes suggestions as to the theoretical and practical significance of social network enabling mechanisms in R&D organizations.

scholarly journals I Know Where You Are Coming From: On the Impact of Social Media Sources on AI Model Performance (Student Abstract)

2020 ◽  
Vol 34 (10) ◽  
pp. 13971-13972
Author(s):  
Yang Qi ◽  
Farseev Aleksandr ◽  
Filchenkov Andrey
Keyword(s):  
Machine Learning ◽  
Social Networks ◽  
Social Media ◽  
Social Network ◽  
Model Performance ◽  
User Profiling ◽  
Personalized Recommendation ◽  
Modal Data ◽  
Social Media Networks ◽  
The Impact

Nowadays, social networks play a crucial role in human everyday life and no longer purely associated with spare time spending. In fact, instant communication with friends and colleagues has become an essential component of our daily interaction giving a raise of multiple new social network types emergence. By participating in such networks, individuals generate a multitude of data points that describe their activities from different perspectives and, for example, can be further used for applications such as personalized recommendation or user profiling. However, the impact of the different social media networks on machine learning model performance has not been studied comprehensively yet. Particularly, the literature on modeling multi-modal data from multiple social networks is relatively sparse, which had inspired us to take a deeper dive into the topic in this preliminary study. Specifically, in this work, we will study the performance of different machine learning models when being learned on multi-modal data from different social networks. Our initial experimental results reveal that social network choice impacts the performance and the proper selection of data source is crucial.

scholarly journals Personality and the Impact of Celebrity Endorsements on Instagram

2021 ◽  
Vol 18 (3) ◽  
pp. 468-474
Author(s):  
Yair Amichai-Hamburger ◽  
Shir Etgar ◽  
Hadar Gil-Ad ◽  
Michal Levitan-Giat ◽  
Gaya Raz
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Locus Of Control ◽  
Strong Influence ◽  
Online Social Network ◽  
Strong Impact ◽  
Celebrity Endorsements ◽  
Internal Locus Of Control ◽  
The Impact ◽  
The Relationship

Celebrities are famous people who often belong to entertainment industry. They are known to have a strong influence on people’s behavior. In the digital age this impact has expanded to include the online arena. Celebrities increasingly utilize Instagram, an online social network, to promote commercial products. It is important to learn to what extent people are influenced by this type of promotion and what sort of people are likely to be swayed by it. Research has demonstrated that people’s personalities have a strong impact on their behaviors online. However, until now, these investigations have not included the relationship between personality and the degree of celebrity influence through social networks. This study examines how much the personality of a user is related to the degree to which he or she is influenced by these Celebrity Instagram messages. Participants comprised 121 students (34 males, 87 females). They answered questionnaires which focused on their personality and were asked about the degree of influence celebrities exerted upon them through Instagram. Results showed that people who are characterized as being open and having an internal locus of control are more resistant to such celebrity influences. This paper demonstrates that the personality of a recipient is likely to influence the degree of impact that a celebrity endorsement is likely to produce. The implications of these results are discussed.

scholarly journals Retweet Prediction Based on User Behavior

2021 ◽  
Author(s):  
Syeda Nadia Firdaus
Keyword(s):  
Machine Learning ◽  
Social Networks ◽  
Social Network ◽  
Prediction Model ◽  
Matrix Factorization ◽  
Information Diffusion ◽  
User Behavior ◽  
Past Research ◽  
The Difference ◽  
The Impact

Social network is a hot topic of interest for researchers in the field of computer science in recent years. These social networks such as Facebook, Twitter, Instagram play an important role in information diffusion. Social network data are created by its users. Users’ online activities and behavior have been studied in various past research efforts in order to get a better understanding on how information is diffused on social networks. In this study, we focus on Twitter and we explore the impact of user behavior on their retweet activity. To represent a user’s behavior for predicting their retweet decision, we introduce 10-dimentional emotion and 35-dimensional personality related features. We consider the difference of a user being an author and a retweeter in terms of their behaviors, and propose a machine learning based retweet prediction model considering this difference. We also propose two approaches for matrix factorization retweet prediction model which learns the latent relation between users and tweets to predict the user’s retweet decision. In the experiment, we have tested our proposed models. We find that models based on user behavior related features provide good improvement (3% - 6% in terms of F1- score) over baseline models. By only considering user’s behavior as a retweeter, the data processing time is reduced while the prediction accuracy is comparable to the case when both retweeting and posting behaviors are considered. In the proposed matrix factorization models, we include tweet features into the basic factorization model through newly defined regularization terms and improve the performance by 3% - 4% in terms of F1-score. Finally, we compare the performance of machine learning and matrix factorization models for retweet prediction and find that none of the models is superior to the other in all occasions. Therefore, different models should be used depending on how prediction results will be used. Machine learning model is preferable when a model’s performance quality is important such as for tweet re-ranking and tweet recommendation. Matrix factorization is a preferred option when model’s positive retweet prediction capability is more important such as for marketing campaign and finding potential retweeters.

scholarly journals Retweet Prediction Based on User Behavior

2021 ◽  
Author(s):  
Syeda Nadia Firdaus
Keyword(s):  
Machine Learning ◽  
Social Networks ◽  
Social Network ◽  
Prediction Model ◽  
Matrix Factorization ◽  
Information Diffusion ◽  
User Behavior ◽  
Past Research ◽  
The Difference ◽  
The Impact

Social network is a hot topic of interest for researchers in the field of computer science in recent years. These social networks such as Facebook, Twitter, Instagram play an important role in information diffusion. Social network data are created by its users. Users’ online activities and behavior have been studied in various past research efforts in order to get a better understanding on how information is diffused on social networks. In this study, we focus on Twitter and we explore the impact of user behavior on their retweet activity. To represent a user’s behavior for predicting their retweet decision, we introduce 10-dimentional emotion and 35-dimensional personality related features. We consider the difference of a user being an author and a retweeter in terms of their behaviors, and propose a machine learning based retweet prediction model considering this difference. We also propose two approaches for matrix factorization retweet prediction model which learns the latent relation between users and tweets to predict the user’s retweet decision. In the experiment, we have tested our proposed models. We find that models based on user behavior related features provide good improvement (3% - 6% in terms of F1- score) over baseline models. By only considering user’s behavior as a retweeter, the data processing time is reduced while the prediction accuracy is comparable to the case when both retweeting and posting behaviors are considered. In the proposed matrix factorization models, we include tweet features into the basic factorization model through newly defined regularization terms and improve the performance by 3% - 4% in terms of F1-score. Finally, we compare the performance of machine learning and matrix factorization models for retweet prediction and find that none of the models is superior to the other in all occasions. Therefore, different models should be used depending on how prediction results will be used. Machine learning model is preferable when a model’s performance quality is important such as for tweet re-ranking and tweet recommendation. Matrix factorization is a preferred option when model’s positive retweet prediction capability is more important such as for marketing campaign and finding potential retweeters.

scholarly journals LIFE ON DISPLAY: WHY IT IS IMPORTANT TO EXPOSE YOUR ACTIONS ON THE SOCIAL NETWORK

2021 ◽  
Vol 6(72) (4) ◽  
pp. 41-48
Author(s):  
A. E. Starchenko ◽  
M. V. Semina
Keyword(s):  
Higher Education ◽  
Social Networks ◽  
Social Network ◽  
Reference Group ◽  
Human Life ◽  
Sociological Study ◽  
The Social ◽  
Personal Accounts ◽  
The Impact ◽  
To Receive

Social networks have emerged relatively recently in human life, but have already become an integral part of it. Companies tell about themselves, their activities, innovations, promotions and events in their profiles. This helps increase audience coverage, tell more about your brand, products, services. People in personal accounts have the opportunity to share their lives and creativity through photos, videos and texts. Now it is not necessary to receive higher education to become an operator, director or actor whose talent is recognized by society. It is enough to start a page on the social network and start sharing your knowledge and creativity. To find out why people post photos, videos and write texts on their social networks, a pilot sociological study was carried out. The method of deep interview with active users of social networks was chosen to carry out the study. The interview allowed getting unique information, to learn the opinion of users about social networks, the impact of the new way of communication on their life, to identify the reasons why users start and maintain profiles. The respondents were 20 users of social networks between the ages of 19 and 22. Interviewees have profiles on the most popular Instagram and Vkontakte networks. As a result of the analysis of the interview, a tendency was revealed to differ in the perception of users of their actions on the social network and similar actions of other users. Their content is perceived by them as opportunities to be in sight, as a resource to form their social status and an element of influence on their reference group. And the same content published by others is perceived as boasting.

The Impact of Social Networks on Science Students' Academic Performance in Ondo State Senior Secondary Schools, Nigeria

2021 ◽  
pp. 50-63
Author(s):  
Jethro Oludare OLOJO
Keyword(s):  
Social Networks ◽  
Academic Performance ◽  
Social Network ◽  
Science Students ◽  
The Social ◽  
Ondo State ◽  
Research Questions ◽  
Senior Secondary Schools ◽  
Senior Secondary ◽  
The Impact

The objective of this study was to examine the impact of social network usage on science students’ academic achievements in Ondo State’s senior secondary schools. The study was also to find the extent to which students under investigation used the social network platforms and the frequencies of their visits. In order to achieve this, a structured questionnaire was designed and administered to students from the three senatorial districts that made up the state. A multistage; which involved simple random and purposive sampling approaches was used to select the sample for the study. 150 copies of the questionnaire were distributed; out of which, 148 (98.78%) copies were returned. For the study, four research questions and two research hypotheses were developed. The hypotheses were assessed using the student's - t statistic at 0.05 significant level; using SPSS version 20 while the research questions formulated were evaluated using frequency counts and percentages. The study revealed that Ondo State senior secondary school science students can efficiently use the social network platforms for academic activities with male students being more proficient than their female counterparts. The study also revealed that the usage of social networks has assisted students to improve their academic performance; irrespective of their classes. Besides, the study showed that Facebook was the most popular of all the social network platforms. To this end, the researcher recommended that teachers, parents, and guidance should monitor the activities of their wards on the social network sites so that they can use the platforms to benefit their lots. Teachers should also use the advantage of students’ exposure to social networking to change their teaching methods from traditional one to online teaching.

scholarly journals Connecting communities to primary care: a qualitative study on the roles, motivations and lived experiences of community health workers in the Philippines

2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Eunice Mallari ◽  
Gideon Lasco ◽  
Don Jervis Sayman ◽  
Arianna Maever L. Amit ◽  
Dina Balabanova ◽  
...  
Keyword(s):  
Qualitative Study ◽  
Community Health ◽  
Community Health Workers ◽  
Financial Incentives ◽  
Lived Experiences ◽  
Health Workers ◽  
The Philippines ◽  
Community Members ◽  
Cross Sectional ◽  
The Impact

Abstract Background Community health workers (CHWs) are an important cadre of the primary health care (PHC) workforce in many low- and middle-income countries (LMICs). The Philippines was an early adopter of the CHW model for the delivery of PHC, launching the Barangay (village) Health Worker (BHW) programme in the early 1980s, yet little is known about the factors that motivate and sustain BHWs’ largely voluntary involvement. This study aims to address this gap by examining the lived experiences and roles of BHWs in urban and rural sites in the Philippines. Methods This cross-sectional qualitative study draws on 23 semi-structured interviews held with BHWs from barangays in Valenzuela City (urban) and Quezon province (rural). A mixed inductive/ deductive approach was taken to generate themes, which were interpreted according to a theoretical framework of community mobilisation to understand how characteristics of the social context in which the BHW programme operates act as facilitators or barriers for community members to volunteer as BHWs. Results Interviewees identified a range of motivating factors to seek and sustain their BHW roles, including a variety of financial and non-financial incentives, gaining technical knowledge and skill, improving the health and wellbeing of community members, and increasing one’s social position. Furthermore, ensuring BHWs have adequate support and resources (e.g. allowances, medicine stocks) to execute their duties, and can contribute to decisions on their role in delivering community health services could increase both community participation and the overall impact of the BHW programme. Conclusions These findings underscore the importance of the symbolic, material and relational factors that influence community members to participate in CHW programmes. The lessons drawn could help to improve the impact and sustainability of similar programmes in other parts of the Philippines and that are currently being developed or strengthened in other LMICs.

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