Abstract On some fundamental level, we can think of scholars as actors possessing, or controlling, various types of resources. Collaboration in science is understood here as a process of pooling and exchanging such resources. We show how diversity of resources engaged in scientific collaboration is related to the structure of collaboration networks. We demonstrate that scholars within their personal networks simultaneously (1) diversify resources in collaboration ties surrounded by structural holes and (2) specialize resources in collaboration ties embedded in dense collaboration groups. These complementary mechanisms decrease individual efforts required to maintain effective collaborations in complex social settings. To this end, we develop a concept of “pairwise redundancy” capturing structural redundancy of ego’s neighbors vis-à-vis each other.
{"title":"Reaching for Unique Resources: Structural Holes and Specialization in Scientific Collaboration Networks","authors":"M. Bojanowski, Dominika Czerniawska","doi":"10.21307/joss-2020-001","DOIUrl":"https://doi.org/10.21307/joss-2020-001","url":null,"abstract":"Abstract On some fundamental level, we can think of scholars as actors possessing, or controlling, various types of resources. Collaboration in science is understood here as a process of pooling and exchanging such resources. We show how diversity of resources engaged in scientific collaboration is related to the structure of collaboration networks. We demonstrate that scholars within their personal networks simultaneously (1) diversify resources in collaboration ties surrounded by structural holes and (2) specialize resources in collaboration ties embedded in dense collaboration groups. These complementary mechanisms decrease individual efforts required to maintain effective collaborations in complex social settings. To this end, we develop a concept of “pairwise redundancy” capturing structural redundancy of ego’s neighbors vis-à-vis each other.","PeriodicalId":35236,"journal":{"name":"Journal of Social Structure","volume":"21 1","pages":"1 - 34"},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47500113","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract Multi-location knowledge-intensive firms span their value chains and thus their locations across space. Increased globalization alters the spatial configuration of such networks of knowledge creation. Longitudinal social network analysis allows detecting temporal changes in the arrangement of nodes and edges in the network and resulting changes in the overall structure. We use this approach to study for Germany the spatio-temporal dynamics of knowledge-intensive services firms – advanced producer services (APS) – in the years between 2009 and 2019. Multi-location APS firms are considered as vanguard of spatial structural change and thus lending to study their location choice behavior. A common approach is to analyze a one-mode intercity network where cities are the nodes. We take a different approach and include the firms’ perspectives. We work directly with the original data structure of a two-mode network including cities and firms as two node sets and we apply stochastic actor-oriented models for network dynamics. Results show that the spatio-temporal dynamics are characterized by both agglomeration and network economies. On a local scale, APS firms continue their location expansion over time and concentrate in agglomerations where many other APS firms and a greater availability of workforce are present. Simultaneously, they also choose new locations in agglomerations further apart from their present locations. On a supra-local scale, the network grows denser over time. Agglomerations that are attractive for APS firms in 2009 become even more attractive in 2019. Our analysis contributes to an understanding of how interactions amongst cities and firms on a local scale give rise to the empirically observed network patterns on a supra-local scale.
{"title":"A Longitudinal Network Analysis of the German Knowledge Economy from 2009 to 2019: Spatio-Temporal Dynamics at the City–Firm Nexus","authors":"Silke Zöllner, Stefan Lüthi, A. Thierstein","doi":"10.21307/joss-2020-005","DOIUrl":"https://doi.org/10.21307/joss-2020-005","url":null,"abstract":"Abstract Multi-location knowledge-intensive firms span their value chains and thus their locations across space. Increased globalization alters the spatial configuration of such networks of knowledge creation. Longitudinal social network analysis allows detecting temporal changes in the arrangement of nodes and edges in the network and resulting changes in the overall structure. We use this approach to study for Germany the spatio-temporal dynamics of knowledge-intensive services firms – advanced producer services (APS) – in the years between 2009 and 2019. Multi-location APS firms are considered as vanguard of spatial structural change and thus lending to study their location choice behavior. A common approach is to analyze a one-mode intercity network where cities are the nodes. We take a different approach and include the firms’ perspectives. We work directly with the original data structure of a two-mode network including cities and firms as two node sets and we apply stochastic actor-oriented models for network dynamics. Results show that the spatio-temporal dynamics are characterized by both agglomeration and network economies. On a local scale, APS firms continue their location expansion over time and concentrate in agglomerations where many other APS firms and a greater availability of workforce are present. Simultaneously, they also choose new locations in agglomerations further apart from their present locations. On a supra-local scale, the network grows denser over time. Agglomerations that are attractive for APS firms in 2009 become even more attractive in 2019. Our analysis contributes to an understanding of how interactions amongst cities and firms on a local scale give rise to the empirically observed network patterns on a supra-local scale.","PeriodicalId":35236,"journal":{"name":"Journal of Social Structure","volume":"21 1","pages":"107 - 133"},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47839832","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
I am delighted to see Stivala’s piece on geodesic cycle length, which responds to and goes considerably beyond my 2017 JOSS. This article (1) regularizes the terminology I used; (2) replicates my analyses using exponential random graph models; and (3) applies these models to other data sets to examine the degree to which these models predict geodesic cycle length. All of these constitute a welcome (and impressively done) contribution. Yet, I also have a sense that some of the motivation of this paper is to establish the superiority of the ERGM approach, and to treat all others as, at best, fallbacks. Given that part of my reason to write the first paper was precisely to try to help us avoid the monoculture that I see developing with the use of ERGMs, Stivala’s contribution provides an excellent opportunity for social networkers to consider the implications and strengths of different models, and different ways of understanding our task as analysts.
{"title":"Comment on Geodesic Cycle Length Distributions in Delusional and Other Social Networks","authors":"J. Martin","doi":"10.21307/joss-2020-003","DOIUrl":"https://doi.org/10.21307/joss-2020-003","url":null,"abstract":"I am delighted to see Stivala’s piece on geodesic cycle length, which responds to and goes considerably beyond my 2017 JOSS. This article (1) regularizes the terminology I used; (2) replicates my analyses using exponential random graph models; and (3) applies these models to other data sets to examine the degree to which these models predict geodesic cycle length. All of these constitute a welcome (and impressively done) contribution. Yet, I also have a sense that some of the motivation of this paper is to establish the superiority of the ERGM approach, and to treat all others as, at best, fallbacks. Given that part of my reason to write the first paper was precisely to try to help us avoid the monoculture that I see developing with the use of ERGMs, Stivala’s contribution provides an excellent opportunity for social networkers to consider the implications and strengths of different models, and different ways of understanding our task as analysts.","PeriodicalId":35236,"journal":{"name":"Journal of Social Structure","volume":"21 1","pages":"77 - 93"},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47065517","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract Martin (2020) describes a misinterpretation of exponential random graph (ERGM) parameters in my contribution (Stivala 2020), with the use of this parametric model obscuring, rather than illuminating, the data. He suggests that this is symptomatic of a trend in the social networks community towards a methodological monoculture focussed on the use of ERGMs. In this Reply I try to clarify how this situation arose in this specific case, and address some more general issues Martin raises, including the use of nodal covariates, what we can learn from ERGMs, and methodological monoculturalism in social network research.
{"title":"Reply to “Comment on Geodesic Cycle Length Distributions in Delusional and Other Social Networks”","authors":"A. Stivala","doi":"10.21307/joss-2020-004","DOIUrl":"https://doi.org/10.21307/joss-2020-004","url":null,"abstract":"Abstract Martin (2020) describes a misinterpretation of exponential random graph (ERGM) parameters in my contribution (Stivala 2020), with the use of this parametric model obscuring, rather than illuminating, the data. He suggests that this is symptomatic of a trend in the social networks community towards a methodological monoculture focussed on the use of ERGMs. In this Reply I try to clarify how this situation arose in this specific case, and address some more general issues Martin raises, including the use of nodal covariates, what we can learn from ERGMs, and methodological monoculturalism in social network research.","PeriodicalId":35236,"journal":{"name":"Journal of Social Structure","volume":"21 1","pages":"94 - 106"},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48014583","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract Since its nascency, the field of social network analysis has been intrinsically linked to human health and well-being. In fact, the very first empirical article ever published in Sociometry evaluated a psychiatric treatment to inter-personal distress that employed the spontaneous interactions unfolding in a triad of physician, patient, and proxy actors (Moreno, 1937). This was a first attempt in a research context to show that there may be direct effects that tie patterns of social relations to individual well-being in small groups. Moreno & Jennings (1938) also made the early and astute argument that the social structure observed through measurement of social relations is inseparable from biological and psychological frames of reference: they are all inherently interdependent. More than 80 years of research in this area has since been developed and yet the field is still flush with opportunities to learn about the interplay between social networks and health. In this special issue of the Journal of Social Structure, we highlight the work of leading scientists in this field.
{"title":"Social Networks and Health: Micro Processes and Macro Structures","authors":"C. Marcum, L. Koehly","doi":"10.21307/joss-2019-003","DOIUrl":"https://doi.org/10.21307/joss-2019-003","url":null,"abstract":"Abstract Since its nascency, the field of social network analysis has been intrinsically linked to human health and well-being. In fact, the very first empirical article ever published in Sociometry evaluated a psychiatric treatment to inter-personal distress that employed the spontaneous interactions unfolding in a triad of physician, patient, and proxy actors (Moreno, 1937). This was a first attempt in a research context to show that there may be direct effects that tie patterns of social relations to individual well-being in small groups. Moreno & Jennings (1938) also made the early and astute argument that the social structure observed through measurement of social relations is inseparable from biological and psychological frames of reference: they are all inherently interdependent. More than 80 years of research in this area has since been developed and yet the field is still flush with opportunities to learn about the interplay between social networks and health. In this special issue of the Journal of Social Structure, we highlight the work of leading scientists in this field.","PeriodicalId":35236,"journal":{"name":"Journal of Social Structure","volume":"20 1","pages":"1 - 6"},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46865178","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Christopher J. Carpenter, Xun Zhu, Rachel A. Smith
Abstract Although scholars have argued that people actively shape and reshape their social networks (e.g., Parks, 2016), this aspect of relational development has received little attention. This study sought to determine if people’s self-perceptions of interpersonal communication skills translated into behavior that led to relationship formation in a new network. A 9-month longitudinal social network analysis (N = 94) of the residents of a first-year university residence hall using Facebook tie data was conducted to assess network changes. Results indicate that both self-perceived network centrality in a hypothetical friendship sociogram (Smith & Fink, 2015) and self-reported connector scores (Boster et al., 2011) are good longitudinal predictors of relationship development. Those who began by self-identifying as central, became central.
摘要尽管学者们认为人们积极塑造和重塑自己的社交网络（例如，Parks，2016），但关系发展的这一方面却很少受到关注。这项研究试图确定人们对人际沟通技能的自我认知是否转化为导致新网络中关系形成的行为。使用Facebook领带数据对大学一年级宿舍的居民进行了为期9个月的纵向社交网络分析（N=94），以评估网络变化。结果表明，在假设的友谊社交图中，自我感知的网络中心性（Smith&Fink，2015）和自我报告的连接者得分（Boster et al.，2011）都是关系发展的良好纵向预测因素。那些从自我认同为中心开始的人，成为了中心。
{"title":"Do People Who Identify as Popular Become Popular in a New Network? A 9-Month Longitudinal Network Analysis","authors":"Christopher J. Carpenter, Xun Zhu, Rachel A. Smith","doi":"10.21307/JOSS-2019-001","DOIUrl":"https://doi.org/10.21307/JOSS-2019-001","url":null,"abstract":"Abstract Although scholars have argued that people actively shape and reshape their social networks (e.g., Parks, 2016), this aspect of relational development has received little attention. This study sought to determine if people’s self-perceptions of interpersonal communication skills translated into behavior that led to relationship formation in a new network. A 9-month longitudinal social network analysis (N = 94) of the residents of a first-year university residence hall using Facebook tie data was conducted to assess network changes. Results indicate that both self-perceived network centrality in a hypothetical friendship sociogram (Smith & Fink, 2015) and self-reported connector scores (Boster et al., 2011) are good longitudinal predictors of relationship development. Those who began by self-identifying as central, became central.","PeriodicalId":35236,"journal":{"name":"Journal of Social Structure","volume":"20 1","pages":"1 - 24"},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44896383","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Allison D. Hepworth, Jessica Kropczynski, Justin A. Walden, Rachel A. Smith
Abstract Background and objective. Nutrition information conveyed by popular entities through online social networking sites (i.e., social media influencers) has the potential to impact consumer eating behavior through mechanisms of social influence. Little is known about how online communities of food-related social media influencers are structured, which could reveal influencers’ opportunities to observe and spread nutrition-related content and information design practices. This study explored patterns of social relationships (social capital, conservation of resources, and homophily) within a network of prominent food bloggers on Twitter (N = 44). Methods. Data on Twitter following/follower relationships and Twitter use (number of tweets, favorited tweets) were collected from bloggers’ Twitter profiles. Bloggers represented eight topical subcategories of food blogs (e.g., family cooking, cocktails) and comprised a one-mode social network with directed ties indicating Twitter following/follower relationships. Structural evidence of patterns of social relationships was investigated through social network visualization, centrality measures (in-degree/out-degree centrality, density, reciprocity), and inferential tests. Results. The overall network density of directed ties was 21%, with wide variability in individual blogger centrality across multiple measures. Cocktails, cooking, special diets, and culinary travel bloggers had more dense ties to bloggers in their own subcategories. Within the network, favorited tweets and outreach (Twitter following relationships) were positively associated with popularity (Twitter follower relationships). Conclusions. Food bloggers in this study formed a partially connected network, supporting the conservation of resources framework. Homophily was evident in some, but not all, topical subcategories. Associations among Twitter use, outreach, and popularity generally supported the social capital framework. Future studies should explore influencers’ motivations for connecting on social networking sites, and how content and information design practices spread among influencers.
{"title":"Exploring Patterns of Social Relationships among Food Bloggers on Twitter Using a Social Network Analysis Approach","authors":"Allison D. Hepworth, Jessica Kropczynski, Justin A. Walden, Rachel A. Smith","doi":"10.21307/joss-2019-038","DOIUrl":"https://doi.org/10.21307/joss-2019-038","url":null,"abstract":"Abstract Background and objective. Nutrition information conveyed by popular entities through online social networking sites (i.e., social media influencers) has the potential to impact consumer eating behavior through mechanisms of social influence. Little is known about how online communities of food-related social media influencers are structured, which could reveal influencers’ opportunities to observe and spread nutrition-related content and information design practices. This study explored patterns of social relationships (social capital, conservation of resources, and homophily) within a network of prominent food bloggers on Twitter (N = 44). Methods. Data on Twitter following/follower relationships and Twitter use (number of tweets, favorited tweets) were collected from bloggers’ Twitter profiles. Bloggers represented eight topical subcategories of food blogs (e.g., family cooking, cocktails) and comprised a one-mode social network with directed ties indicating Twitter following/follower relationships. Structural evidence of patterns of social relationships was investigated through social network visualization, centrality measures (in-degree/out-degree centrality, density, reciprocity), and inferential tests. Results. The overall network density of directed ties was 21%, with wide variability in individual blogger centrality across multiple measures. Cocktails, cooking, special diets, and culinary travel bloggers had more dense ties to bloggers in their own subcategories. Within the network, favorited tweets and outreach (Twitter following relationships) were positively associated with popularity (Twitter follower relationships). Conclusions. Food bloggers in this study formed a partially connected network, supporting the conservation of resources framework. Homophily was evident in some, but not all, topical subcategories. Associations among Twitter use, outreach, and popularity generally supported the social capital framework. Future studies should explore influencers’ motivations for connecting on social networking sites, and how content and information design practices spread among influencers.","PeriodicalId":35236,"journal":{"name":"Journal of Social Structure","volume":"20 1","pages":"1 - 21"},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41794875","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract Family planning programs have made significant contributions to lowering fertility levels in several developing nations. These advances often focus on women as the main agents of population control, ignoring the important role of men. However, in many countries/cultures decisions about fertility are highly embedded in social relationships at all levels, which make it imperative to investigate men’s position in the social structure. This study explores the relationship structures between men in Bangladesh using social network analysis to explore new possibilities for cost-effective healthcare strategies that have more far-reaching effects than the status quo. The results of this research show that men are embedded in un-fragmented and diffuse communication structures, formed across age and educational divide, beyond the bounds of kinship relations and village boundaries. Not only do men not shy away from discussion of contraceptives, but also approve and support their use. Men’s networks, thus, provide a potentially rich, but untapped, channel of communication for effectively and efficiently disseminating population control initiatives.
{"title":"Do Men Discuss Birth Control? A Social Network Analysis in Bangladesh","authors":"Bhanu Bhatia","doi":"10.21307/JOSS-2019-002","DOIUrl":"https://doi.org/10.21307/JOSS-2019-002","url":null,"abstract":"Abstract Family planning programs have made significant contributions to lowering fertility levels in several developing nations. These advances often focus on women as the main agents of population control, ignoring the important role of men. However, in many countries/cultures decisions about fertility are highly embedded in social relationships at all levels, which make it imperative to investigate men’s position in the social structure. This study explores the relationship structures between men in Bangladesh using social network analysis to explore new possibilities for cost-effective healthcare strategies that have more far-reaching effects than the status quo. The results of this research show that men are embedded in un-fragmented and diffuse communication structures, formed across age and educational divide, beyond the bounds of kinship relations and village boundaries. Not only do men not shy away from discussion of contraceptives, but also approve and support their use. Men’s networks, thus, provide a potentially rich, but untapped, channel of communication for effectively and efficiently disseminating population control initiatives.","PeriodicalId":35236,"journal":{"name":"Journal of Social Structure","volume":"20 1","pages":"1 - 19"},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42970133","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract To examine predictors of preschool language abilities, thirty-seven infants at high risk for Autism Spectrum Disorder (ASD) were recorded longitudinally from 5-14 months as they interacted with their caregivers and toys at home. Triadic interactions were coded, categorized as transitive, intransitive or vacuously transitive, and then related to the MacArthur Bates Communicative Development Inventory (CDI-III) and the Mullen Scales of Early Learning (MSEL) at 36 months. The results show that prior to 14 months, early transitive interactions correlate positively and intransitive interactions correlate negatively with CDI-III and MSEL scores at 36 months. By categorizing interactions between 5-14 months by transitivity, we have demonstrated that recurring triadic patterns can predict communicative abilities at 36 months.
{"title":"Transitivity Types Predict Communicative Abilities in Infants at Risk of Autism","authors":"Rebekka Schleier, J. Iverson, A. King, M. West","doi":"10.21307/joss-2019-009","DOIUrl":"https://doi.org/10.21307/joss-2019-009","url":null,"abstract":"Abstract To examine predictors of preschool language abilities, thirty-seven infants at high risk for Autism Spectrum Disorder (ASD) were recorded longitudinally from 5-14 months as they interacted with their caregivers and toys at home. Triadic interactions were coded, categorized as transitive, intransitive or vacuously transitive, and then related to the MacArthur Bates Communicative Development Inventory (CDI-III) and the Mullen Scales of Early Learning (MSEL) at 36 months. The results show that prior to 14 months, early transitive interactions correlate positively and intransitive interactions correlate negatively with CDI-III and MSEL scores at 36 months. By categorizing interactions between 5-14 months by transitivity, we have demonstrated that recurring triadic patterns can predict communicative abilities at 36 months.","PeriodicalId":35236,"journal":{"name":"Journal of Social Structure","volume":"20 1","pages":"119 - 139"},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43854047","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Sula Hood, Elizabeth H. Golembiewski, Hadyatoullaye Sow, Kyle L. Benbow, J. Prather, Lisa Robison, Elisabeth Martin-Hagler
Abstract Background: Family health history is a strong risk factor for many chronic diseases. Ethnic minorities have been found to have a low awareness of their family health history (FHH), which may pose a contributing factor to health disparities. Purpose: The purpose of this mixed-methods social network analysis study was to identify structural and contextual patterns in African American adults’ FHH knowledge based on interpersonal communication exchanges with their family members. Methods: African American adults completed individually administered family network interviews. Participants’ 3-generation family pedigree served as a visual aid to guide their interview. Our primary outcome of interest for this analysis was whether a family member was reported as someone who talks to the participant about their own (i.e., the family member’s) health, which we refer to as a “personal health informant.” To contextualize quantitative findings, participants were asked to describe how they learned about the health history of the relatives they identified during their interview. Results: Participants (n=37) reported an average family network size of 29.4 relatives (SD = 15.5; Range = 10-67). Each participant, on average, named 17% of their familial network as personal health informants. Multivariate regression results showed that participants were more likely to name an alter as a personal health informant if the alter was female (OR = 2.14, p = 0.0519), from the maternal side of the participant’s family (OR = 1.12, p = 0.0006), had one or more chronic health conditions (OR = 2.41, p = 0.0041), was someone who has discussions with the participant about the participant’s health (OR = 16.28, p < 0.0001), was a source of family health information (OR = 3.46, p = 0.0072), and was someone whose health the participant helps to monitor or track (OR = 5.93, p = 0.0002). Complementary qualitative findings indicate that FHH knowledge is facilitated by open, direct communication among relatives. Personal health informants were described as disclosing information for the purposes of informing others for preventive purposes and for gaining social support. Participants also learned about FHH via other methods, including direct observation, during caretaking, and following a relative’s death. Conclusions: Communication and disclosure practices is an important determinant of African Americans’ FHH knowledge. More culturally and contextually meaningful public health efforts are needed to promote family health history sharing, especially regarding paternal family health history, siblings, and extended relatives.
{"title":"Structural and Contextual Patterns in Family Health History Knowledge among African American Adults: A Mixed-Methods Social Network Analysis Study*","authors":"Sula Hood, Elizabeth H. Golembiewski, Hadyatoullaye Sow, Kyle L. Benbow, J. Prather, Lisa Robison, Elisabeth Martin-Hagler","doi":"10.21307/joss-2019-008","DOIUrl":"https://doi.org/10.21307/joss-2019-008","url":null,"abstract":"Abstract Background: Family health history is a strong risk factor for many chronic diseases. Ethnic minorities have been found to have a low awareness of their family health history (FHH), which may pose a contributing factor to health disparities. Purpose: The purpose of this mixed-methods social network analysis study was to identify structural and contextual patterns in African American adults’ FHH knowledge based on interpersonal communication exchanges with their family members. Methods: African American adults completed individually administered family network interviews. Participants’ 3-generation family pedigree served as a visual aid to guide their interview. Our primary outcome of interest for this analysis was whether a family member was reported as someone who talks to the participant about their own (i.e., the family member’s) health, which we refer to as a “personal health informant.” To contextualize quantitative findings, participants were asked to describe how they learned about the health history of the relatives they identified during their interview. Results: Participants (n=37) reported an average family network size of 29.4 relatives (SD = 15.5; Range = 10-67). Each participant, on average, named 17% of their familial network as personal health informants. Multivariate regression results showed that participants were more likely to name an alter as a personal health informant if the alter was female (OR = 2.14, p = 0.0519), from the maternal side of the participant’s family (OR = 1.12, p = 0.0006), had one or more chronic health conditions (OR = 2.41, p = 0.0041), was someone who has discussions with the participant about the participant’s health (OR = 16.28, p < 0.0001), was a source of family health information (OR = 3.46, p = 0.0072), and was someone whose health the participant helps to monitor or track (OR = 5.93, p = 0.0002). Complementary qualitative findings indicate that FHH knowledge is facilitated by open, direct communication among relatives. Personal health informants were described as disclosing information for the purposes of informing others for preventive purposes and for gaining social support. Participants also learned about FHH via other methods, including direct observation, during caretaking, and following a relative’s death. Conclusions: Communication and disclosure practices is an important determinant of African Americans’ FHH knowledge. More culturally and contextually meaningful public health efforts are needed to promote family health history sharing, especially regarding paternal family health history, siblings, and extended relatives.","PeriodicalId":35236,"journal":{"name":"Journal of Social Structure","volume":"20 1","pages":"96 - 118"},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42456805","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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