An Actor-Based Model of Social Network Influence on Adolescent Body Size, Screen Time, and Playing Sports
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{"title"=>"An actor-based model of social network influence on adolescent body size, screen time, and playing sports", "type"=>"journal", "authors"=>[{"first_name"=>"David A.", "last_name"=>"Shoham", "scopus_author_id"=>"7004741739"}, {"first_name"=>"Liping", "last_name"=>"Tong", "scopus_author_id"=>"36165931100"}, {"first_name"=>"Peter J.", "last_name"=>"Lamberson", "scopus_author_id"=>"36177986700"}, {"first_name"=>"Amy H.", "last_name"=>"Auchincloss", "scopus_author_id"=>"14631820900"}, {"first_name"=>"Jun", "last_name"=>"Zhang", "scopus_author_id"=>"55270456900"}, {"first_name"=>"Lara", "last_name"=>"Dugas", "scopus_author_id"=>"20733894900"}, {"first_name"=>"Jay S.", "last_name"=>"Kaufman", "scopus_author_id"=>"35447296100"}, {"first_name"=>"Richard S.", "last_name"=>"Cooper", "scopus_author_id"=>"56662407500"}, {"first_name"=>"Amy", "last_name"=>"Luke", "scopus_author_id"=>"7004429379"}], "year"=>2012, "source"=>"PLoS ONE", "identifiers"=>{"issn"=>"19326203", "pmid"=>"22768124", "scopus"=>"2-s2.0-84863083786", "sgr"=>"84863083786", "doi"=>"10.1371/journal.pone.0039795", "pui"=>"365133397", "isbn"=>"1932-6203 (Electronic)\\n1932-6203 (Linking)"}, "id"=>"a5090892-65e0-3a91-8561-46c3fd5af099", "abstract"=>"Recent studies suggest that obesity may be \"contagious\" between individuals in social networks. Social contagion (influence), however, may not be identifiable using traditional statistical approaches because they cannot distinguish contagion from homophily (the propensity for individuals to select friends who are similar to themselves) or from shared environmental influences. In this paper, we apply the stochastic actor-based model (SABM) framework developed by Snijders and colleagues to data on adolescent body mass index (BMI), screen time, and playing active sports. Our primary hypothesis was that social influences on adolescent body size and related behaviors are independent of friend selection. Employing the SABM, we simultaneously modeled network dynamics (friendship selection based on homophily and structural characteristics of the network) and social influence. We focused on the 2 largest schools in the National Longitudinal Study of Adolescent Health (Add Health) and held the school environment constant by examining the 2 school networks separately (N = 624 and 1151). Results show support in both schools for homophily on BMI, but also for social influence on BMI. There was no evidence of homophily on screen time in either school, while only one of the schools showed homophily on playing active sports. There was, however, evidence of social influence on screen time in one of the schools, and playing active sports in both schools. These results suggest that both homophily and social influence are important in understanding patterns of adolescent obesity. Intervention efforts should take into consideration peers' influence on one another, rather than treating \"high risk\" adolescents in isolation.", "link"=>"http://www.mendeley.com/research/actorbased-model-social-network-influence-adolescent-body-size-screen-time-playing-sports", "reader_count"=>91, "reader_count_by_academic_status"=>{"Unspecified"=>2, "Professor > Associate Professor"=>5, "Student > Doctoral Student"=>10, "Researcher"=>11, "Student > Ph. D. Student"=>29, "Student > Postgraduate"=>3, "Student > Master"=>15, "Other"=>7, "Student > Bachelor"=>4, "Lecturer"=>2, "Lecturer > Senior Lecturer"=>1, "Professor"=>2}, "reader_count_by_user_role"=>{"Unspecified"=>2, "Professor > Associate Professor"=>5, "Student > Doctoral Student"=>10, "Researcher"=>11, "Student > Ph. D. Student"=>29, "Student > Postgraduate"=>3, "Student > Master"=>15, "Other"=>7, "Student > Bachelor"=>4, "Lecturer"=>2, "Lecturer > Senior Lecturer"=>1, "Professor"=>2}, "reader_count_by_subject_area"=>{"Unspecified"=>6, "Agricultural and Biological Sciences"=>4, "Arts and Humanities"=>1, "Business, Management and Accounting"=>3, "Computer Science"=>5, "Decision Sciences"=>1, "Economics, Econometrics and Finance"=>1, "Environmental Science"=>2, "Nursing and Health Professions"=>2, "Mathematics"=>1, "Medicine and Dentistry"=>14, "Design"=>1, "Sports and Recreations"=>8, "Psychology"=>13, "Social Sciences"=>29}, "reader_count_by_subdiscipline"=>{"Medicine and Dentistry"=>{"Medicine and Dentistry"=>14}, "Social Sciences"=>{"Social Sciences"=>29}, "Decision Sciences"=>{"Decision Sciences"=>1}, "Sports and Recreations"=>{"Sports and Recreations"=>8}, "Psychology"=>{"Psychology"=>13}, "Mathematics"=>{"Mathematics"=>1}, "Unspecified"=>{"Unspecified"=>6}, "Environmental Science"=>{"Environmental Science"=>2}, "Arts and Humanities"=>{"Arts and Humanities"=>1}, "Design"=>{"Design"=>1}, "Economics, Econometrics and Finance"=>{"Economics, Econometrics and Finance"=>1}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>4}, "Computer Science"=>{"Computer Science"=>5}, "Business, Management and Accounting"=>{"Business, Management and Accounting"=>3}, "Nursing and Health Professions"=>{"Nursing and Health Professions"=>2}}, "reader_count_by_country"=>{"Iran"=>1, "United States"=>4, "Norway"=>1, "Brazil"=>1, "Denmark"=>1, "United Kingdom"=>2, "Tunisia"=>1, "Portugal"=>2, "Germany"=>1}, "group_count"=>14}

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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/615462"], "description"=>"<p>Behavioral change parameters are adjusted for network structural parameters (<a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0039795#pone-0039795-t003\" target=\"_blank\">Table 3</a> and <a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0039795#pone-0039795-t004\" target=\"_blank\">4</a>).</p><p>Linear and quadratic shape parameters are the effects of the ego’s own behavior (linear) and behavior-squared (quadratic) on his or her future behavior. The “average similarity” parameters represent social influence of the alters’ on the ego.</p>", "links"=>[], "tags"=>["parameters"], "article_id"=>285953, "categories"=>["Information And Computing Sciences", "Biotechnology"], "users"=>["David A. Shoham", "Liping Tong", "Peter J. Lamberson", "Amy H. Auchincloss", "Jun Zhang", "Lara Dugas", "Jay S. Kaufman", "Richard S. Cooper", "Amy Luke"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0039795.t005", "stats"=>{"downloads"=>1, "page_views"=>7, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Network_influence_on_behavior_parameters_and_95_confidence_intervals_/285953", "title"=>"Network influence on behavior, parameters and (95% confidence intervals).", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-02-20 03:06:10"}
  • {"files"=>["https://ndownloader.figshare.com/files/615434"], "description"=>"<p>Probability of ego’s increasing (+1), decreasing (−1), or remaining at the same body mass index (BMI) in the next time step, based on ego’s and average alters’ current BMI.</p>", "links"=>[], "tags"=>["decreasing"], "article_id"=>285922, "categories"=>["Information And Computing Sciences", "Biotechnology"], "users"=>["David A. Shoham", "Liping Tong", "Peter J. Lamberson", "Amy H. Auchincloss", "Jun Zhang", "Lara Dugas", "Jay S. Kaufman", "Richard S. Cooper", "Amy Luke"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0039795.t006", "stats"=>{"downloads"=>1, "page_views"=>4, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Probability_of_ego_8217_s_increasing_1_decreasing_8722_1_or_remaining_at_the_same_body_mass_index_BMI_in_the_next_time_step_based_on_ego_8217_s_and_average_alters_8217_current_BMI_/285922", "title"=>"Probability of ego’s increasing (+1), decreasing (−1), or remaining at the same body mass index (BMI) in the next time step, based on ego’s and average alters’ current BMI.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-02-20 03:05:58"}
  • {"files"=>["https://ndownloader.figshare.com/files/615509"], "description"=>"<p>Network change parameters are adjusted for structural (<a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0039795#pone-0039795-t003\" target=\"_blank\">Table 3</a>) and behavior change parameters (<a href=\"http://www.plosone.org/article/info:doi/10.1371/journal.pone.0039795#pone-0039795-t005\" target=\"_blank\">Table 5</a>).</p>1<p>Positive values for attractiveness indicate that egos generally prefer to become or maintain friendships with alters who have high levels of the BMI or behavior; negative values indicate a disinclination to keep or maintain friendships with individuals with high levels of the BMI or behavior.</p>2<p>Sociability indicates that egos with high levels of BMI or the behavior prefer to have more friends.</p>3<p>Similarity is the measure of homophily on BMI or the behavior. Positive values indicate a preference for alters whose values are similar to the ego’s.</p>", "links"=>[], "tags"=>["jefferson", "sunshine", "parameters"], "article_id"=>285995, "categories"=>["Information And Computing Sciences", "Biotechnology"], "users"=>["David A. Shoham", "Liping Tong", "Peter J. Lamberson", "Amy H. Auchincloss", "Jun Zhang", "Lara Dugas", "Jay S. Kaufman", "Richard S. Cooper", "Amy Luke"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0039795.t004", "stats"=>{"downloads"=>5, "page_views"=>37, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Behavioral_influence_on_network_choice_for_Jefferson_and_Sunshine_High_parameters_and_95_confidence_intervals_/285995", "title"=>"Behavioral influence on network choice for Jefferson and Sunshine High, parameters and (95% confidence intervals).", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-02-20 03:06:22"}
  • {"files"=>["https://ndownloader.figshare.com/files/615328"], "description"=>"<p>For continuous measures, mean values are given with standard deviations in parentheses. For categorical variables, percentages are given.</p>1<p>“Sum of BMI similarities” is the mean value for the <i>total sum of</i> BMI similarities between the actor and each of his or her alters.</p>2<p>“BMI average similarity” is the mean value for the <i>average</i> similarity between an actor and his or her alters.</p>", "links"=>[], "tags"=>["characteristics", "baseline"], "article_id"=>285817, "categories"=>["Information And Computing Sciences", "Biotechnology"], "users"=>["David A. Shoham", "Liping Tong", "Peter J. Lamberson", "Amy H. Auchincloss", "Jun Zhang", "Lara Dugas", "Jay S. Kaufman", "Richard S. Cooper", "Amy Luke"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0039795.t002", "stats"=>{"downloads"=>1, "page_views"=>34, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Respondent_characteristics_at_baseline_Wave_1_unless_otherwise_noted_/285817", "title"=>"Respondent characteristics at baseline (Wave 1), unless otherwise noted.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-02-20 03:05:20"}
  • {"files"=>["https://ndownloader.figshare.com/files/615556"], "description"=>"<p>The playing active sports score is the frequency in the past week: 0 = not at all; 1 = 1 or 2 times; 2 = 3 or 4 times; 3 = 5 or more times. Egos may increase by one level, decrease by one level, or stay at the same level.</p>", "links"=>[], "tags"=>["playing", "sports"], "article_id"=>286043, "categories"=>["Information And Computing Sciences", "Biotechnology"], "users"=>["David A. Shoham", "Liping Tong", "Peter J. Lamberson", "Amy H. Auchincloss", "Jun Zhang", "Lara Dugas", "Jay S. Kaufman", "Richard S. Cooper", "Amy Luke"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0039795.t008", "stats"=>{"downloads"=>0, "page_views"=>3, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Probability_of_changing_ego_8217_s_playing_active_sports_score_in_the_next_time_step_based_on_ego_8217_s_and_average_alters_8217_current_active_sports_score_/286043", "title"=>"Probability of changing ego’s playing active sports score in the next time step, based on ego’s and average alters’ current active sports score.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-02-20 03:06:35"}
  • {"files"=>["https://ndownloader.figshare.com/files/615394"], "description"=>"<p>Change means increasing or decreasing by one 10 hour interval, or staying at the same level.</p>", "links"=>[], "tags"=>["10"], "article_id"=>285884, "categories"=>["Information And Computing Sciences", "Biotechnology"], "users"=>["David A. Shoham", "Liping Tong", "Peter J. Lamberson", "Amy H. Auchincloss", "Jun Zhang", "Lara Dugas", "Jay S. Kaufman", "Richard S. Cooper", "Amy Luke"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0039795.t007", "stats"=>{"downloads"=>0, "page_views"=>3, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Probability_of_changing_ego_8217_s_screen_time_in_the_next_time_step_based_on_ego_8217_s_and_average_alters_8217_current_screen_time_score_in_10_hour_intervals_/285884", "title"=>"Probability of changing ego’s screen time in the next time step, based on ego’s and average alters’ current screen time score (in 10 hour intervals).", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-02-20 03:05:46"}
  • {"files"=>["https://ndownloader.figshare.com/files/615370"], "description"=>"<p>Key terms used in this paper.</p>", "links"=>[], "tags"=>["public health and epidemiology", "computer science"], "article_id"=>285854, "categories"=>["Information And Computing Sciences", "Biotechnology"], "users"=>["David A. Shoham", "Liping Tong", "Peter J. Lamberson", "Amy H. Auchincloss", "Jun Zhang", "Lara Dugas", "Jay S. Kaufman", "Richard S. Cooper", "Amy Luke"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0039795.t001", "stats"=>{"downloads"=>0, "page_views"=>34, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Key_terms_used_in_this_paper_/285854", "title"=>"Key terms used in this paper.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-02-20 03:05:33"}
  • {"files"=>["https://ndownloader.figshare.com/files/615280"], "description"=>"1<p>Parameters are the weights actors place on various network configurations. They are the contributions to the objective function. The 95% confidence intervals quantify the precision of the estimates a score function method.</p>2<p>The basic rate parameter for friendship controls how often actors have the opportunity to change their network (add, keep, or drop a friend). Higher values indicate more network changes.</p>3<p>The outdegree parameter is the weight placed on having a friendship tie with <i>any</i> member of the social network, irrespective of the alter’s characteristics.</p>4<p>The reciprocity parameter is the weight an actor places on reciprocating alters’ friendship nominations.</p>5<p>The transitive triplets parameter is the weight an actor places on naming friends who are also named by the actor’s friend.</p>6<p>Positive values of “same” and “similarity” measures are the effects of homophily on these attributes.</p>", "links"=>[], "tags"=>["influences", "jefferson", "sunshine", "parameters"], "article_id"=>285759, "categories"=>["Information And Computing Sciences", "Biotechnology"], "users"=>["David A. Shoham", "Liping Tong", "Peter J. Lamberson", "Amy H. Auchincloss", "Jun Zhang", "Lara Dugas", "Jay S. Kaufman", "Richard S. Cooper", "Amy Luke"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0039795.t003", "stats"=>{"downloads"=>1, "page_views"=>4, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Structural_influences_on_network_for_Jefferson_and_Sunshine_High_parameters_and_95_confidence_intervals_1_/285759", "title"=>"Structural influences on network for Jefferson and Sunshine High, parameters and (95% confidence intervals).<sup>1</sup>", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2013-02-20 03:05:01"}

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