Let’s talk: The dual process model of supportive communication in peers

Supportive messages occur within most relationships. Researchers have found strong relationships between social support and various physical and psychological health outcomes, but the specific mechanisms at work have yet to be fully explored. Many factors contribute to whether a supportive interaction is processed as helpful or supportive by the recipient including relational factors, message content, past experiences, etc. For peer dyads, the context and supportive messages individuals provide their peer may inhibit or contribute to their perception of their peer’s supportive behavior. The current study examined the impact of contextual factors (such as family communication patterns and relationship quality) on message content and the perception of social support within peer relationships. Emerging adult dyads (N = 127) were recruited from a large Southern university in the United States to discuss one of four topics (e.g., a stressful life event, risky sexual behavior, loss of a loved one, discuss a traumatic event) with a peer so that the processes among contextual factors, supportive message content, and supportive message processing could be examined. The association between contextual factors on how individuals processed a supportive interaction was mediated by the content of the supportive conversation. Limitations, strengths, and implications were discussed

The lived experience of non-offending mothers in cases of intrafamilial child sexual abuse: Towards a preliminary model of loss, trauma and recovery

The non-offending mother in cases of intrafamilial child sexual abuse has received limited empirical attention in comparative to the considerable body of literature examining victims and perpetrators of child sexual abuse. There is growing evidence that demonstrates that nonoffending mothers’ experience significant loss and trauma following the discovery of their children’s sexual victimisation by a family member, particularly where the perpetrators are their partners. An understanding of the non-offending mother’s experience is crucial to guiding statutory agencies and therapeutic interventions when working with these families. However, there is currently not a model or framework that conceptualises mothers’ post-discovery experience, and the factors that might impede or facilitate their recovery. The aim with the present study was to address the gap in the existing literature, by conducting an exploratory investigation of the lived experience of non-offending mothers in order to generate a preliminary model outlining their recovery journey in the aftermath of discovery, drawing from existing theories of loss and trauma. The present study comprises two stages; in the first stage, qualitative interviews were conducted with a sample of eleven mothers. Data derived from the interviews were analysed using qualitative thematic analysis, from which a preliminary model was generated. The model proposed the non-offending mother’s recovery journey comprises three primary phases; the Acute Phase (Discovery and Destabilisation), the Transition Phase (Loss and Disempowerment), and the Transformative Phase (Taking Control and Accommodation). The preliminary model identified unique aspects of the maternal experience not sufficiently accounted for by many of the existing theoretical conceptualisations. The second stage of the study utilised a Delphi methodology to seek feedback on the proposed model from a panel of 18 key experts in the field of intrafamilial child sexual abuse. The input from the Delphi panel was utilised to further refine and validate the preliminary model. The panel confirmed the preliminary model provided a valid representation of the non-offending mother’s post-discovery experience with minor alterations. The findings of the present study are an important progression towards developing a more comprehensive and unified conceptualisation of the experiences of the non-offending mother in the aftermath of discovery. This in turn has important implications for the intervening professionals from both statutory and therapeutic orientations who work with this population

Women rule: An alternative voice on the Supreme Court of Canada

Various studies have researched the relative involvement of elected women versus elected men in issues that are generally considered to be of primary interest to women at the legislative level. However, there is only a small body of research in the area of political science on gender and the judiciary, specifically with regard to Canada. The small number of female justices is a limiting factor, but the presence of women in the judiciary offers an important opportunity for academic study. To achieve effective results in this study, case law of the Supreme Court of Canada from the period of 1982-2003 will be examined. This study will also consider the effects of four women on the nine member bench, this is not only unprecedented in Canada, but elsewhere in the world. A certain set of cases that might be considered to be of interest to women will be analyzed to determine whether women judges make a difference, by bringing to their decisions new principles and precedents, or whether their decisions conformed to those made by male judges. This study utilizes tenets of feminist methodology, such as placing women\u27s experiences at the centre, contextualizing women\u27s lives within their social and cultural milieu, and being attentive to the diversity of women\u27s experiences. By using both qualitative and quantitative methods of research, this study will determine the degree of validity of the hypothesis that the appointment of more female justices would increase the likelihood that certain perspectives, shared by many women, would be available on the bench.Dept. of History, Philosophy, and Political Science. Paper copy at Leddy Library: Theses & Major Papers - Basement, West Bldg. / Call Number: Thesis2005 .G33. Source: Masters Abstracts International, Volume: 44-03, page: 1215. Thesis (M.A.)--University of Windsor (Canada), 2005

Effects of Online Self-Disclosure on Social Feedback During the COVID-19 Pandemic

We investigate relationships between online self-disclosure and received social feedback during the COVID-19 crisis. We crawl a total of 2,399 posts and 29,851 associated comments from the r/COVID19_support subreddit and manually extract fine-grained personal information categories and types of social support sought from each post. We develop a BERT-based ensemble classifier to automatically identify types of support offered in users' comments. We then analyze the effect of personal information sharing and posts' topical, lexical, and sentiment markers on the acquisition of support and five interaction measures (submission scores, the number of comments, the number of unique commenters, the length and sentiments of comments). Our findings show that: 1) users were more likely to share their age, education, and location information when seeking both informational and emotional support, as opposed to pursuing either one; 2) while personal information sharing was positively correlated with receiving informational support when requested, it did not correlate with emotional support; 3) as the degree of self-disclosure increased, information support seekers obtained higher submission scores and longer comments, whereas emotional support seekers' self-disclosure resulted in lower submission scores, fewer comments, and fewer unique commenters; 4) post characteristics affecting social feedback differed significantly based on types of support sought by post authors. These results provide empirical evidence for the varying effects of self-disclosure on acquiring desired support and user involvement online during the COVID-19 pandemic. Furthermore, this work can assist support seekers hoping to enhance and prioritize specific types of social feedback

Essays on Individuals’ Information Assessment, Information Disclosure, Participation, and Response Behaviors in Online Health Communities

The emergence of online health communities (OHCs) has enabled the use of information technologies to address some social and health needs including but not limited to emotional, social, and health-related issues. This information age has encouraged user generated (UG) content, which facilitates both peer-to-peer and business-to-peer interconnections. This rich and active information epoch (i.e., OHCs) is distinct in that value is generated when peers or participants—who may be content generators and/or content consumers—interact together by exchanging information and receiving supports aimed at addressing their specific needs; and this is made possible through the online platforms or support groups acting as the intermediary among users. In this dissertation, I explore the dynamics that take place in OHCs by answering varied sets of questions and addressing and stretching different scholarly discourses including individuals’ information assessment, information disclosure, participation, and response behaviors in OHCs from a variety of theoretical perspectives including disclosure decision-making model and social presence theory, using diverse methodologies such as text analytics, two-stage least squares regression technique, decision trees analysis, and vector autoregression models in the OHC context. The overarching research question is: How does assessment of information and receiver influence patients’ disclosure ability and what user information disclosure mechanisms elicit effective support behaviors in online health communities? Patients with different disease types visit OHCs to get support and this support is made possible because patients participate by interacting with peers and providing responses to each other’s discussion. Support behaviors, especially in the OHC context, is a concept that covers facets such as, provision of response; interactivity or participation in discussions; relationship management; and offering helpful, appropriate, and relevant feedback responses to meet specific information, social, or emotional needs (Huang et al., 2019; Nambisan et al., 2016; Chen et al., 2019). By exploring the research question and with the unique features that these OHC platforms exhibit—the sharing of information, participation, and receiving of supports—these essays make the following contributions. Theoretically, the findings reveal that a patient’s disease type, the sensitivity of information being disclosed, and patient’s expectation of a response show unique effects on disclosure efficacy. These factors constitute mechanisms by which patients in OHCs are motivated to disclose health information in granular forms that elicit effective community responses and feedback. This information exchange mechanisms thereby, facilitate active community participation through giving or receiving of support, and thus, fostering a dynamic interplay between individuals’ disclosure and response behaviors in the online context. Practically, online health community managers can design their platforms to provide automated and customizable tools that improve patients’ information density and information breadth skills for effective response generation; and from the results, platform management can better understand users that are motivated to participate through giving, thereby encouraging those that are weak in receiving. Also, platform managers can improve the skills of those who are weak in giving for users that are motivated to participate through receiving. Essay 1: Promoting Participants’ Information Disclosure and Response Behaviors in Online Health Communities: Disclosure Decision-Making Model Perspective In this first essay, I extend the literature on information disclosure and the disclosure decision-making model (DD-MM) by examining the factors that influence information disclosure (disclosure efficacy) and the effects of disclosure efficacy on the response users receive (response efficacy) at the granular level. Until now, both concepts—disclosure efficacy and response efficacy have been conceptualized as single constructs. This current study breaks new grounds and broaden the DD-MM model by postulating that the subconstructs have different antecedents and consequences. By examining the relationships between the subconstructs of information assessment, disclosure efficacy, and response efficacy using the two-stage least squares regression method, the results reveal some insightful dynamics, otherwise not possible with unidimensional constructs. Essay 2: Investigation of non-linear effects of first impression cues on participation in online health communities: A decision tree induction theory development approach One notable phenomenon that prior literature has extensively explored in OHC platforms is user participation, which is a necessary condition for platform sustainment and value generation. Extant research has studied user participation as a form of giving, that is, how much users participate in online platforms by generating content (e.g., posting messages, replying to messages, or posting pictures).However, participation in OHC platforms can also take the form of receiving (the consumption for content that has been generated – e.g., reading other’s posts, gaining knowledge and support), and this has witnessed little attention in prior research. This third study argues that the giving and receiving participation is a reaction to user initial participation. In this second essay, based on social presence theory (SPT), I use decision tree analysis to interrogate the effect of first impression in the initial posts on users’ giving and receiving participation. The findings provide meaningful insights for advancing research and for assisting platform managers on what to focus on to encourage users’ giving or receiving participation on their platforms. Essay 3: User Two-way Communication Efficacy Behaviors in Online Health Communities: A Longitudinal Study In this second essay, I crack into some unsupported relationships between disclosure efficacy and response efficacy shown in the previous study, which could be due to the use of cross-sectional data in the analysis, giving nonsignificant findings. Over time, it is possible that the effectiveness of the response that disclosers receive could determine whether users will further disclose or not. For example, if a discloser does not receive valuable response that addresses his or her needs, he or she may stop posting or disclosing information on the platform, thus, leading to lurking behaviors or less recommendations for others to join the online platform. This current study proposes a two-way relationship between disclosure efficacy and response efficacy of users’ interactions in online health communities instead of looking at only the one-way relationship from disclosure efficacy to response efficacy (which showed some insignificant results). From an econometric perspective, time has been shown to play a dynamic role on variables and their relationships. Thus, this current paper uses dynamic vector autoregression (VAR) modeling technique with a longitudinal data set to investigate the one-way and two-way relationships between disclosure efficacy and response efficacy and their dimensions (information density and information breadth) and (information persuasiveness and response persuasiveness), respectively. The analysis reveals a recursive relationship between disclosure efficacy and response efficacy and some of their dimensions. This is a departure from some prior literature that proposed a static linear order in end-user information consumption. The significance of the nonlinear recursive relationship is marked extension of the DD-MM model by establishing the reenforcing effect of its key variables

Self-disclosure model for classifying & predicting text-based online disclosure

Les médias sociaux et les sites de réseaux sociaux sont devenus des babillards numériques pour les internautes à cause de leur évolution accélérée. Comme ces sites encouragent les consommateurs à exposer des informations personnelles via des profils et des publications, l'utilisation accrue des médias sociaux a généré des problèmes d’invasion de la vie privée. Des chercheurs ont fait de nombreux efforts pour détecter l'auto-divulgation en utilisant des techniques d'extraction d'informations. Des recherches récentes sur l'apprentissage automatique et les méthodes de traitement du langage naturel montrent que la compréhension du sens contextuel des mots peut entraîner une meilleure précision que les méthodes d'extraction de données traditionnelles. Comme mentionné précédemment, les utilisateurs ignorent souvent la quantité d'informations personnelles publiées dans les forums en ligne. Il est donc nécessaire de détecter les diverses divulgations en langage naturel et de leur donner le choix de tester la possibilité de divulgation avant de publier. Pour ce faire, ce travail propose le « SD_ELECTRA », un modèle de langage spécifique au contexte. Ce type de modèle détecte les divulgations d'intérêts, de données personnelles, d'éducation et de travail, de relations, de personnalité, de résidence, de voyage et d'accueil dans les données des médias sociaux. L'objectif est de créer un modèle linguistique spécifique au contexte sur une plate-forme de médias sociaux qui fonctionne mieux que les modèles linguistiques généraux. De plus, les récents progrès des modèles de transformateurs ont ouvert la voie à la formation de modèles de langage à partir de zéro et à des scores plus élevés. Les résultats expérimentaux montrent que SD_ELECTRA a surpassé le modèle de base dans toutes les métriques considérées pour la méthode de classification de texte standard. En outre, les résultats montrent également que l'entraînement d'un modèle de langage avec un corpus spécifique au contexte de préentraînement plus petit sur un seul GPU peut améliorer les performances. Une application Web illustrative est conçue pour permettre aux utilisateurs de tester les possibilités de divulgation dans leurs publications sur les réseaux sociaux. En conséquence, en utilisant l'efficacité du modèle suggéré, les utilisateurs pourraient obtenir un apprentissage en temps réel sur l'auto-divulgation.Social media and social networking sites have evolved into digital billboards for internet users due to their rapid expansion. As these sites encourage consumers to expose personal information via profiles and postings, increased use of social media has generated privacy concerns. There have been notable efforts from researchers to detect self-disclosure using Information extraction (IE) techniques. Recent research on machine learning and natural language processing methods shows that understanding the contextual meaning of the words can result in better accuracy than traditional data extraction methods. Driven by the facts mentioned earlier, users are often ignorant of the quantity of personal information published in online forums, there is a need to detect various disclosures in natural language and give them a choice to test the possibility of disclosure before posting. For this purpose, this work proposes "SD_ELECTRA," a context-specific language model to detect Interest, Personal, Education and Work, Relationship, Personality, Residence, Travel plan, and Hospitality disclosures in social media data. The goal is to create a context-specific language model on a social media platform that performs better than the general language models. Moreover, recent advancements in transformer models paved the way to train language models from scratch and achieve higher scores. Experimental results show that SD_ELECTRA has outperformed the base model in all considered metrics for the standard text classification method. In addition, the results also show that training a language model with a smaller pre-training context-specific corpus on a single GPU can improve its performance. An illustrative web application designed allows users to test the disclosure possibilities in their social media posts. As a result, by utilizing the efficiency of the suggested model, users would be able to get real-time learning on self-disclosure

Digital dating : online dating profiles of older and younger gay, lesbian, and heterosexual adults

Online dating is a common way for older, gay, and lesbian adults to find a romantic partner, yet little is known about their dating motivations and self-presentations. Adults of different ages, genders, and sexual orientations may have different approaches to dating and presenting themselves online. Adults’ profiles are likely to differ based on evaluations of the desires of potential partners, as well as individuals own stage in life and place in their broader social environment. Using a mixed method approach in three studies, this dissertation examines thousands of dating profiles randomly sampled from two popular dating websites and various regions of the US. The first two studies examine the dating profiles of older and younger gay, lesbian, and heterosexual adults. Study 1 explores the extent to which adults emphasize the “self” versus connections to others. Study 2 examines the degree to which adults discuss and display their bodies and sexuality. Study 3 utilizes a separate dataset of older gay, lesbian, and heterosexual adults and focuses on common profile content and potential regional differences in profile content. Results revealed that older adults were more focused on close social ties in their profiles, while younger adults were focused on the self and were more likely to post different types of photographs. Further, older adults were just as likely as younger adults to discuss sexuality in their profiles, but less likely to display their bodies in photographs. Gay and lesbian adults were more likely to emphasize friendships, while heterosexual adults focused more on family. Gay men and heterosexual women seemed to craft their profiles to appeal to men’s desire for physical attractiveness and sexuality, using photos to display their bodies. Conversely, heterosexual men and lesbian women presented themselves as focused on others, perhaps to appeal to the communal nature associated with women. With regard to regional environment, older gay and lesbian adults residing in environments with low structural support for LGBT people were most likely to emphasize a desire for shared experiences, potentially reflecting feelings of disconnectedness to their environments. Findings suggest that despite the scripted nature of dating profiles, adults with different characteristics may have distinct motivations when seeking a romantic partner.Human Development and Family Science

Reexamining the use of tentative language in emails: The effects of gender salience and gender typicality

Drawing on self-categorization theory, the current study examines the effects of gender salience and interlocutor gender typicality on men and women’s use of tentative language in emails. We conducted an experiment manipulating identity salience using gender-stereotypic conversation topics, and typicality using biographies of the fictitious female interlocutor. The results were consistent with self-categorization theory and previous research on gender-based language use: Men were more tentative when discussing a conversation topic in which their gender group was not considered experts. More important, interlocutor gender typicality influenced participants’ tentative language, such that when the interlocutor was a typical woman, men and women became more tentative discussing a conversation topic in which they were not considered experts. This study has implications for future research on the contextual factors that may influence the use of language in both intragroup and intergroup communication

Exploring the mechanisms of sex and grade differences in relational/indirect/social aggression

The purpose of the project was to explore sex and grade differences observed in RISA (a term used to refer collectively to relational, indirect, and social aggression). Three theories used to explain sex and grade differences, namely, gender socialization theory (Bjorkqvist, 1994;Lagerspetz & Bjorkqvist, 1994; Lagerspetz, Bjorkqvist, & Peltonen, 1988), target-value theory(Bjorkqvist, Lagerspetz, & Kaukiainen, 1992; Lagerspetz et al, 1988; Crick & Grotpeter, 1995),and symbolic capital theory (Campbell, 1993; Cashdan, 1997; Eckert, 1990; Horney 1934a, 1934b, 1934c) were reviewed, expanded upon, and tested. Theories were tested using questionnaires; however, a small subset of participants also completed individual interviews to add greater depth to information provided by the quantitative data. A second purpose of the project was to use a measure that represents the diversity of RISA items found in other measures currently used by researchers since research has suggested inconsistencies in findings may be related to item composition. Participants were 521 (301 girls and 220 boys) in grades six (n = 224), seven (n = 224) and eight (n = 73) from various Canadian schools (average age of 12.2 years) who completed the questionnaires. From this sample, 28 students completed individual interviews. Results indicated that boys and girls did not differ in regard to self-reported use of RISA; however, interviews and peer nominations indicated that girls have the reputation for engaging in RISA more frequently than boys. Post-hoc analyses indicated that the appearance of sex differences in RISA may be influenced by item choice as some items on the self-report measure were more highly reported by boys, while others were more likely to be reported by girls. There was not a great deal of support for any of the theories tested. Results indicated that the pattern of connections for predictors of RISA frequently did not differ by sex. Factors like perceived risk of or discomfort with using aggression, affective reactions to relationship threats, and care about one’s own or a peer’s performance in a number of life domains were connected to RISA for both sexes