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A wealth of research demonstrates a strong link between insecure attachment and depressive symptoms. However, thus far no work has discerned different pathways to depression for each of the insecure subtypes: anxious and avoidant attachment. This work looks at the behaviors that couples engage in during a conflict interaction as a potential mediator for the attachment-depression relationship, with different behaviors mediating the link between anxious and avoidant attachment and depression. For anxiously attached individuals, it was predicted that lack of support and response from the partner (actual or perceived) would account for the relationship between their attachment and depressive symptoms. While for avoidant individuals, it was predicted that partners’ hostile behaviors would account for a positive association between attachment and depression, but humor and relationship-enhancing behaviors would account for a negative association between attachment and depression. Results from this work indicated that for anxiously attached women, their perceptions of their partners’ responsiveness and their partners’ actual hostility mediated the link between their attachment and depressive symptoms.

Organizations often take trust for granted or ignore it, although trust is important for organizational learning and performance. Organizations must continuously learn if they are to survive, and trust facilitates individual and organizational learning. However, many authors either mention the importance of trust, or assume trust is present, and then discuss other topics as if little can be done to better understand the antecedents of trust or to improve trust in an organization. In particular, prior to this study, researchers had not explored the influence of adult attachment and disclosiveness on organizational trust. Human resources development professionals can play a vital role by helping leaders in their organizations attain strategic goals, however, no research study done previously has focused on how trust in an organization is influenced by adult attachment and disclosiveness. There is a need to better understand organizational trust because in today's global economy, an organization's ability to survive may depend in part on individual and organizational learning facilitated by trust. This study focused on a main research question "What portion of the variance in employees' perceptions of organizational trust do employees' adult attachment and disclosiveness explain?" During this research, a revised instrument for measuring organizational trust was developed. The findings of this study showed that disclosiveness did not have a statistically significant influence on organizational trust. In contrast, fearful attachment, in particular was shown to have a modest, statistically significant, and negative influence on organizational trust. / Ph. D.

Mental health practitioners who incorporate animal-assisted interventions into clinical practice harness the human-animal bond for therapeutic benefit. According to the Animal-Assisted Therapy in Counseling Competencies, practitioners have a duty to understand the complex relational processes within animal-assisted interventions in counseling (AAI-C). These bonding processes may resemble that of an attachment bond in which the client desires to maintain closeness to the practitioner and therapy animal as a result of feeling safe and secure. Researchers studying attachment in the human-animal bond have stated that attachment processes may occur within other human-animal relationships, such as between a guardian and a companion animal. However, there is no empirical research on the attachment processes occurring between humans and therapy animals in AAI-C or how these processes affect the bond between the practitioner and client. A component of the working alliance, maintaining a quality bond can improve treatment outcomes in counseling. Therefore, the purpose of this quantitative study was to examine how attachment to a therapy animal impacts the attachment bond between a mental health practitioner and client. Participants completed an online survey with four measures to study the following: (a) client attachment to the therapy animal, (b) practitioner attachment to the therapy animal, (c) the bond between the practitioner and client, and (d) the impact of utilizing an animal in counseling sessions. Data analyses included a multiple regression to determine how practitioners' perceptions of the attachment processes within AAI-C best explain the bond with their clients. Descriptive analysis revealed that practitioners perceived high quality bonding within AAI-C, particularly in their own attachment to the therapy animal. Results of the multiple regression indicated practitioners' attachment to the therapy animal was a significant predictor of the working alliance and bond between the practitioner and client. Practitioners who perceived themselves as extremely skilled in working with the clients' presenting issue also had a statistically significant effect on the working alliance and bond when compared to practitioners who felt less skilled. Implications for practitioners and counselor educators are provided. Limitations and areas of future research are also discussed. / Doctor of Philosophy / Mental health practitioners who incorporate animal-assisted interventions into clinical practice harness the human-animal bond for therapeutic benefit. According to the Animal-Assisted Therapy in Counseling Competencies, practitioners have a duty to understand the complex relational processes within animal-assisted interventions in counseling (AAI-C). These bonding processes may resemble that of an attachment bond in which the client desires to maintain closeness to the practitioner and therapy animal as a result of feeling safe and secure. Researchers studying attachment in the human-animal bond have stated that attachment processes may occur within other human-animal relationships, such as between a guardian and a companion animal. However, there is no practical research on the attachment processes occurring between humans and therapy animals in AAI-C or how these processes affect the bond between the practitioner and client. A component of the working alliance, maintaining a quality bond, can improve treatment outcomes in counseling. Therefore, the purpose of this quantitative study was to examine how attachment to a therapy animal impacts the attachment bond between a mental health practitioner and client. Participants completed an online survey with four measures to study the following: (a) client attachment to the therapy animal, (b) practitioner attachment to the therapy animal, (c) the bond between the practitioner and client, and (d) the impact of utilizing an animal in counseling sessions. Data analyses included a multiple regression to determine how practitioners’ perceptions of the attachment processes within AAI-C best explain the bond with their clients. Descriptive statistics revealed that practitioners perceived high quality bonding within AAI-C, particularly in their own attachment to the therapy animal. Results of the multiple regression indicated practitioners’ attachment to the therapy animal influenced the working alliance and bond between the practitioner and client. Practitioners who perceived themselves as extremely skilled in working with the clients’ presenting issue also had an effect on the working alliance and bond when compared to practitioners who felt less skilled. Implications for practitioners and counselor educators are provided. Limitations and areas of future research are also discussed.

According to adult attachment theory (Hazan and Shaver, 1987), people's levels of insecure attachment, both anxious and avoidant, are associated with their abilities to regulate emotions in a relational context. This study is the first to test emotion dysregulation as a mediator for the relationships between levels of insecure attachment and psychological aggression using dyadic data. Cross-sectional, self-report data were collected from 110 couples presenting for couple or family therapy at an outpatient clinic. Data were analyzed using path analysis informed by the Actor-Partner Interdependence Mediational Model (APIMeM; Ledermann, Macho and Kenny, 2011). While the findings did not support a mediating role of emotion dysregulation between levels of anxious or avoidant attachment and psychological aggression, results indicated direct partner effects between people's own levels of anxious attachment and their partners' psychological aggression. Higher levels of anxious attachment were associated with higher levels of emotion dysregulation in both males and females; higher levels of avoidant attachment were only associated with higher levels of emotions dysregulation in females. Limitations and clinical implications for couple therapists are discussed. / Master of Science

Complex networks are composed of a large number of interacting nodes. Examples of complex networks include the topology of the Internet, connections between websites or web pages in the World Wide Web (WWW), and connections between participants in social networks.Due to their ubiquity, modeling complex networks is importantfor answering many research questions that cannot be answered without a mathematical model. For example, mathematical models of complex networks can be used to find the most vulnerable nodes to protect during a virus attack in theInternet, to predict connections between websites in the WWW, or to find members of different communities insocial networks. Researchers have analyzed complex networksand concluded that they are distinguished from other networks by four specific statistical properties. These four statistical properties are commonly known in this field as: (i) thesmall world effect,(ii) high average clustering coefficient, (iii) scale-free power law degree distribution, and (iv) emergence of community structure. These four statistical properties are further described later in this dissertation. Mostmodels used to generate complex networks attempt to produce networks with these statistical properties. Additionally, most of these network models generate homogeneous complex networks where all the networknodes are considered to have the same properties. Homogenous complex networks neglect the heterogeneous nature ofthe nodes in many complexnetworks. Moreover, somemodels proposed for generating heterogeneous complexnetworks are not general as they make specific assumptions about the properties of the network.Including heterogeneity in the connection algorithm of a modelwould makeitmore suitable for generating the subset of complex networks that exhibit selective linking.Additionally, all modelsproposed, to date, for generating heterogeneous complex networks do not preserve all four of the statistical properties of complexnetworks stated above. Thus, formulation of a model for the generation of general heterogeneous complex networkswith characteristics that resemble as much as possible the statistical properties common to the real-world networks that have received attention from the research community is still an open research question. In this work, we propose two new types of models to generate heterogeneous complex networks. First, we introduce the Integrated Attribute Similarity Model (IASM). IASM uses preferential attachment(PA) to connect nodes based on a similarity measure for node attributes combined with a node's structural popularity measure. IASM integrates the attribute similarity measure and a structural popularity measure in the computation of the connection function used to determine connectionsbetween each arriving (newly created) node and the existing(previously created or old) network nodes. IASM is also the first model known to assign an attribute vector having more than one element to each node, thus allowing different attributes per node in the generated complex network. Networks generated using IASM have a power law degree distribution and preserve the small world phenomenon. IASM models are enhanced to increase their clustering coefficient using a triad formation step (TFS). In a TFS, a node connects to the neighbor of the node to which it was previously connected through preferential attachment, thus forming a triad. The TFS increases the number of triads that are formed in the generated network which increases the network's average clustering coefficient. We also introduce a second novel model,the Settling Node Adaptive Model (SNAM). SNAM reflects the heterogeneous nature of connectionstandard requirements for nodes. The connectionstandard requirements for a noderefers to the values of attribute similarity and/or structural popularityof old node ythat node new xwould find acceptable in order to connect to node y.SNAM is novel in that such a node connection criterion is not included in any previous model for the generation of complex networks. SNAM is shown to be successful in preserving the power law degree distribution, the small world phenomenon, and the high clustering coefficient of complex networks. Next,we implement a modification to the IASM and SNAM models that results in the emergence of community structure.Nodes are classified into classes according to their attribute values. The connection algorithm is modified to include the class similarity values between network nodes. This community structure model preservesthe PL degree distribution, small world property, and does not affect average clustering coefficient values expected from both IASM and SNAM. Additionally, the model exhibits the presence of community structure having most of the connections made between nodes belonging to the same class with only a small percent of the connections made between nodes of different classes. We perform a mathematical analysis of IASM and SNAM to study the degree distribution for networks generated by both models. This mathematical analysis shows that networks generated by both models have a power law degree distribution. Finally, we completed a case study to illustrate the potential value of our research on the modeling of heterogeneous complex networks. This case study was performed on a Facebook dataset. The case study shows that SNAM, with some modifications to the connection algorithm, is capable of generating a network with almost the same characteristics as found for the original dataset. The case study providesinsight on how the flexibility of SNAM's connection algorithm can be an advantagethat makes SNAM capable of generating networks with different statistical properties. Ideas for future research areas includestudyingthe effect of using eigenvector centrality, instead of degree centrality, on the emergence of community structure in IASM; usingthe nodeindex as an indication for its order of arrival to the network and distributing added connections fairly among networknodes along the life of the generated network; experimenting with the nature of attributesto generatea more comprehensive model; and usingtime sensitive attributes in the models, where the attribute can change its value with time, / Ph. D.

This research explores the influence of pregnancy loss and coping strategies employed while connecting to the fetus in a subsequent pregnancy following a late term loss. Nine participants were interviewed using a qualitative, phenomenological methodology to determine participant's experience. Four themes emerged within the data: (1) support network – participants acknowledged who was there for them and who was not, (2) emotional ups and downs – participants reported the emotional ups and downs from loss to the subsequent pregnancy to delivery and after birth, and how they connected during this process (3) coping – participants describe coping strategies used throughout their experience, and (4) moving forward – participants reported their process of finding their new normal and how this event changed their perspective on life. Limitations, future research and clinical implications were all identified and discussed. / Master of Science