Thesis (Ph.D.)--Indiana University, Dept. of Psychological and Brain Sciences, 2006. / "Title from dissertation home page (viewed July 11, 2007)." Source: Dissertation Abstracts International, Volume: 67-08, Section: B, page: 4737. Adviser: Thomas A. Busey.

Thesis (Ph.D.)--Indiana University, Dept. of Applied Health Science, 2006. / Source: Dissertation Abstracts International, Volume: 67-04, Section: B, page: 1953. Advisers: Michael Reece; Stephanie Sanders. "Title from dissertation home page (viewed June 19, 2007)."

Collectivism and individualism are culturally-related psychological structures which have been used to distinguish people within and across various societies. From a review of the literature, it is argued that the most salient feature of individualism is valuing personal independence, which includes self-knowledge, uniqueness, privacy, clear communication, and competitiveness. Collectivism is associated with a strong sense of duty to group, relatedness to others, seeking others' advice, harmony, and working with the group. The purpose of the thesis is to explore how collectivist and individualist attributes affect the way people respond to Likert-type questionnaires. In the first study, a new measurement tool for individualism and collectivism was developed to address critical methodological issues in this field of cross-cultural psychology. This new measure the “Auckland Individualism and Collectivism Scale” defined three dimensions of individualism: (a) Responsibility (acknowledging one's responsibility for one's actions), (b) Uniqueness (distinction of the self from the other) and (c) Compete (striving for personal goals is one's prime interest); and two dimensions of collectivism: (d) Advice (seeking advice from people close to one, before taking decisions), and (e) Harmony (seeking to avoid conflict). The AICS avoids the need for measuring horizontal and vertical dimensions of collectivism and individualism, and the confounding effect of familialism on the collectivism-individualism constructs. The second study investigated the relationship between collectivism and individualism and various response sets that have been reported relating to the way in which individuals respond to Likert-type scales. Using structural equation modelling, the Collectivism-Individualism Model of Response Bias was developed. This model suggests two types of response sets: (a) the Impression-Response Bias which includes response sets such as social desirability and context, that affect the first four stages of responding to questions, namely receiving and retrieving data and making decisions; and (b) the Expression-Response Bias which includes response sets such as the extreme response set and the neutral response set that relate to the application of the responses, namely the actual answer chosen by the respondent. Collectivism is negatively correlated with context and with self deception enhancement whereas individualism is positively correlated with context and self deception enhancement and impression management. Context is positively correlated with extreme response set and negatively correlated with neutral response set. The Collectivism-Individualism Model of Response Bias suggests that collectivist and individualist attributes directly affect the Impression-Response Bias response sets and indirectly affect the Expression-Response Bias response sets. It was concluded that attributes of collectivism and individualism affect the decision made by the respondents and therefore lead to different responses to Likert-type questionnaires. Nevertheless, the effect of collectivism and individualism on the magnitude of the responses would be limited as it is mediated by the Impression-Response Bias response set. / Subscription resource available via Digital Dissertations only.

Thesis (M.Sc.)--Saint Mary's University, 2008. / Includes abstract and appendices. Supervisor: Mark Fleming. Includes bibliographical references (leaves 60-68).

Depression poses a global threat for mental health (Murray & Lopez, 1996). However, in China, national studies of depression epidemiology are very few. Only from 2011 have Chinese researchers began to adopt internationally recognized diagnostic criteria and standardized interview instruments in psychiatric epidemiological surveys (Guo et al., 2011), and previous studies generated inconsistent results of depressive prevalence. As the largest ethnic group in the world, the Chinese account for 18.9% of the world’s population (National Bureau of Statistics of China, 2015). Yet most research on depression is based on Western samples and may not accurately characterize depression as experienced by Chinese populations. This thesis examines depression in non-pregnant and pregnant women in Inner Mongolia, who are under the influence of cultural values of collectivism and social factors specific to China. Chinese society adheres firmly to traditional values (Whyte, 2005), while market reform, birth-control policy, together with high parental investment in childcare and rearing construct a unique and sometimes unfavorable environment for Chinese women that may influence their depression expression. This thesis includes a series of three linked studies. The first study validated the 52- item New Multidimensional Depression Scale (MDAS) with clinically depressed individuals in Inner Mongolia. The aims were to assess whether the MDAS demonstrated good psychometric properties in clinically depressed Chinese patients for the scale to be factor analysed on a Chinese construct of depression symptomatology to show cultural characteristics in China. This aim was achieved by carrying out Exploratory and Confirmatory factor analysis in separate studies. One hundred and seventy-one clinically depressed participants were recruited in Inner Mongolia. They were given the MDAS and Beck Depressive Inventory (BDI) and other scales to complete. The psychometric properties of the MDAS were tested regarding reliability and validity. Following which an Exploratory factor analysis (EFA) was run on MDAS. Several findings emerged in the study. First, the first factor extracted comprised of core psychological and affective symptoms conceptualized in the Western construct of depression. An interpersonal-cognitive factor was extracted as the second factor, followed by a third somatic factor in the cluster of symptoms. The results suggested that core affective and cognitive symptoms for diagnosis are universal across cultures, while Chinese individuals express interpersonal symptoms that characterized their collectivistic culture that emphasizes interpersonal harmony. Study 2 examined depressive symptoms in the antenatal period in Inner Mongolia women. Two-hundred and thirty-four women, mostly in their third trimester, were recruited in an antenatal hospital in Inner Mongolia. They completed the MDAS, Beck Depression Inventory (BDI) and Edinburgh Postpartum Depression Scale (EPDS). In exploring how depression in its item content is expressed and experienced by pregnant Chinese women, the study also searched for the best-fit model of MDAS on pregnant women in Inner Mongolia. It compared three factor models: the three-factor structure of MDAS from study 1, the hypothesized four-factor model corresponding to each subscale (emotional, cognitive, somatic and interpersonal), and the one-factor model corresponding to a unidimensional structure of the MDAS. A best-fit model was found for the four-factor model, supporting using the four hypothesized subscales of MDAS on pregnant women. In a subsequent step, the MDAS was validated and its psychometric properties were tested to show illustrated results. The findings supported measuring interpersonal symptoms in self-report measurements to measure different aspects of depressive severity in Chinese pregnant women. In particular, somatic symptoms should be considered with caution in screening and primary care. The finding has significant implications for assessing with self-report questionnaires, which are widely used in clinical settings. Study 3 was based on the same sample as study 2 and investigated risk factors associated with antenatal depression in China. China has undergone drastic socio-economic and political transformation in the last twenty years. Unfortunately, market reform is creating less favourable employment conditions, and the traditional value of male dominance still stands firmly in the society. Women are facing more financial insecurity and a tight birth control policy and growing stress in work-and-family balance. All these create an environment that could contribute to their depression that could be expressed in a different way from Western populations. Depression may also be underlined by different risk factors related to the social and cultural environment. This study measured demographic characteristics (including age, education, employment, week of gestation, first pregnancy), social support, social activity, work stress, and work-family balance and their relationship with depression. It included three parts. In part 1 participants were classified into depressed and non-depressed groups using EPDS > 10 as the cut-off point for depression. The two groups were compared on demographic variables using the Chi-square test and on psychosocial risk factors using the Mann-Whitney U test. No significant demographic variable was found to distinguish the two groups, whereas self-esteem, work stress and social activities differed significant between depressed and non-depressed pregnant women. Bivariate correlations between psychosocial risk factors and depressive scales (MDAS, BDI and EPDS) gave rise to significant correlations between risk factors and each scale. In the third part hierarchical multiple linear regression analysis examined associations between social and demographic risk factors and depression. The results showed that work stress, work-and-family balance, social activity and social support were significantly associated with depressive severity in overall severity of depression (total MDAS score) and each domain of depressive severity (each subscale of MDAS). In conclusion, the three studies together provide novel insight into our understanding of depression within and outside of pregnancy in Chinese women, in terms of symptoms and risk factors. The Western conceptualization of depression possesses great validity across cultures, that the core symptoms of depression remain universal for diagnosis. Chinese cultural values and social environment are reflected in the cultural expressions of depressive symptoms especially in depressed individuals but less affective in pregnant women. As hypothesized, Chinese society influenced risk factors related to education and work-family balance in pregnant women. The result supported using a scale with a comprehensive interpersonal symptom checklist because it potentially captures Chinese expression and experience, which could be characterized by an interpersonal style of illness presentation. In addition, the best-fit four-factor model supported including interpersonal symptoms in self-report measures and they are also related to different risk factors from other domains of depressive symptoms. This could be linked to some unfavourable social and cultural influence pregnant Chinese women experience. The thesis gives rise to implications for potential clinical applications. The advancement of cultural characteristics in symptom contents in both clinical and pregnant population facilitates a better symptom checklist for assessing depression severity. In particular, it helps to modify existing self-report questionnaires with culturally sensitive symptoms for better discrimination of individuals.

Due to the ever growing diversity of school populations in the United States, it becomes increasingly more vital that school counselors are efficient in multicultural counseling. As the significance of effective multicultural counseling competencies increases, so too does the importance of accurately assessing these proficiencies. To assess school counselors' ability to implement multicultural techniques, specific constructs must be developed. The central focus of this research is to develop an instrument which accurately assesses the multicultural counseling competencies of school counselors and conforms to standards set by the American School Counselor Association and the Association for Multicultural Counseling and Development. By exploring these standards and investigating qualitative and quantitative data regarding current competencies, school counselors can work more effectively with a diverse student body.

Orientador: Juliana Alvares Duarte Bonini Campos / Resumo: Introdução: A dor pode ser resultante do tratamento ortodôntico e deve ser considerada no manejo clínico. Ainda, variáveis demográficas e clínicas podem contribuir para essa condição dolorosa. Objetivo: i.adaptar e validar o Inventário Multidimensional da Dor (MPI) para pacientes em tratamento ortodôntico corretivo, ii.apresentar proposta de cálculo de escore geral dos aspectos psicossociais e comportamentais da dor avaliados pelo MPI, iii.avaliar o impacto de variáveis demográficas e clínicas nesses aspectos. Métodos: Realizou-se validade de face do MPI e elaborou-se versão adaptada para ortodontia (MPI-Ortho). Análise fatorial confirmatória (AFC) foi realizada. Utilizou-se os índices de ajustamento razão de quiquadrado pelos graus de liberdade (χ2/gl), goodness of fit index (GFI), comparative fit index (CFI) e root mean square error of aproximation (RMSEA). A validade convergente, discriminante e confiabilidade foram estimadas. A validade concorrente do MPI-Ortho foi avaliada frente à Escala Visual Analógica. A invariância do modelo fatorial foi avaliada para amostras independentes. A validade de critério discriminante foi estimada segundo sexo e idade. O escore geral foi calculado utilizando a matriz de pesos de regressão da AFC. O escore ponderado foi comparado aos escores obtidos pela média aritmética simples. Foi elaborado modelo estrutural tendo como variáveis dependentes os aspectos psicossociais e comportamentais da dor e independentes variáveis demográficas e clínic... (Resumo completo, clicar acesso eletrônico abaixo) / Abstract: Introduction: Pain may result from orthodontic treatment and should be considered in clinical management. Measuring pain becomes a challenge. Also, demographic and clinical variables may contribute to this painful condition. Aim: i.to perform an adaptation and validation of the Multidimensional Pain Inventory (MPI) in patients under orthodontic treatment, ii.to present a new proposal for calculating general scores of the psychosocial and behavioral aspects of pain, iii.to evaluate the contribution of demographic and clinical variables in these aspects. Methods: the face validities of the MPI were estimated and an adapted version for orthodontics (MPI-Ortho) was developed. A confirmatory factor analysis was carried out (CFA). The reason χ2 by degree of freedom ratio (χ2/df), Goodness of Fit Index (GFI), Comparative Fit Index (CFI) and root mean square error of approximation (RMSEA) were used. Convergent, discriminant validities and reliability were assessed. Concurrent validity was assessed using Visual Analogue Scale. Invariance of the models was evaluated in independent samples. Discriminant criterion validity was estimated according to gender and age. Overall scores were determined using the matrix of regression weights obtained via CFA. Overall weighted scores were compared to the scores estimated as the simple arithmetic mean. A structural model was developed; the psychosocial and behavioral aspects of pain were the dependents variables and the demographic and clinical ch... (Complete abstract click electronic access below) / Mestre

abstract: Random Forests is a statistical learning method which has been proposed for propensity score estimation models that involve complex interactions, nonlinear relationships, or both of the covariates. In this dissertation I conducted a simulation study to examine the effects of three Random Forests model specifications in propensity score analysis. The results suggested that, depending on the nature of data, optimal specification of (1) decision rules to select the covariate and its split value in a Classification Tree, (2) the number of covariates randomly sampled for selection, and (3) methods of estimating Random Forests propensity scores could potentially produce an unbiased average treatment effect estimate after propensity scores weighting by the odds adjustment. Compared to the logistic regression estimation model using the true propensity score model, Random Forests had an additional advantage in producing unbiased estimated standard error and correct statistical inference of the average treatment effect. The relationship between the balance on the covariates' means and the bias of average treatment effect estimate was examined both within and between conditions of the simulation. Within conditions, across repeated samples there was no noticeable correlation between the covariates' mean differences and the magnitude of bias of average treatment effect estimate for the covariates that were imbalanced before adjustment. Between conditions, small mean differences of covariates after propensity score adjustment were not sensitive enough to identify the optimal Random Forests model specification for propensity score analysis. / Dissertation/Thesis / Ph.D. Psychology 2013

abstract: Research methods based on the frequentist philosophy use prior information in a priori power calculations and when determining the necessary sample size for the detection of an effect, but not in statistical analyses. Bayesian methods incorporate prior knowledge into the statistical analysis in the form of a prior distribution. When prior information about a relationship is available, the estimates obtained could differ drastically depending on the choice of Bayesian or frequentist method. Study 1 in this project compared the performance of five methods for obtaining interval estimates of the mediated effect in terms of coverage, Type I error rate, empirical power, interval imbalance, and interval width at N = 20, 40, 60, 100 and 500. In Study 1, Bayesian methods with informative prior distributions performed almost identically to Bayesian methods with diffuse prior distributions, and had more power than normal theory confidence limits, lower Type I error rates than the percentile bootstrap, and coverage, interval width, and imbalance comparable to normal theory, percentile bootstrap, and the bias-corrected bootstrap confidence limits. Study 2 evaluated if a Bayesian method with true parameter values as prior information outperforms the other methods. The findings indicate that with true values of parameters as the prior information, Bayesian credibility intervals with informative prior distributions have more power, less imbalance, and narrower intervals than Bayesian credibility intervals with diffuse prior distributions, normal theory, percentile bootstrap, and bias-corrected bootstrap confidence limits. Study 3 examined how much power increases when increasing the precision of the prior distribution by a factor of ten for either the action or the conceptual path in mediation analysis. Power generally increases with increases in precision but there are many sample size and parameter value combinations where precision increases by a factor of 10 do not lead to substantial increases in power. / Dissertation/Thesis / Masters Thesis Psychology 2014

Although most researchers agree that resilience is defined as the extent to which an individual bounces back and recovers from stress and adversity, the field has not yet settled on the underlying structure of the resilience construct; its lower-order factors remain in dispute and undefined. In this study, five of the most prominent resilience measures (i.e., Ego Resilience, Block & Kremen, 1996; The Resilience Scale, Wagnild & Young, 1993; The Connor-Davidson Resilience Scale, Connor & Davidson, 2003; The Resilience Scale for Adults, Friborg, Hjemdal, Rosenvinge, & Martinussen, 2003; The Brief Resilience Scale, Smith, Dalen, Wiggins, & Tooley, 2008) were administered to two large samples of U.S. adults (N = 396 and 336, respectively). Through a combination of exploratory and confirmatory techniques, seven lower-order resilience factors were identified. Relationships between general resilience, lower-order resilience factors, and correlates were examined. Results reveal that lower-order resilience factors are moderately correlated with one another and are differentially related to outcomes of interest. Follow-up hierarchical regression and relative weights analyses further reveal that general resilience substantially overlaps with Big Five personality measures, but, in many cases, its lower-order factors do not. Consequently, it is recommended moving forward that researchers continue to study the resilience construct, but do so by focusing on lower-order resilience factors, rather than on global measures of the overall resilience construct.