Submitted by Anelise Milech (anelisemilech@gmail.com) on 2017-11-07T13:28:37Z No. of bitstreams: 2 license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) Rodrigo Wiltgen Ferreira.pdf: 685293 bytes, checksum: f897f1cc078ae2e438bfaec967ddf763 (MD5) / Approved for entry into archive by Aline Batista (alinehb.ufpel@gmail.com) on 2018-01-02T13:18:03Z (GMT) No. of bitstreams: 2 Rodrigo Wiltgen Ferreira.pdf: 685293 bytes, checksum: f897f1cc078ae2e438bfaec967ddf763 (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) / Approved for entry into archive by Aline Batista (alinehb.ufpel@gmail.com) on 2018-01-02T13:19:36Z (GMT) No. of bitstreams: 2 Rodrigo Wiltgen Ferreira.pdf: 685293 bytes, checksum: f897f1cc078ae2e438bfaec967ddf763 (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) / Made available in DSpace on 2018-01-02T13:19:45Z (GMT). No. of bitstreams: 2 Rodrigo Wiltgen Ferreira.pdf: 685293 bytes, checksum: f897f1cc078ae2e438bfaec967ddf763 (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) Previous issue date: 2016-07-12 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPES / Objetivo: Avaliar o efeito direto do apoio social do parceiro no nível de atividade física (AF). Métodos: Um estudo transversal em 26 academias foi conduzido em Pelotas-RS. Para a mensuração da AF foi utilizado um questionário próprio com perguntas relacionadas a frequência semanal e duração média de cada sessão de exercícios realizados dentro e fora da academia. Um escore de AF total foi obtido multiplicando a frequência semanal pela duração de cada sessão. Foi utilizada uma adaptação da Escala de Apoio Social para Atividade Física – EASAF para mensurar o apoio social do parceiro. Para fins de análise, o apoio social do parceiro foi utilizado em quartis. A atividade física foi utilizada em três formas (numérica, dicotômica e em quartis). Respectivamente, a Regressão Linear, Poisson e Multinomial foram utilizadas para testar a associação entre a atividade física e o apoio social do parceiro. Resultados: O apoio social do parceiro foi associado com a atividade física em todas as análises. Indivíduos pertencentes ao quartil mais elevado faziam 66,1 (IC95% 11,1 – 121,0) mais minutos de atividade física comparadas aos indivíduos pertencentes ao primeiro quartil. Além disso, indivíduos pertencentes ao quartil mais elevado possuíam probabilidades aumentadas em 1,37 (IC95% 1,01 – 1,85) vezes para realizar 300 minutos/semana de atividades físicas. OS resultados para regressão multinomial seguiram as mesmas tendências. Conclusão: O apoio social do parceiro é diretamente associado com a AF. Pesquisadores devem levar em conta opotencial efeito do apoio social do parceiro para a mudança do comportamento de AF dos indivíduos. / Objective: To evaluate the direct effects of the partner social support in the physical activity (PA) behavior. Methods: Cross-sectional study, conducted in 26 gyms from Pelotas-RS, Brazil. PA was measured with proper questions about frequency and duration of PA performed in/outside the gym. A total PA score was generated multiplying frequency and duration. Partner Social Support (PSS) was measured by an adaptation of Social Support Scale for Physical Activity. PA was analyzed in three forms: numerical, dichotomized (median = 300 min/week) and quartiles. PSS was analyzed in quartiles. Respectively, Linear, Poisson and Multinomial regression were used to quantify the associations. Results: PSS was associated to PA in all analysis. Linear regression showed that persons belonging to the highest PSS quartile performed 66.1 (95%CI 11.1 - 121.0) more minutes of PA than those from the lowest quartile. Poisson regression showed that persons from the highest PSS quartile had 1.37 (95%CI 1.01 – 1.85) higher probability to perform more than 300 min/week of PA. Multinomial regression analysis presented similar results. Conclusion: PSS is directly associated with PA. Researches must consider the potential effect of partner social support on the target behavior change.

Research on stepfamilies strongly supports the importance of positive parent-child relationships on child outcomes. However, most of this research has focused on one or two of these relationships failing to acknowledge the interconnected impact of all three parental figures. To fill this gap, I used latent class analysis and identified six classes of parent-child relationship constellations. The national sample in this study (n=1,159) were all participants in The Stepfamily Experiences Project (STEP). Parent-child relationship quality indicators were based on participants' retrospective reports on the warmth/closeness, communication, and level of active parenting they experienced in their stepfamily household. After identifying classes I examined how class membership was affected by resident parent relationships status, EA sex, stepparent sex, years spent in a stepfamily, the age the EA entered the stepfamily and the time spent with the nonresident parent. Finally, I examined how class membership impacted depression, drug use, and hooking up. Ultimately, the analysis indicated that there is much complexity in the stepfamily experience and its potential influence on later life outcomes.

Using the International Violence Against Women Survey (IVAWS), this paper identifies factors contributing to women’s individual risk of being victimized by their current intimate partner. Additionally, this analysis examines the overlap of physical and sexual violence within intimate relationships. Past research into IPV has identified a numerous predictor variables. Adapting nine such variables (controlling behaviours, male heavy drinking, female only income, female past marriage, female past IPV, respondents’ age, relationship duration, relationship status and violence outside the home) to the IVAWS dataset, a framework identifying risk patterns for physical and sexual violence was developed. The results identify a number of variables that performed as expected and increased a women’s risk of being a victim of IPV; however, some variables decreased women’s risk and therefore acted as protective factors. These findings suggest that IPV at the country level is more complex and requires additional research to fully explain the variation observed.

Using the International Violence Against Women Survey (IVAWS), this paper identifies factors contributing to women’s individual risk of being victimized by their current intimate partner. Additionally, this analysis examines the overlap of physical and sexual violence within intimate relationships. Past research into IPV has identified a numerous predictor variables. Adapting nine such variables (controlling behaviours, male heavy drinking, female only income, female past marriage, female past IPV, respondents’ age, relationship duration, relationship status and violence outside the home) to the IVAWS dataset, a framework identifying risk patterns for physical and sexual violence was developed. The results identify a number of variables that performed as expected and increased a women’s risk of being a victim of IPV; however, some variables decreased women’s risk and therefore acted as protective factors. These findings suggest that IPV at the country level is more complex and requires additional research to fully explain the variation observed.

Using the International Violence Against Women Survey (IVAWS), this paper identifies factors contributing to women’s individual risk of being victimized by their current intimate partner. Additionally, this analysis examines the overlap of physical and sexual violence within intimate relationships. Past research into IPV has identified a numerous predictor variables. Adapting nine such variables (controlling behaviours, male heavy drinking, female only income, female past marriage, female past IPV, respondents’ age, relationship duration, relationship status and violence outside the home) to the IVAWS dataset, a framework identifying risk patterns for physical and sexual violence was developed. The results identify a number of variables that performed as expected and increased a women’s risk of being a victim of IPV; however, some variables decreased women’s risk and therefore acted as protective factors. These findings suggest that IPV at the country level is more complex and requires additional research to fully explain the variation observed.

Using the International Violence Against Women Survey (IVAWS), this paper identifies factors contributing to women’s individual risk of being victimized by their current intimate partner. Additionally, this analysis examines the overlap of physical and sexual violence within intimate relationships. Past research into IPV has identified a numerous predictor variables. Adapting nine such variables (controlling behaviours, male heavy drinking, female only income, female past marriage, female past IPV, respondents’ age, relationship duration, relationship status and violence outside the home) to the IVAWS dataset, a framework identifying risk patterns for physical and sexual violence was developed. The results identify a number of variables that performed as expected and increased a women’s risk of being a victim of IPV; however, some variables decreased women’s risk and therefore acted as protective factors. These findings suggest that IPV at the country level is more complex and requires additional research to fully explain the variation observed.