'I think you understand me' : studying the associations between actual, assumed, and perceived understanding within couples

The current study examined the associations between actual, assumed, and perceived understanding and partners' levels of dyadic adjustment. One hundred fifty-two couples provided questionnaire data (assumed and perceived understanding), participated in a videotaped conflict interaction, and in a video-review task to assess actual understanding (empathic accuracy). The data were analyzed by means of the Actor-Partner Interdependence Model. The results suggest that (a) some aspects of how well someone assumes that (s)he has understood the partner during a preceding conflict interaction were positively associated with his/her own objective level of understanding (actor effect), (b) that someone's perception of how understood (s)he feels was not associated with the partner's objective level of understanding (partner effect), and (c) perceived understanding, but not actual understanding, was positively associated with dyadic adjustment

Getting the most out of your family data with the R-package fSRM

Introduction Family research aims to explore family dynamics but is often limited to the examination of unidirectional processes (e.g. parenting, child effects). As the behavior of one person has consequences that go beyond that one individual, the family functioning should be investigated in its full complexity. The Social Relations Model (SRM; Kenny & La Voie, 1984) is a conceptual and analytical model which can disentangle family dynamics at three different levels: the individual level (actor and partner effect), the dyadic level (relationship effects) and the family level (family effect). Nonetheless, its statistical complexity may be a hurdle for family researchers. The user-friendly R-package fSRM that we developed performs almost automatically those rather complex SRM analyses. Using real data the different features of the package are presented. Methods When a round robin design is used (i.e. every family member rates every other member on the same items), the etiology of the obtained dyadic scores can be unraveled using the SRM. In particular, the estimation of the SRM parameters can be based on a confirmatory factor analysis. Therefor fSRM builds on lavaan (Rosseel, 2012), a popular R-package developed for structural equation modeling. With fSRM, one simple line of R-code suffices to perform the required analysis. Results and discussion The fSRM-output provides easy-to-interpret summary tables of SRM variances, variance decompositions, individual and dyadic reciprocities. SRM means, which may be very informative - but infrequently reported - are straightforwardly obtained and can easily be compared between roles. Moreover, the package is suitable for both single and multigroup studies. Additional options (e.g. intragenerational similarities) are discussed. In sum, fSRM enables family researchers to get easily the most out of their data

Getting the most out of your family data with fSRM

Introduction Family research aims to explore family dynamics but is often limited to the examination of unidirectional processes (e.g. parenting, child effects). As the behavior of one person has consequences that go beyond that one individual, the family functioning should be investigated in its full complexity. The Social Relations Model (SRM; Kenny & La Voie, 1984) is a conceptual and analytical model which can disentangle family dynamics at three different levels: the individual level (actor and partner effect), the dyadic level (relationship effects) and the family level (family effect). Nonetheless, its statistical complexity may be a hurdle for family researchers. The user-friendly R-package fSRM (Stas, Schönbrodt & Loeys, in prep.), performs almost automatically those rather complex SRM analyses. Using real data the different features of the package are presented. Aim and methods When a round robin design is used (i.e. every family member rates every other member on the same items), the etiology of the obtained dyadic scores can be unraveled using the SRM. With fSRM, one simple line of R-code suffices to perform the required analysis. Results and discussion The fSRM-output provides easy-to-interpret summary tables of SRM variances, variance decompositions, individual and dyadic reciprocities. SRM means, which may be very informative - but infrequently reported - are straightforwardly obtained and can easily be compared between roles. Moreover, the package is suitable for both single and multigroup studies. Additional options (e.g. intragenerational similarities) are discussed. In sum, fSRM enables family researchers to get easily the most out of their data

Dietary intake, physical activity and sedentary behavior and association with BMI during the transition to parenthood: a prospective dyadic study

IntroductionLittle is known on how diet, physical activity (PA) and sedentary behavior (SB) changes during pregnancy and after childbirth in primiparous couples. Moreover, it is unclear how potential behavioral changes are associated with changes in BMI. This study examined changes in diet, PA and SB, and their association with changes in BMI in couples transitioning to parenthood.MethodsDietary intake (FFQ), PA, SB (both Actigraph GT3X accelerometers) and BMI of women and men were assessed at 12 weeks of gestation, 6 weeks and 6 months postpartum. Data were analyzed using dyadic longitudinal data analyses techniques.ResultsIn women, a decrease in fruit intake, an increase in alcohol intake, an increase of light-intensity PA, and a decrease in SB were observed from the beginning of pregnancy up to 6 months postpartum. Decreases in fruit intake between 6 weeks and 6 months postpartum was associated with increases in BMI. Men did not show significant dietary changes, while an increase in light-intensity PA and a decrease in moderate-to-vigorous PA (MVPA) was observed at 6 months postpartum when compared to 12 weeks of gestation. Paternal increases in “avoidance food group” intake were associated with increases in BMI between baseline and 6 weeks postpartum. No associations of changes in BMI and changes in PA and SB were found.DiscussionNot only mothers but also fathers experienced unfavorable changes in lifestyle during the transition to parenthood, with impact on BMI changes. This highlights the need to monitor unhealthy changes in lifestyle and body weight in both parents when expecting a child and after childbirth.Clinical trial registrationClinicaltrials.gov, NCT03454958