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The longitudinal actor-partner interdependence model (L-APIM) is frequently used to study dyadic relationships over time. When one deals with categorical longitudinal data, Markov chains emerge as a valuable analytical tool. This approach allows for the identification of interaction patterns in the L-APIM framework through the examination of the transition matrix. In the context of dyadic sample, investigating the similarity of behaviors between individuals becomes important. To address this question, visualization and grouping analysis are employed, providing valuable tools for discerning relationships with behavioral data. We introduce a novel methodological approach to ascertain such behavioral similarity using the probabilities into the transition matrix. In this article, we describe the utilization of multidimensional scaling and hierarchical clustering for identifying analogous behaviors within a dyadic sample. We illustrate the complete methodology using a simulated dataset. Codes in R language are included for implementation.

Understanding the dynamics of interactions between two individuals requires special conceptual and statistical models. The Actor-Partner Interdependence Model (APIM) is the classical conceptual framework for standard dyadic designs, capturing the interdependence between dyad members by identifying the mechanisms of interaction through actor and partner effects. To analyze the temporal dynamics of dyadic interactions, the longitudinal APIM extends the classic model, often employing categorical variables to capture behavior. To analyze such data considering its categorical nature, specific statistical models are required. Markov chain is a powerful approach considering the longitudinal and categorical aspects of the data. This article describes how to adapt Markov chains in the categorical longitudinal dyadic case. It additionally offers a tutorial to model and identify the pattern of interaction using this method for unique case approach to maintain a simple and focused level of analysis. Codes in R language are provided.

This research investigates the relation between climate anxiety, threat perceptions for future generations, and childbearing motivations in childless emerging adults. Using a sample of 1211 Swiss college students aged 18–25, the study explores if threat perceptions mediate the relationship between climate anxiety and childbearing motivations. Results from structural equation modeling (SEM) indicated that climate anxiety significantly predicted greater perceptions of threat, which in turn related to less positive childbearing motivations and more negative childbearing motivations. Specifically, the relationship between climate anxiety and childbearing motivations was partly to fully explained by threat perceptions, suggesting that worries about the future environment could be an important factor in emerging adults' complex reproductive considerations. No gender moderation was found. These findings underscore the need for policy interventions that provide psychological support and targeted educational resources to assist young adults in navigating the complex interplay between climate anxiety, threat perceptions, and their decisions regarding childbearing. [ABSTRACT FROM AUTHOR]

Due to the Syrian civil war, millions of Syrians have fled the country since 2011. Several issues have inhibited their successful resettlement, but few studies have examined the development of the healthcare needs of Syrian forced migrants in Europe. This study examined Syrian forced migrants' healthcare needs in Switzerland, and whether migration type and family functioning affect their mental health. Our sample included 108 individuals from 14 families from the usual asylum process and 19 from the Swiss Resettlement Program (SRP). Each family member was surveyed thrice in 1 year. Several participants reported symptoms of major depressive and post-traumatic stress disorder. However, their general mental health was similar to that of the Western populations. Swiss Resettlement Program participants reported higher overall mental health scores than non-SRP participants, while the two groups showed different progression over time. Children and fathers reported similar levels of mental health, whereas mothers' mental health scores worsened over time. Family functioning was important for mental health in both groups. Overall, considering the structural and family contexts is important when studying forced migrants' mental health. [ABSTRACT FROM AUTHOR]

Drawing on decades of research in family systems, coparenting, and developmental science, we present a clinical approach to address unmet service needs in children's mental health. Specifically, we describe Lausanne Family Play – Brief Intervention (LFP‐B) – a manualized family systems approach providing a caregiver‐caregiver‐child therapy (and sibling/s, when applicable). The LFP‐B is ultra‐brief, typically delivered in as few as three sessions (two assessment sessions followed by a video feedback session), with the aim of reducing children's mental health symptomatology by enhancing the coparenting relationship. We review literature on systemic family therapies and provide a rationale for including coparents and children in child mental health care. We then provide a rationale for using behavioral observations and video feedback in treatment, drawing on research in related family‐based treatments (e.g., parent–child therapies). Finally, we provide an overview of the LFP‐B manual and a case illustration. [ABSTRACT FROM AUTHOR]

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