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Abstract
BackgroundDyadic data analysis (DDA) is increasingly being used to better understand, analyze and model intra- and inter-personal mechanisms of health in various types of dyads such as husband-wife, caregiver-patient, doctor-patient, and parent-child. A key strength of the DDA is its flexibility to take the nonindependence available in the dyads into account. In this article, we illustrate the value of using DDA to examine how anxiety is associated with marital satisfaction in infertile couples.MethodsThis cross-sectional study included 141 infertile couples from a referral infertility clinic in Tehran, Iran between February and May 2017. Anxiety and marital satisfaction were measured by the anxiety subscale of the Hospital Anxiety and Depression Scale and 10-Item ENRICH Marital Satisfaction Scale, respectively. We apply and compare tree different dyadic models to explore the effect of anxiety on marital satisfaction, including the Actor-Partner Interdependence Model (APIM), Mutual Influence Model (MIM), and Common Fate Model (CFM).ResultsThis study demonstrated a practical application of the dyadic models. These dyadic models provide results that appear to give different interpretations of the data. The APIM analysis revealed that both men’s and women’s anxiety excreted an actor effect on their own marital satisfaction. In addition, women’s anxiety exerted a significant partner effect on their husbands’ marital satisfaction. In MIM analysis, in addition to significant actor effects of anxiety on marital satisfaction, women’s reports of marital satisfaction significantly predicted men’s marital satisfaction. The CFM analysis revealed that higher couple anxiety scores predicted lower couple marital satisfaction scores.ConclusionIn sum, the study highlights the usefulness of DDA to explore and test the phenomena with inherently dyadic nature. With regard to our empirical data, the findings confirmed that marital satisfaction was influenced by anxiety in infertile couples at both individual and dyadic level; thus, interventions to improve marital satisfaction should include both men and women. In addition, future studies should consider using DDA when dyadic data are available.
Highlights
Dyadic data analysis (DDA) is increasingly being used to better understand, analyze and model intra- and inter-personal mechanisms of health in various types of dyads such as husband-wife, caregiver-patient, doctor-patient, and parent-child
The within-dyad correlations between marital satisfaction and anxiety were direct and significant, indicating that if one partner was satisfied with their martial satisfaction and had high level of anxiety, the other one was
In summary, this study highlights the usefulness of DDA to examine and test the phenomena with inherently dyadic nature
Summary
Dyadic data analysis (DDA) is increasingly being used to better understand, analyze and model intra- and inter-personal mechanisms of health in various types of dyads such as husband-wife, caregiver-patient, doctor-patient, and parent-child. The dyadic designs (e.g., research on man-woman dyads and caregiver-patient dyads) create observations that are not independent which make the conventional statistical methods as inappropriate analysis tools [10]. This type of design is usually applicable when researchers want to understand relationship processes between two people. Dyadic nonindependence occurs in a variety of contexts that involve two people, such as relationship processes studies in husband-wife, doctor-patient, caregiver-patient, parentchild, siblings and friends In these conditions, statistical analytical techniques that take non-independence into account is required. A detailed description of these models is presented in the Methods section
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