The link between infertility-related distress and psychological distress in couples awaiting fertility treatment: a dyadic approach

Abstract

While there is broad evidence to suggest that individual stress increases, and that high couple relationship quality reduces the risk for psychological distress, our understanding of these associations in couples dealing with infertility remains limited. In this cross-sectional study, we used dyadic data-analysis (Actor-Partner Interdependence Model; APIM) to examine the effects of infertility-related distress (experienced as an individual risk factor) and couple relationship quality (experienced as a couple-based resource), on psychological distress in a sample of 116 infertile couples. 59% of women and 23% of men reported clinical levels of psychological distress, 71% of women and 45% of men reported infertility-related distress, and 3% of participants reported low couple relationship quality. Infertility-related distress predicted psychological distress at the individual level (‘actor effects’) while men’s infertility-related distress predicted women’s psychological distress (partner effect’). Women without medically assisted reproduction (MAR) treatment exposure reported significantly higher couple relationship quality than women with MAR exposure, and men without treatment exposure reported significantly lower infertility-related distress than men with exposure. The level of psychological distress depended on whether both or neither of the partners, or only one partner reported infertility-related distress. Couple relationship quality was not associated with distress, which may imply that dyadic dimensions other than overall satisfaction could be relevant in supporting couples facing infertility.

Keywords:

• Infertility-related distress
• psychological distress
• couple relationship quality
• medically assisted reproduction (or: MAR)
• actor-partner interdependence model (or: APIM)
• couples

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

1 Based on an input during the review process we tested empirical distinguishability by comparing the distinguishable with the indistinguishable APIM model which assumes equal actor and partner effects, intercepts and error variances for the outcomes in men and women (Kenny et al., 2006). We ran delta chi-square tests of comparative model fit between the two versions of each model (Stas et al., 2018). According to the test, distinguishability can be assumed if the test is significant with p < 0.05. The overall test of distinguishability comparing the distinguishable with the indistinguishable model yielded a chi square statistic with 6 degrees of freedom which equals a value of 294.133 and p < 0.001, suggesting that the data were empirically distinguishable by gender.

2 The test of distinguishability suggested that partners can be statistically distinguished based on the gender variable (χ2 = 72.877; df = 6; p < 0.001).