Grant: Op Gr:Understanding/mitigating impacts of COVID-19 on children, youth & families

The COVID-19 pandemic poses a significant threat to the relationships of couples with young children, which has the potential to infiltrate family systems and negatively impact all family members. There is a pressing need for psychosocial programs for couples with young children to guard against relationship deterioration. The current proposal is for a pilot RCT of a brief, fully-online, couples-focused intervention for parents of young children. This will establish feasibility of a future, main RCT and also provide preliminary evidence for its positive benefits to couples and their families. The Love Together, Parent Together (L2P2) program is adapted from the 'Marriage Hack', a previously validated intervention that promotes conflict reappraisal in couples. We have shortened the duration of the program (from one year to four weeks) and will examine its viability in couples with young children during (and following) the pandemic. The design is a two-arm randomised trial (treatment vs. waitlist control), with pre-, 1-week post-, and 3-month follow-up assessments. We will include 120 couples with children under 6-years-old. The intervention involves three 7-minute writing sessions over four weeks, wherein couples are encouraged to reappraise a recent disagreement they had with their romantic partner by taking the perspective of a neutral third party. It is theory-driven, designed to target common negative cycles observed in couples. Primary feasibility outcomes will assess recruitment, eligibility criteria, sample diversity, randomization, retention, and intervention acceptability. Secondary clinical outcomes include an examination of group differences in couple (relationship quality, conflict-related negativity) and family outcomes (parent-child relations, parent mental health, child emotional and behavioural problems). We intend to provide evidence for the feasibility and preliminary effectiveness of the L2P2 program, which may be scalable at the population level.