Interrelatedness of women's health-behaviour cognitions: A dyadic study of female family members on carrying heavy loads during pregnancy in Nepal

British journal of health psychology(2023)

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摘要
ObjectivesDecisions about reproductive health are often influenced by women's female family members, particularly in low-resource contexts. However, previous research has focused primarily on individual behavioural determinants. We investigated the interrelatedness of female family members' reproductive health behaviour with a dyadic version of an extended health action process approach. We investigated this for carrying heavy loads during pregnancy and postpartum, a risk factor for reproductive health in many low-income countries such as Nepal.DesignThis cross-sectional study included dyads of daughters-in-law and mothers-in-law in rural Nepal (N = 476, nested in 238 dyads).MethodsDyads of daughters- and mothers-in-law were surveyed about avoiding carrying heavy loads during pregnancy and postpartum. The effects of a woman's cognitions and her female dyadic partner's cognitions on their intention and behaviour about avoiding carrying loads were estimated using linear mixed models.ResultsThe results showed that a mother-in-law's cognitions were related to her daughter-in-law's intentions and vice versa. The mother-in-law's cognitions were also related to the daughter-in-law's behaviour. The mother-in-law's self-efficacy and injunctive norms related to the daughter-in-law's intention and behaviour over and above the daughter-in-law's own self-efficacy and injunctive norms.ConclusionFemale Nepali family members' cognitions about carrying heavy loads during pregnancy and postpartum are interrelated. Including female family members in interventions to help women manage their reproductive health in low-resource populations seems promising. These novel findings add to the growing body of research indicating the importance of including a dyadic perspective when understanding and changing health behaviour.
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关键词
actor partner interdependence model,dyadic data,health action process approach,low-resource populations,reproductive health,social influence
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