主题分析
妊娠期糖尿病
定性研究
心理干预
护理部
心理学
医学
干预(咨询)
怀孕
社会科学
妊娠期
遗传学
生物
社会学
作者
Min Guo,Judith Parsons,Angus Forbes,Wen-Xin Shi,Min Kong,Yinping Zhang,Rita Forde
摘要
The aims of the study were to explore the experiences of women with gestational diabetes mellitus (GDM) and their partners and examine the factors influencing partner involvement in GDM management, seeking to inform a targeted couple-based intervention.A descriptive qualitative study.We conducted semi-structured interviews with 14 women with GDM and their partners. Participants were recruited through convenience sampling from a tertiary hospital in Xi'an, China. Data were analysed using thematic analysis.Three themes and 12 subthemes were identified. Theme I: Women's expectations of their partner's involvement in GDM management-practical support and emotional support. Theme II: Partner involvement in GDM management-constructive involvement, unhelpful involvement with good intentions and insufficient involvement. Theme III: Factors that influence partner involvement in GDM-knowledge of GDM, GDM risk perception, health consciousness, attitudes towards the treatment plan, couple communication regarding GDM management, family roles and appraisal of GDM management responsibility.Women desired practical and emotional support from partners. The types of partner involvement in GDM management varied. Some partners provided constructive support, while some partners' involvement was limited, non-existent or actively unhelpful. By combining these results with the factors influencing partner involvement, our findings may help healthcare professionals develop strategies to involve partners in GDM care and enhance women's ability to manage GDM.Partner involvement in GDM care may help them understand and better attend to women's needs, thus improving their experience and potential outcomes. This study highlights novel factors that need to be considered in developing couple-based interventions for this population.The reporting follows the COREQ checklist.Some patients were involved in data interpretation. There is no public contribution.
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