Peer Mentoring Programs for Culturally and Linguistically Diverse Refugee and Migrant Women: An Integrative Review.
Shelley GowerZakia JeemiDavid ForbesPaul KebbleJaya A R DantasPublished in: International journal of environmental research and public health (2022)
Refugee and migrant women experience personal, cultural and structural challenges as they adapt to new lives in host countries. Peer mentoring programs are used to facilitate resettlement, build empowerment and improve job-readiness for refugee and migrant women; however, the effectiveness of these programs is not well understood. A systematic search of five databases, plus grey literature from January 2005 to December 2020, was undertaken, resulting in 12 articles. A narrative synthesis using thematic analysis identified the key components and outcomes of effective programs. Most mentoring programs were co-designed with community-based service providers, using participatory approaches to ensure cultural acceptability. Communication and sharing were facilitated using workshops and individual in-person or telephone mentoring. The training and support of mentors was critical. However, differences in expectations between mentors and mentees at times resulted in attrition. Qualitative evaluation revealed enhanced social support, greater empowerment and confidence for the women. There was improved access to the social determinants of health such as education, but limited success in obtaining employment. Mentoring programs can enhance refugee and migrant women's wellbeing and social connectedness in resettlement contexts. However, it is unclear whether these benefits can be sustained over the longer term. Future programs should be rigorously evaluated through qualitative and quantitative analyses to generate conclusive evidence for best practice.
Keyphrases
- public health
- polycystic ovary syndrome
- social support
- healthcare
- systematic review
- pregnancy outcomes
- mental health
- cervical cancer screening
- depressive symptoms
- breast cancer risk
- primary care
- machine learning
- type diabetes
- pregnant women
- preterm infants
- multiple sclerosis
- single cell
- health information
- social media
- deep learning
- mental illness
- health promotion
- data analysis