Assessment and Management of Obesity and Self-Maintenance (AMOS): An Evaluation of a Rural, Regional Multidisciplinary Program.
Sarah Jane PriorSharon P LuccisanoMichelle L KilpatrickGiuliana O MurfetPublished in: International journal of environmental research and public health (2022)
Obesity is common in rural areas, and reduced specialist healthcare access impedes its management. A pilot nurse-practitioner-led Assessment and Management of Obesity and Self-Maintenance (AMOS) Clinic focused on individualised obesity care in people living with type 2 diabetes delivered in a rural setting. This study aimed to explore participant and staff experiences of the multidisciplinary obesity clinic to identify barriers and facilitators to self-care, health, and well-being. A two-stage, mixed-method design was used. Initially, three focus groups involving a sample of AMOS participants and semi-structured staff interviews helped identify key barriers/facilitators. These findings informed a survey delivered to all AMOS participants. Qualitative data were analysed using an inductive two-step thematic networks technique to identify themes. Quantitative data were summarised using descriptive statistics. A total of 54 AMOS participants and 4 staff participated in the study. Four themes were identified to describe AMOS participant experiences': 1. affordability; 2. multidisciplinary care; 3. person-centred care; and 4. motivation. Specialised, multidisciplinary and individualised obesity care available through one clinic facilitated self-care and improved health and well-being. Dedicated multidisciplinary obesity clinics are recommended in rural and remote areas.
Keyphrases
- healthcare
- insulin resistance
- metabolic syndrome
- weight loss
- quality improvement
- type diabetes
- high fat diet induced
- weight gain
- palliative care
- primary care
- mental health
- public health
- south africa
- systematic review
- randomized controlled trial
- pain management
- skeletal muscle
- clinical trial
- electronic health record
- machine learning
- climate change
- social media
- deep learning