<p> Globally, more than 1.9 billion people are overweight, and 600 million are obese (World Health Organization [WHO], 2016). The consequences are expensive: The associated costs to treat co- morbid illnesses in the United States amounted to $190.2 billion (Cawley & Meyerhoefer, 2012). Elevated body mass index (BMI) is directly related to premature death, cardiovascular diseases, diabetes, musculoskeletal disorders, and cancers (WHO, 2016). Weight regain after weight loss has emerged as one of the most significant obstacles for weight management therapeutics, undoubtedly perpetuating the epidemic of excess weight that affects over 60% of American adults (Maclean, Bergouignan, Cornier, & Jackman, 2011). Weight management is a complex and covert interplay between biology, psychology, and environment (Brownell, 2010; Moffitt, Haynes, & Mohr, 2015). The majority of weight management treatments have demonstrated high prevalence of relapse after weight loss and failed long-term efficacy after diverse healthcare treatments (Dombrowski et al., 2012; Moffitt et al., 2015; Munsch, Meyer, & Biedert, 2012). This dissertation examined the most effective forms of evidence-based psychotherapeutic and technological interventions for weight management treatment, focusing specifically on populations between the normal and overweight BMI range from peer-reviewed journals dated from 1950-2017. The objectives of this doctoral project were four-fold: (a) to conduct a systematic literature review and gather information from experts in the field regarding weight management, (b) to explore the biopsychosocial implications related to weight re-gain after loss, (c) to identify the most effective psychotherapeutic interventions and mHealth implications that aid long-term weight management, and (d) to disseminate these findings using a professional presentation.</p>
| Identifer | oai:union.ndltd.org:PROQUEST/oai:pqdtoai.proquest.com:10256732 |
| Date | 11 March 2017 |
| Creators | Assar, Sara |
| Publisher | Alliant International University |
| Source Sets | ProQuest.com |
| Language | English |
| Detected Language | English |
| Type | thesis |
Page generated in 0.0014 seconds