Practice improvement of obesity within mental health Services

Document Type:Dissertation

Subject Area:Health Care

Document 1

Community Health Needs Assessment EBP………………………………………. Evidence Based Practice HBM………………………………………. Health Belief Model NICE………………………………………National Institute of Clinical Excellence UK…………………………………………United Kingdom SMI………………………………………. Severe Mental Illness WHO………………………………………. World Health Organization Acknowledgment Practice improvement of obesity within mental health Services Abstract The issue of obesity has become a global disaster that is affecting people regardless of age, gender, social status and even physical health. 3% of the adult people are suffering from obesity. The present amount of money spent on treating health complications associated with obesity is over 5 billion Euros every financial year, and the amount is bound to double in the next 30 years (Department of Health, 2013). Some of the health complications associated with obesity involve cancer, type II diabetes and even heart failure diseases.

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People suffering from severe mental illness are more exposed to obesity than other people within the society. Different health professionals and scholars have debated the reason behind this increased prevalence among SMI people for a long time. This will ensure they are physically fit when discharged after recovering unlike in cases where doctors intervene after a patient has gained several kilos, something that proves difficult to manage. The research will help in determining the right intervention that helps in the management of obesity among mental health care patients to avoid a cyclic event where the patient comes back to the hospital suffering from depression and anxiety resulting from their poor body images. Obesity and mental illness The prevalence of obesity among people suffering from severe mental illness is higher and increasing at an alarming rate compared to other people in inpatient healthcare settings are in the society (Long et al.

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The increased cases are assumed to be caused by dietary habits, inadequate body exercise, lack of motivation in life, and reduced self-esteem as a result of their body images. Research has found the most of the obesity cases are associated with prescription of mood stabilizers/antipsychotic drugs and body mass index among adults in secure mental health facilities (Haw & Rowell, 2011). Although all female people were issued dietary instructions from specialists, it is only a third of them observed it daily. Their research realized that patients were consuming takeaway meals at least two times in a week, on top of the meals provided in the health facility. Also, the physical activity within the secure setting is limited by some issues such as limited opportunities resulting from understaffing, risk matters, and poor motivation among patients.

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It is because of such issues that obesity is declared as a disaster within secure healthcare settings. Research by Wardle termed the services as “obesogenic” surroundings. ” Some of the genetic syndromes seem to increases risks of obesity such as Williams, Down’s and Prader-Willi syndromes (Nordstrøm et al. People who have the challenge of moderate learning are exposed to specific of overweight compared to the ones with more pronounced levels. According to research, living styles affect the weight of people who have a learning disability. Further, living with relatives or even independently can expose one to high risks of becoming obese. These increased cases of obesity among adult people are attributed to poor socio-economic style of living. ” After examining the utility of physical activity to monitor levels of energy expenditure among 17 male people with learning challenges, McKeon realized that half of them recorded low activity and concluded that people with profound problems have low chances of participating in physical activities.

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Therefore, the different studies conducted the two categories of individuals presently as victims of obesity and overweight because of poor feeding habits, lack of exercise and even reduced self-esteem. It is the responsibility of care providers, within secure settings and in the society to devise most effective interventions for managing weight gain among such people. Statement of the Problem Obesity is a condition of excessive body fat assumed to a have a BMI of over 30 kg per square meter, and it is used in determining the potential risk of people to health complications. During the 1800s, it only 3% of the US population that was considered obese but research shows that over 34% of adults in the country are presently suffering from obesity.

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The process of improving one’s diet involves consumption of balanced diets with right portions of food that are recommended to keep health and physical body image. For instance, intake of fruits and grains that contain fiber is essential for the human body because it helps in secretion of intestinal bacteria and decreases chances of developing diabetes, chronic heart diseases as well as other gastrointestinal complications (Anderson et al. Further, such fiber is essential in reducing chances of becoming obese and helps in cutting weight. The increased cases of obesity among mental health patients call for increased research to come up with different interventions for managing the problem. Researching on the factors resulting in obesity among mentally challenged people and effective intervention methods is important because of the increased cases of obese psychiatric patients admitted to healthcare facilities for a long time.

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The significance of the study The issue of obesity has become a threat to mentally challenged people who stay for a long time in secure health facilities where their dietary habits are not properly monitored. Such people become obese by the time they recover and get discharged. While in the society, such people tend to lose self-esteem because of their distorted body images, resulting in anxiety and depression. The same people go to the hospital again to seek help, this time not because of mental disorder but to keep fit and regain their body image, creating a series of cyclic events within the healthcare setting. Research on the intervention practices for mental health patients provides insight to the providers such as nurses and dieticians who take care of them in hospitals and even people they interact with the society.

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The issue of non- commitment by most of the respondents on what they may feel is another public ridicule because of their low self-esteem, and poor body image will limit the research In such a case, the interview will involve a lot of professionalism to ensure that no respondent feels ridiculed or mocked because of his/her body image. Lastly, the sample size might also limit the research outcome as well as time frame, funding and survey methodology adopted. Chapter two: Background Information on Psychiatric obesity Causes of Obesity Obesity is categorized as one of the complicated and multifactorial health disorder characterised by environmental and genetic factors. Genetics of obesity disorder Single genetic animal structures have resulted in the determination of numerous genetic products that result in obesity such as leptin receptors, carboxypeptidase and even agouti that signal proteins (Comuzzie, 1998).

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The most important is the products of mutated genes among these models because they possess human homologues that seem to function the same, meaning that such proteins may help in development as well as maintenance of obesity. For instance, “leptin levels in most obese humans are high and correlate extremely well with body fatness” (Considine et al. The assumption of single-genetic mutation as a cause of obesity may be rare, numerous studies have shown the relationship between particular body tissues carrying candidate genes assumed to be part of “animal model obesity”, and other phenotype features such as BMI. Example of animals that are closely related to human obesity has been developed, such as mice which gains a lot of weight when fed with a lot of fats.

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Although the difference in genetics may not result in significant changes in the protein structures of the genes, they may effect on the functioning of protein products. The complication of obesity genes indicates simple answers concerning its causal are unlikely. The extent to which some behaviours are based on environment or genetics may not be the same between populations and individuals. Toxic Environment Research shows that “obesity has a strong heritable component, with approximately 30%–70% of the variability in body weight or fat mass being genetically determined” (Osler et al. Such variability rate indicates a significant effect of genetics compared to its contribution in some diseases associated with obesity such as CVD, diabetes or schizophrenia. However, it doesn’t explain a significant variation component of human weight based on genetics which is accounted by different environmental variables.

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Various studies have concluded that a significant percentage of family resemblance concerning BMI among adult people is attributed to genetics instead of a family environment that is commonly shared. Research shows that 25% of the increased cases of overweight among male people and 16% of females in the US is associated with smoking cessation. However, the advantages of smoking cessation are many compared to adverse effects of becoming overweight, which can be managed if cessation smoking is coupled with frequent physical exercising. The association between obesity, depression, and anxiety The issue of overweight and obesity among mental health patients has attracted a lot of attention in the United because it has become a basic challenge in the health sector. Research shows that above 33% of adult people and 17% young people in the United States were reported as obese in 2012(Ogden et al.

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The same research indicated that most of the American citizens were overweight, representing 69% adult people and approximately 24% of young people. Therefore, challenges resulting from obesity can be addressed by exploring some of the confounding factors such socioeconomic conditions. For instance, Georgia has experienced considerable effect as a result of the obesity epidemic. Although its prevalence is below the recommended national standard, its prevalence in the state has increased three times for the past 25 years. The epidemic is attributed to continuing struggling among many communities and government of Georgia State to meet health and economic needs of its people. Such communities serve as avenues to research on the complicated relationship between mental health and obesity. Each person interviewed was used as a unit of analysis, and it had a sample size of 1234 respondents.

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The outcome of this survey were valid because of different techniques used in data collection. The idea of taking their survey to public gathering helped in direct interaction with people and even observe their physical health status. In such a case, the researchers were able to note evident cases of depression and anxiety among different people in the county as well as seeking clarification concerning their views on how obesity can be managed. Taking surveys in food pantries helped in observing the economic status of such people through their buying and consumption styles to determine their economic status. Factors resulting to poor health among SMI people Service-related factors The physical welfare of people suffering from SMI has been ignored by care provider in the society and even within healthcare settings.

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For instance, research by Brugha et al. found that “in 145 people with SMI at a psychiatric day care facility, 41% had medical problems requiring care and 44% had unmet needs” (Brugha et al. A lot of literature report shows inadequate assessment and poor recording and monitoring of health status among people with mental health problems. A UK research on monitoring of physical health by care providers noted that although overall practice consultation was above standard for such group of people, the data collected was insufficient. On the other hand, a panel of professionals from the United States has developed a recommendation for frequent monitoring of the physical health of SMI patients. The recommendation assumes that “mental health care providers carry out the necessary monitoring of physical health as they believe that in addition to the physical health checks carried out in primary care settings, additional monitoring by mental health practitioners will result in earlier detection of serious conditions” (Marder et al.

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The State policies in Australia argue that health of SMI victims ought to be involved in case management. Although the specification of responsibilities is important in the society, there is need to acknowledge that health care provision among SMI people in both primary and secondary settings is the responsibility of practitioners and other care providers in the society. Most importantly, each of the two role players is already aware of their specific duties concerning when, where and how they should take part. According to research by Lawn et al. , “people with schizophrenia smoke out of habit and routine, for relaxation purposes, as a way of making social contact, for pleasure and as a way of gaining control in their lives. Smoking is ingrained in the culture of psychiatry” (Lawn et al.

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Physical activity Report by WHO identifies lack of physical exercise among the factors engineering loss of lives in developed nations. People suffering from mental health complications least participate in physical activities compared to other people in the society. The most common models that were social ecology, transtheoretical and human belief framework model. Social Ecology model Socioecological model is referred as a field of science that deals with the relationship between natural surroundings and living things. The framework concentrates on different contexts that affect the relationship between human beings and his surroundings such as social-cultural, institutional and structural (Stokols, 1992). It is within socio-ecology framework were peoples’ behavior develop from the complicated relational exchange between the two parameters. The primary determinants of human behavior are as a result of the internal and external mechanism.

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Further, the other assumption belief that individuals relate to the surroundings based different levels such as personal, population, medium group and even organizational level. Peoples’ perceptions and experiences can be affected by varying interactions happening at different levels. According to the second and third beliefs, interventions based on behaviors ought to be flexible to align with special and surroundings that are individually constructed. Finally, the environment is affected by and affects individuals relating to it (Stokols, 1992). The last assumption states that designing of interventions can be made in such a way that it targets changes in the environment that enhance health behaviors. Different patients may be at various stages of behavioral change, and various responses should be developed to suit their stages.

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The process of weight management calls for a long-lasting commitment to healthy living and ought to be perceived as a chronic condition that calls for continued support all through the behavioral change process. Health Belief Model The HBM model focuses on the multifaceted factors of behavior related to human health such as contextual and psychosocial factors, making it significant for determining effective interventions of weight management. The main concepts of this model focus on individual’s likelihood of developing a change of behavior considering his/her contextual and perception effects. Personal judgments involve the “perceived susceptibility to and severity of a given health threat, and the perceived benefits and barriers to making behavior change to address that health threat” (Daddario, 2007). They can be something formal such as a reminder notice from the dentist, a quick, subconscious glance at an informational poster, or something as fleeting as a sneeze” (Rosenstock, 1974).

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While applying the HBM theory to manage weight in different settings, perceived susceptibility is referred as a feeling of vulnerability developed by an individual concerning the adverse effects of being overweight. An individual could be aware of he/she is obese but has no sense of being exposed to CVD, high blood pressure or even diabetes because of obesity. The severity of perceived obesity refers to the approximated effect that can result from diseases related to overweight. An obese person may be aware of risks exposing him/her to diabetes but not get concerned about the probable burden and challenges related to diabetes. The needs of its research questions will dictate the design that has been selected. The study compares two different groups of mental health patients to determine whether early intervention regarding monitoring their BMI and dietary habits can help in managing obesity.

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A qualitative approach is both interactive and subjective, and it will assist in promoting understanding of human lifestyle and effective intervention that is practical in the long run. Sampling design/Size Sample size refers to a population subset which can be used in data collection (Parahoo, 2006). Determination of sample size involves both probability and non-probability sampling techniques. Cumulatively, the sample size will involve 25 participants; 17 from secure healthcare setting and the other eight from the society but all the participants have same characteristics. Data collection Research by Kombo & Tromp defines data collection as a process of combining certain data with the purpose of agreeing or refuting certain facts. The study will use two research instruments to collect data; the instruments will be made of the structured questionnaires and observation method.

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The two approaches of collecting data are most appropriate because the research will involve the use of facts recorded on patient’s file as well as observing their physical appearance which will help in determining if a patient is depressed or has reduced self-esteem. Data instruments The research will involve primary sources of data that will include observation and use of two different questionnaires. In this case, observation will include looking at the physical health of the participants such as their body size, depression, and anxiety that are physically observable. Such observations will serve as insight concerning the level patient’s self-esteem in the society. Data Collection Procedures The process of data collection for mental health patients will be formalized through observation of specific protocols and some prescribed procedures by the concerned institutions.

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The research will entail first seeking approval from the academic institution which will issue a written document authorizing the study. Later, the document will be taken to State agencies that approve conduction of research to seek further approval for researching within the scope area. Finally, if the academic institution approves the outcome of the study, the researcher will target at making presentations during the national nursing workshops. This research will have a lot of benefits to the above targeted groups, for instance, it will serve as a guideline to healthcare providers by offering effective intervention that can help in managing obesity in secure settings. On the other hand, presenting it to learners pursuing medical profession will give insight of obesity prevalence within the society and different management interventions.

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Lastly, publishing the research as a journal article will be fundamental to different State governments concerning development of policies that help in fighting increased cases of obesity among mental health patients. Research Timeframe (GANT Chart) Ethical consideration Failing to address and identify matters of ethics can jeopardise the process of conducting research as well as its outcome. Further, it will uphold the principle of beneficence by treating all the participants with equity through advising those concerning different ways that can help in improving their self-esteem. Bibliography Anderson, J. , Baird, P. , Davis Jr, R. , Ferreri, S.  British Journal of Psychiatry, 155(06), pp. Burns, N. and Grove, S.  Understanding Nursing Research. 4th ed. Special Care Dentistry, 15, 56–60 Carney, R. and Goldberg, A. Weight Gain after Cessation of Cigarette Smoking.

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 New England Journal of Medicine, 310(10), pp. Clément, K.  New England Journal of Medicine, 333(6), pp. Comuzzie, A. The Search for Human Obesity Genes.  Science, 280(5368), pp. Considine, R. Serum Immunoreactive-Leptin Concentrations in Normal-Weight and Obese Humans.  New England Journal of Medicine, 334(5), pp. Covell, N. H. , Weissman, E. Department of Health (2013).  Obesity and healthy eating - GOV. UK. [online] Gov. uk. Gaining on Fat.  Scientific American, 275(2), pp. Glanz, K. , Rimer, B. , and Viswanath, K. Obesity, serious mental illness and antipsychotic drugs.  Diabetes, Obesity and Metabolism, 11(7), pp. Houser, J.  Nursing Research. Toronto: Jones and Bartlett Publishers Inc. , Pantelis, C. Medical co morbidity in schizophrenia. Medical Journal of Australia 178, pp. S67–S70. Lawn, S. https://doi. org/10. 1108/14636646200900020 Long, C. , Rowell, A. , Gayton, A. , Cuijpers, P.

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, Penninx, B. and Zitman, F. Overweight, Obesity, and Depression.  Archives of General Psychiatry, 67(3), p. American Journal of Psychiatry 161, pp. McGuire, M. and Beerman, K. Nutritional Sciences from Fundamentals to Food. 2, pp. O. Dietary aspects related to health and obesity in Williams syndrome, Down syndrome, and Prader-Willi syndrome. Food and Nutrition Research, 59, 1–12. https://doi. org/10.  Survey of Anesthesiology, 58(4), p. Osler, M. , Holst, C. , Prescott, E. and Sørensen, T. Obesity, dyslipidaemias, and smoking in an inpatient population treated with antipsychotic drugs.  Acta Psychiatrica Scandinavica, 110(4), pp. Peet, M. Diet, diabetes, and schizophrenia: Review and hypothesis.  British Journal of Psychiatry, 184(S47), pp. , Rimer, & K. Viswanath (Eds. ), Health behavior and health education: Theory, research, and practice (4th Ed. San Francisco, CA: JosseyBass Ravussin, E. and Bogardus, C.

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