Prevention and Detection of Obesity

NB: We do not resell your papers. Upon ordering, we do an original paper exclusively for you.

NB: All your data is kept safe from the public.

More than 30% of the adults in the US are overweight; that is, they have a body mass index of 25 to 29.9 kg/m². Overweight grownups are at a heightened risk for the development of diabetes and high blood pressure, in addition to turning obese. Although extensive endeavors for the management of obesity have led to the significantly diffident and inconstant loss of weight, detection, and prevention of obesity amid overweight persons may be highly successful since such people are less probable of identifying themselves as overweight, do not have much weight to lose, and may deem managing weight a sensible objective.

Hindrances to the detection and prevention of obesity encompass failure to establish that patients have become overweight, time limitations, inadequate training, and restricted availability of electronic tools for diabetes (Hazlehurst et al., 2014). Electronic tools such as Electronic Health Records (EHRs) have the capacity of rising above hindrances to detection and prevention of obesity via computerized backing that reminds health professionals to counsel the patient and offer adequate resources that facilitate a controlled, evidence-based approach.

This study seeks to discuss the significance of electronic tools in the detection and prevention of obesity. The benefits of electronic tools for obesity lie in the excellent physician detection of overweight, improved counseling and objective-setting amid overweight individuals, and enhanced patient advancement toward the set target. Studies affirm that early diagnosis and behavior-anchored treatment of individuals with obesity or overweight results in facilitated medical results (Baer et al., 2015).

Nevertheless, there are some instances where the overweight is not recognized by health professionals and ends up developing into obesity. If electronic tools for obesity are aimed at the standardization of weight management coupled with awareness, their assistance in the identification, diagnosis, and counseling of obesity and overweight persons is improved.

The application of electronic tools for obesity may result in the diagnosis, prevention, and treatment of obesity-associated concerns at a population situation instead of just amidst a few individuals (Hazlehurst et al., 2014). In this regard, electronic tools for obesity may be executed by health professionals in the scope of medical backgrounds to improve the diagnosis and management of obesity. The use of electronic-based alarms and management tools enhances the detection of overweight, as well as the rate of counseling. Amid the patients for whom electronic tools for obesity have been employed, most demonstrate the long-term behavioral transformation and positive sentiments regarding the intervention.

As contemporary health care transformations place increasing emphasis on the progressive adoption and meaningful application of electronic tools for diabetes, there will be an improvement in the detection of overweight and counseling for weight management. On this note, using electronic tools for the detection and prevention of obesity may be a vital element for effecting change in practice.

Electronic tools for obesity are playing a crucial role in transforming the long-term information setting. They are turning out to be significantly popular and have been proved to be greatly effective in the advancement of knowledge and initiation of reforms in the health care sector. Medical decision backing tools in EHRs provide the potential for the improvement of diagnosis and management of obesity, overweight, and promotion of caregivers adoption of evidence-based commendations regarding obesity (Gartee, 2011).

Research shows that when the use of electronic tools is reinforced by other aspects, detection and prevention of obesity become more successful. Such aspects encompass willingness to change, integration of behavioral transformation approaches, and collaboratively setting objectives. The aspects may be easily adapted to the motivational interviewing advance that health professionals consider very significant for the facilitation of behavioral changes geared toward the prevention of obesity.

Though the application of electronic tools seems to be closely linked to incitement of medical action such as the performance of tests, avoidance of unhelpful medication and provision of medical guidance, the incorporation of counseling enhances effectiveness. Therefore, successful prevention and detection of obesity call for health professionals and researchers to make informed judgments concerning the best electronic tool for obesity, the level of physical exercises, decrease in sedentary action, suitable nutrition, and constructive psychosocial results. With increasing technological expertise and the chance to explore the application of electronic tools in obesity prevention and detection, there is a need for systematic evaluation of the interventions and their influence on body mass index (Baer et al., 2015).

The use of electronic tools in the prevention and detection of obesity holds much promise in the simplification of some facets of health care since they are usually flaunted as effective and economical approaches.

In conclusion, overweight grownups are at high risk for the development of problems such as diabetes, high blood pressure, and obesity. Prevention and detection of obesity amid overweight individuals might be highly successful because such people are less likely to identify themselves as overweight, have a little weight to lose, and may consider managing weight a reasonable idea. The advantage of electronic tools for obesity is evident in the outstanding detection of overweight by the health professional, enhancement of counseling and setting of objectives amid overweight persons and improvement of patient progress toward the set target. Amid the individuals for whom electronic tools for obesity have been utilized, most express lasting behavioral change and positive reactions concerning the intervention.

References

Baer, H. J., Wee, C. C., DeVito, K., Orav, E. J., Frolkis, J. P., Williams, D. H., & Bates, D. W. (2015). Design of a cluster-randomized trial of electronic health record-based tools to address overweight and obesity in primary care. Clinical Trials, 12(4), 374-383.

Gartee, R. (2011). Electronic health records: Understanding and using computerized medical records (2nd ed.). Upper Saddle River, NJ: Prentice Hall.

Hazlehurst, B. L., Lawrence, J. M., Donahoo, W. T., Sherwood, N. E., Kurtz, S. E., Xu, S., & Steiner, J. F. (2014). Automating assessment of lifestyle counseling in electronic health records. American Journal of Preventive Medicine, 46(5), 457-464.

Click Here To Order Now!

Prevention and Detection of Obesity

Do you need this or any other assignment done for you from scratch?

We have qualified writers to help you.

We assure you a quality paper that is 100% free from plagiarism and AI.

You can choose either format of your choice ( Apa, Mla, Havard, Chicago, or any other)