Evaluation of the Severity of Depression and Anxiety Paper Example

Chapter 1: Introduction and Overview of the Problem

Mixed anxiety and depression are a category listed in the Tenth Revision of the International Statistical Classification of Diseases and Related Health Problems (ICD-10) (Bandelow, Michaelis, & Wedekind, 2017). Both disorders are common in primary care patients and are more disabling, both socially and regarding physical functioning, than many chronic diseases (Olariu et al., 2015). Many of the patients who present with these disorders may not be diagnosed or treated appropriately. Nevertheless, the Hamilton Depression Rating Scale (HAM-D) and the Hamilton Anxiety Rating Scale (HAM-A) have proven useful for many years as ways of determining a patient's level of depression and anxiety before, during, and after treatment. Chapter 1of this scholarly project will establish the background regarding the implementation of HAM-D and HAM-A to assess the severity of depression and anxiety. Further, it will describe the significance of the problem and outline the PICOT question to be examined in the project. Additionally, this chapter will introduce the diffusion of innovation theory as a theoretical framework that will boost the understanding of the complex range of variables that can affect the implementation of HAM-D and HAM-A in assessing the severity of depression and anxiety among patients in a 24-hr supervised clinical dependency treatment center.

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Background

According to Maina, Mauri, and Rossi (2016), a high rate of psychological comorbidity is observed in individuals with substance use disorders. Approximately 85% of patients with depression have significant anxiety, and 90% of patients with anxiety disorder have depression (Bandelow et al., 2017). For instance, major depression was found to be highly correlated with all anxiety disorders in an extensive European survey, with an odds ratio of33.7 (Bandelow et al., 2017). Notably, this is a concern: if the relapse time is shorter during treatment, a higher drop-out rate occurs, and long-term substance use is a more significant problem for people with comorbid major depression or anxiety than individuals without a comorbid mental disorder. According to Olariu et al. (2015), psychiatric comorbidity is a significant aspect influencing treatment response to substance use disorders. Correspondingly, among substance use disorder patients, a clinically significant degree of depression and anxiety predicts an inadequate response to addiction treatment. Moreover, the treatment of dependence and psychological disorders is often the responsibility of diverse services, which may obstruct the treatment process. Thus, effective integrated diagnosis and treatment are neededfor dependence and comorbid anxiety and depression in treatment centers.

Rating scales for depression and anxiety can be helpful, but most are designed to assess the severity of an already diagnosed disease instead of making a new diagnosis. Notwithstanding, the data suggest that the accuracy of depression and anxiety recognition by non-psychiatrists is low (Olariu et al., 2015). Additionally, the evidence suggests thatanxiety and depression are significantly undertreated. For example, in a study by Bandelow et al. (2017), only 20.6% of participants with anxiety disorder sought professional assistance. Of these, 23.2% received no treatment at all, 19.6% received only psychological treatment, 30.8% received only drug treatment, and 26.5% received both drug and psychotherapy treatment.

The Significance of the Problem

The poor recognition of depression and anxiety is related to reduced quality of life and survival (Olariu et al., 2015). Also, untreated depression and anxiety raise the chance of individuals further engaging in addiction. Notably, untreated depression and anxiety ruin families, lead to problems at work, and make it difficult for individuals to overcome other serious illnesses. For instance, untreated depression is responsible for around 200 million days lost from work each year in the United States. The annual cost of untreated depression is approximately $43.7 billion in lost productivity, absenteeism from work, and direct treatment costs (Bandelow et al., 2017). Following the adverse effects of depression and anxiety on patients and the economy, assessmentsof theseverity need to be sufficient to ensure that patients receive the right psychiatric interventions.

Question Guiding the Inquiry (PICOT)

Various aspects may affect the assessment of depression and anxiety in clinical dependency treatment centers. In this project, the implementation of HAM-D and HAM-A will be examined as techniques to enhance the evaluation of the severity of depression and anxiety and to recommend psychiatric interventions accordingly. Thus, the PICOT question guiding the project is as follows: Does the implementation of the HAM-D and HAM-A within eight weeks among patients in 24-hr supervised clinical dependency treatment centers (population) positively affect the evaluation of depression and anxiety incidences (outcome) and facilitate recommendations for psychiatric interventions as compared to current practice?

Theoretical Framework

Since the transition to HAM-D and HAM-A implementation is anticipated, a favorable strategy is for health care practitioners in the 24-hr supervised clinical dependency treatment center to adopt the practice beginning at the initial stage of transition. Moreover, the spread of the HAM-D and HAM-A depends on early adoption. Mainly, this goal can be attained by using the diffusion of innovation theory, which serves as a theoretical framework for the establishment of conditions that advance innovation adoption and the related techniques of adoption (Mohammadi, Poursaberi, & Salahshoor, 2018). The theory facilitates the assessment of how certain clinical behaviors are embraced and enables the focus to be directed toward perceived innovation characteristics that increasingly drive adoption.

According to Roger's diffusion of innovation theory, innovation is a process, an idea, or a technology that is viewed as new to people within a particular social system (Mohammadi et al., 2018). Diffusion refers to the process through which information concerning the innovation flows from one individual to another over time within the social system (Mohammadi et al., 2018). Based on this theory, four primary aspects, namely, the attributes of the innovation, communication channels, time, and the social system, influence the spread of a new idea. Additionally, Rodgers considered the features of an innovation to be effective aspects of adoption. In particular, he provided five characteristics of an innovation, including relative advantage, compatibility, simplicity, observability, and trialability, as determinants of the adoption and diffusion of the innovation (Mohammadi et al., 2018).

Rogers defined relative advantage as "the degree to which an innovation is perceived as being better than the superseding idea" (Fahy, 2017). Similarly, he defined compatibility as "the degree to which an innovation is perceived as consistent with existing values, past experiences, and needs of potential adopters" (Fahy, 2017). Additionally, he defined simplicity as "the degree to which an innovation is perceived as difficult to understand and use" (Fahy, 2017). Likewise, trialability referred to the ability of end users to experiment with innovation while observation is "the degree to which the results of an innovation are visible to others" (Fahy, 2017). Notably, the more innovation can be integrated with experience, existing value, and the requirements of possible adopters, the higher its possibility of diffusion and adoption.

Rogers described five categories of adopters, namely innovators, early adopters, early majority, late majority, and laggards (Dearing & Cox, 2018). Innovators are the people willing to take risks and have financial liquidity and scientific sources, which allow them to adopt inventions. Early adopters are similar to innovators regarding financial liquidity but they are more discreet in adoption choices. Conversely, early majority adopt an innovation after a period that is significantly longer than early adopters and innovators. However, the late majority group approaches an innovation with skepticism and they adopt it after a majority of people has adopted the innovation. Finally, laggards are the last to adopt an innovation. These people have no aversion to change agents (Dearing & Cox, 2018).

Similarly, this project uses the diffusion of innovation theory to discern the aspects that enhance the adoption of HAM-D and HAM-A to determine the process by which the idea is adopted by patients and healthcare providers in a24-hr supervised clinical dependency treatment center. The innovations to be examined in this project are HAM-D and HAM-A.

Definition of Terms

Hamilton Depression Rating Scale (HAM-D) - this is the most widely utilized clinician-administered depression assessment scale. It provides an indication of depression and, over time, avail a valuable guide to progress. The scale has two common versions with either 17 or 21 items and is scored between 0 and 4 points (Sharp, 2015).

Hamilton Anxiety Rating Scale (HAM-A) - this is a rating scale developed to quantify the severity of anxiety symptoms, often utilized in psychotropic drug evaluations. It comprises 14 aspects, each described by a combination of symptoms. Mainly, each item is rated on a 5-point scale, ranging from 0 (not present) to 4 (severe) (Thompson, 2015).

Depression - According to Cesar and Chavoushi (2013), depression is a mental condition attributed to severe feelings of inadequacy and hopelessness, mainly accompanied by low energy and a lack of interest in life.

Anxiety disorders- are a group of mental disorders characterized by feelings of fear and anxiety (World Health organization, 2017).

Psychiatric Interventions - these are treatments such as psychotherapy and medication that psychiatrists use to bring change in individuals with mental disorders (Maina et al., 2016)

Conclusion to Chapter

This chapter established that individuals with dependence face a high prevalence of psychological comorbidity that often goes undiagnosed or untreated. When depression and anxiety disorders are untreated, they affect patients adversely. The literature supports the notion that the accuracy of depression and anxiety recognition by non-psychiatrists is low. Thus, effective integrated diagnosis and treatment are neededfor dependence and comorbid anxiety and depression in treatment centers.

The desired outcome of this project is to implement the use of HAM-D and HAM-A to assess the severity of depression and anxiety. The diffusion of innovation theory provides a framework that shows how this idea can be adopted and embraced in asupervised clinical dependency treatment center. Consequently, the evaluation of depression and anxiety can improve, which can facilitate the recommendation of effective psychiatric interventions.

References

Bandelow, B., Michaelis, S., & Wedekind, D. (2017). Treatment of anxiety disorders. Dialogues in Clinical Neuroscience, 19(2), 93. Retrieved from https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5573566/

Cesar, J., & Chavoushi, F. (2013). Background paper 6.15 Depression. Sabate E. Depression in young people and elderly: Priority Medicine for Europe and the world. A public Health Approach to innovation. Retrieved from https://www.who.int/medicines/areas/priority_medicines/BP6_15Depression.pdf

Dearing, J. W., & Cox, J. G. (2018). Diffusion of innovations theory, principles, and practice. Health Affairs, 37(2), 183-190. doi: 10.1377/hlthaff.2017.1104

Fahy, N. (2017). Incorporating psychological theory into the model of diffusion of innovations in healthcare (Doctoral dissertation, University of Oxford). Retrieved f...