Research Paper on Psychological Comorbidity: Mixed Anxiety and Depression

Introduction and Overview of the Problem

Mixed anxiety and depression is 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 in terms of physical functioning than many chronic diseases (Olariu, Forero, CastroRodriguez, RodrigoCalvo, Alvarez, MartinLopez, & Fullana, 2015). Yet, many of the patients who present with these disorders may not be diagnosed or thus 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 one of 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 PICO question to be examined in the project. Additionally, this chapter will introduce the Diffusion of Innovation Theory, the theoretical framework that will boost the understanding of the complex range of variables that can affect the implementation of the HAM-D and HAM-A in assessing the severity of depression and anxiety among patients in 24hr supervised clinical dependency treatment center.

Is your time best spent reading someone else’s essay? Get a 100% original essay FROM A CERTIFIED WRITER!

Save 25%

Background

There is a high rate of psychological comorbidity in individuals with substance abuse dependence. 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 a large European survey with odds ratio being 33.7 (Bandelow et al., 2017). Notably, this is a concern if, during treatment, the time to relapse is shorter, the drop-out rate is high, and long-term substance use is greater for those with comorbid major depression or anxiety disorder than those without a comorbid mental disorder. Evidently, psychiatric comorbidity is a significant aspect influencing treatment response for substance dependence (Olariu et al., 2015). Correspondingly, among substance dependence patients, a clinically significant degree of depression and anxiety predict poor response to dependence treatment. Nevertheless, the treatment of dependence and psychological disorders is often the responsibility of diverse services, which may obstruct the treatment process. Thus, there is a need for effective integrated diagnosis and treatment for 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, data suggest that the accuracy of depression and anxiety recognition by non-psychiatrists is low (Olariu et al., 2015). Additionally, there is evidence for significant undertreatment of anxiety and depression. 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% receive only drug treatment, and 26.5% received both drug and psychotherapy treatment.

The Significance of the Problem

Poor recognition of depression and anxiety is related to reduced quality of life and survival (Olariu et al., 2015). In addition, untreated depression and anxiety raise the chance of engaging in addiction further. Notably, this ruins 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 U.S. 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, there is a need to assess their severity sufficiently to ensure patients receive the right psychiatric interventions.

Question Guiding Inquiry (PICO)

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 a technique to enhance the assessment of the severity of depression and anxiety to recommend psychiatric interventions accordingly. Thus, the PICO question guiding the project is as follows: Does the implementation of the HAM-D and HAM-A (Intervention) among patients in 24hr supervised clinical dependency treatment centers (Population) affect the evaluation of depression and anxiety incidences effectively (Outcome) to facilitate recommendation for psychiatric interventions?

Theoretical Framework

Since the transition to HAM-D and HAM-A implementation is anticipated, a favorable strategy is for health care practitioners in the 24hr 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 on the basis the diffusion of innovation theory that 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 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 stated that five characteristics of an innovation that include relative advantage, compatibility, simplicity, observability, and trialability, are determinants of the adoption and diffusion of the innovation (Mohammadi et al., 2018). Notably, the more innovation can integrate with existing values, past experience and the needs of potential adopters, the greater its possibility of diffusion and adoption.

Similarly, this project uses the diffusion of innovation theory to discern the aspects that enhance the adoption of HAM-D and HAM-A and determine the process by which the idea is adopted by patients and healthcare providers in the 24hr supervised clinical dependency treatment center. In this project, the innovation to be examined is 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, avails 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 evaluation. It comprises of 14 items, each defined by a series of symptoms. Mainly, each item is rated on a 5-point scale, ranging from 0 (not present) to 4 (severe) (Thompson, 2015).

Diffusion of Innovation Theory - this is a theory profound by Everett Rogers that seeks to describe how, why, and at what rate new ideas or technology spread (Mohammadi et al., 2018).

Conclusion

This chapter established that there is a high rate of psychological comorbidity in individuals with the dependence that often go undiagnosed or untreated. When depression and anxiety disorders are untreated, they affect people and the country adversely. The literature supports that the accuracy of depression and anxiety recognition by non-psychiatrists is low. Thus, there is a need for effective integrated diagnosis and treatment for dependence and comorbid anxiety and depression in treatment centers.

The desired outcome of this project is the increased implementation 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 the supervised 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. PMCID: PMC5573566

Mohammadi, M. M., Poursaberi, R., & Salahshoor, M. R. (2018). Evaluating the adoption of evidence-based practice using Rogers's diffusion of innovation theory: a model testing study. Health promotion perspectives, 8(1), 25. DOI: 10.15171/hpp.2018.03

Olariu, E., Forer, C. G., CastroRodriguez, J. I., RodrigoCalvo, M. T., Alvarez, P., MartinLopez, L. M., ... & Fullana, M. A. (2015). Detection of anxiety disorders in primary care: A metaanalysis of assisted and unassisted diagnoses. Depression and anxiety, 32(7), 471-484. DOI: 10.1002/da.22360

Sharp, R. (2015). The Hamilton rating scale for depression. Occupational Medicine, 65(4), 340-340. DOI:10.1093/occmed/kqv043

Thompson, E. (2015). Hamilton rating scale for anxiety (HAM-A). Occupational Medicine, 65(7), 601-601. DOI: 10.1.1.964.6326