Depression is common in human beings in case of any distress or disease. Whether Diabetes II and its pathophysiological sequel has any role in enhancing the depressive state in sufferers’ has been investigated in this study with an attempt to eliminate other contributory factors of depression such as demographic traits or ethnicity (Lee et al, 2009). The title of the paper is succinct enough and illustrative of the content of this study as it mentions all the dependent variables under investigation. In addition, the authors have explored the role of diabetic complications, resultant quality of life, and depression on a readily measurable parameter, the A1C (Hb A1c) or glycohemoglobin level, which is an indicator of diabetes pathology.
The abstract clearly states the purpose of the study as elaborated above and explains the study method used in the form of a cross-sectional survey of 55 identified and shortlisted diabetes patients. The mode of measuring depression has also been stated in the abstract which rounds off by highlighting the main findings of the research followed by the recommendations based on this study.
The introduction is comprehensive in content and begins by explaining the basis of the study due to the significant levels of depression (28%) encountered in the diabetic population of the United States. Adequate sources have been cited for an appropriate level of conviction to justify the study. The common pathophysiological mechanisms associated with both diabetes and depression have been explained as the basis for establishing a correlation between the two and their close interdependence.
The complex interplay between social, psychological, and biological processes has been cited as a reason leading to the need for investigating the involvement of demographic characteristics in the complex interplay between the concurrence of diabetes, depression, and quality of life. The introduction has a good flow leading to the final investigational aims of the study. The problem being investigated has certain implications for nursing as the results can serve as pointers towards nursing interventions that can help in alleviating depression in susceptible individuals. The study design seems to be appropriate as distinctive parameters have been shortlisted and appropriate quantitative tools used to measure the endpoints with a good degree of confidence.
The study design involved a combination of qualitative and quantitative approaches. It was conducted as a cross-sectional survey in the form of questionnaire’s submitted to willing volunteers shortlisted after satisfying definite criteria of age, sex, knowledge of the English language, educational background, and history of the disease, after prior sanction from appropriate authorities at a University of Maryland affiliated diabetes clinic. The level of depression was assessed with Beck Depression Inventory-II (BDI-II) which incorporates the use of the Lickert scale and the quality of life evaluated with Medical Outcomes Study 36 Item Short-Form Health Survey (SF-36).
IDS-SR was used to assess the major domains of depression satisfying the criteria of DSM-IV. The degree of Diabetes control was measured by A1c levels and both macro and micro comorbidities were evaluated for obtaining coherence of results. The hypothesis and research questions have a strong correlation and have been adequately addressed by citing numerous studies which indicate an investigation in this direction.
The literature review is comprehensive and prominent workers in this area have been cited which establishes a strong basis for the study itself as well as the design used to evaluate specific parameters. The conceptual and theoretical frameworks for the study are pertinent as there is a strong degree of association between the parameters studied which are capable of yielding significant points for statistical analysis. Both demographic, as well as clinical data, were analyzed using appropriate modes of statistical analysis which needed transformation due to the skewness of the data obtained. Correlations between endpoints were measured using multiple regression and hierarchical analysis and chi-square and t-tests were used, which offered some degree of confidence in interpretation.
Both measures of depression, BDI-II and IDS-SR correlated well in the indication of the prevalence of depression among the participants and gave figures between 41% and 46% respectively. 49% of the participants elicited mental component scores which were poor when compared to the normative data for the general US population. So was the case with physical component scores which were worse in 71% of the participants when compared to the national normative sample’s median value.
As indicated by BDI-II scores there was no significant difference between the prevalence of depression between males and females, however, females showed a significant tendency to suffer from moderate to severe levels of depression. Black patients (53%) were found to be more likely to suffer from depression than white patients (33%). It was also inferred that depressed patients significantly fell into the younger age group and they had a tendency to suffer from moderate to severe levels of depression. After evaluation of depression levels, the authors have focused their attention on the frequency of diabetes-related comorbidities in such participants and no correlation based on varying degrees of depressive states and comorbidities like hypertension, hyperlipidemia, obesity, nephropathy, etc., micro comorbidities as well as the A1c values were observed.
Transformed variables were used to determine the correlation between measures of depression and quality of life and average MCS (mental subscale) and PCS (Physical subscale) scores were found significantly worse for the depressed patients. The regression analysis has been performed to predict the depression scores based on gender, race, and age. The data is well tabulated and explanations coherent enough to show the confidence level of the analysis.
However, in this study, too many correlative approaches and normalization of values have been employed which can lead to some degree of misinterpretation due to bias of comprehension and understanding of qualitative aspects based on purely speculative statistical analysis. Individual variations and medication history, compliance habits in participants have not been considered and too much emphasis has been placed on confining the study to a small group of participants within a specific clinical location. Other factors like climate, living conditions, lifestyles, and socio-cultural backgrounds may elicit different responses.
The study has merely substantiated previous reports of the correlation between depression and diabetes and found some level of significant correlation and higher occurrence based on sex (females) and race (blacks). No direct relationship of depression to the measurable biological parameter A1c was obtained which is therefore not a good indicator of the correlation between diabetes and depression. Despite the comprehensive study design and deep statistical analysis, the study has only pointed towards the need for addressing the issue of depression in diabetics and not come up with any definite pointer towards establishing a correlation as variable factors are too many and too much reliance on statistical tools, however appropriate cannot serve to predict events in a diabetic.
The only constructive argument put forward by the authors is the need for identifying and addressing the problem of depression in patients suffering from type II diabetes at an early stage which suggests a need for alertness by the attending healthcare professionals and nursing staff. Treatment initiated at an early stage can assist in enhancing the quality of life as well as compliance with medication in the patients which can prevent further deterioration and occurrence of comorbidities. The study indicates a more comprehensive future research in a broader population and a larger sample size to substantiate and confirm the analysis obtained.
Reference
Lee H., Chapa D., Kao C., et al, (2009) Depression, quality of life, and glycemic control in individuals with type 2 diabetes, Journal of the American Academy of Nurse Practitioners 21, 214–224.