Success in Treatments for People Diagnosed with DepressionLauren P.
Mortimer Georgian Court University IntroductionThe healthcare industry is and will continue to evolve to provide patients with the best care possible. To do so, researchers must conduct studies and trials to keep up with the newest interventions. The authors of the article, “A Systematic Review of Comparative Efficacy of Treatments and Controls for Depression”, wanted to test the variations between treatments that have been approved for depression and controls such as a placebo. Due to depressions biological aspects, many patients need to try numerous treatments before finding the one or combination that works for them.
The authors wanted to gather enough data to determine which treatment or treatments are most effective for a majority of the patients. Collectively, the authors believed that the results would show little difference between the approved treatments and controls. VariablesThe authors conducted a univariate analysis of variance (ANOVA) with 2 factors to determine the percentage symptom reduction.
The independent variables of this test were the data source (published data or the FDA data), and the comparison of antidepressants and a placebo, and percentage symptom reduction was the outcome or dependent variable. In the second ANOVA, the blinding status of either blinded or un-blinded and treatment type were the independent variables, and the percentage symptom reduction was the dependent variable. By using the Tukey’s Least Significant Difference post-hoc test, the authors were able to compare the percentage reduction between any of the listed treatments that were considered active and the other controls. Lastly, the third ANOVA tested the influence of being blinded or which category of psychotherapy the patient used on the results for the trials of psychotherapy. The independent variables for this test were Cognitive Behavioral Therapy or CBT, Cognitive therapy, Behavioral Therapy, Interpersonal Psychotherapy and other therapies including support groups, etc. The dependent variable, just as the last two ANOVA tests was the percentage symptom reduction.
Design of StudyA systematic review design was used for this article. This type of design is needed for a study such as this one, because the authors wanted to analyze numerous trials and studies to collect pertinent data on treatments for depression. These published trials were analyzing the success of psychotherapies and alternative therapies for the treatment of depression. To calculate the percentage of symptom outcomes, the results from the type of treatment the patient’s received was transformed into the necessary format.Sampling Strategy, Sampling Size, Sample CharacteristicsThe research strategy used to conduct the research aspect of this article is called a “snowball search”. Within this type of search, the authors dove deep into the internet and found meta-analyses, reviews of psychotherapy and alternative treatments for depression.
A search of the FDA (Food and Drug Administration) website presented 62 trials on antidepressants which involved 13,802 patients. Next, the authors found over 100 published trials that involved 10,310 patients. The 3-month long exploration for data focused on published articles from 1975 to 2009.
The decades long literature search was useful because it explored many aspects of depression treatment studies and trials and allowed for the authors of this article to make unbiased conclusions. Dr. Pim Cuijpers’ 243 psychotherapy trials caught the attention of these authors and were extensively studied.
The next objective was focused on data from unconventional therapy trials that used controls. The Cochrane Reviews website had a number of articles that were reviewed and included different variations of depressive disorders. Inclusion and Exclusion CriteriaThe extensive research for reliable and valid studies was stretched to websites such as Pubmed, Psychinfo and the Cochrane Register of Controlled Trials because the authors felt information may have been previously overlooked. The search included, manuscripts that were narrowed in focus including depression trials of treatments that have been customarily accepted such as psychotherapy or exercise and acupuncture.
Inclusion criteria comprised published trials that focused on adults that were diagnosed with depression, able to walk and were between the ages of 18 and 65. The acceptable articles and trials had to use one at least one of the following scales, the Hamilton Rating Scale for Depression (HRSD), Beck Depression Inventory (BDI), or Montgomery-Asberg Depression Rating Scale (MADRS) or be able to estimate the average standard and results of acute treatments. The data that was excluded from use in this article, included trials that were out of the age limit of 18-65, whether the patient was older or younger, trials that included patients with underlying medical issues, trials that did not follow up with the patients one week after the completion of treatment, trials that concentrated on treatment resistant or hospitalized depressed patients, trials that involved imprisoned patients and finally trials that were not published in English or reported in peer-reviewed journals such as dissertations. Any trials that did not use the scales mentioned above were also excluded, along with trials that used unorthodox methods of treatment such as telephone therapy. Instruments, Reliability and ValidityThis article did not use any surveys or questionnaires, the authors of this study went through months of research, making sure they specified their search to only the most important trials and studies.
To regulate the reliability and validity of their research, the authors expanded their search to many different internet websites such as Pubmed and Cochrane. Although they broadened their search browsers they narrowed the material they wanted to focus on. The authors also conducted three different univariate analysis of variance (ANOVA) tests to determine their results to make sure it was unbiased. To conclude whether the results were valid, the authors used the ANOVA tests on the SPSS version 19.0 (IBM). According to the article, another test used was the Levene’s Test of Equality of Error Variance, which was used to determine if there were any differences in the results cross the groups of un-blinded depression treatments.
Data Analysis/Results and LimitationsThe first ANOVA test shows that antidepressants were more effective than the placebo, but data source did not matter. The published articles on antidepressants showed greater reduction than the FDA data. The second test established that “treatment type was a significant predictor of percentage symptom reduction in both un-blinded and blinded trials, but the magnitude and pattern of significance differed as a function of blinding” (Khan, Faucett, Lichtenberg, Firsch and Brown, 2012). Finally, the third ANOVA showed un-blinded participants reported more success than the blinded and that combination therapy was the most effective, and there was no difference between each treatment alone. The results of this study demonstrates the importance of involving patients in their care. The limitations of this article include, the specific groups that these treatments appeal to, the generalization of data, severity of depression and the specific design (double blind paradigm) used in this study. Works CitedKhan, A.
, Faucett, J., Lichtenberg, P., Kirsch, I., & Brown, W. A.
(2012). A Systematic Review of Comparative Efficacy of Treatments and Controls for Depression. PLoS ONE, 7(7), e41778. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3408478/