Depression Case Study

The first step in the analysis was to categorize each patient by whether or not they passed the clinical threshold during their treatment and if their change was reliable. Clinical cutoff scores and Reliable Change Indexes (RCI) for the PHQ-9 and GAD-7 were obtained from past research [@Delgadillo2012; @Griffiths2015; @Kroenke2001; @Spitzer2006]. Clinical cutoff scores for the BASE-6 were obtained from unpublished pilot research and corresponded to the clinical cutoff of the commonly used OQ-45 measure.

The diagnostic validity of PHQ-9 has also been reviewed in another study by reviewing the data collected from 3000 patients. The analysis of the data showed good sensitivity (80%) and high specificity (92%) for PHQ-9 for diagnosis of major depression in the primary care clinics (Inoue et al., 2012). The high sensitivity data explains that PHQ-9 has acceptable screening accuracy for major depression because it correctly identified people with major depression. Additionally, a high specificity data confirms that the number of people who were correctly screened as not having depression was low.

Mean performance for all participants was measured for each phase to determine overall improvement. The procedure for calculating the percentage of nonoverlapping data (PND) was used to determine the effectiveness of the intervention. AIMSWeb computation CBM was also used for benchmark scores. AIMSWeb computation CBM probes were also measured monthly from September to December to determine follow-up performance. The scores were categorized as being very low performance (below 10th percentile), low performance (between 11th and 25th percentile), and average performance (between 26th and 75th

The CGI-I is a stand-alone clinical assessment utilized in clinical trials which provides a clinicians view of the participants functioning prior to, and after initiating, treatment (Busner & Targum, 2007). It provides an overall summary measure that considers available information including history, psychosocial circumstances, behavior, and impact of the symptoms of the participant 's ability to function (Busner & Targum, 2007). Through evaluation the severity of symptoms on a scale of 1-7 and the changes on a similar scale after initiation of treatment, it can track progress across time. It is easily understood by the non-researcher, which enables the team to engage an independent clinician in the completion of the assessment which

3) A t-value of -1.99, which was the calculated statistic for the Health Functioning measure in this study and corresponds to a study-bound p-value of 0.049, does not indicate a significant difference in these populations. Though the p-value is slightly lower than the study-wide alpha value of 0.05, the division of this value amongst the 15 measures according to the Bonerroni principle that works to reduce Type I errors means each test-specific alpha value is 0.0033. 0.049 > 0.0033, therefore the difference for this

- The mean of the grades of the experiential group at the level of Generalized anxiety is reducing after the therapeutic intervention in favor of the post-test.

First, a professional translator, with experience from medical sciences, translated the original question items into Finnish. The draft was checked and corrected by two of the researchers (AR, JR) and an MS nurse expert on HRQOL. Thereafter, the Finnish version was retranslated into English by an independent specialist (a medical doctor). The publisher of the original MSQOL-54 gave her permission for the use of the scale after having commented on the back translation.

Coding will be done by researcher, and confirmed by the research team. There will be an ongoing peer and participants’ auditing throughout the study. MAXQDA, the computer-assisted analysis software with fast coding, organization, and analytical functions will be used to complement the analysis of the researcher (MAXQDA, 2016). Detail description of interview procedure, and information will be ensured during data collection for complete transfer of data from stage to stage (Carson, et al., 2001; Gomm, Hammersley, & Foster, 2009).

Data synthesis was using the "Review Manager 5.1 software program 2011" (p.48), the standardized mean differences (SMD) used in those studies were post treatment date with 95% confidence intervals (CI) outstanding within different scale

The trials success rate is going to based off of a scale. “The main aim of the study is to evaluate the feasibility of administering the McGill Quality of Life Questionnaire (MQOL), reported to have the best clinometric quality rating, content validity, construct validity and internal consistency of reviewed quality of life questionnaires.” There will be a randomized, controlled trial that will last three weeks. Patients will be assigned into two different groups, the control group and the experimental

Placebo group: Montgomery–Åsberg Depression Rating Scale (MADRS) with a mean value of 21.72 and SD 6.58 pre-treatment reduced to a mean value of 17.40 with SD 8.28 post treatment. (p>0.001)

Each RCT’s internal and external validity was further analyzed examining power analyses, intention to treat, exclusion and inclusion criteria, loss rate, confounding variables, and P-values. Power analysis was examined in each article – a score of 90 percent or greater indicates appropriate sized sample for an effect to be detected post intervention (Rothwell, 2006). Intention to treat analysis was conducted to evaluate if the subjects were analyzed in the same group to which they were randomized. Population distribution was evaluated through inclusion and exclusion criteria. A large indicator of study validity is loss rate (Rothwell, 2006). If 10 percent or more of participants are unaccounted for it is difficult to conclude if their results would have a positive or negative impact on the overall outcome of the study. Lastly, P-values determine statistical significance; values less than 0.5 generally indicate strong evidence against the null hypothesis. P-value analysis helps determine if the outcomes of the study suggest no benefit, benefit, or possible harm to studied participants (Rothwell, 2006).

A split analysis was performed for the UC and CD group separately. There was a positive, strong correlation for both groups to report more severe disease activity if they had PHQ-8 scores 10, r=0.77 and r=1.15 for CD and UC patients, respectively. CD patients with moderate to severe depression are 2.17 times more likely to report moderate to severe disease activity, using the HBI, as compared to those with none or mild depression (OR = 2.17, 95% CI, p = 0.02). Furthermore, UC patients with moderate to severe depression are 3.15 times more likely to report moderate to severe disease activity, as per the SCCAI, as compared to those with none or mild depression (OR = 3.15, 95% CI, p = 0.01). Again, the gender difference did not reach statistical significance for neither CD or UC patients.

Then, each was given a standardized test to measure depression (higher test scores indicate higher levels of depression). Similarly, random samples of 20 individuals with one or more comorbidities (arthritis, hypertension, and/or heart ailment) were taken from the three geographic locations. They were also

The method Jelenchicks et al. (2012) study was for older adolescent college students to complete online surveys containing the Patient Health Questionnaire-9 depression scale and a weeklong experience sampling method approach to collect data. Only 273 participants had completed the survey out of the 373 students enrolled in the target class according to Jelenchicks et al. (2012). The results were that 49% of participants did not express any signs of depression on the Patient Health Questionnaire-9 depression scale. However, 35% resulted in mild, and 14% resulted in moderate to severe depression. Most participants