week 6 discussion program evaluation

1

Explore the data

Student name

Faculty name

Due date

1. Brief Description of My Dataset

To complete this assignment, I prepared a small hypothetical data on the basis of which Patient Health Questionnaire - Adolescent version (PHQ-A) would be my outcome measure. PHQ-A is a short self-report assessment scale that evaluates depressive symptoms in adolescents in the last two weeks. It is made up of nine items, which correlate with a core symptom of depression.

The respondents are asked to rate the frequency of occurrence of each symptom on a four-point Likert scale with the following response options:

0 = Not at all,

1 = Rarely, 2 = Sometimes,

and

3 = Nearly every day.

The PHQ-A has been implemented in both community and clinical practice due to its brevity, administration simplicity, and straightforward scoring guidelines.

The PHQ-A is rated in its standard version by adding the responses to all the nine items to get one total severity score. Since all the items are phrased in the same direction the higher the answer, the more frequent or severe the symptom, there are no reverse-scored items to the total score. The potential scale of the total score is consequently 0-27 with a score of 0 indicating a lack of depressive symptoms and 27 indicating very frequent depressive symptoms on all items. Cut-off bands (minimal, mild, moderate, moderately severe, and severe depression) are occasionally applied in clinical practice, however, in this exercise I paid attention to the continuous total score.

In my hypothetical dataset I came up with three variables:

ID - a number that identifies a participant (101 -110).

PHQA_PRE: Total PHQ-A score at intake.

PHQA_POST: Score at six-month after intake.

There were no subscale scores and no mean-averaged variables. The dataset instead models overall change of symptoms over time with the use of these two total scores being within the valid PHQ-A scoring range (The jamovi project, 2025).

2. Screenshot of My Dataset

3. Descriptive Statistics

Attached as pdf: Jamovi descriptives and frequency tables output as a PDF.

4. Brief Interpretation

In the case of the hypothetic dataset, descriptive statistics were created on the PHQ-A total scores of the pre-test and post-test. The mean of pre-test scores (column B) was 18.3, the median of 18.5, and the standard deviation of 5.50, and the range was 9-27. The mean and median post-test scores (column C) were equal (mean=14.0, median=14.0) and the standard deviation was 5.29 and the minimum score was 6 whereas the maximum score was 22. These findings indicate that both variables fall within the range of 0 to 27 of PHQ-A expected range. Frequency tables showed a single instance of each observed score and the counts were 10.0 per cent, 100.0 per cent respectively and this showed a general spread distribution across the values (Magdum, 2022).

Combined, the descriptive statistics indicate that subjects came into the program having moderately high levels of depressive symptoms, which had a slight reduction at the six-month follow-up (R Core Team, 2025). The difference in the mean and the median between the pre-test and the post-test is in line with the general improvement but the scores of the participants remain within a high range and some of the participants have high levels of symptoms. The data set has no extreme outliers and all the values are within the valid scoring range, and no data were missing in this hypothetical sample.

References

Magdum, R. (2022). What is Data Exploration? and its Importance in Data Analytics.  Int. Res. J. Eng. Technol,  9(01), 01.

R Core Team (2025). R: A Language and environment for statistical computing. (Version 4.5) [Computer software]. Retrieved from https://cran.r-project.org. (R packages retrieved from CRAN snapshot 2025-05-25).

The jamovi project (2025). jamovi. (Version 2.7) [Computer Software]. Retrieved from https://www.jamovi.org.