The Relationship between Pain and Depression in a San Antonio Mental Health Urgent Care Population Open Access

Dickmann, Leslie (Summer 2018)

Permanent URL: https://etd.library.emory.edu/concern/etds/b8515n45p?locale=en%255D
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Abstract

Background:  Pain and depression are two critical public health issues facing health care providers today, and the relationship between depression and pain is complex.  The current study sets out to examine whether depression is associated with pain in a mental health urgent care population.  Given the potential differences between the population used in this study and other populations used for pain and depression research (e.g. chronic pain sufferers, elderly), results from previous studies may not reflect those obtained in the current population.

Methods:  The current population consists of 1,366 individuals seeking mental healthcare at the Sigma Mental Health Urgent Care (SMHUC) clinic located in San Antonio, TX.  Intake data was obtained using remindtrac, a health technology tool, depression was measured using the PHQ-9, and pain using a numeric rating scale.  Descriptive statistics were used to characterize the population, and logistic regression was used to characterize the association between depression and pain. 

Results:  The mean PHQ-9 score in the urgent care population was 14.9 (SD = 7.1) indicating a moderate level of depression.  The mean pain score was 3.5 (SD = 3.5) indicating a mild level of pain in this population. Pain was significantly associated with depression (OR 1.11, 95% CI 1.09 – 1.13), although only individuals with moderately severe or severe depression had a probability of moderate to severe pain > 0.5.

Conclusions:  In the SMHUC population, all individuals with minimal, mild, or moderate depression (PHQ-9 < 15) have a rather low probability of moderate to severe pain.  It is only in the cases of moderately severe to severe depression (PHQ-9 = 15-27) that the probability of moderate to severe pain may be a concern and may need to be monitored more closely.

Table of Contents

Section, Page

Research question, 1

Introduction, 1

Methods, 7

Results, 16

Discussion, 20

References, 27

Table 1. The PHQ-9 questions and scoring system, 12

Table 2. Descriptive statistics of the entire SMHUC study population used in this analysis, 35

Table 3. Descriptive statistics of the SMHUC study population stratified by student or non-student, 38

Table 4. Descriptive statistics of the SMHUC study population stratified by pain category, 40

Table 5. Association between PHQ-9 score and pain category using logistic regression, 42

Table 6. Probability table for PHQ-9 score and moderate to severe pain, 43

Figure 1. Graphical representation of the logistic regression fits for the association between pain category and PHQ-9 score, 44

Figure 2. ROC curve illustrating the sensitivity and specificity of the adjusted logistic regression model used in the analysis, 45

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