Comorbidity of Pain and Depression Among Persons With Traumatic Brain Injury

Objective

To assess the prevalence of pain, depression, and comorbid pain and depression among a civilian sample of persons with traumatic brain injury (TBI).

Design

Longitudinal survey design with 1-year follow-up.

Setting

Inpatient rehabilitation and the community.

Participants

Participants (N=158) admitted to inpatient rehabilitation after moderate to severe TBI.

Interventions

Not applicable.

Main Outcome Measures

Depression was assessed with the Patient Health Questionnaire-9 (PHQ-9); pain was assessed with a numerical rating scale from 0 (no pain) to 10 (worst pain). Participants who reported average pain ≥4 were classified as having pain, and participants with PHQ-9 scores ≥10 were classified as depressed.

Results

Both pain and depression were more prevalent at baseline assessment (pain: 70%; depression: 31%) than at year 1 (pain: 34%; depression: 22%). Comorbid pain and depression declined from 27% at baseline to 18% at year 1. Pain was significantly associated with depression at baseline (relative risk: 2.62, P=.003) and at year 1 (relative risk: 7.98, P<.001).

Conclusions

Pain and depression are common and frequently co-occur in persons with TBI. Although their frequency declined over the first year after injury, the strength of their association increased. Assessment and treatment of both conditions simultaneously may lead to improved outcomes, both early after TBI and over time.     

Sensitivity and Specificity of the Beck Depression Inventory-II in Persons With Traumatic Brain Injury

Homaifar BY, Brenner LA, Gutierrez PM, Harwood JF, Thompson C, Filley CM, Kelly JP, Adler LE. Sensitivity and specificity of the Beck Depression Inventory-II in persons with traumatic brain injury.

Objectives

Our objective was to examine the Beck Depression Inventory-II (BDI-II) in a traumatic brain injury (TBI) sample using a receiver operating characteristic (ROC) curve to determine how well the BDI-II identifies depression. An ROC curve allows for analysis of the sensitivity and specificity of a diagnostic test using various cutoff points to determine the number of true positives, true negatives, false positives, and false negatives.

Design

This was a secondary analysis of data gathered from an observational study. We examined BDI-II scores in a sample of 52 veterans with remote histories of TBI.

Setting

This study was completed at a Veterans Affairs (VA) Medical Center.

Participants

Participants were veterans eligible to receive VA health care services.

Interventions

Not applicable.

Main Outcome Measures

Outcome measures included the BDI-II and the Structured Clinical Interview for DSM-IV Axis I Disorders (SCID-IV).

Results

We generated an ROC curve to determine how well the BDI-II identifies depression using the SCID-IV as the criterion standard for diagnosing depression, defined here as a diagnosis of major depressive disorder. Results indicated a cutoff score of at least 19 if one has a mild TBI or at least 35 if one has a moderate or severe TBI. These scores maximize sensitivity (87%) and specificity (79%).

Conclusions

Clinicians working with persons with TBI can use the BDI-II to determine whether depressive symptoms warrant further assessment.     

Rasch Analysis of the Community Integration Measure in Persons With Traumatic Brain Injury

Objective

To examine the measurement properties of the Community Integration Measure (CIM) in persons with traumatic brain injury (TBI).

Design

Rasch analysis was used to retrospectively evaluate the CIM.

Setting

Rehabilitation hospital.

Participants

Persons (N=279) 1 to 15 years after a TBI.

Interventions

None.

Main Outcome Measure

CIM.

Results

The CIM met Rasch expectations of unidimensionality and reliability (person separation ratio=2.01, item separation ratio=4.52). However, item endorsibility was poorly targeted to the participants' level of community integration. A ceiling effect was found with this sample.

Conclusions

The CIM is a relatively reliable and unidimensional scale. Future iterations might benefit from the addition of items that are more difficult to endorse (ie, improved targeting).