Preliminary validity and test-retest reliability of two depression questionnaires compared with a diagnostic interview in 99 patients with chronic pain seeking specialist pain treatment

Interpretation of the Patient Health Questionnaire 9 in High-Impact Chronic Pain: Do We Measure Depressive Symptoms the Way We Think?

OBJECTIVES

Depression is prevalent among patients with chronic pain and may impact pain management. An accurate assessment is, however, complicated by overlapping symptoms. This study investigated how patients with high-impact chronic pain interpreted and responded to the Patient Health Questionnaire 9 (PHQ-9) to identify problematic items and causes hereof.

MATERIALS AND METHODS

Cognitive interviews using the Three-Step Test-Interview procedure were conducted during the completion of the PHQ-9 in 33 patients with high-impact chronic pain referred to interdisciplinary treatment. Responses were analyzed using 4 coding categories: (1) "congruent" (response consistent with intention); (2) "incongruent" (response not consistent intention); (3) "ambiguous" (response both congruent and incongruent or insufficient to evaluate congruency); and (4) "confused" (response with confused or misunderstood statements). Next, the content of responses to problematic items was analyzed to identify causes for noncongruency, and encountered response difficulties were identified across all items.

RESULTS

Three items (items 2, 6, and 9) performed as intended (>97% congruent responses), while 7 items (items 1, 3, 4, 5, 7, 8, and 10) were identified as problematic (<50% congruent responses). Problematic items had 1 or more issues: Responses were based on (1) pain-related issues or (2) other (non-pain) factors unrelated to depression, or item structure caused response difficulties due to wordings, reversion, or having 2 questions in 1.

DISCUSSION

Problematic items limit the construct validity of the PHQ-9, leaving an increased risk of inflated depression scores in high-impact chronic pain. Identified problems should guide future revisions to enhance validity and screening accuracy for the benefit of both research and clinical practice.

Depression predicts chronic pain interference in racially diverse, income-disadvantaged patients

BACKGROUND

Chronic pain is one of the most common reasons adults seek medical care in the US, with prevalence estimates ranging from 11% to 40%. Mindfulness meditation has been associated with significant improvements in pain, depression, physical and mental health, sleep, and overall quality of life. Group medical visits are increasingly common and are effective at treating myriad illnesses, including chronic pain. Integrative Medical Group Visits (IMGV) combine mindfulness techniques, evidence based integrative medicine, and medical group visits and can be used as adjuncts to medications, particularly in diverse underserved populations with limited access to non-pharmacological therapies.

OBJECTIVE AND DESIGN

The objective of the present study was to use a blended analytical approach of machine learning and regression analyses to evaluate the potential relationship between depression and chronic pain in data from a randomized clinical trial of IMGV in diverse, income disadvantaged patients suffering from chronic pain and depression.

METHODS

The analytical approach used machine learning to assess the predictive relationship between depression and pain and identify and select key mediators, which were then assessed with regression analyses. It was hypothesized that depression would predict the pain outcomes of average pain, pain severity, and pain interference.

RESULTS

Our analyses identified and characterized a predictive relationship between depression and chronic pain interference. This prediction was mediated by high perceived stress, low pain self-efficacy, and poor sleep quality, potential targets for attenuating the adverse effects of depression on functional outcomes.

CONCLUSIONS

In the context of the associated clinical trial and similar interventions, these insights may inform future treatment optimization, targeting, and application efforts in racialized, income disadvantaged populations, demographics often neglected in studies of chronic pain.

TRIAL REGISTRATION

NCT from clinicaltrials.gov: 02262377.

Socio-Demographics, Pain Characteristics, Quality of Life and Treatment Values Before and After Specialized Interdisciplinary Pain Treatment: Results from the Danish Clinical Pain Registry (PainData)

Background and Aims

PainData is an electronic internet-based clinical pain registry established to improve the understanding and treatment of high-impact chronic pain. The primary aim of this paper is to describe socio-demographics, pain characteristics, quality of life, and treatment values at baseline and follow-up in individuals referred to public and private interdisciplinary pain centers in Denmark between 2018 and 2020.

Methods

Self-reported patient-reported outcomes collected through PainData before (n=12,257) and after (n=4,111) treatment across 13 public and private interdisciplinary specialized pain centers in Denmark (87% of all pain centers in Denmark) are described.

Results

Mean duration of pain was 10 years, and one in three patients reported chronic widespread pain. More than 40% reported opioid use, and 50% had tried four or more different treatment modalities prior to referral. More than 60% reported poor sleep, severe fatigue, and memory and/or concentration deficits. Mean scores on pain catastrophizing, fear of movement, and pain-related disability were high, whereas scores on pain acceptance and self-efficacy were low. Physical and mental health were rated as poor and fair, respectively. One in four patients reported being very much improved or much improved after treatment. Items commonly reported after treatment were increased knowledge about pain, emotions and mood (66.5%), being better at accepting life with chronic pain (63.1%), and improved activity pacing (60.6%).

Conclusion

The PainData registry, containing data from a large cohort of individuals, can help to improve the understanding and treatment of high-impact chronic pain, and collaborations with other researchers are welcome.