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Watson S, Trudelle-Jackson E, Weber M, Brizzolara K. Predictors of treatment adherence in patients with centralized low back pain. J Back Musculoskelet Rehabil 2025:10538127251332211. [PMID: 40239177 DOI: 10.1177/10538127251332211] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 04/18/2025]
Abstract
BackgroundTreatment adherence is central to treatment success in rehabilitation for musculoskeletal conditions, including low back pain (LBP). Unfortunately, non-adherence to prescribed treatment is common and undermines treatment success.ObjectiveTo identify predictors of treatment adherence in physical therapy for patients with LBP.Methods209 cases of patients receiving physical therapy for a chief complaint of centralized LBP were retrospectively analyzed for predictors of treatment adherence. Symptom duration, pain intensity, level of disability, the presence of an opioid prescription, and patient cost were assessed as predictors of treatment adherence. Patients who completed their prescribed plan of care were classified as adherent.ResultsLogistic regression analysis revealed that individuals who had an opioid prescription were 2.56 (95% CI = 1.25-5.24, p = 0.010) times less likely to be adherent with treatment compared to individuals without an opioid prescription. Individuals who had symptoms for less than 1 month were 3.21 (95% CI = 1.12-9.24, p = 0.030) times less likely to be adherent with treatment compared to individuals who had experienced symptoms for 4 months to 1 year. Finally, individuals who paid greater than $40 per visit were 3.45 (95% CI = 1.31-9.09, p = 0.011) times less likely to be adherent with treatment compared to individuals who did not have to pay each visit.ConclusionThe results of this study may help clinicians quickly identify and address risk factors for lower treatment adherence in patients with LBP to mitigate the impact of suboptimal treatment adherence on patient outcomes.
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Affiliation(s)
- Seth Watson
- Lott Physical Therapy, Corsicana, TX, USA
- Texas Woman's University, Dallas, TX, USA
| | | | - Mark Weber
- Texas Woman's University, Dallas, TX, USA
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Chen Y, Ju P, Xia Q, Cheng P, Gao J, Zhang L, Gao H, Cheng X, Yu T, Yan J, Wang Q, Zhu C, Zhang X. Potential Role of Pain Catastrophic Thinking in Comorbidity Patients of Depression and Chronic Pain. Front Psychiatry 2022; 13:839173. [PMID: 35898637 PMCID: PMC9309267 DOI: 10.3389/fpsyt.2022.839173] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/19/2021] [Accepted: 05/11/2022] [Indexed: 11/17/2022] Open
Abstract
BACKGROUND Although comorbidity of major depressive disorder (MDD) and chronic pain (CP) has been well-studied, their association with pain catastrophizing is largely elusive. This study aimed to investigate the potential effects of pain catastrophizing in patients with a comorbidity. METHODS In total, 140 participants were included in this study and divided into three groups according to the Diagnostic and Statistical Manual of Mental Disorders and the International Association for the study of pain (i.e., the comorbidity group: patients with depression with chronic pain, n = 45; depression group: patients with depression without chronic pain, n = 47; and healthy controls: n = 48). The Hamilton Depression Rating Scale (HAMD)-24 and Hamilton Anxiety Rating Scale (HAMA)-14 were used by professional psychiatrists to evaluate the severity of depression and anxiety. Beck Depression Inventory-II (BDI-II) and Beck Anxiety Inventory (BAI) were conducted by patients' self-report to assess the symptom severity. The pain intensity numerical rating scale (PI-NRS) was used to assess the pain intensity. Pain Catastrophizing Scale (PCS) and Pain Anxiety Symptoms Scale (PASS) were used to estimate pain-related negative thinking. RESULTS The results showed that PASS and PCS scores were significantly different among the three groups. Particularly, the scores in the comorbidity group were the highest. The Pearson correlation analysis revealed a positive correlation between PCS (including the patients' helplessness, magnification, rumination, and total scores) and the severity of depression symptoms, anxiety symptoms, and pain intensity (P < 0.05). A stepwise regression analysis further demonstrated that the total PCS score, high monthly income level, and BDI score had positive impacts on PASS (P < 0.05). We also found that the total BDI score, disease course ≥1 year, and pain intensity had positive effects on PCS (P < 0.05), whereas years of education (≤ 12 years) had a negative effect on PCS (P = 0.012). In all, we have clearly demonstrated that PCS and PASS could serve as potentially predictive factors in patients suffering from comorbidity of MDD and CP. CONCLUSION Our results suggested that the pain-related catastrophic thinking and anxiety were more severe in the comorbidity group than in MDD-only group and healthy group. Pain-related catastrophizing thoughts and anxiety may have potentially effects on the comorbidity of depression and chronic pain.
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Affiliation(s)
- Yuanyuan Chen
- Anhui Clinical Research Center for Mental Disorders, Affiliated Psychological Hospital of Anhui Medical University, Hefei, China.,Anhui Clinical Center for Mental and Psychological Diseases, Hefei Fourth People's Hospital, Hefei, China.,Department of Geriatric Psychology, Anhui Mental Health Center, Hefei, China
| | - Peijun Ju
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China.,Shanghai Key Laboratory of Psychotic Disorders, Shanghai, China
| | - Qingrong Xia
- Anhui Clinical Research Center for Mental Disorders, Affiliated Psychological Hospital of Anhui Medical University, Hefei, China.,Anhui Clinical Center for Mental and Psychological Diseases, Hefei Fourth People's Hospital, Hefei, China.,Department of Geriatric Psychology, Anhui Mental Health Center, Hefei, China
| | - Peng Cheng
- Anhui Clinical Research Center for Mental Disorders, Affiliated Psychological Hospital of Anhui Medical University, Hefei, China.,Anhui Clinical Center for Mental and Psychological Diseases, Hefei Fourth People's Hospital, Hefei, China.,Department of Geriatric Psychology, Anhui Mental Health Center, Hefei, China
| | - Jianliang Gao
- Anhui Clinical Research Center for Mental Disorders, Affiliated Psychological Hospital of Anhui Medical University, Hefei, China.,Anhui Clinical Center for Mental and Psychological Diseases, Hefei Fourth People's Hospital, Hefei, China.,Department of Geriatric Psychology, Anhui Mental Health Center, Hefei, China
| | - Loufeng Zhang
- Anhui Clinical Research Center for Mental Disorders, Affiliated Psychological Hospital of Anhui Medical University, Hefei, China.,Anhui Clinical Center for Mental and Psychological Diseases, Hefei Fourth People's Hospital, Hefei, China.,Department of Geriatric Psychology, Anhui Mental Health Center, Hefei, China
| | - Hua Gao
- Anhui Clinical Research Center for Mental Disorders, Affiliated Psychological Hospital of Anhui Medical University, Hefei, China.,Anhui Clinical Center for Mental and Psychological Diseases, Hefei Fourth People's Hospital, Hefei, China.,Department of Geriatric Psychology, Anhui Mental Health Center, Hefei, China
| | - Xialong Cheng
- Anhui Clinical Research Center for Mental Disorders, Affiliated Psychological Hospital of Anhui Medical University, Hefei, China.,Anhui Clinical Center for Mental and Psychological Diseases, Hefei Fourth People's Hospital, Hefei, China.,Department of Geriatric Psychology, Anhui Mental Health Center, Hefei, China
| | - Tao Yu
- Anhui Clinical Research Center for Mental Disorders, Affiliated Psychological Hospital of Anhui Medical University, Hefei, China.,Anhui Clinical Center for Mental and Psychological Diseases, Hefei Fourth People's Hospital, Hefei, China.,Department of Geriatric Psychology, Anhui Mental Health Center, Hefei, China
| | - Junwei Yan
- Anhui Clinical Research Center for Mental Disorders, Affiliated Psychological Hospital of Anhui Medical University, Hefei, China.,Anhui Clinical Center for Mental and Psychological Diseases, Hefei Fourth People's Hospital, Hefei, China.,Department of Geriatric Psychology, Anhui Mental Health Center, Hefei, China
| | - Qiru Wang
- Minhang Branch, Department of Pharmacy, Fudan University Shanghai Cancer Center, Shanghai, China
| | - Cuizhen Zhu
- Anhui Clinical Research Center for Mental Disorders, Affiliated Psychological Hospital of Anhui Medical University, Hefei, China.,Anhui Clinical Center for Mental and Psychological Diseases, Hefei Fourth People's Hospital, Hefei, China.,Department of Geriatric Psychology, Anhui Mental Health Center, Hefei, China
| | - Xulai Zhang
- Anhui Clinical Research Center for Mental Disorders, Affiliated Psychological Hospital of Anhui Medical University, Hefei, China.,Anhui Clinical Center for Mental and Psychological Diseases, Hefei Fourth People's Hospital, Hefei, China.,Department of Geriatric Psychology, Anhui Mental Health Center, Hefei, China
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Tumenta T, Ugwendum DF, Chobufo MD, Mungu EB, Kogan I, Olupona T. Prevalence and Trends of Opioid Use in Patients With Depression in the United States. Cureus 2021; 13:e15309. [PMID: 34221762 PMCID: PMC8238014 DOI: 10.7759/cureus.15309] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/28/2021] [Indexed: 01/15/2023] Open
Abstract
Background Depression and prescription opioid use have a bi-directional relationship. Depression commonly co-occurs with chronic noncancer pain and is known to be associated with opioid use. Studies have found an increased risk of depression only in patients with opioid dependence. Other studies have found an increased risk of opioid misuse in depressed patients. In addition, chronic pain conditions can lead to depression without the use of opioids. Methods We used the National Health and Nutrition Examination Survey (NHANES) data collected over seven survey cycles spanning 14 years: 2005/2006-2017/2018. Included in our study were participants ≥18 years who completed the patient health (PHQ-9) questionnaire. Persons with documented use of opioids were considered to have chronic use of opioids. Relevant data files were merged, and analytical weights computed in keeping with the survey analytical guidelines. Prevalence measures are reported as proportions. Associations were assessed using the Chi-square test. Binary logistic regression was used to assess the trend in the prevalence of opioid use. We used STATA-16 for data analysis and p-values <0.05 were considered statistically significant. Results A total of 36,459 participants met the inclusion criteria. The prevalence of depression was 7.7% (95% CI: 7.3-8.2). The prevalence of any narcotic use was 6.0%. Among depressed individuals, Blacks: OR 0.71 (95% CI: 0.54-0.93) and Hispanics: OR 0.48 (95% CI: 0.34-0.67) were less likely to be on narcotics compared to non-Hispanic Whites. The prevalence of opioid use was stable over the first 12 years, followed by a significant drop in the last two years. Conclusion Beyond the risk for opioid misuse, and opioid use disorder, depression should also be considered when prescribing opioids. It is therefore important to implement a training to screen for depression in patients receiving opioids for pain management.
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Affiliation(s)
| | - Derek F Ugwendum
- Public Health (Alumni), George Washington University, Washington, USA
| | | | | | - Irina Kogan
- Psychiatry, Interfaith Medical Center, Brooklyn, USA
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