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A Cross-Sectional Study of Biopsychosocial Factors Associated with Utilization of Osteopathic Manipulative Treatment Among US Adults

Journal: Journal of Osteopathic Medicine Date: 2025/12, 125(12):Pages: A760–761. doi: Subito , type of study: cross sectional study

Full text    (https://www.degruyterbrill.com/document/doi/10.1515/jom-2025-2000/html)

Keywords:

biopsychosocial factors [2]
cross sectional study [863]
demographics [22]
OMT [3779]
osteopathic manipulative treatment [3799]
patients [157]
USA [1707]
utilization [24]

Abstract:

Context: Osteopathic manipulative treatment (OMT) is a manual intervention used in osteopathic medicine to treat somatic dysfunction[1,2]. While commonly associated with musculoskeletal conditions such as low back pain, neck pain, and sports injuries[3-5], OMT has broader therapeutic applications, including support for systemic and chronic health issues through its effects on structural alignment, circulation, autonomic tone, and patient perception[6-8]. Although a growing body of evidence supports its clinical efficacy—particularly in randomized controlled trials and systematic reviews—OMT remains significantly underutilized. One survey from 2018 found 77.74% of osteopathic physicians use OMT on less than 5% of their patients, and 57% of osteopathic physicians did not use OMT at all[9]. Furthermore, sparse data exists to estimate use of OMT individually, as it is commonly grouped with chiropractic care in most national surveys. The 2012 NHIS data showed that 8.5% of US adults had used either chiropractic or osteopathic manipulation in the previous 12 months[10]. However, a secondary analysis on the same subset of respondents showed that of the 8.5% that used manipulation therapy, 97.6% used chiropractic[11]. This would put use of OMT at 0.2% of the US adult population[10,11]. This is far fewer than the population likely to benefit, as approximately 20% of the US adult population has conditions that OMT has been associated with effective symptom relief [3-5, 12-14]. This gap between evidence and real-world uptake suggests barriers in awareness, referral patterns, and access. Understanding the demographic, clinical, and psychological correlates of OMT utilization is essential to inform targeted outreach, improve referral practices, and support the broader integration of OMT into patient-centered care models. Objective: To identify demographic, clinical, and psychological characteristics associated with the use of OMT among U.S. adults using a biopsychosocial framework, with the goal of informing population outreach, access strategies, and clinical integration. Methods: A cross-sectional analysis was conducted using data from a nationally representative survey of 3,022 U.S. adults collected in August 2024. The sample was quota-matched to reflect U.S. distributions by age, sex, race/ethnicity, and geography. Participants with incomplete data were excluded. The Thought Impact Scale (TIS) was collapsed into quartiles, and Pearson Chi-square tests were used to evaluate associations between OMT use and demographic, medical, and TIS variables. For continuous psychometric measures, Levene’s test was used to assess variance equality, followed by either independent samples t-tests or Welch’s t-tests as appropriate. Unadjusted logistic regressions were performed for each variable, followed by a multivariate logistic regression model containing all demographic predictors. Models were then done with each non-demographic variable adjusted for all demographics. Variance inflation factors (VIFs) were calculated to assess multicollinearity. Analyses were performed using Python in Google Colab, with pandas, pyreadstat, numpy, scipy.stats, and statsmodels.api. Statistical significance was set at two-sided p ≤ 0.05.ResultsOf the 3,022 respondents, 102 (3.4%) reported using OMT in the past year. Age and employment status were the strongest demographic predictors. Adults aged 35–49 had significantly higher odds of OMT use compared to those aged 18–34 (adjusted odds ratio [aOR] = 2.07; 95% CI: 1.22–3.51; p < 0.001). Full-time (aOR = 3.40; 95% CI: 1.92–6.03) and part-time employment (aOR = 2.22; 95% CI: 1.13–4.38) were also significantly associated with increased OMT use. No significant differences were found for sex, race/ethnicity, income, education, residence, or insurance status in the adjusted model.Several chronic medical conditions were independently associated with OMT utilization. These included Long COVID-19 (aOR = 4.45; 95% CI: 2.44–8.12), chronic lung disease (aOR = 4.30; 95% CI: 2.27–8.15), fibromyalgia (aOR = 3.52 95% CI: 1.82-6.79), chronic pain (aOR = 3.29 95% CI: 2.17-4.98), stroke (aOR = 3.25; 95% CI: 1.55–6.83), and chronic kidney disease (aOR = 3.14; 95% CI: 1.55–6.35). Other conditions significantly linked to OMT use included hypertension, diabetes, migraines, panic disorder, asthma, rheumatoid arthritis, anxiety, depression, low back pain, and acute COVID-19. Conditions such as cancer, high cholesterol, and heart disease were not significant after adjustment. BMI categories also showed no significant adjusted associations.Psychological traits were strong independent predictors. Higher scores on several Multidimensional Assessment of Interoceptive Awareness (MAIA) subscales—Body Listening (aOR = 1.08; 95% CI: 1.03–1.14), Not Worrying (aOR = 1.08; 95% CI: 1.03–1.13), Self-Regulation (aOR = 1.07; 95% CI: 1.02–1.12), Attention Regulation (aOR = 1.04; 95% CI: 1.01–1.06), and Emotional Awareness (aOR = 1.04; 95% CI: 1.00–1.08)—were all associated with greater odds of OMT use. Additionally, lower scores on the Spiritual Index of Wellbeing subscales Life Scheme (aOR = 0.95; 95% CI: 0.92–0.98) and Self-Efficacy (aOR = 0.91; 95% CI: 0.88–0.94) indicated that OMT users were more likely to report reduced perceived meaning and control over health. Participants in the highest TIS quartile were nearly three times more likely to use OMT compared to those in the lowest quartile (aOR = 2.81; 95% CI: 1.46–5.41; p = 0.001), suggesting a strong relationship between subconscious bodily orientation and treatment-seeking behavior. No significant differences were observed for Big Five personality traits, locus of control, or additional MAIA subscales. Overall, OMT utilization was associated with a distinct profile of middle-aged, employed individuals who have chronic medical conditions and exhibit greater body awareness, emotional sensitivity, and lower perceived control over health outcomes. Conclusion: This study identified multiple demographic, clinical, and psychological predictors of OMT utilization in a nationally representative sample. OMT users were more likely to be employed adults aged 35–49 with chronic or post-viral conditions and specific psychological profiles characterized by interoceptive sensitivity and reduced self-efficacy. These findings can inform referral patterns, provider training, and access initiatives aimed at expanding OMT’s role in patient-centered care. Future longitudinal studies are needed to assess causal pathways, evaluate long-term outcomes, and refine strategies for incorporating OMT into chronic disease management.


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