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Table 1 Potential Predictor Variables Evaluated in 28 Therapy-Specific Logistic Regression Models

From: Complementary and alternative medical therapies for chronic low back pain: What treatments are patients willing to try?

  Dependent Variables for Logistic Regressions
Potential Predictor Variable High Knowledge of Therapy* Prior Use of Therapy* Prior Use of Therapy for Back Pain* High Expectations of Success of Therapy* Likelihood of Trying Therapy at No Cost* Likelihood of Trying Therapy for $10 Co-pay**
Geographic location (Boston vs. Seattle) X X X X X X
Age (65+ vs. < 65) X X X X X X
Gender (female vs. male) X X X X X X
Race (white, non-white) X X X X X X
Education (no college vs. some college) X X X X X X
≥ 5 years since first back pain X     X X
≥ 90 days of LBP in last 6 mo. X     X X
High symptom bothersomeness (7 – 10) on a 0 – 10 scale X     X X
High knowledge of therapy (4 or 5) on a 1 – 5 scale     X X X
Prior use of therapy     X X X
Prior use of therapy for back pain     X X X
High expectations of therapy (7 – 10) on a 0 – 10 scale      X X
Medication usage in past week      X X
Prior harm from therapy      X X
  1. * Separate models were done for each of the five therapies (acupuncture, chiropractic, massage, meditation, t'ai chi) ** Separate models were done for acupuncture, chiropractic, and massage. An X indicates that a particular potential predictor variable was evaluated in a model with the specific dependent variable.