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Table 1

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

Dependent Variables for Logistic Regressions
Potential Predictor VariableHigh 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)XXXXXX
Age (65+ vs. < 65)XXXXXX
Gender (female vs. male)XXXXXX
Race (white, non-white)XXXXXX
Education (no college vs. some college)XXXXXX
≥ 5 years since first back painXXX
≥ 90 days of LBP in last 6 mo.XXX
High symptom bothersomeness (7 – 10) on a 0 – 10 scaleXXX
High knowledge of therapy (4 or 5) on a 1 – 5 scaleXXX
Prior use of therapyXXX
Prior use of therapy for back painXXX
High expectations of therapy (7 – 10) on a 0 – 10 scaleXX
Medication usage in past weekXX
Prior harm from therapyXX
* 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.