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Table 4 Predictors of impact and general health status

From: Impact of comorbidities and treatment burden on general well-being among women’s cancer survivors

Unadjusted predictors Description Effect measureb Global physical health (GPH) Global mental health (GMH) Impact score
Effect estimatea Effect size (ω2) Effect estimatea Effect size(ω2) Effect estimatea Effect size(ω2)
Age (categorical) 29–55,56-63,64-71,72+ |∆max| 3.44 0.00 1.13 0.00 7.37 0.00
Age (continuous) 29–89 β − 0.04 0.00 0.01 0.00 −0.16 0.00
Race White vs Others β 5.54* 0.02 5.49* 0.02 −9.66 0.01
Rurality Urban Residence vs Rural β 1.01 0.00 0.86 0.00 0.74 0.00
Adjusted Predictorsc     ω2partial   ω2partial   ω2partial
Education (categorical) < HS (l), HS-college, Graduate (h) |∆max,adj| 10.82** 0.05 7.52* 0.03 5.51 0.00
Education (ordinal) 1,2,3 βadj 4.12** 0.04 3.49** 0.03 −2.35 0.01
Marital status Married vs Others βadj 3.17 0.01 4.05* 0.03 −7.38 0.02
Employment (categorical) Disabled (l), < Full Time, Full Time (h) |∆max,adj| 7.63 0.01 5.30 0.02 26.20** 0.05
Income (categorical, non-missing) 0-35 K(l),35-75 K,75 + K (h) |∆max,adj| 6.97* 0.03 6.78* 0.03 4.51 -0.01d
Income (ordinal, non-missing) 1,2,3 βadj 3.42* 0.03 3.39* 0.03 − 2.28 0.00
Financial security Comfortable vs Not comfortable βadj 6.55*** 0.06 9.71*** 0.15 −18.0*** 0.10
Health literacy No help needed vs Help needed βadj 1.81 0.00 3.36 0.01 −8.61* 0.02
No. of prior comorbidities (ordinal) 0,1,2,3+ β adj −3.59*** 0.15 −2.35*** 0.08 4.17** 0.04
Cancer type (categorical) Other (l), Endometrial, Breast (h) |∆max| 4.01 0.01 2.90 0.00 2.84 -0.01d
Cancer treatment (categorical) S, RS, CS, RCS, other |∆max,adj| 2.45 −0.018 3.76 0.00 10.48 0.01
Chemotherapy Yes vs No β adj −1.25 0.00 −2.70 0.01 4.87 0.00
Self-management difficulty score
(continuous, non-missing)
1 = Lowest – 5 = Highest β adj −0.88 0.00 −1.51 0.01 11.75*** 0.13
Impact Score (continuous) 0 = Lowest – 100 = Highest β adj −0.25*** 0.28 −0.22*** 0.23 n/a n/a
  1. a * p < .05, ** p < .01, *** p < .001
  2. b|∆max| = maximum mean difference, β, β adj = mean (adjusted) difference using regression weights
  3. cEstimates were adjusted by differing sets of antecedent covariates chosen a priori for each predictor based on salience and non-overlap from the following list: age, race, rurality, education, marital status employment, income financial security, health literacy, number of comorbidities, cancer type, chemotherapy, challenge, and impact (Please see Appendix B for the specific predictor-covariate sets)
  4. d Although the population parameter \( \hat{\omega^2} \)estimates is always positive, the estimate can be negative in situations where predictive power is weak