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. 2020 May 5;3(2):e157. doi: 10.1002/hsr2.157

TABLE 5.

Association between UP and the participants' self‐management

(n = 528) Regular self‐monitoring of body weight a Wound checking a Regular self‐monitoring of blood sugar a
OR [95% CI] P‐value OR [95% CI] P‐value OR [95% CI] P‐value
Model 1
UO 0.90 [0.56; 1.43] .654 1.48 [0.92; 2.39] .108 1.03 [0.62; 1.69] .913
Self‐view
Average 0.73 [0.48; 1.10] .138 0.77 [0.51; 1.15] .197 0.99 [0.65; 1.53] .976
Positive 1.14 [0.49; 2.75] .759 0.69 [0.29; 1.64] .396 0.81 [0.32; 1.97] .642
Model 2
UO 0.83 [0.45; 1.53] .554 1.59 [0.86; 2.98] .142 1.45 [0.72; 2.93] .304
Self‐view
Average 0.73 [0.47; 1.14] .171 0.70 [0.45; 1.10] .127 0.76 [0.45; 1.27] .296
Positive 1.05 [0.38; 2.96] .920 0.54 [0.19; 1.51] .239 0.32 [0.09; 1.02] .058
Regular self‐monitoring of blood pressure a Keeping a diabetes diary a Having a diet plan a Sum‐score b
OR [95% CI] P‐value OR [95% CI] P‐value OR [95% CI] P‐value β [95% CI] P‐value
Model 1
UO 0.83 [0.52; 1.33] .449 1.53 [0.92; 2.55] .100 1.45 [0.63; 3.27] .372 0.11 [−0.29; 0.51] .583
Self‐view
Average 1.07 [0.71; 1.61] .737 1.03 [0.64; 1.64] .914 0.87 [0.41; 1.85] .714 −0.12 [−0.46; 0.22] .493
Positive 0.97 [0.41; 2.26] .944 0.55 [0.20; 1.46] .246 1.15 [0.28; 4.33] .841 −0.23 [−0.95; 0.48] .522
Model 2
UO 0.97 [0.53; 1.79] .923 1.84 [0.87; 3.89] .11 1.46 [0.50; 4.26] .485 0.27 [−0.19; 0.72] .253
Self‐view
Average 0.93 [0.59; 1.45] .746 0.92 [0.52; 1.62] .763 0.84 [0.37; 1.94] .688 −0.27 [−0.60; 0.07] .120
Positive 0.67 [0.24; 1.86] .450 0.31 [0.08; 1.14] .085 1.09 [0.20; 5.58] .914 −0.67 [−1.43; 0.09] .084

Note: Model 1 included the variables UO and self‐view. Model 2 included UO, self‐view, age, sex, BMI, blood pressure treatment status, systolic blood pressure, smoking status, education, participation in a diabetes education program, treatment with insulin, and history of MI. In the analysis for Table 5, we only included individuals with an average or comparatively high Framingham risk (n = 528).

Abbreviation: UP, unrealistic comparative pessimism.

a

Binary logistic regression analysis.

b

Linear regression analysis.