## Abstract ## Life satisfaction judgments are thought to reflect people's overall evaluation of the quality of their lives as a whole. Because the circumstances of these lives typically do not change very quickly, life satisfaction judgments should be relatively stable over time. However, some evidence suggests that these judgments can be easily manipulated, which leads to low stability even over very short intervals. The current study uses a unique data set that includes multiple assessments of life satisfaction over both long (up to four years) and short (over the course of a single interview) intervals to assess whether information that is made salient during the course of an interview affects life satisfaction judgments at the end of the interview. Results suggest that this intervening information has only small effects on the final judgment and that placement within an interview has little influence on the judgment that people provide. ## Supplemental Material ## This OSF page provides additional supplemental material that could not be included in the main text. Specifically, we report details of the regression analyses predicting Time 2 DUST life satisfaction from the set of predictor described in the paper, after controlling for Time 1 life satisfaction. The first model is the baseline model predicting Time 2 life satisfaction from Time 1 life satisfaction. The second model adds the predictors. The final model reverses the direction, predicting Time 1 life satisfaction from Time 2 life satisfaction and the predictors. ``` > summary(baselineModel) Call: lm(formula = ls2 ~ ls1, data = final[which(final$selectVar == TRUE), ]) Residuals: Min 1Q Median 3Q Max -5.6870 -0.3216 -0.0043 0.3130 4.4090 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 1.90832 0.13073 14.60 <2e-16 *** ls1 0.68266 0.02142 31.88 <2e-16 *** --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Residual standard error: 0.9108 on 1574 degrees of freedom (11 observations deleted due to missingness) Multiple R-squared: 0.3923, Adjusted R-squared: 0.3919 F-statistic: 1016 on 1 and 1574 DF, p-value: < 2.2e-16 > summary(completeModel) Call: lm(formula = ls2 ~ ls1 + persE + persA + persN + persC + persO + selfefficy + avgspirituality + domainSat + nFriends + famQual + impair + activityLimit + rateMemory + betterMemory + aidMemory + mcode13_1 + mcode13_2 + mcode13_3 + mcode13_4 + mcode13_5 + mcode13_6 + mcode13_7 + mcode13_8 + totpleasant + avghappy + avgcalm + avgfrustrated + avgworried + avgsad + care7 + socialize7 + exercise7 + goout7 + laundry7 + cleanrepair7 + dinner7 + finance7 + shop7, data = final[which(final$selectVar == TRUE), ]) Residuals: Min 1Q Median 3Q Max -4.4155 -0.3535 0.0489 0.4250 4.2607 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 1.294e+00 4.557e-01 2.838 0.004593 ** ls1 4.616e-01 2.433e-02 18.978 < 2e-16 *** persE -2.104e-02 3.596e-02 -0.585 0.558478 persA 6.729e-02 4.648e-02 1.448 0.147917 persN -1.063e-01 3.501e-02 -3.036 0.002441 ** persC -3.666e-02 4.247e-02 -0.863 0.388222 persO -1.932e-02 3.557e-02 -0.543 0.587107 selfefficy 6.570e-02 1.807e-02 3.636 0.000286 *** avgspirituality 8.405e-02 2.672e-02 3.145 0.001693 ** domainSat 1.829e-01 3.344e-02 5.469 5.27e-08 *** nFriends 5.794e-02 2.511e-02 2.308 0.021134 * famQual 1.204e-01 3.669e-02 3.281 0.001059 ** impair -3.197e-02 1.640e-02 -1.950 0.051416 . activityLimit -1.330e-02 2.451e-02 -0.543 0.587327 rateMemory -2.871e-02 2.740e-02 -1.048 0.294772 betterMemory -2.722e-02 5.574e-02 -0.488 0.625424 aidMemory 1.254e-02 2.046e-02 0.613 0.539973 mcode13_1 -1.707e-04 2.219e-04 -0.769 0.441906 mcode13_2 -5.467e-04 2.455e-04 -2.227 0.026095 * mcode13_3 1.449e-04 3.749e-04 0.386 0.699216 mcode13_4 -1.021e-05 2.660e-04 -0.038 0.969399 mcode13_5 -3.133e-04 4.230e-04 -0.741 0.458959 mcode13_6 -2.663e-04 2.246e-04 -1.186 0.235922 mcode13_7 -8.639e-05 3.598e-04 -0.240 0.810281 mcode13_8 2.924e-04 3.494e-04 0.837 0.402719 totpleasant 2.591e-04 9.499e-05 2.728 0.006443 ** avghappy 1.436e-01 2.930e-02 4.901 1.05e-06 *** avgcalm -2.602e-02 2.931e-02 -0.888 0.374743 avgfrustrated 3.140e-02 2.443e-02 1.285 0.198815 avgworried 2.244e-03 3.063e-02 0.073 0.941596 avgsad -6.397e-02 3.050e-02 -2.097 0.036120 * care7 1.202e-02 4.852e-02 0.248 0.804357 socialize7 1.850e-01 6.288e-02 2.942 0.003307 ** exercise7 -4.897e-02 4.766e-02 -1.028 0.304305 goout7 8.731e-03 5.004e-02 0.174 0.861508 laundry7 5.516e-02 5.344e-02 1.032 0.302111 cleanrepair7 -1.369e-02 7.072e-02 -0.194 0.846512 dinner7 7.696e-02 6.011e-02 1.280 0.200627 finance7 -7.558e-02 4.799e-02 -1.575 0.115518 shop7 -9.333e-02 6.467e-02 -1.443 0.149159 --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Residual standard error: 0.832 on 1535 degrees of freedom (12 observations deleted due to missingness) Multiple R-squared: 0.5053, Adjusted R-squared: 0.4927 F-statistic: 40.19 on 39 and 1535 DF, p-value: < 2.2e-16 > summary(completeModelR) Call: lm(formula = ls1 ~ ls2 + persE + persA + persN + persC + persO + selfefficy + avgspirituality + domainSat + nFriends + famQual + impair + activityLimit + rateMemory + betterMemory + aidMemory + mcode13_1 + mcode13_2 + mcode13_3 + mcode13_4 + mcode13_5 + mcode13_6 + mcode13_7 + mcode13_8 + totpleasant + avghappy + avgcalm + avgfrustrated + avgworried + avgsad + care7 + socialize7 + exercise7 + goout7 + laundry7 + cleanrepair7 + dinner7 + finance7 + shop7, data = final[which(final$selectVar == TRUE), ]) Residuals: Min 1Q Median 3Q Max -5.4834 -0.3653 0.0864 0.4587 3.9686 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 1.682e+00 4.293e-01 3.918 9.33e-05 *** ls2 4.117e-01 2.169e-02 18.978 < 2e-16 *** persE 8.897e-02 3.388e-02 2.626 0.00873 ** persA -2.678e-02 4.392e-02 -0.610 0.54213 persN -6.574e-02 3.311e-02 -1.985 0.04728 * persC -7.772e-02 4.007e-02 -1.940 0.05259 . persO -5.199e-02 3.356e-02 -1.549 0.12158 selfefficy 2.624e-02 1.713e-02 1.532 0.12564 avgspirituality -6.084e-03 2.532e-02 -0.240 0.81012 domainSat 3.677e-01 3.047e-02 12.065 < 2e-16 *** nFriends -2.441e-02 2.374e-02 -1.028 0.30400 famQual -1.937e-02 3.476e-02 -0.557 0.57746 impair -3.665e-03 1.550e-02 -0.236 0.81319 activityLimit 3.813e-02 2.312e-02 1.649 0.09938 . rateMemory 1.575e-02 2.588e-02 0.609 0.54289 betterMemory 4.466e-02 5.263e-02 0.849 0.39625 aidMemory -1.526e-02 1.932e-02 -0.790 0.42985 mcode13_1 -5.406e-05 2.095e-04 -0.258 0.79646 mcode13_2 -2.589e-04 2.321e-04 -1.115 0.26484 mcode13_3 -7.880e-05 3.541e-04 -0.223 0.82392 mcode13_4 5.621e-06 2.512e-04 0.022 0.98215 mcode13_5 -6.116e-04 3.992e-04 -1.532 0.12571 mcode13_6 8.322e-05 2.122e-04 0.392 0.69496 mcode13_7 -4.842e-04 3.395e-04 -1.426 0.15409 mcode13_8 2.882e-04 3.299e-04 0.874 0.38252 totpleasant -3.936e-05 8.991e-05 -0.438 0.66160 avghappy 1.084e-01 2.775e-02 3.906 9.78e-05 *** avgcalm 3.189e-02 2.767e-02 1.152 0.24931 avgfrustrated -1.271e-02 2.308e-02 -0.551 0.58190 avgworried -1.835e-03 2.892e-02 -0.063 0.94941 avgsad 1.945e-02 2.884e-02 0.674 0.50024 care7 -5.768e-02 4.579e-02 -1.260 0.20799 socialize7 -8.476e-02 5.950e-02 -1.424 0.15453 exercise7 3.977e-02 4.501e-02 0.884 0.37706 goout7 2.945e-02 4.725e-02 0.623 0.53320 laundry7 6.563e-02 5.045e-02 1.301 0.19347 cleanrepair7 -3.855e-02 6.678e-02 -0.577 0.56385 dinner7 -3.225e-02 5.679e-02 -0.568 0.57017 finance7 3.472e-02 4.535e-02 0.766 0.44399 shop7 5.738e-02 6.109e-02 0.939 0.34771 --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Residual standard error: 0.7857 on 1535 degrees of freedom (12 observations deleted due to missingness) Multiple R-squared: 0.4759, Adjusted R-squared: 0.4625 F-statistic: 35.73 on 39 and 1535 DF, p-value: < 2.2e-16 > ```