Run MATRIX procedure: 
 
***************** PROCESS Procedure for SPSS Version 4.0 ***************** 
 
          Written by Andrew F. Hayes, Ph.D.       www.afhayes.com 
    Documentation available in Hayes (2022). www.guilford.com/p/hayes3 
 
************************************************************************** 
Model  : 4 
    Y  : SMF 
    X  : OSWB 
   M1  : PC 
   M2  : SC 
   M3  : SD 
 
Sample 
Size:  337 
 
************************************************************************** 
OUTCOME VARIABLE: 
 PC 
 
Model Summary 
          R       R-sq        MSE          F        df1        df2          p 
      .0266      .0007     9.5684      .2364     1.0000   335.0000      .6271 
 
Model 
              coeff         se          t          p       LLCI       ULCI 
constant    20.8434      .9022    23.1036      .0000    19.0688    22.6180 
OSWB         -.0254      .0522     -.4862      .6271     -.1282      .0774 
 
Standardized coefficients 
          coeff 
OSWB     -.0266 
 
Covariance matrix of regression parameter estimates: 
           constant       OSWB 
constant      .8139     -.0463 
OSWB         -.0463      .0027 
 
************************************************************************** 
OUTCOME VARIABLE: 
 SC 
 
Model Summary 
          R       R-sq        MSE          F        df1        df2          p 
      .0036      .0000    26.0004      .0044     1.0000   335.0000      .9472 
 
Model 
              coeff         se          t          p       LLCI       ULCI 
constant    15.4046     1.4872    10.3584      .0000    12.4793    18.3300 
OSWB          .0057      .0861      .0663      .9472     -.1637      .1751 
 
Standardized coefficients 
          coeff 
OSWB      .0036 
 
Covariance matrix of regression parameter estimates: 
           constant       OSWB 
constant     2.2117     -.1258 
OSWB         -.1258      .0074 
 
************************************************************************** 
OUTCOME VARIABLE: 
 SD 
 
Model Summary 
          R       R-sq        MSE          F        df1        df2          p 
      .3193      .1019     4.1846    38.0247     1.0000   335.0000      .0000 
 
Model 
              coeff         se          t          p       LLCI       ULCI 
constant     2.2908      .5966     3.8396      .0001     1.1172     3.4644 
OSWB          .2130      .0345     6.1664      .0000      .1451      .2810 
 
Standardized coefficients 
          coeff 
OSWB      .3193 
 
Covariance matrix of regression parameter estimates: 
           constant       OSWB 
constant      .3560     -.0203 
OSWB         -.0203      .0012 
 
************************************************************************** 
OUTCOME VARIABLE: 
 SMF 
 
Model Summary 
          R       R-sq        MSE          F        df1        df2          p 
      .3893      .1516    11.5205    14.8264     4.0000   332.0000      .0000 
 
Model 
              coeff         se          t          p       LLCI       ULCI 
constant     7.1385     1.6888     4.2271      .0000     3.8165    10.4606 
OSWB         -.2460      .0605    -4.0660      .0001     -.3650     -.1270 
PC            .3264      .0610     5.3471      .0000      .2063      .4465 
SC            .0988      .0367     2.6948      .0074      .0267      .1709 
SD            .3394      .0917     3.7018      .0003      .1591      .5198 
 
Standardized coefficients 
          coeff 
OSWB     -.2170 
PC        .2753 
SC        .1373 
SD        .1997 
 
Covariance matrix of regression parameter estimates: 
           constant       OSWB         PC         SC         SD 
constant     2.8520     -.0503     -.0753     -.0146     -.0341 
OSWB         -.0503      .0037     -.0001      .0000     -.0018 
PC           -.0753     -.0001      .0037     -.0003      .0008 
SC           -.0146      .0000     -.0003      .0013     -.0002 
SD           -.0341     -.0018      .0008     -.0002      .0084 
 
************************** TOTAL EFFECT MODEL **************************** 
OUTCOME VARIABLE: 
 SMF 
 
Model Summary 
          R       R-sq        MSE          F        df1        df2          p 
      .1600      .0256    13.1123     8.8010     1.0000   335.0000      .0032 
 
Model 
              coeff         se          t          p       LLCI       ULCI 
constant    16.2412     1.0561    15.3783      .0000    14.1637    18.3186 
OSWB         -.1814      .0612    -2.9667      .0032     -.3017     -.0611 
 
Standardized coefficients 
          coeff 
OSWB     -.1600 
 
Covariance matrix of regression parameter estimates: 
           constant       OSWB 
constant     1.1154     -.0635 
OSWB         -.0635      .0037 
 
************** TOTAL, DIRECT, AND INDIRECT EFFECTS OF X ON Y ************** 
 
Total effect of X on Y 
     Effect         se          t          p       LLCI       ULCI       c_cs 
     -.1814      .0612    -2.9667      .0032     -.3017     -.0611     -.1600 
 
Direct effect of X on Y 
     Effect         se          t          p       LLCI       ULCI      c'_cs 
     -.2460      .0605    -4.0660      .0001     -.3650     -.1270     -.2170 
 
Indirect effect(s) of X on Y: 
          Effect     BootSE   BootLLCI   BootULCI 
TOTAL      .0646      .0348     -.0008      .1359 
PC        -.0083      .0205     -.0518      .0318 
SC         .0006      .0087     -.0174      .0182 
SD         .0723      .0264      .0258      .1296 
 
Completely standardized indirect effect(s) of X on Y: 
          Effect     BootSE   BootLLCI   BootULCI 
TOTAL      .0570      .0304     -.0007      .1194 
PC        -.0073      .0180     -.0445      .0285 
SC         .0005      .0076     -.0153      .0160 
SD         .0638      .0229      .0231      .1129 
 
*********************** ANALYSIS NOTES AND ERRORS ************************ 
 
Level of confidence for all confidence intervals in output: 
  95.0000 
 
Number of bootstrap samples for percentile bootstrap confidence intervals: 
  5000 
 
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