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. Author manuscript; available in PMC: 2022 Oct 29.
Published in final edited form as: J Health Commun. 2019 Oct 30;24(12):865–877. doi: 10.1080/10810730.2019.1680773

Table 3.

Summary of Direct Structural Path Analysis Coefficients of Three Experimental Conditions (AIA, NCI, and FLU; N = 460)

Conditions AIA NCI FLU
Outcome /
  Predictors b (beta) t R 2 b (beta) t R 2 b (beta) t R 2
Attitudes / .42 .34 .29
  Knowledge .19 (.08) 1.08 −.27 (−.08) .23 −.35 (−.12) .22
  Social Sharing .17 (.29)*** 4.17 .22 (.36)*** .04 .20 (.31)*** .05
  Social Norm −.05 (−.07) −1.12 −.17 (−.23)** .05 −.10 (−.12) .06
  Perceived Behavioral Control .16 (.18) 1.74 .21 (.24)* .09 .25 (.26)** .08
  Ease of Use .32 (.35)*** 3.75 .01 (.02) .08 .03 (.03) .08
Perceived Behavioral Control / .66 .62 .35
  Social Sharing .11 (.16)** 3.09 .10 (.14)** .04 .20 (.30)*** .05
  Knowledge −.69 (−.24)*** −4.75 −.81 (−.21)*** .20 −.62 (−.20)** .21
  Ease of Use .66 (.65)*** 12.77 .66 (.65)*** .05 .37 (.35)*** .07
Cues to Action / .24 .28 .24
  Attitudes .15 (.37)*** 4.68 .16 (.41)*** .03 .05 (.12) .03
  Social Sharing .05 (.20)* 2.47 .05 (.20)* .02 .11 (.43)*** .02
  Social Norm −.001 (−.01) −.07 < .001(< .001) .02 −.03 (−.08) .03
Social Sharing / .14 .12 .13
  Social Norm .25 (.22)** 2.92 .11 (.09) .09 .32 (.25)** .10
  Ease of Use .50 (.34)*** 4.52 .49 (.35)*** .11 .50 (.31)*** .12
Intention / .44 .64 .49
  Social Norm −.06 (−.06) −.97 .02 (.02) .06 −.04 (−.04) .07
  Social Sharing .31 (.33)*** 4.60 .25 (.29)*** .05 .42 (.46)*** .07
  Attitudes .45 (.31)*** 3.73 .48 (.33)*** .09 .42 (.28)*** .10
  Cues to Action .76 (.21)** 2.97 1.05 (.28)*** .21 .31 (.09) .24
  Perceived Behavioral Control .02 (.01) .18 .20 (.16)** .07 .09 (.06) .10
Knowledge / .09 .07 .04
  Ease of Use −.11 (−.30)*** −3.98 −.07 (−.26)** .02 −.06 (−.19)* .03

Note:

*

p < .05

**

p < .01

***

p < .001.

Outcome variables are italicized. Standardized coefficients (beta) are provided in parentheses. T-statistics (t) are calculated based on unstandardized coefficients (B). R-squared (R2) value denotes the proportion of the variance for an outcome variable that is explained by all of its predictors in the model. Results exclude a case of missing data.