| Literature DB >> 26649307 |
Lijuan Wang1, Lin Wang1.
Abstract
OBJECTIVES: The primary objective of this study was to use the theory of planned behavior (TPB) to examine the association between TPB variables and the moderate-to-vigorous physical activity (MVPA) of children in Shanghai, China. Gender differences were also explored.Entities:
Mesh:
Year: 2015 PMID: 26649307 PMCID: PMC4663291 DOI: 10.1155/2015/536904
Source DB: PubMed Journal: Biomed Res Int Impact factor: 3.411
Intercorrelations and descriptive data for theory planned behavior measures and physical activity behavior (N = 353).
| Variable | Behavior | Intention | Attitude | Subjective norm | M | SD |
|---|---|---|---|---|---|---|
| Behavior | 15.26 | 11.21 | ||||
| Intention | 0.30 | 3.93 | 1.77 | |||
| Attitude | 0.07 | 0.33 | 4.99 | 1.76 | ||
| Subjective norm | 0.06 | 0.19 | 0.17 | 5.21 | 1.82 | |
| PBC | 0.24 | 0.56 | 0.35 | 0.30 | 4.64 | 1.64 |
Note: p < 0.05; p < 0.01; p < 0.001.
Gender differences among MVPA and TPB variables.
| Gender | |||
|---|---|---|---|
| Boys | Girls |
| |
| Duration of MVPA | 16.75 (12.53) | 13.71 (9.43) | 6.59 |
| Behavioral intention | 4.14 (1.84) | 3.72 (1.69) | 4.80 |
| Attitude | 4.99 (1.84) | 4.98 (1.74) | 0.01 |
| Subjective norm | 5.27 (2.63) | 5.15 (1.80) | 0.39 |
| PBC | 4.62 (1.75) | 4.66 (1.52) | 0.04 |
Note: p < 0.05; p < 0.01.
Hierarchical multiple regression analysis predicting behavior.
| Step | Variables |
|
|
|
| SE |
|
|---|---|---|---|---|---|---|---|
| 1 | 0.301 | 0.090 | 0.088 | ||||
| Intention | 1.896 | 0.321 | 0.301 | ||||
|
| |||||||
| 2 | 0.097 | 0.097 | 0.092 | ||||
| Intention | 1.551 | 0.388 | 0.246 | ||||
| PBC | 0.662 | 0.420 | 0.097 | ||||
|
| |||||||
| 3 | 0.316 | 0.100 | 0.089 | ||||
| Intention | 1.622 | 0.394 | 0.257 | ||||
| PBC | 0.784 | 0.442 | 0.115 | ||||
| Attitude | −0.365 | 0.351 | −0.057 | ||||
| Subjective norm | −0.082 | 0.330 | −0.013 | ||||
|
| |||||||
| 4 | 0.334 | 0.112 | 0.099 | ||||
| Intention | 1.495 | 0.396 | 0.237 | ||||
| PBC | 0.874 | 0.441 | 0.128 | ||||
| Attitude | −0.351 | 0.349 | −0.055 | ||||
| Subjective norm | −0.107 | 0.329 | −0.326 | ||||
| Gender | −2.474 | 1.147 | −0.110 | ||||
Note: p < 0.05; p < 0.01; p < 0.001.
Hierarchical multiple regression analysis predicting intention.
| Step | Variables |
|
|
|
| SE | β |
|---|---|---|---|---|---|---|---|
| 1 | 0.581 | 0.337 | 0.331 | ||||
| Attitude | 0.145 | 0.047 | 0.144 | ||||
| Subjective norm | 0.017 | 0.045 | 0.017 | ||||
| PBC | 0.550 | 0.052 | 0.508 | ||||
|
| |||||||
| 2 | 0.593 | 0.352 | 0.344 | ||||
| Attitude | 0.144 | 0.047 | 0.143 | ||||
| Subjective norm | 0.544 | 0.052 | 0.511 | ||||
| PBC | 0.237 | 0.062 | 0.212 | ||||
| Gender | −0.429 | 0.153 | −0.121 | ||||
Note: p < 0.05; p < 0.01; p < 0.001.
Hierarchical multiple regression analysis predicting behavior by gender.
| Step | Variables | Boys | Girls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|
|
|
|
| SE |
|
|
|
| SE |
| ||
| 1 | 0.09 | 0.09 | 0.07 | 0.07 | |||||||
| Intention | 1.70 | 0.39 | 0.31 | 1.84 | 0.49 | 0.27 | |||||
|
| |||||||||||
| 2 | 0.11 | 0.09 | 0.08 | 0.07 | |||||||
| Intention | 1.36 | 0.47 | 0.25 | 1.41 | 0.62 | 0.21 | |||||
| PBC | 0.72 | 0.53 | 0.12 | 0.74 | 0.65 | 0.10 | |||||
|
| |||||||||||
| 3 | 0.12 | 0.10 | 0.08 | 0.06 | |||||||
| Intention | 1.46 | 0.47 | 0.27 | 1.41 | 0.64 | 0.21 | |||||
| PBC | 0.86 | 0.53 | 0.14 | 0.79 | 0.71 | 0.11 | |||||
| Attitude | −0.66 | 0.40 | −0.12 | −0.05 | 0.59 | −0.01 | |||||
| Subjective norm | −0.15 | 0.39 | −0.03 | −0.08 | 0.53 | −0.01 | |||||
Note: p < 0.05; p < 0.01; p < 0.001.
Hierarchical multiple regression analysis predicting intention by gender.
| Step | Variables | Boys | Girls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|
|
|
|
| SE | β |
|
|
| SE | β | ||
| 1 | 0.40 | 0.39 | 0.30 | 0.29 | |||||||
| Attitude | 0.22 | 0.07 | 0.21 | 0.08 | 0.06 | 0.08 | |||||
| Subjective norm | −0.05 | 0.06 | −0.05 | 0.09 | 0.06 | 0.09 | |||||
| PBC | 0.55 | 0.07 | 0.52 | 0.55 | 0.07 | 0.49 | |||||
Note: p < 0.05; p < 0.01; p < 0.001.