| Literature DB >> 24901413 |
Lee Ku-Yuan1, Lan Li-Chi2, Wang Jiun-Hao3, Fang Chen-Ling4, Shiao Kun-Sun5.
Abstract
To control the latent social risk of disease, the government usually spreads accurate information and attempts to improve the public's attitude toward adopting prevention. However, these methods with the Knowledge, Attitudes, and Practices (KAP) model do not always work. Therefore, we used the theory of planned behavior (TPB) to understand dog owners' behavior and distinguished the knowledge effect as objective knowledge (OK) and subjective knowledge (SK). A total of 310 dog owners completed a questionnaire based on our model. We employed structural equation modeling to verify the structural relationships and found three main results. First, our model was fit, and each path was significant. People with better attitudes, stronger subjective norms, and more perceptive behavioral control have stronger behavioral intention. Second, perceived behavioral control, not attitude, was the best predictive index in this model. Finally, on perceived behavioral control, subjective knowledge showed more influence than objective knowledge. We successfully extended TPB to explain the behavioral intention of dog owners and presented more workable recommendations. To reduce the latent social risk of disease, the government should not only address dog owners' attitudes, but also their subjective norms and perceptive behavioral control. Indeed, perceptive behavioral control and SK showed the most influence in this model. It is implied that the self-efficacy of dog owners is the most important factor in such a behavior. Therefore, the government should focus on enhancing dog owners' self-efficacy first while devoted to prevention activities.Entities:
Mesh:
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Year: 2014 PMID: 24901413 PMCID: PMC4078556 DOI: 10.3390/ijerph110605934
Source DB: PubMed Journal: Int J Environ Res Public Health ISSN: 1660-4601 Impact factor: 3.390
Figure 1The hypotheses in this study.
The means and standard deviations of the latent variables.
| A | SN | PBC | BI | OK | SK | |
|---|---|---|---|---|---|---|
| M | 4.44 | 4.14 | 4.48 | 4.25 | 6.6 | 3.20 |
| SD | 0.72 | 0.79 | 0.82 | 0.93 | 1.23 | 1.21 |
Reliability and convergent validity.
| Cronbach’s α | AVE | CR | |
|---|---|---|---|
| A | 0.903 | 0.764 | 0.906 |
| SN | 0.839 | 0.639 | 0.841 |
| PBC | 0.940 | 0.843 | 0.942 |
| BI | 0.884 | 0.678 | 0.862 |
| SK | 0.945 | 0.802 | 0.942 |
Discriminant validity.
| A | SN | PBC | BI | SK | |
|---|---|---|---|---|---|
| A | |||||
| SN | 0.462 | ||||
| PBC | 0.397 | 0.303 | |||
| BI | 0.410 | 0.372 | 0.410 | ||
| SK | 0.107 | 0.168 | 0.124 | 0.104 |
The fitness of the model.
| Index | Criteria | Result |
|---|---|---|
| χ2/df | <5 | 1.64 |
| GFI | >0.9 | 0.94 |
| AGFI | >0.8 | 0.91 |
| NFI | >0.9 | 0.98 |
| NNFI | >0.9 | 0.99 |
| CFI | >0.9 | 0.99 |
| IFI | >0.9 | 0.99 |
| RFI | >0.9 | 0.98 |
| PNFI | >0.5 | 0.77 |
| PGFI | >0.5 | 0.65 |
| RMSEA | <0.08 | 0.046 |
| RMR | <0.05 | 0.042 |
| SRMR | <0.05 | 0.032 |
Figure 2The SEM result.