Mixed In Key Tpb
To understand more about variations in social support across cultures, the current study applies the Theory of Planned Behavior (TPB) to three support provision behaviors of talking about emotions, giving advice, and distracting attention in the U.S. and China. Guided by the TPB, structural models of talking about emotions, giving advice, and distracting attention were built. The study (a) assesses and compares overall fit of the three models for Americans and Chinese, (b) examines how attitudes, subjective norms, and perceived behavioral control together predicted behavioral intentions of the three support provision behaviors for both Americans and Chinese, and (c) compares how Americans and Chinese were similar and different with regard to ratings of the TPB key components (attitudes, subjective norms, perceived behavioral control, and intentions) and strengths of associations between the three predictors (attitudes, subjective norms, and perceived behavioral control) and intentions. 289 American college students and 227 Chinese college students participated in this research. Data were collected from self-reported questionnaires. Data analyses were conducted by employing various techniques, such as structural equation modeling, mix-model ANOVAs, and t-tests. Results indicate that (a) overall the three TPB models fitted almost equally for Americans and Chinese, (b) the TPB demonstrated mixed predictive power for intentions of support provision behaviors, and (c) there were broad similarities regarding ratings of the TPB components and strengths of associations between the three predictors and behavioral intentions between Americans and Chinese. And couched in these broad similarities, there also were some cultural differences with respect to ratings of the TPB components and strengths of associations between the three predictors and intentions between the two cultures. Implications and limitations of the study, as well as directions for future research were discussed by the end of this document.
Mixed In Key Tpb
The stronger models, TTM and SCT, were weight management-related and both included self-efficacy. We found few studies that have analyzed change in self-efficacy as a predictor, but they have generally confirmed the present findings (i.e., greater improvements leading to greater weight losses) [19, 64]. In the present study, we used a slightly different change variables than in previous research (i.e., residuals as opposed to pre-post subtraction), but found similar results, indicating that self-efficacy improvement predicts weight change independently of its baseline scores. The consistency of these results can be explained by self-efficacy theory itself, since efficacy beliefs are presented as a function of enactive mastery experiences, vicarious learning, verbal persuasion, and physiological and emotional activation . It could be hypothesized that, as participants were losing weight, they improved their self-efficacy towards weight loss behaviors, by means of enhanced mastery experiences and possibly positive emotional activation from being able to getting closer to their goals. Another factor that could have contributed to the changes in self-efficacy was verbal persuasion by the intervention team and peers. Jeffery  reviewed the role of theory-based interventions conducted within his work and pointed out self-efficacy as the most important predictor of weight outcomes. US obesity treatment guidelines also reflect the importance of considering self-efficacy on weight loss treatment [65, 66]. Interestingly, baseline self-efficacy values have shown mixed evidence as prospective predictors of weight loss , raising the question of reciprocity between self-efficacy and outcomes; heightened self-efficacy values can be a reflection of weight loss results as much as a predictor of weight loss. This question remains unresolved by the present results.
The sustainable intensification of agriculture and conservation of biodiversity are major challenges that the agricultural sector is currently facing. The diversification of cropping systems has the potential to contribute to sustainable intensification while also preserving biodiversity (Meynard et al. 2018; Rosa-Schleich et al. 2019). One possibility to diversify cropping systems, which has not received much attention by European farmers in the recent past, is the application of mixed cropping systems (e.g., Martin-Guay et al. 2018). One form of mixed cropping, also referred to as intercropping or the cultivation in mixed stands, is the simultaneous cultivation of two or more coexisting main crops in one field (e.g., Gaba et al. 2015). Especially the cultivation of non-legumes and legumes in mixed stands can provide a number of benefits due to the application of basic ecological concepts and the ability of legumes to fixate atmospheric nitrogen (e.g., Bedoussac et al. 2015; Rosa-Schleich et al. 2019) (Fig. 1). Reduced requirements for synthetic fertilizers, improved water use efficiency, and decreased nitrogen leaching are some examples of the advantages associated with mixed stands (e.g., Gaba et al. 2015).
Nevertheless, since the agricultural sector has evolved around pure stands over the past few decades and path dependencies have emerged, changing the production systems towards mixed stands is challenging for farmers (e.g., Bedoussac et al. 2015; Lemken et al. 2017). Learning and opportunity costs arise if farmers change towards mixed cropping, decreasing the potential benefits and reducing the willingness to adopt mixed cropping. In Europe and Germany in particular, crop rotations are largely dominated by cereal crops while grain legumes only play a minor role (e.g., Bedoussac et al. 2015; Hart et al. 2017; Mawois et al. 2019; Meynard et al. 2018). Introducing legumes into the crop rotation, either as a sole crop or in mixed stands, therefore means that most farmers cannot rely on their own know-how since they do not have experience in the cultivation (e.g., Mawois et al. 2019). Furthermore, while it has been shown that mixed stands are efficient in low-input agricultural systems with respect to fertilization (Pelzer et al. 2012), a lack of research about the economic efficiency of mixed stands in high-input agricultural systems persists (e.g., Rosa-Schleich et al. 2019). Extensive operational knowledge that is relevant for the practical implementation by farmers is very limited, e.g., information about crop protection in mixed stands (e.g., Bedoussac et al. 2015). Similar to the case of legume cultivation, which has been described as an innovation niche opposing the dominant cereal crops (Meynard et al. 2018), the adoption of mixed cropping is therefore associated with high uncertainty for farmers and adoption is consequently low (e.g., Lemken et al. 2017).
In addition, until recently the political focus on mixed cropping in Europe and specifically Germany has been very limited, meaning that mixed cropping has had to compete with the established cereal crops in terms of profitability (e.g., Lemken et al. 2017). In Germany, mixed stands of legumes and non-legumes have been included into a nationwide political support scheme with the latest changes to regulations for ecological focus areas under the Common Agricultural Policy for the first time in 2018 (BMEL 2018). Moreover, with the upcoming reform of the Common Agricultural Policy in 2020, further changes can be expected in Germany, as well as the other European countries, increasing uncertainty for farmers and limiting the positive effects of the recent changes on mixed cropping adoption. Including mixed cropping into a subsidy scheme is however a lever to increase adoption by European farmers (e.g., Bedoussac et al. 2015).
In addition to this specified injunctive group norm, it is also possible to consider descriptive norms in the context of the peer group, i.e., what the peer group actually does. A relationship to a farmer who has already adopted a specific practice can lead to the sharing of accurate information about the practice in question (Dessart et al. 2019). Since information about the cultivation of mixed stands is currently very limited, especially with regard to the associated costs and benefits for specific combinations of plant species, this line of reasoning is applicable in our case. We assume that farmers who know other farmers who have already adopted mixed cropping have a higher intention of adopting it as well, and therefore, we have included the following hypothesis:
According to the original TPB framework, two constructs directly influence the actual performance of a certain behavior: the intention to perform the behavior and the perceived behavioral control (Ajzen 1991). The intention accounts for the motivation a person has, while the perceived behavioral control refers to the ability of a person to perform the behavior in question. A person that, ceteris paribus, has a lower intention to perform a certain behavior is less likely to actually perform said behavior, even if that person has the ability to execute it (Ajzen 1991). A higher perceived behavioral control over a certain behavior increases the likelihood of performing such a behavior (Ajzen 1991). This line of reasoning is applicable for the adoption of mixed cropping, especially considering that mixed cropping is a new production method for most farmers. Furthermore, Lemken et al. (2017) find that technical barriers negatively influence the adoption of mixed cropping. Technical barriers can reduce the actual behavioral control. Since perceived behavioral control serves as a proxy for actual behavioral control and is of greater interest when focusing on psychological factors (Ajzen 1991), we assume that the perceived behavioral control is relevant for the actual adoption decision of mixed cropping. Consequently, the following hypotheses are formulated:
Approximately half of the surveyed 172 farmers (50.58%) know a farmer who has already adopted mixed cropping with (at least) two main crops, which serves as the indicator for descriptive group norm in our structural model. A total of 13.37% of the farmers in our sample have currently included mixed stands in their crop rotation. This share is a little higher than the share Lemken et al. (2017) found in their sample of German farmers in 2016, using a similar specification of mixed stands. Only 36.05% of the farmers currently have legumes in pure stands as main crops included in their crop rotation, indicating that legume cultivation itself also faces challenges which is emphasized by Mawois et al. (2019).