Normativebeliefs refer to beliefs of an individual that are accepted by specific people or groups and dictate whether behaving in a particular fashion is appropriate . Fishbein and Ajzen [6,14] propose the theory of reasoned action and first used the term “normative belief” as antecedent variables of norms. Bicchieri  also states that “Only the joint presence of a conditional preference for conformity and the belief that other people will conform will produce an agreement between normativebeliefs and behavior”. Ajzen  discusses behavioral, normative, and control beliefs in the theory of planned behavior, which are antecedent variables of attitudes, subjective norm, and perceived behavioral control respectively. The value–belief–norm theory and other empirical studies [17,26] have revealed that beliefs, and norms are related through a continuous process of causality. In addition, these empirical studies also indicate that normativebeliefs affect subjective norms, attitudes, and behavioral intentions . Ajzen and Fishbein  (p. 2) explain that “While a social norm is usually meant to refer to a rather broad range of permissible, but not necessarily required behaviors, normative belief refers to a specific behavioral act the performance of which is expected or desired under the given circumstances”. In examining the relationships between social norms and behaviors, Lapinski and Rimal  conclude that findings of the effects of social norms (which include subjective norms, injunctive norms, and descriptive norms) on behavior are mixed in normative influences. They confirmed that norms are also “dynamic phenomena and individuals, acting on either self-interest or altruistic motives, continuously alter the normative contours” in beliefs . Thus, the following hypotheses are formulated to be investigated in this study.
For each of the health behaviors, the focus outcome measure was intention to feed one’s child healthy foods in the behavioral scenario depicted (i.e. playdate at the parent’s house) and intention to protect one’s child from (the effects of excessive) exposure to the sun in the sun protection condition. The intentions measure incorporated the randomized observability manipulation – with respondents being asked whether or not they would engage in the target behavior either when they were observed by other parents or when they were not told they were being observed (in the case of sun protection) or when being observed was not mentioned (in the case of obesity.) Message type was randomized with respondents being exposed to a message that either emphasized normative justifications or personal benefit justifications for a specific child protective behavior or they were exposed to no relevant messages on the topic. Other measures include attitudes,
The constructs of TRA (i.e. behavioral beliefs, outcome evaluation, normativebeliefs, motivation to comply, behav- ioral intention, and dietary behaviors) were used to develop an item pool; the recommendations of questionnaire con- struction based on TRA as stated by Fishbein were consid- ered for developing the statements. The pool was developed in six dimensions through doing a literature re- view  and seeking the comments of a panel of three health education specialists, two nutritionists, one nurse, and one biostatistician. The items were worded carefully in order to minimize ambiguities and enhance readability. In total, the item pool comprised 78 items on perceptual factors affecting diabetic men’s dietary behaviors. The items of the “Dietary behaviors” dimension were scored from 1 (“Almost Never”) to 5 (“Almost always”) while the other items were scored on a five-point Likert-type scale as follows: 1: “Strongly agreed”; 2: “Agreed”; 3: “No opinion”; 4: “Disagreed”; and 5: “Strongly disagreed”. Higher scores on the inventory reflected more positive behavioral beliefs and higher likelihood to show healthy dietary behaviors. Some items had been worded negatively and thus, were scored reversely.
We investigated whether belief-based differences exist between students who have strong and weak in- tentions to integrate complementary and alternative therapy (CAT) into future psychology practice by recommending CAT or specific CAT practitioners to clients. A cross-sectional methodology was used. Psychology undergraduate students (N = 106) participated in a paper-based questionnaire design to ex- plore their underlying beliefs related to CAT integration. The study was undertaken at a major university in Queensland, Australia. The theory of planned behaviour belief-based framework guided the study. Multivariate analyses of variance examined the influence of behavioural, normative, and control beliefs on the strong and weak intention groups. A multiple regression analysis investigated the relative impor- tance of these belief sets for predicting intentions. We found that clear differences emerged between strong and weak intenders on behavioural and normativebeliefs, but not control beliefs. Strong intenders perceived the positive outcomes of integrating CAT, such as being able to offer clients a more holistic practice and having confidence in the practitioners/practices, as more likely to occur than weak intenders, and perceived the negative outcome of compromising my professional practice as less likely. Strong in- tenders were more likely than weak intenders to perceive that a range of important referents (e.g., clients) would think they should integrate CAT. Results of the regression analysis revealed the same pattern of results in that behavioural and normativebeliefs, but not control beliefs, significantly predicted intentions. The findings from this study can be used to inform policy and educational initiatives that aim to encour- age CAT use in psychology practice.
The target behaviour was defined as ‘taking part in dance in school as an extra-curricular activity within the next two weeks’. Instrumental and affective outcome beliefs were elicited with a request to list the ‘advantages’ and ‘disadvantages’ and the ‘things you would like’ and ‘things you would dislike’ respectively. Normativebeliefs were elicited by asking for ‘people or groups of people’ who would ‘approve’ and ‘disapprove’ respectively. Control beliefs were elicited by asking for personal or situational circumstances that would ‘make it easy’ and ‘make it hard’ to participate. The order in which the questions were presented remained the same throughout as previous research suggests that responses are not influenced by question order . Instrumental outcome beliefs were elicited first followed by affective outcome beliefs, normativebeliefs, and finally control beliefs.
The Theory of Planned Behaviour (TPB; ) is a well- validated decision-making model that has been applied to hand hygiene in hospital and other contexts [6-11]. The TPB proposes that the best determinant of behav- iour is intention which is influenced by three factors: at- titude, subjective norm, and perceived behavioural control. Attitude refers to positive or negative evalua- tions of the behaviour (e.g., performing hand hygiene is good); subjective norm refers to perceptions of pressure from others to perform the behaviour (e.g., important others would want me to perform hand hygiene); and perceived behavioural control refers to perceptions of the ease or difficulty of performing the behaviour of interest (e.g., it would be easy for me to perform hand hygiene). Perceptions of control are also considered to directly influence behaviour. The TPB’s belief base pro- poses that attitudes are determined from the individual’s beliefs about the advantages/disadvantages of performing the behaviour (behavioural beliefs; e.g., performing hand hygiene will result in a reduction of the spread of infec- tions). Subjective norms are determined by a person’s beliefs about whether important referents approve/disap- prove of them performing the behaviour (normativebeliefs; e.g., other nurses would approve of me perform- ing hand hygiene). Perceived behavioural control is based on the individual’s beliefs about whether internal
Most social scientists agree that individual behavior is motivated in large part by “social” factors, such as the desire for prestige, esteem, popularity, or acceptance. Normativebeliefs constitute the underlying determinants of the subjective norms and are concerned with the likelihood that important referent individuals or groups would approve or disapprove of performing the behavior. Burnkrant and Cousineau (1975) defined normative influence as the tendency to conform to the expectations of others. Generally speaking, people who believe that most referents with whom they are motivated to comply think they should perform the behavior will perceive social pressure to do so; conversely, people who believe that most referents with whom they are motivated to comply would disapprove of their performing the behavior will have a subjective norm that puts pressure on them to avoid performing the behavior (Ajzen, 1991). Therefore, peer communication is conceptualized as encouragement or approval of certain behaviors and intentions through either spoken (reinforcement) or unspoken (modeling) messages that peers send to each other.
“Opt-out” referral pathways aim to improve cessation outcomes. SSS staff indicated that some of the women referred via the pathway were ready to make positive changes and appreciated the encouragement. An outcome evaluation of the pathway showed that the numbers of women setting quit dates with the services and reporting short term abstinence doubled in the period after implementation, compared to the time-matched comparison period . Conversely, many women contacted by the SSS staff were not ready to make changes to their smoking behaviors at the time. By having increased contact with the latter group, the SSS felt they could influence attitudes and behavior by educating and raising their awareness about smoking cessation support in hard-to-reach communities. Informing women from these communities about the dangers of smoking in pregnancy may, in the long term, help challenge community normativebeliefs about the safety and acceptability of smoking in pregnancy. This could in turn lead to more women considering quitting in current or subsequent pregnancies. Providing information about the SSS support available could also increase self-referrals to SSS for professional support.
This empirical research aims at determining to what degree differences in sex account for the acceptance of the artificial pancreas (AP). The focus of this paper is put on the communication strategy the Dutch organization Inreda Diabetic B.V. targets to enhance to market their product to diabetes type 1 patients. Results are generated on the basis of existing scientific literature and through the creation of a website survey by the usage of ‘Lime Survey’, forwarded to 601 Inreda Diabetic B.V. patient contacts of which 413 responses were collected. On the basis of 395 valid replies the impact of the five independent variables; perceived usefulness, compatibility, complexity, normativebeliefs and motivation to comply, on acceptance were measured by using the statistical analysis program SPSS. Acceptance was operationalized by intention to use, which is the willingness of patients to use the AP. This paper reveals that there are slight differences existing between sex and male and female’s degree of acceptance. Usefulness is of higher importance for women, whereas normativebeliefs is of greater influence for men, complexity and motivation to comply are both insignificant regardless sex and compatibility impinges on men and women’s intention to use by a moderate degree. Inreda Diabetic B.V. is advised to use the gained information as a rough outline of which factors may be necessary to be taken into account when pursuing their marketing and communication strategy and gives a first insight on the impact of sex and male and female’s likeliness to accept the AP. Nevertheless, the outcomes may be different if other factors such as age, culture, race or trialability and observability were included.
think are the advantages of [target behaviour]?") and disadvantages ("What do you think are the disadvantages of [target behaviour]?"). For normativebeliefs participants reported who would approve ("Who are the people/groups of people important to you who would approve of you [target behaviour]?") and disapprove ("Who are the people/groups of people important to you who would disapprove of you [target behaviour]?"). For control beliefs, participants listed factors which might encourage ("List any factors or circumstances that might help or encourage you to [target behaviour]) and prevent ("List any factors or circumstances that might prevent or discourage you from [target behaviour].") them from engaging in sun- protective behaviours.
Table 4 reports the descriptive statistics (means and stand- ard deviations) of the theoretical variables. Normality of distribution and possible collinearity were assessed and results were satisfactory (see the research report for detailed results ). The mean value of the intention to use HTA recommendations is not markedly different between groups. However, all theoretical variables have a higher mean among ophthalmologists. The majority of theoretical variables have a mean value higher than 3, which corresponds to a positive value. One exception is the variable habit that has a negative value (lower than 3) in both groups. Moreover, personal and social normativebeliefs have a negative value among orthopaedic sur- geons. These findings indicate that there might be signifi- cant differences between the two groups of specialists. Differences in intention to use HTA recommendations between specialties
Our study is not without limitations. First of all, we relied on self-report to assess normativebeliefs and behaviors and as a result, our measures may be affected by inaccurate reporting as well as recall bias and social desirability bias. Additionally, while all of the normativebeliefs and several behaviors were assessed continuously, several behaviors were dichotomous in nature, thus the ICC estimates obtained are on a logistic scale and not directly comparable. It is also important to note that our data come from men nested within camp-based peer networks in Dar es Salaam, and as such, may not be generalizable to other social networks of youth in urban sub-Saharan African settings. We also excluded camps that were the most unsafe and recognize that these camps may have contributed data that could have shaped the results presented. Specifically, since men in more violent camps may have been more likely to engage in other risky behaviors, excluding these camps likely decreased the variability of norms and behaviors reported, leading to conservative estimates of the clustering across the networks. Also, while we made multiple attempts to contact and enroll all members of these camp-based networks, we were only able to obtain behavioral and social network data from an average of 78.1% of network members. While over a quarter of our networks had response rates over 90%, only 2 networks provided complete data and the low response rate in some camps is not ideal for studies using sociocentric network properties. Missing data is important to studies of social networks (Kossinets, 2006) and may have shaped the structural properties of the networks described in this study. Future studies examining effects of network structure may need to be restricted to networks with greater than 50% response rate, as has been done in previous studies (McFarland, Moody, Diehl, Smith, & Thomas, 2014), and may need to consider the best methods to impute missing network ties (Huisman, 2009). Fortunately, by having each participant identify all individuals known to him/her in their camp network, and not limiting participants to identifying up to a fixed number of friends, our data are not biased by the fixed choice effect (Kossinets, 2006). Moreover, we are not able to separate social selection from social influence in understanding why normativebeliefs and behaviors may be clustering within peer networks.
The belief based analyses above were also conducted to determine if there were any differences in beliefs according to the demographic characteristics of age (younger participants, aged 12 to 16 years versus older participants, aged 17 to 20 years), gender (male versus female) and location (metropolitan versus regional). The results for behavioural beliefs were identical to those reported above. For normativebeliefs, the only variation to those results reported above was for older participants whereby sun-protectors were more likely than non sun-protectors to believe that their friends (rather than family) would think they should perform sun protective behaviours. For control beliefs, both younger and regional sun-protectors were significantly more likely than non sun-protectors to report that all of the listed motivating factors would help them to perform sun safety. In addition, older sun-protectors were more likely than non sun-protectors to rate only one motivating factor (user-friendly sunscreen) as helpful in the performance of sun safety behaviours. Older sun-protectors rated a range of additional barriers to performing sun safety (including sun protection being unavailable and too expensive) than non sun-protectors. Predicting Sun Protective Behaviour
The questionnaire was formatted as a paper based sur- vey and was divided into five sections. The first part was about socio-demographic characteristics of the students. This covered age, gender, family residential status like urban and rural background, year of study, family income status, family business, past entrepreneurship experi- ence. The second part evaluates the behavioural belief of the students about pharmacy ownership. The third part includes statements on the control beliefs of students about pharmacy ownership. The fourth part assessed the normativebeliefs of study participants’ students about pharmacy ownership. The fifth part of the questionnaire assessed the intent of entrepreneurship among partici- pants. The total survey items comprised of 26 questions, eight questions related to demography of the respond- ents, six questions related to behavioural belief, seven questions related to control beliefs, four questions were related normativebeliefs and one question about intent of entrepreneurship among study respondents.
The interview responses provided a detailed source of information about behavioral beliefs, normativebeliefs and control beliefs. Constant comparative approach analysis identi ied familiar verbatim transcripts on salient consequences (advantages/disadvantages), social referents (approval/disapproval) and circumstances (facilitator/barrier).
outcome expectancy [29-32], self-efficacy [30,33], social support [29,30], enjoyment of physical activity [29,30], social influences , that were developed in the frame- work of other health belief models. There was one more questionnaire, developed by Blue et al., assesses the indirect measures of the theory of planned behavior including behavioral beliefs, normativebeliefs and con- trol beliefs to predict physical activity intentions of per- sons at risk for diabetes . No questionnaire was found in the context of direct measures of the Theory of Planned Behavior. The main objective of this study was to design and develop an instrument in such a fra- mework. However, this study included an additional construct (self-identity) to the original theory. As Ajzen suggests the Theory of Planned Behavior is open for further extension with additional constructs . Studies have shown that individuals who identify themselves as exercisers have more favorable intentions and engage significantly more in exercise than those who do not [36-38]. It is argued that self-identity may play an important role in predicting physical activity [36-38]. Furthermore, this study was limited to a sample of female diabetic patients. It is estimated that more than 1.5 million people with diabetes live in Iran. The preli- minary results derived from a national study indicated that the prevalence of type 2 diabetes was 3.6% among adults aged over 30 (4.3% of women and 2.6% of men) . The figures clearly indicate that, as many other countries, women in Iran are suffering more from dia- betes. In addition, the existing data from Iran indicate that prevalence of sedentary lifestyle in females is higher than males [40-42]. Sarrafzadegan et al. found that abdominal obesity was nearly six times as prevalent in women as in men (71.7% vs. 12%, P < 0.05) .