The effects of social-cognitive variables on preventive nutrition and behavioral intentions were studied in 580 adults at 2 points in time. The authors hypothesized that optimistic self-beliefs operate in 2 phases and made a distinction between action self-efficacy (preintention) and coping self-efficacy (pmtintantion). Risk perceptions, outcome expectancies, and action self-efficacy were specified as predictors of the intention at Wave 1. Behavioral intention and coping serf-efficacy served as mediatcn linking the 3 predictors with low-fat and high-fiber dietary intake 6 months later at Wave 2. Covariance structure analysis yielded a good model fit for the total sample and 6 subsamples created by a median split of 3 moderators: gender, age, and body weight. Parameter estimates differed between samples; the importance of perceived self-efficacy increased with age and weight.Key words: health cognitions, risk appraisals, self-efficacy, outcome expectancies, preventive nutrition, body weightThe Berlin Risk Appraisal and Health Motivation Study (BRAHMS) was designed to examine the social-cognitive determinants of health behaviors, such as physical exercise, smoking, alcohol consumption, and preventive nutrition. In the study reported in this article, our focus is on self-reported nutrition. Eating a healthy diet low in saturated fat and high in fiber is a common medical recommendation. According to current medical knowledge, such nutrition helps reduce the risk of cardiovascular disease and other ailments. However, most people do not adhere to this advice, and many have not even developed an explicit intention to adopt it, Three factors specified by social-cognitive health behavior theodes were considered as possible predictors: (a) risk appraisals, defined as one's perceived vulnerability compared to that of others; Co) behavior-specific outcome expectancies (i.e., expected benefits of preventive nutrition); and (c) self-efficacy befiefs in the face of obstacles and barriers to adopt health behaviors. Moreover, the roles of gender, age, and body weight were examined.Ralf Schwa, Gesundeheitspsychologie, Freie Universitat Berlin, Berlin, Germany; Britta Rennet, Department of Psychology, Emst-MoritzArndt-Universi~t C_neifswald, Griefswald, Germany.This research was supported by the Deutsche Forschungsgemeinsehaft and the Techniker Krankenkasse for Berlin ond Brandenburg. We thank Andr6 Hahn and Thomas yon Lengerke for their collaboration on this project and Barbel Kntiuper, Gerdemarie SchmRz, and Lars Satow for their helpful comments on the first dra~.Correspondence concerning this article should be addressed to Ralf Schwarzer, Gesundheitspsychologie, Freie Universittit Berlin, Habelschwerdter Allee 45, 14195 Berlin, Germany. Electronic mail may be sent to health @ zedat fu-berlin.de. Perceived Self-Efficacy and Preventive NutritionThe construct of self-efficacy represents one core aspect of social-cognitive theory (Bandura, 1997). Whereas outcome expectancies refer to the perception of the possible consequences of o...

a b s t r a c tUnderstanding why people select certain food items in everyday life is crucial for the creation of interventions to promote normal eating and to prevent the development of obesity and eating disorders. The Eating Motivation Survey (TEMS) was developed within a frame of three different studies. In Study 1, a total of 331 motives for eating behavior were generated on the basis of different data sources (previous research, nutritionist interviews, and expert discussions). In Study 2, 1250 respondents were provided with a set of motives from Study 1 and the Eating Motivation Survey was finalized. In Study 3, a sample of 1040 participants filled in the Eating Motivation Survey. Confirmatory factor analysis with fifteen factors for food choice yielded a satisfactory model fit for a full (78 items) and brief survey version (45 items) with RMSEA .048 and .037, 90% CI .047-.049 and .035-.039, respectively. Factor structure was generally invariant across random selected groups, gender, and BMI, which indicates a high stability for the Eating Motivation Survey. On the mean level, however, significant differences in motivation for food choice associated with gender, age, and BMI emerged. Implications of the fifteen distinct motivations to choose foods in everyday life are discussed.

A growing number of people use the Internet to obtain health information, including information about vaccines. Websites that allow and promote interaction among users are an increasingly popular source of health information. Users of such so-called Web 2.0 applications (e.g. social media), while still in the minority, represent a growing proportion of online communicators, including vocal and active anti-vaccination groups as well as public health communicators. In this paper, the authors: define Web 2.0 and examine how it may influence vaccination decisions; discuss how anti-vaccination movements use Web 2.0 as well as the challenges Web 2.0 holds for public health communicators; describe the types of information used in these different settings; introduce the theoretical background that can be used to design effective vaccination communication in a Web 2.0 environment; make recommendations for practice and pose open questions for future research. The authors conclude that, as a result of the Internet and Web 2.0, private and public concerns surrounding vaccinations have the potential to virally spread across the globe in a quick, efficient and vivid manner. Web 2.0 may influence vaccination decisions by delivering information that alters the perceived personal risk of vaccine-preventable diseases or vaccination side-effects. It appears useful for public health officials to put effort into increasing the effectiveness of existing communication by implementing interactive, customized communication. A key step to providing successful public health communication is to identify those who are particularly vulnerable to finding and using unreliable and misleading information. Thus, it appears worthwhile that public health websites strive to be easy to find, easy to use, attractive in its presentation and readily provide the information, support and advice that the searcher is looking for. This holds especially when less knowledgeable individuals are in need of reliable information about vaccination risks and benefits.

Social cognition models of health behavior are commonly understood as being universal, which implies that they are applicable to groups varying in age or cultural background, for example. Cultural uniqueness and characteristics of life-span development, however, necessitate the study of differential effects. Accordingly, the health action process approach (HAPA) was examined in younger and middle-aged/ older adults from South Korea (N ϭ 697) who participated in a longitudinal health screening study with a 6-month time lag. The HAPA model had a good fit within the middle-aged/older adult sample. Physical activity was predicted by planning, coping self-efficacy, and intention, which were, in turn, predicted by action self-efficacy, outcome expectancies, and risk perceptions. Conversely, the results indicated a poor model fit in the younger adult sample. The results suggest a different motivation for the involvement in physical activity as a function of age.

Curiosity refers to the desire for acquiring new information. The aim of this study was to develop a questionnaire to assess social curiosity, that is, interest in how other people think, feel, and behave. The questionnaire was administered to 312 participants. Factor analyses of the 10-item Social Curiosity Scale (SCS) yielded 2 factors: General Social Curiosity and Covert Social Curiosity. Evidence of convergent validity was provided by moderately high correlations of the SCS with other measures of curiosity and self-perceived curiosity, whereas discriminant validity was demonstrated by low correlations of the SCS with other personality traits, such as neuroticism and agreeableness. Of interest, social interaction anxiety was observed to facilitate covert social curiosity while inhibiting general social curiosity.

SummaryA systematic review and meta‐analysis were conducted to assess the effectiveness of app‐based mobile interventions for improving nutrition behaviours and nutrition‐related health outcomes, including obesity indices (eg, body mass index [BMI]) and clinical parameters (eg, blood lipids). Seven databases were searched for studies published between 2006 and 2017. Forty‐one of 10 132 identified records were included, comprising 6348 participants and 373 outcomes with sample sizes ranging from 10 to 833, including 27 randomized controlled trials (RCTs). A beneficial effect of app‐based mobile interventions was identified for improving nutrition behaviours (g = 0.19; CI, 0.06‐0.32, P = .004) and nutrition‐related health outcomes (g = 0.23; CI, 0.11‐0.36, P < .001), including positive effects on obesity indices (g = 0.30; CI, 0.15‐0.45, P < .001), blood pressure (g = 0.21; CI, 0.01‐0.42, P = .043), and blood lipids (g = 0.15; CI, 0.03‐0.28, P = .018). Most interventions were composed of four behaviour change technique (BCT) clusters, namely, “goals/planning,” “feedback/monitoring,” “shaping knowledge,” and “social support.” Moderating effects including study design, type of app (commercial/research app), sample characteristics (clinical/non‐clinical sample), and intervention characteristics were not statistically significant. The inclusion of additional treatment components besides the app or the number or type of BCTs implemented did not moderate the observed effectiveness, which underscores the potential of app‐based mobile interventions for implementing effective and feasible interventions operating at scale for fighting the obesity epidemic in a broad spectrum of the population.

The question of which factors drive human eating and nutrition is a key issue in many branches of science. We describe the creation, evaluation, and updating of an interdisciplinary, interactive, and evolving “framework 2.0” of Determinants Of Nutrition and Eating (DONE). The DONE framework was created by an interdisciplinary workgroup in a multiphase, multimethod process. Modifiability, relationship strength, and population-level effect of the determinants were rated to identify areas of priority for research and interventions. External experts positively evaluated the usefulness, comprehensiveness, and quality of the DONE framework. An approach to continue updating the framework with the help of experts was piloted. The DONE framework can be freely accessed (http://uni-konstanz.de/DONE) and used in a highly flexible manner: determinants can be sorted, filtered and visualized for both very specific research questions as well as more general queries. The dynamic nature of the framework allows it to evolve as experts can continually add new determinants and ratings. We anticipate this framework will be useful for research prioritization and intervention development.

BackgroundAlthough mobile technologies such as smartphone apps are promising means for motivating people to adopt a healthier lifestyle (mHealth apps), previous studies have shown low adoption and continued use rates. Developing the means to address this issue requires further understanding of mHealth app nonusers and adoption processes. This study utilized a stage model approach based on the Precaution Adoption Process Model (PAPM), which proposes that people pass through qualitatively different motivational stages when adopting a behavior.ObjectiveTo establish a better understanding of between-stage transitions during app adoption, this study aimed to investigate the adoption process of nutrition and fitness app usage, and the sociodemographic and behavioral characteristics and decision-making style preferences of people at different adoption stages.MethodsParticipants (N=1236) were recruited onsite within the cohort study Konstanz Life Study. Use of mobile devices and nutrition and fitness apps, 5 behavior adoption stages of using nutrition and fitness apps, preference for intuition and deliberation in eating decision-making (E-PID), healthy eating style, sociodemographic variables, and body mass index (BMI) were assessed.ResultsAnalysis of the 5 behavior adoption stages showed that stage 1 (“unengaged”) was the most prevalent motivational stage for both nutrition and fitness app use, with half of the participants stating that they had never thought about using a nutrition app (52.41%, 533/1017), whereas less than one-third stated they had never thought about using a fitness app (29.25%, 301/1029). “Unengaged” nonusers (stage 1) showed a higher preference for an intuitive decision-making style when making eating decisions, whereas those who were already “acting” (stage 4) showed a greater preference for a deliberative decision-making style (F4,1012=21.83, P<.001). Furthermore, participants differed widely in their readiness to adopt nutrition and fitness apps, ranging from having “decided to” but not yet begun to act (stage 2; nutrition: 6.88%, 70/1017; fitness: 9.23%, 95/1029) to being “disengaged” following previous adoption (stage 5; nutrition: 13.77%, 140/1017; fitness: 15.06%, 155/1029).ConclusionsUsing a behavior stage model approach to describe the process of adopting nutrition and fitness apps revealed motivational stage differences between nonusers (being “unengaged,” having “decided not to act,” having “decided to act,” and being “disengaged”), which might contribute to a better understanding of the process of adopting mHealth apps and thus inform the future development of digital interventions. This study highlights that new user groups might be better reached by apps designed to address a more intuitive decision-making style.