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To improve the frequency of adoption of mobile health services (MHSs) by users (consumers), it is critical to understand users' MHS adoption behaviors. However, the literature primarily focuses on MHS adoption-related factors and lacks consideration of the joint impacts of reasons for (RF) and reasons against (RA) on users' attitudes and adoption behaviors regarding MHSs. To fill this gap, this study integrates behavioral reasoning theory (BRT) and protective motivation theory (PMT) to develop a research model by uncovering the reasoning process of personal values, RF and RA, adoption attitudes and behavior toward MHSs. In particular, health consciousness (HC) is selected as the value. Comparative advantage, compatibility and perceived threat severity are considered the RF subconstructs; value barriers, risk barriers and tradition and norm barriers are deemed the RA subconstructs.

A total of 281 responses were collected to examine the model with the partial least squares structural equation modeling (PLS-SEM) method.

The results show that HC positively affects attitude through RA and RF. Additionally, RF partially mediates the relationship between HC and adoption behavior. This study contributes to a deeper understanding of user adoption behavior in MHS and provides practical guidance for the health services industry.

This study contributes to the existing MHS literature by understanding the joint influences of personal values, RF and RA on user attitude, which eventually determines users' adoption decisions regarding MHSs.

The study aims to explore how segmentation as a methodology can be adapted to the healthcare context to provide a more nuanced understanding of the served population and to facilitate the design of patient-centric services.

The study was based on a collaborative project with a national healthcare organization following the principles of action design research. The study describes the quantitative segmentation performed during the project, followed by a qualitative interview study of how segments correspond with patient behaviors in an actual healthcare setting, and service design workshops facilitated by segments. A number of design principles are outlined based on the learnings of the project.

The segmentation approach increased understanding of patient variability within the service provider organization and was considered an effective foundation for modular service design. Patient characteristics and life circumstances were related to specific patterns of health behaviors, such as avoidance or passivity, or a persistent proactivity. These patterns influenced the patients' preferred value co-creation role and what type of support patients sought from the care provider.

The proposed segmentation approach is immediately generalizable to further healthcare contexts and similar services: improved understanding of patients, vulnerable patients in particular, improves the fit and inclusivity of services.

The segmentation approach to service design was demonstrated to be effective in a large-scale context. The approach allows service providers to design service options that improve the fit with individual patients' needs for support and autonomy. The results illuminate how patient characteristics influence health and value co-creation behaviors.

This study aims to examine the recent literature on health-promoting behavior, health needs and associated factors among older adults.

An massive search of five databases involving documents in the past decade was commenced.

This review showed a significant relationship between older adults’ demographic characteristics (marital status, income, chronic disease, education level and smoking status) and health-promoting behaviors. This review showed that older adults with a high level of education, high income, chronic diseases and smoker and married older adults are associated with better health-promoting behaviors.

The result of the current review supports the Pender Health Promotion Model that individual personal characteristics can affect the level of engagement in health-promoting behaviors. Assessing the health-promoting behaviors of older adults can help in identifying their health needs.

This study aims to examine the extent to which anti‐smoking websites use intervention strategies that have been informed by four prominent theories of health‐related behavior change: the health belief model, the theory of reasoned action/theory of planned behavior, the transtheoretical model, and social cognitive theory.

Content analysis was applied to 67 unique and independent anti‐smoking websites to determine their use of 20 intervention strategies based on the four theories.

The findings reveal that anti‐smoking websites used the health belief model the most and social cognitive theory the least. In addition, websites devoted to smoking cessation used these theories more extensively than websites devoted to smoking prevention.

The sample size is somewhat small, which may result in lack of sufficient statistical power. Also, the analysis may have overlooked some important intervention strategies that are particularly effective for smoking intervention programs.

Anti‐smoking website designers should take more advantage of the internet as a health promotion medium and use more intervention strategies that have been informed by scientifically tested theories of behavior change, particularly with respect to affective and behavioral strategies.

This study contributes to current knowledge about which kinds of anti‐smoking messages are available online and how extensively they employ theory‐based intervention strategies.

This study aims to predict the behavior of donors to give to the health sector compared with other sectors in Shiraz city, South Iran, using the revised theory of planned behavior (TPB).

This was a descriptive-analytic cross-sectional study. A standard questionnaire, which comprising 32 items, was used to survey 277 donors affiliated with various charitable associations in the city of Shiraz, South of Iran, in 2018. Participants were selected using stratified sampling and simple random sampling techniques. The authors used a revised TPB, a general model to predict and explain behavior across various types of behaviors and predict behavior based on an individual’s attitudes and beliefs. This model was used to examine the influence of eight social-psychological variables (attitude, perceived behavioral control [PBC], subjective norm, descriptive norm, moral norm, past behavior, intention behavior, self-reported) on an individual’s intention to donate to health sector charity. Data was analyzed using SPSS software version 22.0.

The score of all constructs of TPB in the health sector was significantly higher than in the non-health sector (P < 0.001), except for the PBC. This indicates that it does not influence the donors’ behavioral intention in selecting of charitable activity domains (e.g. health and non-health). The constructs of the moral norm, descriptive norm and past behavior in the health sector donors; and the constructs of attitude, moral norms and the variables of the annual income, and work experience in the non-health sector donors were identified as significant predictors of donors’ intention behavior. Moreover, attitude, moral norm, descriptive norm, past behavior, male gender and the annual income were the significant predictors of donors’ intention to give to health charity initiatives.

One of the most important mechanisms to compensate for the shortage of resources of the health system is the use of donors’ participation capacity. However, different donors act differently in selecting charitable activity domains, including the health sector and non-health sector (e.g. school-building donors’ association, house-building donors’ association, city-building donors’ association, library-building donors’ association, etc.). To attract donors’ participation in the health sector, some interventions to change the behavioral intention of donors towards the health sector through constructs of TPB should be taken.

Although the health information seeking behavior of consumers through the internet has received great attention, limited attempt has been made to integrate both the health information seeking behavior and the usage behavior in a mobile online context. The purpose of this paper is to explore the factors that influence consumer mobile health information seeking (MHIS) and usage behavior based on information quality, perceived value, personal health value, and trust.

A survey was conducted to collect data. A two-step approach of structure equation modeling based was used to test the measurement model and hypothesis model.

Information quality, perceived value, and trust were found to have positive effects on both the intention to seek and to use health information, and that the intention to seek affects the intention to use. Among the three components of perceived value, the utilitarian and epistemic values were found to have significant effects on intention to seek. In addition, the current health status of health consumers moderates the relationships between MHIS and usage intention and their determinants.

Studies have primarily focussed on online health information seeking behavior, whereas a few of these studies have examined the seeking behavior intention and the usage behavior intention in a general model. The results indicate that health information usage behavior intention is closely related to the seeking behavior intention in the mobile context, which enriches the research on the relationship between information seeking and its outcomes. Furthermore, this study highlights the impact of information quality, perceived value, and trust on the intention to seek, and the impacts of information quality and trust on the intention to use, which have been overlooked in previous studies on MHIS.

People spend a lot of time communicating with their co-workers each day; however, research has yet to explore how colleagues influence each other’s health behaviors. The purpose of this paper is to examine the association between health-related communication and health behaviors among co-workers in a workplace wellness program.

Participants (n=169) were recruited from a large south-western university and its local school district through e-mail announcements sent from a wellness administrator. Participants were part of a workplace wellness program that offers several daily group fitness classes, as well as cooking classes, and other educational programs for faculty and staff.

Structural equation modeling was used to examine the association between people’s perceived social influence and social support from co-workers, organizational socialization and their health behaviors. Results indicated that perceived social influence from co-workers had an indirect effect on people’s health behaviors through their perceived social support from their co-workers, as well as through their organizational socialization.

These variables were examined cross-sectionally, meaning that causal relationships and directionality cannot be determined in this study.

Co-worker communication and socialization appear to be important factors in understanding individuals’ health behaviors; thus, organizations that offer workplace wellness programs should provide opportunities for socialization and co-worker communication to facilitate employees’ healthy behaviors.

Although the authors only looked at one wellness program and did not examine these variables in programs of varying sizes and types, this study uniquely incorporates interpersonal and organizational communication perspectives in order to give new insight into co-workers’ health-related communication.

The health belief model (HBM) is the behavioral change theory most widely used in health behavior studies. Several studies have identified the limitations of this model, one of which concerns the validity in predicting behavioral changes. The purpose of this paper, scoping review, is to map the validity of HBM variables in predicting behavioral changes based on available synthesized evidences.

A scoping review was conducted using the Arksey and O’Malley’s framework. PubMed, Health Evidence, Cochrane Database of Systematic Reviews, ScienceDirect and Google Scholar were searched using a combination of keywords: health belief model, review, systematic review and meta-analysis between February 15 and March 18, 2016.

Of the 1,457 articles, 4 met the inclusion criteria. All results showed that HBM variables were consistently related to behaviors and the strength of the correlation were varied. Perceived barriers and perceived benefits were the strongest predictor, while perceived severity was the weakest. The association between HBM variables and behaviors was moderated by some aspects of behavioral outcomes, the study design and the time interval between measurement of the HBM variables and behavior.

Although the four main variables of HBM have been shown to be related to behavior, the overall outcomes are varied and have not demonstrated conclusive evidence during the last ten years. The results of this scoping review imply the need for a systematic review and meta-analysis of the results of recent studies. In addition, more longitudinal studies are needed to ensure the validity of HBM variables by considering any possible moderators.

The purpose of this paper was to develop a predictor model for an online nutrition course on sugar reduction. The proposed model is based on health knowledge, healthy behavior, social support, self-efficacy, attitude and the health belief model in relation to people’s behavior within a Facebook group. Subsequently, the model can be used to design a robust online training course for human resources, thereby reducing the training costs which managers have experienced as being expensive.

A single pre-post experimental group design was used. Pre and post data were collected from 100 Facebook users using an online questionnaire, within a three-week intervention.

The results show a significant difference between pre- and post-test scores of health knowledge and healthy behavior, indicating an effective intervention. In addition, perceived barriers, attitude, self-efficacy and emotional support were significant predictors of the healthy behavior model, predicting 70 percent of healthy behavior. However, knowledge had no significant relationship with any of the three dependent variables (self-efficacy, attitude and healthy behavior) proposed.

This model has proved to be an effective intervention which can be used in online training of human resources, because the content of the training is known from the predictor model, thereby greatly reducing the training cost, since everything is done online. Moreover, the provided model and predictors show that the content to be delivered in the training program is not knowledge but perceived barriers, attitude, self-efficacy and emotional support.

This study is one of the first to propose an integrative model that suggests attitude and self-efficacy as key predictors of healthy behavior whereas knowledge is not.

The purpose of this paper is to identify and describe adolescents’ health-related behaviours from a socio-ecological perspective. Socio-ecological factors have been widely shown to be related to health behaviours (smoking, alcohol consumption, physical activity and diet) in adolescence and to affect health. The review integrates evidence with socio-ecological factors (social relationships, family, peers, schooling and environment).

The data were collected from electronic databases and by manual search consisting of articles (n=90) published during 2002-2014. The selected articles were analysed using inductive content analysis and narrative synthesis.

The findings suggest that there was a complex set of relations connected to adolescent health behaviours, also encompassing socio-ecological factors. The authors tentatively conclude that socio-ecological circumstances influence adolescents’ health-related behaviour, but that this review does not provide the full picture. There seemed to be certain key factors with a relation to behavioural outcomes that might increase health inequality among adolescents.

School health education is an important pathway for interventions to reduce unhealthy behaviours among adolescents including those related to socio-ecological factors.

Some socio-ecological factors were strongly related to health behaviours in adolescence, which may indicate an important pathway to current and future health. This paper may help schoolteachers, nurses and other school staff to understand the relationships between socio-ecological factors and health-related behaviours, which may be useful in developing health education to reduce health disparities during adolescence.