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The author examined effects of endorser type and message framing on visual attention and ad effectiveness in health ads, including the moderator of involvement. This paper aims to discuss this issue.

An experiment was conducted with a 2 (celebrity vs. expert) × 2 (positive vs. negative framing) between-subject factorial design. Eye-tracking measured visual attention and a questionnaire measured ad effectiveness and product involvement.

Experimental data from 78 responses showed no vampire effect in the health advertisements. Celebrity endorsement with negative message framing received more attention and had less ad recall than that with positive message framing. Negative and positive message framing attracted the same amount of attention and ad recall in the expert endorsement condition. High involvement participants paid more attention to the ad message with the expert than that with the celebrity, but ad recall was not significantly increased. Low involvement participants exhibited the same attention to the ad message with the expert and with the celebrity, but had greater recall of the ad message with the expert. Visual attention to the endorser was associated with ad attitude but not with ad recall. Ad attitude impacted behavioral intention.

Studies examining influences of celebrity and message framing on ad effectiveness have focused on the response to advertising stimuli, not the information process. The author provides empirical evidence of the viewers' information processing of endorsers and health messages, and its relationship with ad effectiveness. The study contributes to the literature by combining endorser and message framing in health ads to promote public health communication from the information processing perspective.

Consumers consider retailers' standard private labels (PLs) as relevant choices, compared to national brands (NBs), and their demand for private label products has increased significantly over the past decade. At the same time, PLs have undergone a profound transformation as retailers have enhanced their quality. The goal of this research is to investigate the impact of claims used to highlight the enhanced quality of standard PL products on consumers' perceptions and behaviours.

A between-subjects experiment, set in a store laboratory, was used to study consumers' perceptions and behaviours. The impact of six non-nutrition claims – linked, according to the self-other trade-off, either to concern for consumers' health (internal to the self) or for the environment (external to the self) – on consumers' reactions has been studied. Then, the data collected were analysed with partial least squares structural equation modelling (PLS-SEM).

This research indicates that health claims retailers make to echo consumers' own concerns have positive impacts at three basic levels: the brand, the retail chain and the store. It also highlights the central role of trust in standard PLs, which, once activated by the non-nutrition claims made by retailers and the increase in the quality of standard PLs thus inferred by consumers, can improve consumers' attitude toward the food retailers' stores and reinforce their intentions to visit again and recommend them.

From a theoretical perspective, this research supplements cue utilisation theory as it applies this framework to standard PLs and establishes that consumers use extrinsic cues (i.e. communications on non-nutrition claims) to infer the quality of standard PL brand products. It also complements scant studies on retailers' corporate social responsibility (CSR) with quality aspects of their own labels as it specifies the levers (i.e. the claims) to use to improve retailers' CSR image and consumers' behaviours.

From a managerial perspective, this research highlights the superiority of retailers' claims related to consumer health and, more specifically, of claims highlighting the natural origin of ingredients. For this specific assertion, trust in the standard PL and the CSR image of the brand have direct and indirect impacts, via attitude toward the stores, on consumers' intentions to return to and to recommend these stores.

Despite the increasing importance of products as effective tools for communicating companies' CSR policies, scant research has been conducted on consumers' reactions to non-nutrition claims, which are increasingly prominent in the marketplace.

The environment in which users acquire medical and health information has changed dramatically, with online health communities (OHCs) emerging as an essential means for accessing health information. It is imperative to comprehend the factors that shape the users' compliance willingness (UCW) to health information in OHCs.

This study adopted the information adoption model (IAM) and theory of planned behavior (TPB) to investigate the influence of argument quality (AQ), source credibility (SC) and subjective norms (SN) on UCW while considering the two types of online health information – mature and emerging treatments. The authors conducted an explanatory-predictive study based on a 2 (treatment types: mature vs. emerging) * 2 (AQ: high vs. low) * 2 (SC: high vs. low) scenario-based experiment, using the partial least squares structural equation modeling (PLS-SEM).

SC positively influences AQ. AQ, SC and SN contribute to information usefulness (IU). These factors positively affect UCW through the mediation of IU. SN were found to improve UCW directly. Moreover, the moderating effect of SC on AQ and IU was more substantial for emerging treatments.

The research model integrates IAM and TPB, considering information types as an additional variable. The approach and findings provide a valuable explanation for UCW to health information in OHCs.

Gamification unlocks unprecedented opportunities in healthcare, wellness and lifestyle context. In this scenario, by leveraging on such an approach, information technologies now enabled gamification-based mobile applications primarily employed in health and wellness contexts, focusing on areas such as disease prevention, self-management, medication adherence and telehealth programs. The synergistic integration of gamification-based methodologies in conjunction with the utilization of digital tools, (e.g. as for Internet of Things, mobile applications) for the realm of digital therapeutics (DTx), thus unveiled powerful approaches and paradigms, yielding innovative applications that, through the harnessing of sensors and software-based systems, transform healthcare maintenance, wellness and lifestyle into an engaging pursuit, as a game. This paper explores the factors influencing individuals' intention to autonomously utilize mobile gamification-based apps for self-care and wellness maintenance.

Through explorative research designs an experiment has been conducted among a sample of 376 participants regarding the use of a fictitious gamification-based DTx solution, consisting in a mobile app namely “Health'n’Fit”.

Findings from an experiment conducted with a sample of 460 participants shed light on the possible antecedents and consequents of gamification. Results of the SEM model indicate that customization (CU), trust (TR), mobility (MO) and social value (SV) are the main determinants, although at a different extent of the playful experience; Moreover, gamification positively impacts attitudes and, in turn, perceived usefulness, intention to use and behavioral intentions.

This paper offers a dual-pronged approach that holds practical significance in the realm of healthcare innovation. First, the authors delve into the antecedents shaping individuals' intention to engage with gamification-based DTx, unraveling the factors that influence user adoption. Beyond this, the authors extend their focus to the realm of healthcare service design. By harnessing the potential of gamification and technology, the authors illuminate pathways to conceptualize and create novel healthcare services. This work not only identifies the building blocks of user engagement but also serves as a guide to innovatively craft healthcare solutions that leverage this amalgamation of technology and gamification, contributing to the evolution of modern healthcare paradigms.

In a social context, the paper introduces pioneering technological synergies that merge gamification and DTx to enhance individuals' health and wellness maintenance. By proposing innovative combinations, the authors present novel avenues for promoting healthier lifestyles and behavior change. This not only underscores the potential of technology to positively impact individuals but also highlights the significance of aligning technological advancements with societal well-being. As the research advocates for these innovative solutions, it reinforces the importance of collaborative technological and marketing endeavors, ultimately contributing to the betterment of society as a whole.

This is the first paper exploring the combined effect of gamification and DTx, by shedding light on the peculiarities of both the antecedents of individuals' intention to use such combined technologies.

As convenience and anonymity, people with mental illness are increasingly willing to communicate and share information through social media platforms to receive emotional and spiritual support. The purpose of this paper is to identify the degree of depression based on people's behavioral patterns and discussion content on the Internet.

Based on the previous studies on depression, the severity of depression is divided into four categories: no significant depressive symptoms, mild MDD, moderate MDD and severe MDD, and defined each of them. Next, in order to automatically identify the severity, the authors proposed social media digital cues to identify the severity of depression, which include textual lexical features, depressive language features and social behavioral features. Finally, the authors evaluate a system that is developed based on social media digital cues in the experiment using social media data.

The social media digital cues including textual lexical features, depressive language features and social behavioral features (F1, F2 and F3) is the relatively best one to classify four different levels of depression.

This paper innovatively proposes a social media data-based framework (SMDF) to identify and predict different degrees of depression through social media digital cues and evaluates the accuracy of the detection through social media data, providing useful attempts for the identification and intervention of depression.

This study aims to evaluate and summarize the effectiveness of cognitive behavioral therapy (CBT) and internet-based CBT (ICBT) interventions on relapse prevention and severity of symptoms among individuals with major depressive disorder (MDD). CBT is one of the most used and suggested interventions to manage MDD, whereas ICBT is a novel effective proposed approach.

The review was conducted following the preferred reporting items for systematic review and meta-analysis protocol. A comprehensive and extensive search was performed to identify and evaluate the relevant studies about the effectiveness of CBT and ICBT on relapse prevention and severity of symptoms among patients with MDD.

A total of eight research studies met the inclusion criteria and were included in this systematic review. RCT studies were conducted to assess and evaluate the effectiveness of CBT and ICBT on relapse prevention and severity of symptoms among patients with MDD. It has been found that CBT is a well-supported and evidently based effective psychotherapy for managing depressive symptoms and reducing the relapse and readmission rate among patients diagnosed with MDD. The ICBT demonstrated greater improvements in depressive symptoms during major depressive episodes among patients with MDDS. The ICBT program had good acceptability and satisfaction among participants in different countries.

Despite the significant findings from this systematic review, certain limitations should be acknowledged. First, it is important to note that all the studies included in this review were exclusively conducted in the English language, potentially limiting the generalizability of the findings to non-English speaking populations. Second, the number of research studies incorporated in this systematic review was relatively limited, which may have resulted in a narrower scope of analysis. Finally, a few studies within the selected research had small sample sizes, which could potentially impact the precision and reliability of the overall conclusions drawn from this review. The authors recommend that nurses working in psychiatric units should use CBT interventions with patients with MDD.

This paper, a review of the literature gives an overview of CBT and ICBT interventions to reduce the severity of depressive symptoms and prevent patients’ relapse and rehospitalization and shows that CBT interventions are effective on relapse prevention among patients with MDD. In addition, there is still no standardized protocol to apply the CBT intervention in the scope of reducing the severity of depressive symptoms and preventing depression relapse among patients with major depressive disorder. Further research is needed to confirm the findings of this review. Future research is also needed to find out the most effective form and contents of CBT and ICBT interventions for MDD.

CBT is a psychological intervention that has been recommended by the literature for the treatment of major depressive disorder (MDD). It is a widely recognized and accepted approach that combines cognitive and behavioral techniques to assist individuals overcome their depressive symptoms and improve their overall mental well-being. This would speculate that effectiveness associated with several aspects and combinations of different approaches in CBT interventions and the impact of different delivery models are essential for clinical practice and appropriate selection of the interventional combinations.

This systematic review focuses on the various studies that explore the effectiveness of face-to-face CBT and ICBT in reducing depressive symptoms among patients with major depressive disorder. These studies were conducted in different countries such as Iran, Australia, Pennsylvania and the USA.

Campaigns to promote the COVID-19 vaccination messages to vaccine-hesitant consumers in the late stages of the pandemic are often met with resistance. This study aims to explore a way to leverage positive emotions induced from entertainment media consumption to promote vaccination messages to this audience group.

An online experiment was conducted with vaccine-hesitant consumers (N = 409). Participants viewed personally relevant entertainment music videos or mundane videos and vaccinated messages embedded in user-generated comments.

Data revealed that feelings of inspiration and nostalgia induced from entertainment media consumption increased vaccination intentions via increased risk perceptions and reduced anti-vaccination attitudes.

Social marketers should consider leveraging the combined effect of entertainment media-induced positive emotions and user-generated comments to motivate behavioral change among vaccine-hesitant individuals in the late stages of the COVID-19 pandemic.

The present study adds to social marketing literature by showing mechanisms that positive emotions induced from entertainment social media consumption might lead to health behavioral change.

This paper aims to propose a framework model of belief consistency on the confirmatory bias theory, trying to explore the interactions between cues of credence-label structure and different controversial types of health foods, as well as the intermediary mechanism of belief consistency.

This paper presents a conceptual framework of belief consistency based on confirmation bias theory. The interactions between cues of credence-label structure and different controversial types of health foods, as well as the intermediary mechanism of belief consistency.

Consumers’ willingness to purchase varies under interactions between cues of credence-label structure (product-level and ingredient-level credence-label cues) and different controversial types of health foods (noncontroversial health foods and controversial health foods). In the consumption context of noncontroversial health foods, the presence of product-level credence-label cues causes confirmation bias, greater perception of health belief consistency and higher willingness to purchase healthy foods. In the consumption context of controversial health foods, the presence of ingredient-level credence-label cues results in the prevention of confirmation bias, lower perception of unhealthy belief consistency and higher willingness to purchase health foods.

This paper offers a significant tool for researchers to enrich relevant theories in the field of the conceptual framework of cues of credence-label structure. It also discusses practical implications for enterprise marketing and for the health and welfare of consumers.

This paper explores optimal service resource management strategy, a continuous challenge for health information service to enhance service performance, optimise service resource utilisation and deliver interactive health information service.

An adaptive optimal service resource management strategy was developed considering a value co-creation model in health information service with a focus on collaborative and interactive with users. The deep reinforcement learning algorithm was embedded in the Internet of Things (IoT)-based health information service system (I-HISS) to allocate service resources by controlling service provision and service adaptation based on user engagement behaviour. The simulation experiments were conducted to evaluate the significance of the proposed algorithm under different user reactions to the health information service.

The results indicate that the proposed service resource management strategy, considering user co-creation in the service delivery, process improved both the service provider’s business revenue and users' individual benefits.

The findings may facilitate the design and implementation of health information services that can achieve a high user service experience with low service operation costs.

This study is amongst the first to propose a service resource management model in I-HISS, considering the value co-creation of the user in the service-dominant logic. The novel artificial intelligence algorithm is developed using the deep reinforcement learning method to learn the adaptive service resource management strategy. The results emphasise user engagement in the health information service process.

Today, e-government (electronic government) applications have extended to the frontiers of health-care delivery. E-Nabız contains personal health records of health services received, whether public or private. The use of the application by patients and physicians has provided efficiency and cost advantages. The success of e-Nabız depends on the level of technology acceptance of health-care service providers and recipients. While there is a large research literature on the technology acceptance of service recipients in health-care services, there is a limited number of studies on physicians providing services. This study aims to determine the level of influence of trust and privacy variables in addition to performance expectancy, effort expectancy, social influence and facilitating factors in the unified theory of acceptance and use of technology (UTAUT) model on the intention and behavior of using e-Nabız application.

The population of the study consisted of general practitioners and specialist physicians actively working in any health facility in Turkey. Data were collected cross-sectionally from 236 physicians on a voluntary basis through a questionnaire. The response rate of data collection was calculated as 47.20%. Data were collected cross-sectionally from 236 physicians through a questionnaire. Descriptive statistics, correlation analysis and structural equation modeling were used to analyze the data.

The study found that performance expectancy, effort expectancy, trust and perceived privacy had a significant effect on physicians’ behavioral intentions to adopt the e-Nabız system. In addition, facilitating conditions and behavioral intention were determinants of usage behavior (p < 0.05). However, no significant relationship was found between social influence and behavioral intention (p > 0.05).

This study confirms that the UTAUT model provides an appropriate framework for predicting factors influencing physicians’ behaviors and intention to use e-Nabız. In addition, the empirical findings show that trust and perceived privacy, which are additionally considered in the model, are also influential.