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The rapid advancement of technology has transformed the health-care industry and enabled the emergence of m-Health solutions such as health apps. The viability and success of these apps depends on the definition of a monetization model appropriate to their specificities. In this sense, the purpose of this paper is to study the mechanisms of monetization of health apps, to stablish how alternative revenues determine if a health app is to be free or paid.

Probability models are used to identify the factors that explain if a health app is free or paid.

Results show that the presence of alternative monetization mechanisms negatively impacts the likelihood of a health app being paid for. The use of personal data to customize advertising (the monetization of “privacy capital”) or the inclusion of ads on the app are alternative means of monetization with potential to decrease the likelihood of a health app being paid for. The possibility of in-app purchases has a lower negative impact on the probability of a health app being paid for. The choice of platform to commercialize an app is also a strategic decision that influences the likelihood of an app being paid for.

This work stands out for bringing together the two largest platforms present in Portugal and for focusing on the perspective of revenue and monetization of health apps and not on the perspective of downloads.

Racism occurs in many ways and varies across countries, evolving and adapting to sociocultural history, as well as contemporary economic, political and technological changes. This chapter discusses the multilevel dimensions of racism and its diverse manifestations across multiracial societies. It examines how different aspects of racism are mediated interpersonally, and embedded in institutions, social structures and processes, that produce and sustain racial inequities in power, resources and lived experiences. Furthermore, this chapter explores the direct and indirect ways racism is expressed in online and offline platforms and details its impacts on various groups based on their intersecting social and cultural identities. Targets of racism are those who primarily bear the adverse effects. However, racism also affects its perpetrators in many ways, including by limiting their social relations and attachments, and by imposing social and economic costs. This chapter thus analyses the many aspects of racism both from targets and perpetrators' perspectives.

Pregnant employees experience considerable interpersonal discrimination. This study explores the range of possible reactions of observers to pregnancy self-disclosure, interpersonal discrimination and various allyship interventions, and the attentional processes that lead to those reactions. Consequently, it uncovers socio-cognitive processes underlying support for and backlash toward pregnancy in the workplace.

This study used a thought-listing technique to explore observers’ spontaneous thoughts related to pregnancy. Working adults were randomly assigned to read through one of the six scenarios depicting pregnancy self-disclosure, interpersonal discrimination and male allyship interventions (i.e. stating the organization’s anti-discrimination policy, confronting the transgressor by calling out sexism, pivoting the conversation to highlight the strengths of the pregnant employee and a hybrid intervention combining highlighting strengths and confrontation) after which participants listed the top three thoughts that came to their mind (1,668 responses). Responses were thematically analyzed to explore spontaneous reactions toward the pregnant employee, transgressor and ally in the scenario.

Surprisingly, across all scenarios, the most sexist thoughts emerged during pregnancy self-disclosure, even in the absence of any transgression. After a transgression occurred, any allyship intervention was better than none in eliciting lesser sexist backlash against the pregnant employee. Stating the organization’s anti-discrimination policy was most beneficial for the pregnant employee in eliciting the least sexist backlash but at the cost of generating unfavorable impressions of the ally. Calling out the transgressor’s bias elicited the most sexist backlash toward the pregnant employee, yet it created favorable impressions of the ally. In contrast, highlighting the strengths of the pregnant employee created the most favorable impression of the ally while eliciting a few sexist thoughts about the pregnant employee. Overall, the hybrid intervention was the most effective at balancing the competing goals of generating support for the pregnant employee, creating favorable impressions of the ally, as well as holding the transgressor accountable.

This study demonstrates that the type of allyship intervention critically redirects the attentional focus of observers to certain aspects of a discrimination episode and relevant schemas which can generate support or backlash toward targets, transgressors and allies, thereby advancing or obstructing equity and inclusion in organizations.

This chapter examines the connections between race and class divisions and examines how they shape racial inequities in the distribution of resources, power and privilege. Throughout history, racial identity has been a key factor in determining a person's position in modern capitalist societies. As such, issues of race and class have preoccupied sociologists and other scholars with diverse ideological orientations. This is highlighted in debates around the nexus of race and class in the production of racial structures, laws and institutions that legitimate and perpetuate the normalisation and centrality of whiteness. This chapter summarises some of the historical and ongoing debates, providing a synthesis of how race and class divisions continue to shape contemporary intergroup relations and social policy. It delves into racial capitalism and how race intersects with other social identities to determine socio-economic hierarchy in many western countries.

Lead is a well-established environmental contaminant that over the last 50 years has become recognized as a neurotoxin with its greatest concern for the developing child (i.e. both in-utero and postnatally). What is problematic is that children exposed to lead often come from lower socioeconomic status (SES), are largely Black communities and are further at increased risk for developing adverse childhood experiences (ACEs). The literature on ACEs had focused much on trauma, single parenting, child abuse, lack of finances and stress, etc., but has not considered the intersectionality of these ACEs as risk factors within environmental neurotoxic exposures such as lead poisoning. This is important as most low SES communities are Black. In particular, within the New York City Housing Authority (NYCHA), Black families have been neglected of proper lead-abatement to their apartments for nearly 70 years.

This is a viewpoint/perspective paper that examines the lived experiences of Black folxs in NYCHA through a Black critical theory (BlackCrit) and antiblackness framework pertaining to ACEs, and lead poisoning within the NYCHA system of New York City. This perspective paper draws upon the last three years of news reports, five decades of publicly available data sets from NYCHA and the comptroller to raise an awareness of how Black children are treated by NYCHA generation after generation which can be argued as a mass atrocity against NYCHA residents. Furthermore, the systematic and institutionalized racism and environmental injustices by NYCHA and the state can also be considered as a crime against humanity. As such, BlackCrit could help to position awareness, advocacy and knowledge about Black folxs residing in NYCHA to achieve fair, safe and affordable public housing to experience Black joy across future generations.

Thus, rather than civic and state government response efforts focusing their full attention and resources to serving and supporting individuals affected by ACEs they should equally consider the environments in which Black people live and also allocate funds proportionally to address these areas often overlooked. Moreover, proportions of these funds should be redirected especially to lead-abatement and removal of known sources of lead exposures, evaluation of suspected sources of lead exposures (i.e. drinking water, baby food and formula, children’s juice and cereal products, superfund and other waste sites, electronic recycling plants, etc.) and accompanied by all affected children undergoing full and comprehensive neuropsychological testing and follow up studies paid for by the state. The goal should have two fundamental objectives: (1) accepting accountability for failing to address these preventable neuropsychological issues directly affecting Black children generation after generation and (2) offering the proper waived or reimbursable supports and resources to help Black children sustain the best quality of life (QOL) trajectory possible when diagnosed with lead poisoning.

The manuscript is a viewpoint/perspective paper grounded in BlackCrit and an antiblackness framework. There are ample public news reports and public data available from NYCHA on these matters over the last three years. However, the scope of this paper was not to delve too deep into these numbers per se, but rather to address the concerns leading up to and arguably contributing to, at least in part, to these numbers of lead-exposed Black children in NYCHA. Lead poisoning has never been considered as an ACE and its relationship to mass atrocity research is novel which may pave a new avenue for research of this kind through the utility of BlackCrit and antiblackness framework to support and advocate for change so that Black children can be provided with a basic human right of safe housing and experience Black joy.

BlackCrit has not been used in the context of lead poisoning research. Mostly individuals and families of middle- and low-income have been studied in the context of poverty and lead poisoning. However, many people who live in poverty, in public housing, within New York are Black. Thus, Black children are generation after generation exposed to unaddressed lead-abatement and it appears that now more than ever BlackCrit should become the framework for how this work should be discussed in the literature to raise awareness to state governments regarding Black folx's persistent lead poisoning, NYCHA's neglect and mass atrocity research as a long overdue advocacy effort to bring the necessary voice, authentic narrative, and actual knowledge of the lived experiences of Black families in NYCHA with lead poisoning.

The goal of this viewpoint/perspective paper should have two fundamental objectives (1) NYCHA and New York State accepting accountability for failing to address these preventable lead poisoning issues directly affecting Black children; and (2) offering the proper support and resources to help Black children sustain the best QOL trajectory possible when diagnosed with lead poisoning.

Lead poisoning research has never been approached through a mass atrocity and BlackCrit framework and perspective. This is the first report on bridging these fields within the context of NYCHA public housing neglect of lead-abatement and continued poisoning of current and future generations of Black children. This failure of NYCHA lead-abatement contributes annually to economic loss in New York State for many years to come which could be entirely avoided.

This paper delves into evaluating the effectiveness of warning messages as a deterrent against excessive fat consumption. It examines how consumers perceive the fat content of food products when presented with two distinct label types: (1) a textual warning, providing succinct information about the fat content, and (2) a pictorial warning, offering a visual representation that immediately signifies the fat content.

Two quantitative studies were carried out. Study 1 employed a questionnaire to evaluate the efficacy of textual and pictorial warning messages on high- and low-fat food products. Similarly, Study 2 replicated this comparison while incorporating a neuromarketing instrument to gauge participants’ cerebral reactions.

Results indicate that pictorial warnings on high-fat foods significantly deter consumers’ purchasing intentions. Notably, these pictorial warnings stimulate the left prefrontal area of the cerebral cortex, inducing negative emotions in consumers and driving them away from high-fat food items.

While the influence of images over text in shaping consumer decisions is well understood in marketing, this study accentuates the underlying mechanism of such an impact through the elicitation of negative emotions. By understanding this emotional pathway, the paper presents fresh academic and managerial perspectives, underscoring the potency of pictorial warnings in guiding consumers towards healthier food choices.

1. Textual warnings do not seem to discourage high-fat product consumption.

2. A pictorial warning represents the fat content of an equivalent product.

3. Pictorial warnings decrease the intention to purchase a high-fat product.

4. Pictorial warnings determine an increase in negative emotions.

Textual warnings do not seem to discourage high-fat product consumption.

A pictorial warning represents the fat content of an equivalent product.

Pictorial warnings decrease the intention to purchase a high-fat product.

Pictorial warnings determine an increase in negative emotions.

This research paper aims to investigate the effects of internal audit’s (IA) use of data analytics and the performance of consulting activities on perceived IA quality.

The authors conduct a 2 × 2 between-subjects experiment among upper and middle managers where the use of data analytics and the performance of consulting activities by internal auditors are manipulated.

Results highlight the importance of internal auditor use of data analytics and performance of consulting activities to improve perceived IA quality. First, managers perceive internal auditors as more competent when the auditors use data analytics. Second, managers perceive internal auditors’ recommendations as more relevant when the auditors perform consulting activities. Finally, managers perceive an improvement in the quality of relationships with internal auditors when auditors perform consulting activities, which is strengthened when internal auditors combine the use of data analytics and the performance of consulting activities.

From a theoretical perspective, this research builds on the IA quality framework by considering digitalization as a contextual factor. This research focused on the perceptions of one major stakeholder of the IA function: senior management. Future research should investigate the perceptions of other stakeholders and other contextual factors.

This research suggests that internal auditors should prioritize the development of the consulting role in their function and develop their digital expertise, especially expertise in data analytics, to improve perceived IA quality.

This research tests the impacts of the use of data analytics and the performance of consulting activities on perceived IA quality holistically, by testing Trotman and Duncan’s (2018) framework using an experiment.

This study aims to examine the mediating effects of corporate governance mechanisms like the board of directors on the association between disruptive technology adoption by audit clients and the risk of material misstatements, including inherent risk and control risk. In particular, the authors study the mediating effects of board characteristics such as board size, independence and gender diversity.

Based on a sample of 100 audit clients listed on the FTSE 100 from 2015 to 2021, this study uses structural equation modelling to test the research objectives.

The findings indicate a significant and negative association between disruptive technology adoption by audit clients and inherent risk. However, there is no significant evidence observed for control risk. The utilisation of disruptive technology by the audit client has a significant impact on the board characteristics, resulting in an increase in board size, greater independence and gender diversity. The authors also find strong evidence that board independence mediates the association between disruptive technology usage and both inherent risk and control risk. In addition, board size and gender exhibit distinct and differential mediating effects on the association and across the two types of risks.

The study reveals that the significant role of using disruptive technology by audit clients in reducing the risk of material misstatements is closely associated with the board of directors, which makes audit clients place greater emphasis on the construction of effective corporate governance.

This study offers essential primary evidence that can assist policymakers and standard setters in formulating guidance and recommendations for board size, independence and gender quotas, ensuring the enhancement of effective governance and supporting the future of audit within the next generation of digital services.

With respect to relevant stakeholders, it is imperative for audit clients to recognise that corporate governance represents a fundamental means of addressing the ramifications of applying disruptive technology, particularly as they pertain to inherent and control risks within the audit client.

This study contributes to the existing literature by investigating the joint impact of corporate governance and the utilisation of disruptive technology by audit clients on inherent risk and control risk, which has not been investigated by previous research.

The purpose of this study is to develop a magnetic resonance imaging (MRI)-safe iron-free electrical actuator for MR-guided surgical interventions.

The paper deals with the design of an MRI compatible electrical actuator. Three-dimensional electromagnetic and thermal analytical models have been developed to design the actuator. These models have been validated through 3D finite element (FE) computations. The analytical models have been inserted in an optimization procedure that uses genetic algorithms to find the optimal parameters of the actuator.

The analytical models are very fast and precise compared to the FE models. The computation time is 0.1 s for the electromagnetic analytical model and 3 min for the FE one. The optimized actuator does not perturb imaging sequence even if supplied with a current 10 times higher than its rated one. Indeed, the actuator’s magnetic field generated in the imaging area does not exceed 1 ppm of the B₀ field generated by the MRI scanner. The actuator can perform up to 25 biopsy cycles without any risk to the actuator or the patient since he maximum temperature rise of the actuator is about 20°C. The actuator is compact and lightweight compared to its pneumatic counterpart.

The MRI compatible actuator uses the B₀ field generated by scanner as inductor. The design procedure uses magneto-thermal coupled models that can be adapted to the design of a variety actuation systems working in MRI environment.

This study aims to obtain methods to identify and find the place of damage, which is one of the topics that has always been discussed in structural engineering. The cost of repairing and rehabilitating massive bridges and buildings is very high, highlighting the need to monitor the structures continuously. One way to track the structure's health is to check the cracks in the concrete. Meanwhile, the current methods of concrete crack detection have complex and heavy calculations.

This paper presents a new lightweight architecture based on deep learning for crack classification in concrete structures. The proposed architecture was identified and classified in less time and with higher accuracy than other traditional and valid architectures in crack detection. This paper used a standard dataset to detect two-class and multi-class cracks.

Results show that two images were recognized with 99.53% accuracy based on the proposed method, and multi-class images were classified with 91% accuracy. The low execution time of the proposed architecture compared to other valid architectures in deep learning on the same hardware platform. The use of Adam's optimizer in this research had better performance than other optimizers.

This paper presents a framework based on a lightweight convolutional neural network for nondestructive monitoring of structural health to optimize the calculation costs and reduce execution time in processing.