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A critical step in influencer marketing is influencer outreach, where a brand reaches out to an influencer and forms a partnership. Yet little is known about how factors related to this process might influence the outcomes of sponsored posts. To address this gap, the authors investigated whether, how and when the order of influencers' product use and brand outreach (i.e. use/outreach order) affects post persuasiveness.

The authors conducted three experimental studies. Studies 1 and 2 examined the effect of disclosure type (use-first, outreach-later vs. outreach-first, use-later vs. no disclosure) on consumers' responses to the post. Study 3 investigated the moderating effects of compensation disclosure type.

The results revealed that when the influencer used the product before (vs. after) being contacted by the brand, consumers had more favorable attitudes about the product and greater purchase intention upon reading the sponsored posts; perceived information diagnosticity mediated this effect. However, this tendency was mitigated if the influencer disclosed the specific monetary payment from the brand.

This research advances understanding of sponsorship disclosure and provides a way to manage its impact on message persuasiveness.

This study aims to examine the impact that diagnostic factors such as duration of diagnostic period, number of professionals consulted and perceived social support have on parental stress during the diagnostic process of autism spectrum disorder (ASD).

Forty parents of 2–18 year-old children/adolescents with a formal ASD diagnosis recruited from five specialized private clinics in Lisbon completed a survey which included diagnostic questionnaire, parental stress scale and social support scale from April to December 2022.

Data analysis indicated that the mean age of the diagnosis was 5.6 years with a delay of 3.95 years from first concern until final diagnosis. On average, parents consulted a mean of 3.62 professionals. Other findings indicated that as age of parents increased, levels of parental stress decreased. Parents with higher levels of social support had lower levels of parental stress. Furthermore, higher age of child at first concern predicted higher affective social support.

This study reflects on the experience of obtaining the ASD diagnosis in Portugal, raising awareness on the importance of providing early detection and social support for distressed parents.

This paper proposes a progressive, multi-level framework for diagnosing maintenance performance: rapid performance health checks of key performance for different equipment groups and end-to-end process diagnostics to further locate potential performance issues. A question-based performance evaluation approach is introduced to support the selection and derivation of case-specific indicators based on diagnostic aspects.

The case research method is used to develop the proposed framework. The generic parts of the framework are built on existing maintenance performance measurement theories through a literature review. In the case study, empirical maintenance data of 196 emergency shutdown valves (ESDVs) are collected over a two-year period to support the development and validation of the proposed approach.

To improve processes, companies need a separate performance measurement structure. This paper suggests a hierarchical model in four layers (objective, domain, aspect and performance measurement) to facilitate the selection and derivation of indicators, which could potentially reduce management complexity and help prioritize continuous performance improvement. Examples of new indicators are derived from a case study that includes 196 ESDVs at an offshore oil and gas production plant.

Methodological approaches to deriving various performance indicators have rarely been addressed in the maintenance field. The proposed diagnostic framework provides a structured way to identify and locate process performance issues by creating indicators that can bridge generic evaluation aspects and maintenance data. The framework is highly adaptive as data availability functions are used as inputs to generate indicators instead of passively filtering out non-applicable existing indicators.

This study aims to explore auto mechanics awareness of repairs and maintenance related to the car’s cybersecurity and provide insights into challenges based on current practice.

This study is based on an empirical study consisting of semistructured interviews with representatives from both branded and independent auto workshops. The data was analyzed using thematic analysis. A version of the capability maturity model was introduced to the respondents as a self-evaluation of their cybersecurity awareness.

Cybersecurity was not found to be part of the current auto workshop work culture, and that there is a gap between independent workshops and branded workshops. Specifically, in how they function, approach problems and the tools and support available to them to resolve (particularly regarding previously unknown) issues.

Only auto workshop managers in Sweden were interviewed for this study. This role was picked because it is the most likely to have come in contact with cybersecurity-related issues. They may also have discussed the topic with mechanics, manufacturers or other auto workshops – thus providing a broader view of potential issues or challenges.

The challenges identified in this study offers actionable advice to car manufacturers, branded workshops and independent workshops. The goal is to further cooperation, improve knowledge sharing and avoid unnecessary safety or security issues.

As cars become smarter, they also become potential targets for cyberattacks, which in turn poses potential threats to human safety. However, research on auto workshops, which has previously ensured that cars are road safe, has received little research attention with regards to the role cybersecurity can play in repairs and maintenance. Insights from auto workshops can therefore shed light upon the unique challenges and issues tied to the cybersecurity of cars, and how they are kept up-to-date and road safe in the digital era.

The role of evidence-based psychological knowledge in cases of juvenile offending is essential to make appropriate decisions relating to youth who violate legal or social norms, as it carries implications for treatment, intervention and practice. Psychological expert opinions therefore need to meet high formal and methodological requirements while maintaining ethical standards. The purpose of this study is to investigate psychological expert opinions in cases of juvenile misbehavior reported to regional courts in Poland. Juvenile court proceedings concern cases of demoralization and/or delinquent offenses. Demoralization is a legal concept described in the Act of June 9, 2022 on juvenile support and resocialization. This concept was not defined; it was only described through examples of behaviors indicating demoralization. These include the following: violations of the principles of community life; evading compulsory education or schooling; use of alcohol, narcotic drugs, psychotropic substances, their precursors, substitutes or new psychoactive substances; and prostitution.

To reach these goals, court records of juvenile cases in six district courts (N = 253) were gathered and analyzed. A semistructured questionnaire was used to examine the cases in which psychologists were appointed and to analyze the procedures used by these experts for assessing adolescents and their families.

Findings revealed that family judges appoint psychologists both in cases of “demoralization” (i.e. status offenses) and in cases of juvenile delinquency. The opinions were delivered by psychologists who were mostly members of diagnostic teams. Results indicate that such opinions generally comply with the minimal standards recommended by the Ministry of Justice, yet a few problems were observed with the determination of levels of demoralization.

The limitations of diagnostic tools used by psychologists are discussed, and recommendations for future practice are provided.

This review provides an overview of recent advances in electrochemical sensors for analyte detection in saliva, highlighting their potential applications in diagnostics and health care. The purpose of this paper is to summarize the current state of the field, identify challenges and limitations and discuss future prospects for the development of saliva-based electrochemical sensors.

The paper reviews relevant literature and research articles to examine the latest developments in electrochemical sensing technologies for saliva analysis. It explores the use of various electrode materials, including carbon nanomaterial, metal nanoparticles and conducting polymers, as well as the integration of microfluidics, lab-on-a-chip (LOC) devices and wearable/implantable technologies. The design and fabrication methodologies used in these sensors are discussed, along with sample preparation techniques and biorecognition elements for enhancing sensor performance.

Electrochemical sensors for salivary analyte detection have demonstrated excellent potential for noninvasive, rapid and cost-effective diagnostics. Recent advancements have resulted in improved sensor selectivity, stability, sensitivity and compatibility with complex saliva samples. Integration with microfluidics and LOC technologies has shown promise in enhancing sensor efficiency and accuracy. In addition, wearable and implantable sensors enable continuous, real-time monitoring of salivary analytes, opening new avenues for personalized health care and disease management.

This review presents an up-to-date overview of electrochemical sensors for analyte detection in saliva, offering insights into their design, fabrication and performance. It highlights the originality and value of integrating electrochemical sensing with microfluidics, wearable/implantable technologies and point-of-care testing platforms. The review also identifies challenges and limitations, such as interference from other saliva components and the need for improved stability and reproducibility. Future prospects include the development of novel microfluidic devices, advanced materials and user-friendly diagnostic devices to unlock the full potential of saliva-based electrochemical sensing in clinical practice.

Moral transgressions committed by person-brands can negatively impact consumers through the transgression’s diagnosticity (severity, centrality and consistency). This paper aims to test how a transgression’s centrality and consistency impact important consumer perceptions and behavioral intentions toward a person-brand, holding constant the transgression in question. These outcomes are crucial for person-brands to understand how to minimize and manage the impact of a given transgression.

This paper uses three online consumer experiments to manipulate transgression diagnosticity via centrality and consistency and identifies the resulting impact on consumer-brand identification, trustworthiness and consumer digital engagement intentions through PROCESS models.

High-diagnosticity transgressions lower consumer digital engagement intentions regarding the person-brand and their endorsed products. This effect is serially mediated by consumer-brand identification, as predicted by social identity theory, and by perceived trustworthiness of the person-brand.

Person-brands should emphasize the nondiagnostic nature of any transgressions in which they are involved, including a lack of centrality and consistency with their brand, and guard against the appearance of diagnostic transgressions.

This paper shows that transgression diagnosticity impacts consumer engagement through the pathway of consumer-brand identification and trustworthiness. It also manipulates aspects of diagnosticity that can be influenced by the person-brand (centrality and consistency) while holding the transgression constant. As such, this paper extends the literature on transgressions, on person-branding strategy, and on social identity theory.

This paper aims to investigate the efficacy of teeth flux sensors in detecting, locating and assessing the severity of short-circuit faults in the stator windings of induction machines.

The experimental study involves inducing short-circuit winding turn variations on the induction machine’s stator and continuously measuring the RMS values across teeth flux sensors. Two crucial steps are taken for machine diagnosis: measurements under load operating conditions for fault detection and measurements under no-load conditions to determine fault location and severity.

The experimental results demonstrate that the proposed approach using teeth flux sensors is reliable and effective in detecting, locating and evaluating the severity of stator winding faults.

While this study focuses on short-circuit faults, future research could explore other fault types and alternative sensor configurations to enhance the comprehensiveness of fault diagnosis.

The methodology outlined in this paper holds the potential to significantly reduce maintenance time and costs for induction machines, leading to substantial savings for companies.

This research contributes to the field by presenting an innovative approach that uses teeth flux sensors for a comprehensive fault diagnosis in induction machines. The originality lies in the effectiveness of this approach in providing reliable fault detection, location and severity evaluation.

The primary objective of this paper is to show a systematic and methodological approach for the digitalization of critical clinical pathways (CPs) within the healthcare domain.

The methodology entails the integration of service design (SD) and action research (AR) methodologies, characterized by iterative phases that systematically alternate between action and reflective processes, fostering cycles of change and learning. Within this framework, stakeholders are engaged through semi-structured interviews, while the existing and envisioned processes are delineated and represented using BPMN 2.0. These methodological steps emphasize the development of an autonomous, patient-centric web application alongside the implementation of an adaptable and patient-oriented scheduling system. Also, business processes simulation is employed to measure key performance indicators of processes and test for potential improvements. This method is implemented in the context of the CP addressing transient loss of consciousness (TLOC), within a publicly funded hospital setting.

The methodology integrating SD and AR enables the detection of pivotal bottlenecks within diagnostic CPs and proposes optimal corrective measures to ensure uninterrupted patient care, all the while advancing the digitalization of diagnostic CP management. This study contributes to theoretical discussions by emphasizing the criticality of process optimization, the transformative potential of digitalization in healthcare and the paramount importance of user-centric design principles, and offers valuable insights into healthcare management implications.

The study’s relevance lies in its ability to enhance healthcare practices without necessitating disruptive and resource-intensive process overhauls. This pragmatic approach aligns with the imperative for healthcare organizations to improve their operations efficiently and cost-effectively, making the study’s findings relevant.

Aster Retail (AR) is the retail pharmacy division of the Aster Dr Moopen's Healthcare (ADMH) Group. The group delivers healthcare services across the Middle East, India and the Far East, with a portfolio of hospitals, clinics, diagnostic centres and retail pharmacies. AR, under the leadership of Chief Executive Officer (CEO) Jobilal Vavachan, is well known for its people-centric approach, unique culture and innovative human resource (HR) practices. AR has won multiple awards for HR practices, service quality and business performance. In a recent corporate restructuring (2018), “Aster Primary Care” was carved out by combining the group's Clinics and Retail businesses. This case discusses the evolution of AR's HR journey and the challenges associated with integrating culturally diverse businesses without compromising the values of ADMH and its promise, “We'll Treat You Well.”