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Clinical staff working in mental health services experience high levels of work-related stress, burnout and poor well-being. Increased levels of stress, burnout, depression and anxiety and poorer mental well-being among health-care workers are associated with more sick days, absenteeism, lower work satisfaction, increased staff turnover and reduced quality of patient care. Virtual reality (VR) relaxation is a technique whereby experiences of pleasant and calming environments are accessed through a head-mounted display to promote relaxation. The purpose of this paper is to describe the design of a study that assesses the feasibility and acceptability of implementing a multi-session VR relaxation intervention amongst mental health professionals, to improve their relaxation levels and mental well-being.

The study follows a pre–post-test design. Mental health staff will be recruited for five weeks of VR relaxation. The authors will measure the feasibility and acceptability of the VR relaxation intervention as primary outcomes, alongside secondary outcomes evaluating the benefits of VR relaxation for mental well-being.

The study aims to recruit 20–25 health-care professionals working in both inpatient and specialist community mental health settings.

Research indicates the potential of VR relaxation as a low-intensity intervention to promote relaxation and reduce stress in the workplace. If VR relaxation is shown to be feasible and acceptable, when delivered across multiple sessions, there would be scope for large-scale work to investigate its effectiveness as an approach to enable health-care professionals to de-stress, relax and optimise their mental well-being. In turn, this may consequently reduce turnover and improve stress-related sick leave across health-care services.

The purpose of this study is to increase the resilience capacity of residential health-care professionals to achieve intrapreneurial development in workers. Through training based on the development of emotional competencies and the application of mindfulness techniques, the aim is for the individual to become aware of his or her role, learn to manage emotions and reduce feelings of distress and anxiety.

The proposed programme has a duration of eight weeks. Every four days of training, mindfulness sessions are integrated, and at the beginning and end of the working day, 10 min are spent with superiors to give feedback on what happened during the day and the setting of new objectives. A control group is also established where they do not undergo such training. After the delivery of the programme, the results obtained after the application of the methodology to a sample of 91 residential health-care professionals are presented. By means of a validated resilience questionnaire composed of 25 items, the aim is to measure the resilience capacity of the participants before and after training and to observe the impact of the programme.

The results of this study show that the training has led to an improvement in the overall resilience capacity by 3.93% and has been able to reduce the existing gap between those over 45 years of age and younger people, although the age-related variable still represents a significant difference.

This study provides an innovative way of fostering entrepreneurship. While participants work on resilience management through mindfulness techniques, organisational commitment is achieved.

The authors aim to develop a conceptual framework for longitudinal estimation of stress-related states in the wild (IW), based on the machine learning (ML) algorithms that use physiological and non-physiological bio-sensor data.

The authors propose a conceptual framework for longitudinal estimation of stress-related states consisting of four blocks: (1) identification; (2) validation; (3) measurement and (4) visualization. The authors implement each step of the proposed conceptual framework, using the example of Gaussian mixture model (GMM) and K-means algorithm. These ML algorithms are trained on the data of 18 workers from the public administration sector who wore biometric devices for about two months.

The authors confirm the convergent validity of a proposed conceptual framework IW. Empirical data analysis suggests that two-cluster models achieve five-fold cross-validation accuracy exceeding 70% in identifying stress. Coefficient of accuracy decreases for three-cluster models achieving around 45%. The authors conclude that identification models may serve to derive longitudinal stress-related measures.

Proposed conceptual framework may guide researchers in creating validated stress-related indicators. At the same time, physiological sensing of stress through identification models is limited because of subject-specific reactions to stressors.

Longitudinal indicators on stress allow estimation of long-term impact coming from external environment on stress-related states. Such stress-related indicators can become an integral part of mobile/web/computer applications supporting stress management programs.

Timely identification of excessive stress may improve individual well-being and prevent development stress-related diseases.

The study develops a novel conceptual framework for longitudinal estimation of stress-related states using physiological and non-physiological bio-sensor data, given that scientific knowledge on validated longitudinal indicators of stress is in emergent state.

This study examines the dualities of digital services – that is, how customers’ favorite everyday digital services can positively and negatively contribute to their well-being. Thus, the study describes the meanings of favorite digital services as part of customers’ everyday lives and the types of well-being to which such services can contribute.

We used a qualitative research approach through semi-structured interviews conducted in 2021 to collect data from 14 young adults (22–31 years old) who actively used digital services in their daily lives.

Our findings revealed that customers’ favorite everyday digital services can contribute to their mental well-being, social well-being, and intellectual well-being. Within these three dimensions of well-being, we identified nine dualities of digital services that describe their positive and negative contributions: (1) digital escapism versus digital disruption, (2) digital relaxation versus digital stress, (3) digital empowerment versus digital subjugation, (4) digital augmentation versus digital emptiness, (5) digital socialization versus digital isolation, (6) digital togetherness versus digital exclusion, (7) digital self-expression versus digital pressure, (8) digital learning versus digital dependence, and (9) digital inspiration versus digital stagnation.

These findings suggest that everyday digital services have the potential to contribute to customer well-being in various aspects – both positively and negatively – accentuating the need for service providers to decipher the impacts of their offerings on well-being. Indeed, understanding the relationship between digital services and customer well-being can help companies tailor their services to customers’ needs. Companies that prioritize customer well-being not only benefit their customers but also create sustainable growth opportunities in the long run. Further, companies can use the derived information in service design to develop marketing strategies that emphasize the positive impacts of their digital services on customer well-being.

Although prior transformative service studies have investigated the well-being of multiple stakeholders, such studies have focused on services related to the physical and healthcare domains. Consequently, the role of everyday digital services as contributors to customer well-being is an under-researched topic. In addition, the concept of well-being and its various dimensions has received limited attention in previous service research. By investigating everyday digital services and their multidimensional contribution to customer well-being, this study broadens the perspective on well-being within TSR and aids in refining a more precise conceptualization.

The research aims to investigate the impact of thermo-mechanical aging on SBR under cyclic-loading. By conducting experimental analyses and developing a 3D finite element analysis (FEA) model, it seeks to understand chemical and physical changes during aging processes. This research provides insights into nonlinear mechanical behavior, stress softening and microstructural alterations in SBR compounds, improving material performance and guiding future strategies.

This study combines experimental analyses, including cyclic tensile loading, attenuated total reflection (ATR), spectroscopy and energy-dispersive X-ray spectroscopy (EDS) line scans, to investigate the effects of thermo-mechanical aging (TMA) on carbon-black (CB) reinforced styrene-butadiene rubber (SBR). It employs a 3D FEA model using the Abaqus/Implicit code to comprehend the nonlinear behavior and stress softening response, offering a holistic understanding of aging processes and mechanical behavior under cyclic-loading.

This study reveals significant insights into SBR behavior during thermo-mechanical aging. Findings include surface roughness variations, chemical alterations and microstructural changes. Notably, a partial recovery of stiffness was observed as a function of CB volume fraction. The developed 3D FEA model accurately depicts nonlinear behavior, stress softening and strain fields around CB particles in unstressed states, predicting hysteresis and energy dissipation in aged SBRs.

This research offers novel insights by comprehensively investigating the impact of thermo-mechanical aging on CB-reinforced-SBR. The fusion of experimental techniques with FEA simulations reveals time-dependent mechanical behavior and microstructural changes in SBR materials. The model serves as a valuable tool for predicting material responses under various conditions, advancing the design and engineering of SBR-based products across industries.

The construction industry is one of the most stressful industries. Thus, quantity surveyors (QSs) who work at sites frequently experience high levels of occupational stress. The gender of a QS also has a significant impact on his/her occupational stress. Hence, this study aims to investigate the management of occupational stress in QSs working at sites for contractors (hereinafter referred to as CQSs).

The study adopted a mixed approach using semi-structured interviews and a questionnaire survey for female and male CQSs to identify, validate and rank the stressors and symptoms of occupational stress in CQSs and the strategies of managing that stress based on their significance levels. Manual content analysis and the mean weighted rating were used to analyse the data collected.

Heavy workload was the most significant occupational stressor of CQSs, whereas sleeping disorders were their primary symptom of occupational stress. Establishing a proper work programme was identified as the most effective stress management strategy for male and female CQSs. This study shows that many site QSs are stressed owing to their heavy workloads and work obligations and that their stress-related attributes significantly depend on their genders.

This study is significant because no previous studies have been conducted on managing occupational stress in CQSs in male and female CQSs. The study findings can be used to identify the stressors and symptoms of occupational stress in CQSs early and use appropriate management strategies to enhance the work satisfaction and productivity of CQSs suffering from occupational stress.

Polymethyl methacrylate (PMMA) is a remarkable biocompatible material for bone cement and regeneration. It is also considered 3D printable but requires in-depth process–structure–properties studies. This study aims to elucidate the mechanistic effects of processing parameters and sterilization on PMMA-based implants.

The approach comprised manufacturing samples with different raster angle orientations to capitalize on the influence of the filament alignment with the loading direction. One sample set was sterilized using an autoclave, while another was kept as a reference. The samples underwent a comprehensive characterization regimen of mechanical tension, compression and flexural testing. Thermal and microscale mechanical properties were also analyzed to explore the extent of the appreciated modifications as a function of processing conditions.

Thermal and microscale mechanical properties remained almost unaltered, whereas the mesoscale mechanical behavior varied from the as-printed to the after-autoclaving specimens. Although the mechanical behavior reported a pronounced dependence on the printing orientation, sterilization had minimal effects on the properties of 3D printed PMMA structures. Nonetheless, notable changes in appearance were attributed, and heat reversed as a response to thermally driven conformational rearrangements of the molecules.

This research further deepens the viability of 3D printed PMMA for biomedical applications, contributing to the overall comprehension of the polymer and the thermal processes associated with its implementation in biomedical applications, including personalized implants.

The recent pandemic disrupted the way in which businesses transact with each other. In response to maintaining cleanliness in business-to-business (B2B) settings, artificial intelligence (AI)-enabled robots have been adopted as substitutes for cleaning personnel, yet their implications remain largely underexamined. This study aims to examine B2B buyer responses to cleaning information notices (human vs AI-enabled agent) placed at either the entry to the premises or the sales counter, thereby adding to the nascent literature in this line of inquiry.

Three field experiments were conducted across diverse B2B businesses (wholesalers in Studies 1–2 and a commercial business in Study 3). To achieve greater empirical rigor and generalizability, this research used diverse stimuli across different B2B settings. In addition, the results ruled out alternate explanations and shed light upon political ideology as a boundary condition. Finally, a single-paper meta-analysis confirmed H1, consolidating the established effect.

Featuring over 1,000 B2B buyers, the results show that politically liberal B2B buyers express greater preference for human over AI-performed cleaning while labor-orientated buyers are indifferent. Importantly, this effect is driven by greater relaxation associated with humans, which in turn, increases their future patronage and referral intent.

The results enrich the collective knowledge of the adoption of AI-enabled robots, reinforcing for marketing practitioners and businesses that the reliance on human-based outcomes remains a preferred touchpoint in B2B settings, particularly for liberals.

Cannabis use continues to increase worldwide, and a number of nation states are changing their cannabis policies. Policy changes require research into key populations, namely, people who use cannabis. This study aims to examine sociodemographic differences of young Finns who reported using cannabis mainly for self-medication versus mainly recreationally, as well as their reported effects of cannabis use.

The data come from an anonymous online survey (N = 247, 70.0% males, 25.9% females, 4.1% other) that was analysed using multiple logistic regression. The authors focused on whether various demographic indicators differed between those who reportedly used cannabis mainly for recreational purposes and mainly for self-medicinal purposes. The authors also qualitatively examined the respondents’ experienced effects of cannabis, both desired and undesired.

Being older and female, living in a smaller city and earlier age of initiation of cannabis use were statistically significant in predicting the medicinal use of cannabis. The majority of recreational effects were related to themes such as relaxation and pleasure, but many participants also reported desired medical effects. Similarly, many participants reported several undesired effects.

Understanding especially young people’s motivations to use cannabis, which include using it for various medical effects, can improve the design of harm reduction and treatment programmes as well as enhance the well-being of people who use cannabis.

This study gives a nuanced account of sociodemographic factors and motivations of young people who use cannabis in Finland as well as the reported effects it has on them, which complements data from national drug surveys.

This study intend to investigate a theoretical model looking at how particular tourist emotions, such as “joy,” “love,” and “positive surprise,” might predict their behavior by looking at how satisfied they are with their whole experience when visiting spas, and to examine the relationship of emotional experience, destination image, satisfaction and intention to revisit for spa tourism.

A sample of 345 individuals who traveled to Alleppey as domestic tourists participated in the research study. A non-probability (purposive) sampling method in this study. The structural model was analyzed using Structural Equation modeling (SEM), and the path coefficients were examined to test the hypotheses.

The results supported the hypotheses, indicating that specific emotions, image of the destination, and satisfaction significantly impacted tourists' intentions to revisit Alleppey as a spa tourism destination. This study demonstrated that “emotions of joy, love, and positive surprise” have a considerable influence on the image of the destination and satisfaction. The findings reveal a substantial correlation between satisfaction and behavioral intention (“Intention to revisit”). The research suggests that a higher degree of satisfaction would encourage visitors to revisit the location.

The research suggests that a higher degree of satisfaction would encourage visitors to revisit the location. This research offers vital information for developing, planning, and putting into practice tourism policies in the spa tourism sector. This article focuses on domestic travelers who travel to Alleppey, so the conclusions may not be relevant to research utilizing foreign tourists.

According to the literature study, and to the authors` knowledge, only limited number of studies that look at spa tourism from a wellness perspective. Additionally, Alleppey is used in the study as the study’s setting, providing insight into the visitor experiences of this expanding spa tourism business. This study gives understanding about how emotional experience predicts behavioral intentions.