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Incidents of violence and aggression are a regular occurrence within adult forensic mental health inpatient settings and often lead to the use of restrictive practices such as seclusion. Such events are frequently attributed to the complexity of the patients. Research commonly focuses on patient’s characteristics and their association with seclusion use. Less attention has been centred on forensic mental health nurses’ attitudes to seclusion and the association of nursing staff characteristics.

A cross-sectional survey was undertaken using a standardised questionnaire, “Survey of Nurses’ Attitudes to Seclusion”. Responses were received from n = 147 nurses at a high secure forensic mental health hospital in the UK.

Key findings indicate that most participants believed seclusion should remain part of clinical practice. A correlation was identified between forensic mental health nurses’ attitudes to seclusion use and their characteristics: gender, age range, educational level and experience.

This paper presents novel information on seclusion reduction opportunities through modifiable workforce factors such as gender-sensitive rostering and staff training and development. Furthermore, recruitment and retention strategies should be prioritised so forensic mental health is perceived as an attractive career and a safe workplace.

The paucity of research in this area has prompted calls for further research to explore nursing staff characteristics and seclusion use. This is particularly important now due to the current global difficulty in the recruitment and retention of mental health nurses.

Low back disorder is one of the most prevalent and costly injuries in the construction industry. Back-support exoskeletons are increasingly perceived as promising solutions. However, the intended benefits of exoskeletons may not be realized if intention-to-use the device is low. Social influence could increase intention-to-use exoskeletons. This study aims to evaluate the impact of social influence on construction workers' intention-to-use back-support exoskeletons.

A field study involving 37 construction workers was conducted, with workers who used exoskeleton for one week, and their peers and supervisors. Data were collected using questionnaires and semi-structured interviews, and analyzed using descriptive statistics and thematic analysis, respectively.

The workers felt that the exoskeleton is easy to use and the functions are well integrated. Workers' intention-to-use exoskeleton was mainly influenced by employers providing and requiring the use of the device. The attitude of the workers and the perception of peers and supervisors did not have a significant impact on workers' intention-to-use exoskeleton, whereas the subjective norm of construction workers had a positive impact on the intention-to-use exoskeletons.

The study involved only 37 workers, including 15 workers who used the exoskeleton, and 14 peers and 8 supervisors of the workers.

This study contributes to existing knowledge on the influence of social influence on intention-to-use exoskeletons. The study also highlights how exoskeleton designs and the construction workplace can influence behavioral intention-to-use exoskeletons.

Exoskeletons are moving into industries with the potential to reduce muscle strains and prevent occupational injuries. Although exoskeletons have been designed and tested in laboratory settings, rare empirical studies of their application in construction have been reported. Therefore, the purpose of this study is on in a real-life setting testing the applicability of adopting exoskeletons in the construction industry.

A feasibility study of exoskeletons in construction is conducted by testing a passive exoskeleton, designed for shoulder support. Five bricklayers tested in a two-month period the exoskeleton, each wearing it for a three-day period while carrying out normal work activities. Test data in terms of interviews were collected and analyzed using qualitative content analysis.

The application of exoskeletons in construction revealed several limitations, where the two primary ones are the exoskeleton is not designed while considering the tasks of a bricklayer causing several challenges and the exoskeleton only supports a single upward motion while limiting other movements and even counteracted when a downward movement was necessary.

The identified challenges could easily have been revealed by coupling the design and testing of exoskeletons to actual application. Thus, the design approach needs to be reversed. Instead of designing an exoskeleton to support a specific body part or motion and then identifying where it is applicable, it should target specific industries and focus on the actual work and movements and the necessary support. As part of the change, the design metrics should be reevaluated to reflect the work to support.

Concrete workers perform physically demanding work in awkward postures, exposing their backs to musculoskeletal disorders. Back-support exoskeletons are promising ergonomic interventions designed to reduce the risks of back disorders. However, the suitability of exoskeletons for enhancing performance of concrete workers has not been largely explored. This study aims to assess a passive back-support exoskeleton for concrete work in terms of the impact on the body, usability and benefits of the exoskeleton, and potential design modifications.

Concrete workers performed work with a passive back-support exoskeleton. Subjective and qualitative measures were employed to capture their perception of the exoskeleton, at the middle and end of the work, in terms of discomfort to their body parts, ease of use, comfort, performance and safety of the exoskeleton, and their experience using the exoskeleton. These were analyzed using descriptive statistics and thematic analysis.

The exoskeleton reduced stress on the lower back but caused discomfort to other body parts. Significant correlations were observed between perceived discomfort and usability measures. Design modifications are needed to improve the compatibility of the exoskeleton with the existing safety gears, reduce discomfort at chest and thigh, and improve ease of use of the exoskeleton.

The study was conducted with eight concrete workers who used the exoskeleton for four hours.

This study contributes to existing knowledge on human-wearable robot interaction and provides suggestions for adapting exoskeleton designs for construction work.

Recognizing construction workers' activities is critical for on-site performance and safety management. Thus, this study presents the potential of automatically recognizing construction workers' actions from activations of the erector spinae muscles.

A lab study was conducted wherein the participants (n = 10) performed rebar task, which involved placing and tying subtasks, with and without a wearable robot (exoskeleton). Trunk muscle activations for both conditions were trained with nine well-established supervised machine learning algorithms. Hold-out validation was carried out, and the performance of the models was evaluated using accuracy, precision, recall and F1 score.

Results indicate that classification models performed well for both experimental conditions with support vector machine, achieving the highest accuracy of 83.8% for the “exoskeleton” condition and 74.1% for the “without exoskeleton” condition.

The study paves the way for the development of smart wearable robotic technology which can augment itself based on the tasks performed by the construction workers.

This study contributes to the research on construction workers' action recognition using trunk muscle activity. Most of the human actions are largely performed with hands, and the advancements in ergonomic research have provided evidence for relationship between trunk muscles and the movements of hands. This relationship has not been explored for action recognition of construction workers, which is a gap in literature that this study attempts to address.

Financial institutions actively seek to leverage the capabilities of artificial intelligence (AI) across diverse operations in the field. Especially, the adoption of AI advisors has a significant impact on trading and investing in the stock market. The purpose of this paper is to test whether AI advisors are less preferred compared to human advisors for investing and whether this algorithm aversion diminishes for trading.

The four hypotheses regarding the direct and indirect relationships between variables are tested in five experiments that collect data from Prolific.

The results of the five experiments reveal that, for investing, consumers are less likely to use AI advisors in comparison to human advisors. However, this reluctance to AI advisors decreases for trading. The author identifies the perceived importance of careful decision-making for investing and trading as the psychological mechanism. Specifically, the greater emphasis on careful decision-making in investing, as compared to trading, leads to consumers’ tendency to avoid AI advisors.

This research is the first to investigate whether algorithm aversion varies based on whether one’s approach to the stock market is investing or trading. Furthermore, it contributes to the literature on carefulness by exploring the interaction between a stock market approach and the lay belief that algorithms lack the capability to deliberate carefully.

This study aims to empirically investigate the impact of adopting big data and data analytics (BD&A) on audit quality (AQ).

A questionnaire was distributed among audit practitioners working at audit firms in Egypt and 205 responses were collected. Partial least square structural equation modeling (PLS-SEM) was used to analyze and test research hypotheses.

The results reveal that BD&A has a direct significant positive effect on the audit process (AP) and auditor competence (AC). However, an insignificant impact of BD&A is found on audit fees (AF). In addition, the results indicate that BD&A has significant positive direct and indirect impacts on AQ.

The results of this study will benefit several auditing stakeholders, such as audit firms, audit regulators, novice financial auditors and academic scholars.

This research is one of the earliest to empirically address the role of BD&A in enhancing AQ. It incorporates AP, AC and AF as mediators into a single model to explain the impact of BD&A on AQ. Also, it attempts to provide empirical evidence from a developing country with a less-regulated audit environment.

Grounded on the distributed theory and the social exchange theory, the current study investigates the determinants that positively influence job performance among educators within the realm of higher education in India. It particularly assesses the impact of perceived academic leadership on performance and explores the mediating and moderating effects of organizational citizenship behavior and informal institutional leadership.

Employing a descriptive research design, this study encompasses a broad cross-section of faculty members from various higher educational institutions across India. Data were gathered from 826 educators using a snowball sampling technique, with questionnaires administered online. Each variable was measured using prevalidated scales.

The findings from the moderated mediation model indicate a significant indirect relationship between perceived academic leadership and job performance, which is mediated by organizational citizenship behavior. Furthermore, informal institutional leadership demonstrates significant conditional indirect effects, enhancing the link between academic leadership and job performance up to a threshold, beyond which its influence diminishes.

This study pioneers the exploration of academic dynamics beyond mere titles and ranks in the Indian educational sector. It delineates both the direct and indirect roles these dynamics play in enhancing faculty performance, providing a novel insight into the complexities of academic leadership.

Energy-related financial literacy (ERFL) which consists of energy literacy, financial literacy and lifecycle cost literacy, can play an instrumental role in addressing climate change by ensuring efficient energy consumption (macro level benefit) and promoting financial well-being (micro level benefit) of households. This study aims to highlight the ERFL level and its effect on the energy consumption of the sample households in the state of West Bengal, India.

The study used primary data on 155 sample households from the two districts, i.e. Hooghly and North 24 Parganas in West Bengal, India, surveyed from September 2022 to November 2022 using a structured questionnaire. The study used the conceptual framework suggested by Blasch et al. (2018) to measure the ERFL. Pertinent statistical techniques and the ordinary least square regression method were used to attain the objectives of the study.

The outcome of the study showed that the average ERFL score was found to be moderate (63%). The findings of the study also indicated that the ERFL exerts a positive influence on reducing energy consumption among the sample households in India.

There is a dearth of research studies on the topic of ERFL around the globe. The very few studies so far conducted are mostly in the context of European economies and Nepal. Perhaps, to the best of the our knowledge, this is the first study on the issue of ERFL in the Indian context. Therefore, the present study will make an original contribution to the small but growing scholarship on ERFL.

This study analyzes the role of cooperative behavior in facing the risk of encouraging innovative agricultural production projects by small-scale farmers in the context of farmers in developing countries.

A within-subjects field experiment was conducted with small-scale Colombian panela cane farmers. The authors used the collected data to run the regression analyses.

The results suggest that when small farmers can follow cooperative behavior by joining a group and pooling resources to face risk, they are more willing to invest in a novel and profitable alternative, albeit riskier. However, the possibility of cooperating with a group to invest in a novel production project depends on its expected risk level.

These results will help develop agricultural policies for sustainable development. Establishing informal networks for small-scale farmers to deal with unpredictable risks may aid in developing innovative systems.

Agriculture is highly vulnerable to climatic impacts, which, combined with the inherent risk of innovation, may reduce small farmers' willingness to adopt innovation. Cooperation appears to be a mechanism for pooling resources and facing risk.

Research has focused on experimentally testing the effect of cooperative behavior when facing risk. The authors contribute to the literature by demonstrating the impact of the ability of small-scale farmers in rural areas to collectively manage risk on investment in innovative projects.