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The study aims to drive conceptual clarity around resistance to information technology projects, integrating multiple facets of the phenomenon from earlier studies.

The study conducts a meta-synthesis of qualitative studies on resistance to technology projects; it analyzes those studies at a case-specific level, compares and contrasts emergent concepts against each other, and “translates” those to the rest of the studies. The study uses the seven-step meta-ethnography method by Noblit and Hare to reciprocally translate emergent concepts to construct the conceptual model.

Through meta-synthesis, the study derives a new conceptual model for resistance to information technology projects, exemplifying how the identified antecedents create user resistance and how the phenomenon progresses within organizations.

This study enriches the observations and conclusions of past individual studies while explicating various facets of the mechanisms that generate and progress technology resistance within organizations. It offers fresh insights into the equivocal nature of the phenomenon and the distinctive ways it progresses from individual to group level.

Many ambitious and costly digital transformation efforts do not succeed due to user resistance. Understanding the mechanisms that create user resistance can help organizations manage technology projects better, thereby reducing the technology assimilation gap and protecting returns on related investments.

There have been extensive studies on technology acceptance (enablers) within organizations, while those relating to technology inhibitors are somewhat limited. However, the symmetry of understanding between enablers and inhibitors is vital for organizations to assimilate promising technologies and transform their business models. This model uses a new lens of sensemaking theory to explain how the antecedents trigger perceived threats and resistance behavior; it highlights the nuances around the development of resistance within individuals and its progression to groups. The resultant model offers better generalizability in organizational contexts.

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.

This study aims to co-develop a Frailty, Health and Care Needs Assessment (FHCNA) questionnaire for people experiencing homelessness and explore the feasibility of its use by non-clinical staff in homeless hostels.

The FHCNA, aimed at identifying frailty and other health and care priorities for people experiencing homelessness, was co-designed in workshops (online and in person) with homelessness and inclusion health staff. Its feasibility was tested by staff and their clients in two hostels, with pre- and post-study focus groups held with hostel staff to gain input and feedback.

The FHCNA was co-developed and then used to collect 74 pairs of resident and key worker inputted data (62% of eligible hostel residents). The mean age of clients was 48 years (range 22–82 years). High levels of unmet need were identified. Over half (53%) were identified as frail. Common concerns included difficulty walking (46%), frequent falls (43%), chronic pain (36%), mental health issues (57%) and dental concerns (50%). In total, 59% of clients reported difficulty in performing at least one basic activity of daily living, while only 14% had undergone a Care Act Assessment. Hostel staff found using the FHCNA to be feasible, acceptable and potentially useful in facilitating explorations of met and unmet health and social care needs of hostel clients. By identifying unmet needs, the FHCNA has the potential to support staff to advocate for access to health and social care support.

To the best of the authors’ knowledge, this is the first study to co-develop and feasibility test a questionnaire for use by non-clinically trained staff to identify frailty and other health and care needs of people experiencing homelessness in a hostel setting.

Paramedics are responsible for managing emergencies, caring for patients and performing life-saving procedures under heavy workloads, which can have a significant negative effect on their emotional eating and food addiction (FA) behaviors. Thus, this cross-sectional study aims to shed light on the relationship between emotional eating tendencies and FA in paramedics by considering their food preferences, sex, and body mass index (BMI) factors.

The questionnaire consisted of Yale Food Addiction Scale and Emotional Eating Questionnaire (EEQ), as well as sex, age, weight, height and number of snacks and main meals collected face-to-face from the 196 paramedics.

The FA prevalence was 14.9%, and more than half of the paramedics were emotional eaters. The total score of the EEQ was significantly higher in the FA diagnosed group than in the group FA not diagnosed (p < 0.001). The food preferences of the paramedics were found to differ significantly depending on whether they were diagnosed with FA or emotional eating. Being a food addict or emotional eater significantly increases the odds of consuming chocolate-wafer, pie-cake, chips, pastries, pasta and fries (p < 0.05), and participants with FA diagnosis and emotional eaters were more likely to prefer these foods than those with nondiagnosis and nonemotional eaters (p < 0.05).

Findings highlighted the connection between FA and the emotional eating behavior of paramedics, indicating that they attempt to compensate for their emotional ups and downs through eating. The job-related stress and emotional eating behaviors of paramedics may increase their BMI and susceptibility to FA.

To replicate and extend research on psychopathy and intrinsic interpersonal preferences under the broader umbrella of affiliation, intimacy and antagonism, this paper aims to examine motivational correlates of psychopathy in a nonclinical sample (N = 125).

We used a multimethod design, including self-reports, a behavioral task and a physiological assessment of motive dispositions (automatic affective reactions to stimuli of interpersonal transactions measured with facial electromyography).

Results showed that self-reported psychopathy was negatively associated with self-reported intimacy motive. In the same vein, via the social discounting task, this paper found a negative association between psychopathy and a tendency to share hypothetical monetary amounts with very close others. Finally, regarding fEMG findings, multilevel analyses revealed that although individuals with low levels of psychopathy reacted more positively to affiliative stimuli, individuals with high levels of psychopathy reacted equally positively to both affiliative and antagonistic stimuli, and these results were robust across psychopathy measures. Results remained mostly unchanged on the subscale level.

These findings highlight the contribution of multimethod assessments in capturing nuances of motivation. Implicit physiological measures might be particularly sensitive in capturing motive dispositions in relation to psychopathy. Identifying mechanisms that foster positive connections between psychopathic traits and nonprosocial tendencies may be theoretically and clinically informative, with implications for forensic and penal practices.

This paper aims to reflect on the outcomes of a community-based video-conferencing intervention for depression, predating the COVID-19 pandemic. The study investigates the potential implications of its findings for enhancing adherence to digital mental health interventions. The primary objective is to present considerations for researchers aimed at minimising the intention-behaviour gap frequently encountered in digital mental health interventions.

A randomised control feasibility trial design was used to implement a telehealth model adapted from an established face-to-face community-based intervention for individuals clinically diagnosed with depression. In total, 60 participants were initially recruited in association with a local mental health charity offering traditional talking-based therapies with only eight opting to continue through all phases of the project. Modifications aligning with technological advancements were introduced.

However, the study faced challenges, with low uptake observed after an initial surge in recruitment interest. The behaviour-intention gap highlighted technology as a barrier to service accessibility, exacerbated by participant age. Furthermore, the clinical diagnosis of depression, characterised by low mood and reduced interest in activities, emerged as a potential influencing factor.

The limitations of the research include its pre-pandemic execution, during a nascent stage of technological mental health interventions when participants were less familiar with online developments.

Despite these limitations, this study's reflections offer valuable insights for researchers aiming to design and implement telehealth services. Addressing the intention-behaviour gap necessitates a nuanced understanding of participant demographics, diagnosis and technological familiarity.

The study's relevance extends to post-pandemic society, urging researchers to reassess assumptions about technology availability to ensure engagement. This paper contributes to the mental health research landscape by raising awareness of critical considerations in the design and implementation of digital mental health interventions.

Reflections from a pre-pandemic intervention in line with the developments of a post-pandemic society will allow for research to consider that because the technology is available does not necessarily result in engagement.

Current and predicted continued dramatic increases in international migration and ethnocultural diversity of older adult cohorts pose challenges for health care services. Review studies on ethnoculturally diverse older adults and health care show a lack of focus on their service use experiences. This study aims to report a meta-ethnography that addresses this knowledge gap through answering the review question: How do ethnoculturally diverse older adults who are immigrants experience health careservices?

The authors applied a seven-phase method of meta-ethnography to guide the review. The authors conducted two literature searches (April 2018 and June 2020) in MEDLINE, CINAHL, Embase, Sociological Abstracts and Abstracts in Social Gerontology that yielded 17 papers eligible for review.

“There’s always something positive and something negative” is the overarching metaphor for answering the review question. Findings highlight positive and negative tensions within ethnoculturally diverse older adults’ health care use experiences of understanding and being understood, having trust in providers and the health care system, having needs, preferences and resources met and desire for self-care over dependency. The majority of experiences were negative. Tipping points towards negative experiences included language, fear, provider attitudes and behaviours, service flexibility, attitudes towards Western and traditional health care and having knowledge and resources.

The authors propose concrete actions to mitigate the tipping points. The authors discuss policy recommendations for health care system changes at the micro, meso and macro service levels to promote positive experiences and address mainstream service policy inequities.

An abundance of techniques has been presented so forth for waste classification but, they deliver inefficient results with low accuracy. Their achievement on various repositories is different and also, there is insufficiency of high-scale databases for training. The purpose of the study is to provide high security.

In this research, optimization-assisted federated learning (FL) is introduced for thermoplastic waste segregation and classification. The deep learning (DL) network trained by Archimedes Henry gas solubility optimization (AHGSO) is used for the classification of plastic and resin types. The deep quantum neural networks (DQNN) is used for first-level classification and the deep max-out network (DMN) is employed for second-level classification. This developed AHGSO is obtained by blending the features of Archimedes optimization algorithm (AOA) and Henry gas solubility optimization (HGSO). The entities included in this approach are nodes and servers. Local training is carried out depending on local data and updations to the server are performed. Then, the model is aggregated at the server. Thereafter, each node downloads the global model and the update training is executed depending on the downloaded global and the local model till it achieves the satisfied condition. Finally, local update and aggregation at the server is altered based on the average method. The Data tag suite (DATS_2022) dataset is used for multilevel thermoplastic waste segregation and classification.

By using the DQNN in first-level classification the designed optimization-assisted FL has gained an accuracy of 0.930, mean average precision (MAP) of 0.933, false positive rate (FPR) of 0.213, loss function of 0.211, mean square error (MSE) of 0.328 and root mean square error (RMSE) of 0.572. In the second level classification, by using DMN the accuracy, MAP, FPR, loss function, MSE and RMSE are 0.932, 0.935, 0.093, 0.068, 0.303 and 0.551.

The multilevel thermoplastic waste segregation and classification using the proposed model is accurate and improves the effectiveness of the classification.

Coronavirus disease 2019 (COVID-19) pandemic has led to unprecedented mental health repercussions in the lives of every individual including university students. Therefore, study on students’ psychological state and its associated factors during the pandemic are of importance. This study aims to discuss the aforementioned issue.

An online survey was done on a total of 207 university students of Pakistan to collect information on socio-demographic characteristics, concerns or fears amidst COVID-19 and mental distress. Validated tools; Perceived Stress Scale (PSS), Generalized Anxiety Disorder Scale (GAD-7) and Patient Health Questionnaire (PHQ-9)-Depression were used to assess stress, anxiety and depression, respectively.

Around 14% of the university students were experiencing severe stress and anxiety, while 8.2% had severe depression. The authors found that stress among university students was related to psychiatric illness or symptoms (OR = 5.1: 1.1, 22.9) and unpredictability due to the pandemic (OR = 3.7: 1.2, 11.2). The significant determinants of anxiety were psychiatric illness/symptoms (OR = 6.6: 3.4, 12.9), implementation of public health measures (OR = 3.7: 1.1, 11.6), employed mothers (OR = 2.4: 1.1, 5.0) and lack of support from university administration (OR = 2.2: 1.0, 5.0). While the factors associated with depression included psychiatric illness or symptoms (OR = 8.4: 3.3, 21.5), unpredictability due to pandemic (OR = 6.8: 2.2, 20.7), impaired social support system (OR = 3.7: 1.3, 10.4) and studying without a scholarship (OR = 2.1: 1.0, 4.4).

These findings call for an urgent need to develop appropriate interventions and educational programs that could address the psychological needs of students.

The study directs the role of university and faculty in dealing the mental health needs of the student in COVID-19 pandemic time.

Educational programs are important that could address the psychological needs of students in COVID-19 pandemic.

University students reported mental distress during COVID-19 pandemic which shows that younger people are at risk of COVID-19 repercussions. Moreover, several stressors (i.e. impaired social support system and lack of support from universities) were revealed that could be mitigated by implementing appropriate strategies.