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This paper aims to introduce the goal-oriented requirements extraction approach (GOREA). It is an elicitation approach that uses, specifically, healthcare business goals to derive the requirements of e-health system to be developed.

GOREA consists of two major phases: (1) modelling e-health business requirements phase and (2) modelling e-health information technology (IT) and systems requirements phase. The modelling e-health business requirements phase is divided into two main stages: (1) model e-health business strategy stage and (2) model e-health business environment stage. The modelling e-health IT and systems requirements phase illustrates the process of obtaining requirements of e-health system from the organizational goals that are determined in the previous phase. It consists of four main steps that deal with business goals of e-health system: (1) modelling e-health business process (BP) step; (2) modelling e-health business goals step; (3) analysing e-health business goals step; and (4) eliciting e-health system requirements step. A case study based on the basic operations and services in hospital emergency unit for checking patient against COVID-19 virus and taking its diagnostic testing has been set and used to examine the validity of the proposed approach by achieving the conformance of the developed system to the business goals.

The results indicate that (1) the proposed GOREA has a positive influence on the system implementation according to e-health business expectations; and (2) it can successfully fulfil the need of e-health business in order to save the citizens life by checking them against COVID-19 virus.

The proposed approach has some limitations. For example, it is only validated using one e-health business goal and thus it has to be authenticated with different e-health business goals in order to address different e-health problems.

Many e-health projects and innovations are not established based on robust system requirements engineering phase. In order to ensure the success delivery of e-health services, all characteristics of e-health systems and applications must be understood in terms of technological perspectives as well as the all system requirements.

This study evaluated the impact of a faculty training program on student assessment using the Kirkpatrick model.

A self-reported survey assessed 111 Saudi and non-Saudi participants' satisfaction. Subjective and objective measures (self-reported measures, assessment literacy inventory and performance-based assessment tasks) gauged participants' learning level. Pre- and post-training data were collected from 2020 to 2022.

A highly significant effect on satisfaction (>80%) and learning levels was observed, as manifested by workplace practices of student assessment (>70%, the cut-off score). Pre- and post-training comparisons of participants' satisfaction and assessment literacy scores showed significant improvements following training. Multiple regression analyses showed no significant effects for gender and educational attainment but a substantial impact of academic cluster on participants' student assessment skills.

Long-term effects of training faculty on assessment practices and student achievement will be studied at the institutional level in future research.

The current study contributes to human capital investment via faculty training on student assessment, helping them comply with assessment best practices. This assures the quality, fairness and consistency of assessment processes across disciplines in higher education institutions, enhances assessment validity and trust in educational services and may support institutional accreditation.

This study provides opportunities for sharing best practices and helps establish a community of practice. It enhances learning outcomes achievement and empowers higher education graduates with attributes necessary to succeed in the labor market. The human capital investment may have a long-term impact on overall higher education quality.

This study contributes to the scarce literature investigating the impact of training faculty from different clusters on student assessment using subjective and objective measures. It provides developing and evaluating a long-term student assessment program following the Kirkpatrick model.

The basic intention of this research is to investigate the role of information transparency of financial institutions and psychological attitude of the individuals toward their attention to saving and borrowing. This study also tries to know how an individual's psychological factor affects a person's attitude to motivate them to save or borrow and contribute to well-being by giving them confidence that they can face financial challenges. So, the main concern of this study is to explore different factors that ultimately contribute to the financial well-being (FWB) of individual.

A survey was conducted by using a well-structured questionnaire to collect data and test the developed hypotheses by using SmartPLS. Data were collected from 120 customers of seven different commercial banks in Pakistan.

The findings of this study show that perceived information transparency positively affects FWB. It is also because transparent shared information creates positive change in individuals' perceived self-efficacy and leads to FWB. Furthermore, an individual's psychological attitude toward borrowing and saving did not contribute to the FWB of people who belong to Pakistan.

The research area is limited to one city of Pakistan and analysis is done with small numbers of sample, it can be increased and more areas can be explored.

This research provides significant implications for people and economists by providing awareness about the antecedents of FWB. The policymakers or managers who work in financial institutions should provide more transparent information and create less risky opportunities to improve the individual's well-being. If person, manager and financial institution can properly utilize the information of this study, then they are able to improve their FWB. By providing more transparent services and favorable experience with your dealings, it could help to obtain and retain more loyal internal (employees) and external customers. The loyal customers and sincere employees can increase the productivity level of organization. The more productive organizations in countries means better society and progress in the economy.

This research contributes to the body of knowledge that how perceived information transparency and psychological attitude of borrowing create improvement and upward changes in the FWB of a person.

Indian patients have different medicine systems available at the service that alter their healthseeking behaviour (HSB). This study aims to examine the beliefs and behaviour of patients in India towards the healthcare system and how it affects their intention to use healthcare chatbots.

A survey instrument was developed from standard scales and validated by experts. The data was collected from 397 respondents in an urban area and tested using a structural equation model in SAS JMP software.

The study found that awareness and perception of chatbots and distrust on doctors and health systems impact trust in a chatbot. The results show that trust in chatbots influences the intention to use chatbots. The belief in alternative medicine systems and HSB also influence the intention to use chatbots. The study findings also imply that health-care chatbots should cater to HSB and the belief in alternative medicine.

The study was conducted only among the urban population because services based on technology are more available in metro cities. Bengaluru is considered the representative population of urban India.

The level of disruption that chatbots can provide to the healthcare system makes this study significant. The study findings will help to manage the factors that can enable chatbot inclusivity, as the current system is inaccessible to many patients.

This paper addresses an identified need to study patients’ trust in the Indian healthcare system and their intention to use chatbots. The level of disruptions these chatbots can cause in the health-care system is undeniable and patients’ trust in these chatbots will eventually transform the health-care sector.

This research investigates the barriers for Complementary and Alternative Medicine (CAM) adoption among the patients in India. Despite the established role of CAM in the Indian healthcare system for several years, the WHO (WHO) reports limited adoption of these therapies among Indian patients. This study investigates the key barriers toward wider CAM use within the Indian context.

This study used a combined interpretive structural modeling (ISM)-MICMAC approach to identify barriers to CAM usage. In the first phase, a comprehensive literature review was conducted to understand the barriers. Subsequently, experts in the Indian healthcare system were identified and interviewed to capture the contextual intricacies of these barriers within the Indian context.

The study identified ten key barriers to CAM adoption through ISM. A hierarchical model was developed to understand the relationships and interactions among these barriers, revealing their linkages. A MICMAC chart was created to determine the driving and dependent power of the barriers, categorizing them as dependent barriers, linkage barriers or independent barriers. The House of CAM framework was then derived from the ISM-MICMAC analysis, providing a structured, sequential approach for CAM adoption.

The awareness of the potential benefits and usage of CAM is significantly low among Indian patients. There is a pressing need to investigate and systematically conceptualize the barriers to CAM adoption. This research provides valuable insights for policymakers, insurers, practitioners of alternative and complementary medicine, multi-specialty hospitals offering CAM services and regulatory bodies. Understanding these barriers will enable these stakeholders to develop and implement strategies that effectively address these issues.

This research makes substantial contributions to the understanding of barriers to the adoption of CAM. Through a comprehensive investigation, the study introduces the House of CAM framework developed using ISM-MICMAC analysis, providing a strategic approach for targeted intervention against identified barriers.