Data Collection Plan Research Articles

Development of Electronic Business Management Information System At Trinita Elektro Manado Store

The purpose of the study was to determine the results of the development of an electronic business management information system and to produce a valid, practical, and efficient electronic business management management information system at the Trinita Elektro Store. The type of research used is research and development or Research and Development (R&D) using the Borg & Gall development model whose research and development steps consist of data collection and initial planning, product development (initial product), product validation, product revision. , product trial 1, product revision 2, product trial 2 and (8) final product (dissemination and implementation). The subjects in this study were business owners, technicians, cashiers, and customers at the Trinita Elektro Store. Data collection techniques using literature studies, interviews and questionnaires / questionnaires. The instruments used are expert validation sheets and product trial questionnaires. While the data analysis technique used is quantitative descriptive analysis. The results showed that the electronic business management information system was feasible to be tested after being validated by design experts and materials experts at the address https://trinitaelektro.website/.
 Keywords : research and development, management information system, electronic business.

Statistical perspectives on reliability of artificial intelligence systems

Artificial intelligence (AI) systems are increasingly popular in many applications. Nevertheless, AI technologies are still developing, and many issues need to be addressed. Among those, the reliability of AI systems needs to be demonstrated so that AI systems can be used with confidence by the general public. In this paper, we provide statistical perspectives on the reliability of AI systems, focusing on the time dimension. That is, the system can perform its designed functionality for the intended period of time. We introduce a so-called “SMART” statistical framework for AI reliability research, which includes five components: Structure of the system, Metrics of reliability, Analysis of failure causes, Reliability assessment, and Test planning. We review traditional methods in reliability data analysis and software reliability, and discuss how those existing methods can be transformed for reliability modeling and assessment of AI systems. Different from traditional reliability studies, the focus of AI reliability is on the software system to include the training data. Thus, we describe recent developments in modeling and analysis of AI reliability for software systems. The paper outlines statistical research challenges in this area, including out-of-distribution detection, the effect of the training set, adversarial attacks, model accuracy, and uncertainty quantification. We discuss how those topics can be related to AI reliability, with illustrative examples. The final element of SMART (test planning), is critical for the demonstration of AI reliability. Therefore we discuss data collection and testing planning, highlighting methods for improving system design in order to achieve higher AI reliability. The paper closes with some concluding remarks.

WASTE MANAGEMENT SITES - REDUCE, REUSE, AND RECYCLE (TPS3R) CONSTRUCTION STUDY IN SEKANAK AREA, PALEMBANG CITY

In Palembang, one of Indonesia's major municipalities, there were several challenges with the solid waste management system, notably in families. Adopting the 3R strategy to reduce waste production is one way to address the waste problem in Palembang (reuse, reduce, recycle). The Reduce-Reuse-Recycle Waste Management Site, or TPS3R, is located in Indonesia. It follows a pattern of waste management on a local or regional scale. One of the numerous tributaries of the Musi River, a significant river in this city that passes through Palembang, is the Sekanak River. The accumulation of waste in the drainage channel and its tributaries is one of the factors contributing to the decline in river water quality. Near the center of the city, the Sekanak region extends along the river's about 10-meter-wide course. Due to the fact that many residents who live close to rivers neglect waste management, the quality of the river water is damaged. It is projected that the TPS3R construction will be able to address the waste issue in the Sekanak area by looking at social, technological, and TPS3R feasibility development factors. The approach of the feasibility study is made up of the stages of work activities, preparatory activities, field surveys, data collection, analytical activities, and activity plan recommendations. The total investment cost for the 15 m × 20 m facility that makes up TPS3R is IDR 290,824,000. The cost of building the infrastructure and purchasing the equipment are included in this amount. Over the course of four days, the weight of organic waste per person per day ranged from 259.60 to 395.07 grams, with an average of 307.12 grams, whereas the weight of non-organic trash per day ranged from 114.02 to 188.85 grams. Average daily intake is 149.34 grams per person

COVID-19 data driven planning: The SouthEast Texas approach.

This coautoethnographic case study used the Open-Source Public Health Intelligence process to explore and share the South East Texas Regional Advisory Councils' (SETRAC) experience in collecting, processing, disseminating/visualizing, and analyzing COVID-19 data during the pandemic in the largest national medical setting in the United States. Specifically, it details the production of Business Intelligence reports powered by PowerBI both with general publics and with Regional Healthcare Preparedness Program (HPP) Coalition Coordinators, County Judges and City Mayors, Texas Department of State Health Services (DSHS) executive leadership, the Offices of the Texas Governor, and the Federal Pandemic Task Force led by the US Vice President, in order to provide a foundation for situational awareness, inter-regional collaboration, allocation of scare resources, and local, regional, and state policy decisions. It highlights best practices in risk and crisis communications during the COVID-19 response, underscores cross-sector collaboration and standardization of data collection for effective planning and response, discusses pervasive data revealed during the analysis, and evaluates collaborative and feedback processes that have implications for the Health Care System and Homeland Security Enterprise information sharing.

Using the Census Planning Database to Generate Differential Expected Yield Rates to Self-administered Mail Surveys

Expected yield rates are essential to a survey’s data collection plan, as they inform requisite sample sizes to meet the survey’s objectives. Given an overall expected yield rate for a self-administered mail survey, this short take describes a simple method for using the Census Planning Database to assign differential yield rates to lower-level geographies within the study area.

Registration and primary outcome reporting in behavioral health trials

BackgroundRegistration of research studies is designed to lock investigators into a data collection and analysis plan before a study starts and thereby limit their ability to engage in flexible data analysis and selective outcome reporting. Studies of registered clinical trials show that one- to two-thirds are registered after the study has started and that non-adherence to important design and analytic features, such as reporting data pertaining to all primary outcomes, remains high. Less is known about the effects of registration on research transparency and integrity outside of clinical trials. To address this gap in knowledge, the current study examined the effects of registration on the reporting of research findings in a sample of behavioral health trials published in BMC Public Health.MethodsRegistered trials published in the BMC Public Health section “Health Behavior, Health Promotion and Society” between 2011 and 2015 were included in the study. For each trial, we reviewed associated online submissions from 13 different registration sites. For those determined to have been prospectively registered, we used the trial registry, MEDLINE (Pubmed), PsychINFO, Web of Science and e-mails to investigators to identify subsequent publications from the study that reported results pertaining to primary outcomes. The two investigators then independently reviewed the outcome publication(s) and compared the primary outcomes reported in these to the registered primary outcomes.ResultsThe final analytic sample comprised 136 locatable, registered trials with an identifiable start date. Sixty-eight of the 136 were prospectively registered. Among these prospectively registered trials, only 16 published manuscripts reported outcomes and methods that were concordant with their registrations.ConclusionsRetrospective submission of protocols for publication and retrospective registration remain common in public health research, and adherence to prespecified outcomes is rare. In its current form, registration of behavioral and health promotion trials is likely to have minimal effect on preventing selective outcome reporting in publications, and the pervasiveness of vague and incomplete registry entries means that registries will have limited utility in terms of facilitating replication studies.

Implementing effective community-based surveillance in research studies of maternal, newborn and infant outcomes in low resource settings

BackgroundGlobally adopted health and development milestones have not only encouraged improvements in the health and wellbeing of women and infants worldwide, but also a better understanding of the epidemiology of key outcomes and the development of effective interventions in these vulnerable groups. Monitoring of maternal and child health outcomes for milestone tracking requires the collection of good quality data over the long term, which can be particularly challenging in poorly-resourced settings. Despite the wealth of general advice on conducting field trials, there is a lack of specific guidance on designing and implementing studies on mothers and infants. Additional considerations are required when establishing surveillance systems to capture real-time information at scale on pregnancies, pregnancy outcomes, and maternal and infant health outcomes.Main bodyBased on two decades of collaborative research experience between the Kintampo Health Research Centre in Ghana and the London School of Hygiene and Tropical Medicine, we propose a checklist of key items to consider when designing and implementing systems for pregnancy surveillance and the identification and classification of maternal and infant outcomes in research studies. These are summarised under four key headings: understanding your population; planning data collection cycles; enhancing routine surveillance with additional data collection methods; and designing data collection and management systems that are adaptable in real-time.ConclusionHigh-quality population-based research studies in low resource communities are essential to ensure continued improvement in health metrics and a reduction in inequalities in maternal and infant outcomes. We hope that the lessons learnt described in this paper will help researchers when planning and implementing their studies.

Digitization of urban bicycling data

Urban bicycling data collection with mobile digital devices has become ubiquitous in cities across the globe in the last decade. However, planners, developers, data and city scientists often struggle to process, avoid biases, clean datasets, and select relevant data points, when processing, analyzing and modelling vast troves of data, when engineering applications for urban mobility. This paper aims to shed light on these data sources and bases using a descriptive and comparative analysis of the social layers embodied into this data. These ultimately and inadvertently might result in algorithmic analysis and predictive simulations with inadequate sensitivity and specificity outputs for desired requirements. Actors and social groups have vested and specific interests in these bicycling databases, which in turn shape data bases biases or disclosure policies. Therefore, their data will reflect mostly the way they interact with bicycles, cyclists and cities. How pervasive, available for academic research, and which uses are currently made with bicycling bulk data collections in the case of Berlin? Sixteen social groups that operate or hold digital bicycling data systems in that city are investigated. Results show that a clear distinction between the data produced by public and private social groups, as different uses and disclosure polices for it are identified. These contrasts significantly reduce the range of models and applications that can derive from this data. In the development of diagnostic and prognostic systems, public owned are more suitable, whereas private is for commercial application. Digitization of urban bicycling data appeared to produce different data quality and quantity. The brief description and grouping of a specific sociotechnical ensemble dynamic, such as the one conducted here, is particularly useful for the early stages of research, data collection planning and modelling, and in the design of requirements for technology development.

Energy Aware Data Collection with Route Planning for 6G Enabled UAV Communication

With technological advancements in 6G and Internet of Things (IoT), the incorporation of Unmanned Aerial Vehicles (UAVs) and cellular networks has become a hot research topic. At present, the proficient evolution of 6G networks allows the UAVs to offer cost-effective and timely solutions for real-time applications such as medicine, tracking, surveillance, etc. Energy efficiency, data collection, and route planning are crucial processes to improve the network communication. These processes are highly difficult owing to high mobility, presence of non-stationary links, dynamic topology, and energy-restricted UAVs. With this motivation, the current research paper presents a novel Energy Aware Data Collection with Routing Planning for 6G-enabled UAV communication (EADCRP-6G) technique. The goal of the proposed EADCRP-6G technique is to conduct energy-efficient cluster-based data collection and optimal route planning for 6G-enabled UAV networks. EADCRP-6G technique deploys Improved Red Deer Algorithm-based Clustering (IRDAC) technique to elect an optimal set of Cluster Heads (CH) and organize these clusters. Besides, Artificial Fish Swarm-based Route Planning (AFSRP) technique is applied to choose an optimum set of routes for UAV communication in 6G networks. In order to validated whether the proposed EADCRP-6G technique enhances the performance, a series of simulations was performed and the outcomes were investigated under different dimensions. The experimental results showcase that the proposed model outperformed all other existing models under different evaluation parameters.

401(k) Plan Asset Allocation, Account Balances, and Loan Activity in 2019

The Employee Benefit Research Institute (EBRI) and the Investment Company Institute (ICI) have been collaborating for the past four years to collect data on participants in 401(k) plans. This effort, known as the EBRI/ICI Participant-Directed Retirement Plan Data Collection Project, has obtained data for 401(k) plan participants from certain of EBRI and ICI members serving as plan record keepers and administrators. The EBRI/ICI database is large and representative of the 401(k) plan participant universe, as it pulls data from a variety of plan record keepers and administrators and covers a wide range of plan sizes. This report includes 1999 information on 10.3 million active participants in 32,674 plans with $573.4 billion in assets. The 1999 EBRI/ICI database accounts for 11 percent of all 401(k) plans, 26 percent of all 401(k) participants, and about 35 percent of the assets held in 401(k) plans. Key findings include: (1) For all 401(k) participants in the 1999 EBRI/ICI database, three-quarters of plan balances are invested directly or indirectly in equity securities. (2) The average account balance (net of plan loans) for all participants was $55,502 at year-end 1999, which is 18 percent higher than the average account balance at year-end 1998. (3) Investment options offered by plan sponsors influence participants' asset allocation. (4) The asset allocation of participants' account balances varies with age. Younger participants tend to concentrate their assets in equity fund investments, while older participants invest more in fixed-income securities.

Improving access to cardiac rehabilitation in rural and remote areas: a protocol for a community-based qualitative case study

Background/AimsHeart disease is the largest single cause of death and contributes to poor quality of life and high healthcare costs in Australia. There are higher rates of heart disease in rural and remote areas, with the highest rates in Aboriginal and Torres Strait Islander people. Cardiac rehabilitation is known to improve health outcomes for people with heart disease but referral rates remain low (30.2% overall and 46% following acute coronary syndrome) in Australia. Further, access to cardiac rehabilitation in rural and remote areas is affected by there being few centre-based services, and poor use of home-based services. The aim of this protocol is to investigate: (i) understanding of cardiac rehabilitation by health staff, community leaders and community participants discharged from hospital following treatment for heart disease; (ii) access and support for cardiac rehabilitation in rural and remote areas via health service availability in each community.MethodsA qualitative case study methodology, using an interpretive descriptive framework, will be used together with content analysis that will encompass identification of themes through a deductive/inductive process.ConclusionsTo improve access to services and health outcomes in rural and remote areas, a strong evidence base is essential. To achieve this, as well as having appropriate methodology, it is necessary to build relationships and trust with local communities and healthcare providers. This research protocol describes a qualitative community-based case study, together with processes to build sound relationships required for effective data collection through semi-structured interviews or focus groups. Each step of the pre-research planning data collection and analysis is described in detail for the guidance of future researchers.

The National Health and Nutrition Examination Survey (NHANES), 2021-2022: Adapting Data Collection in a COVID-19 Environment.

The National Health and Nutrition Examination Survey (NHANES) is a unique source of national data on the health and nutritional status of the US population, collecting data through interviews, standard exams, and biospecimen collection. Because of the COVID-19 pandemic, NHANES data collection was suspended, with more than a year gap in data collection. NHANES resumed operations in 2021 with the NHANES 2021-2022 survey, which will monitor the health and nutritional status of the nation while adding to the knowledge of COVID-19 in the US population. This article describes the reshaping of the NHANES program and, specifically, the planning of NHANES 2021-2022 for data collection during the COVID-19 pandemic. Details are provided on how NHANES transformed its participant recruitment and data collection plans at home and at the mobile examination center to safely collect data in a COVID-19 environment. The potential implications for data users are also discussed. (Am J Public Health. 2021;111(12):2149-2156. https://doi.org/10.2105/AJPH.2021.306517).

Correlates of the Adherence to a 24-hr Wrist-Worn Accelerometer Protocol in a Sample of High School Students

This study (a) compared accelerometer wear time and compliance between distinct wrist-worn accelerometer data collection plans, (b) analyzed participants’ perception of using accelerometers, and (c) identified sociodemographic and behavioral correlates of accelerometer compliance. A sample of high school students (n = 143) wore accelerometers attached to the wrist by a disposable polyvinyl chloride (PVC) wristband or a reusable fabric wristband for 24 hr over 6 days. Those who wore the reusable fabric band, but not their peers, were instructed to remove the device during water-based activities. Participants answered a questionnaire about sociodemographic and behavioral characteristics and reported their experience wearing the accelerometer. We computed non-wear time and checked participants’ compliance with wear-time criteria (i.e., at least three valid weekdays and one valid weekend day) considering two valid day definitions separately (i.e., at least 16 and 23 hours of accelerometer data). Participants who wore a disposable band had greater compliance compared with those who wore a reusable band for both 16-hr (93% vs. 76%, respectively) and 23-hr valid day definitions (91% vs. 50%, respectively). High schoolers with the following characteristics were less likely to comply with wear time criteria if they (a) engaged in labor-intensive activities, (b) perceived that wearing the monitor hindered their daily activities, or (c) felt ashamed while wearing the accelerometer. In conclusion, the data collection plan composed of using disposable wristbands and not removing the monitor resulted in greater 24-hr accelerometer wear time and compliance. However, a negative experience in using the accelerometer may be a barrier to high schoolers’ adherence to rigorous protocols.

Abstract 11270: Including the Patient’s Perspective in the Planning of Data Collection in the Recurrent Pericarditis Registry, RESONANCE

Introduction: In conjunction with pericardial disease physician specialists, industry experts, and recurrent pericarditis (RP) patients the RESONANCE Registry was designed to collect retrospective and prospective, longitudinal, observational data in real-world clinical practice across the United States (US). We aimed to collect data that were complete and meaningful in terms of patient experience and health related quality of life (HRQoL). Herein, we describe a novel patient-centric research approach to obtain feedback on evaluation tools for incorporation in the RESONANCE Registry (NCT04687358). Methods: Ten adult patients with a self-reported duration of disease ranging from 8 months to 25 years participated in an advisory board during which they provided feedback through a virtual platform. Their feedback informed development of multiple registry aspects. These included selection of patient reported outcomes measures (PROMs), to be collected every three months at prospective data collection timepoints, and design of several questionnaires, including evaluation of specific RP episode characteristics. Results: Prior to finalization, registry case report forms were optimized based on feedback provided by patients. Areas of data-capture informed by patient input included selection of PROMs to be assessed and patient-centric tools used for self-assessment of disease experience and HRQoL. For example, sections of a patient questionnaire were modified to include documentation of the presenting symptom, breathlessness, fear of episodes, and patient management of each episode. Conclusions: This patient-centered research collaboration resulted in enhancements to the RESONANCE Registry that enabled capture of information meaningful to patients’ daily experiences, preferences, and expectations. Patient participation in tangible aspects of research, including registry tools and design, can increase engagement with the communities that have a vested interest in improving patient care. In addition, patient involvement can help to ensure research efforts reflect the needs of not only the healthcare community but of patients alike, with an ultimate goal of improving clinical outcomes.

Planning the Design and Execution of Student Performance Assessment in Serious Games

Serious Games (SGs) are used to support knowledge acquisition and skill development. For this, there is a need to measure the results achieved (both during and after students play) to ensure the game effectiveness. In this context, the aim is to develop and evaluate the AvaliaJS, a conceptual model to structure, guide and support the planning of the design and execution of the student's performance assessment in SGs. AvaliaJS has two artifacts: a canvas model, for high-level planning, and an assessment project document, for more detailed specifications of the canvas. To analyze and exemplify the use of the model, the artifacts were applied to three ready-made games as a proof of concept. In addition, the quality of AvaliaJS was evaluated by experts in SGs development and assessment using a questionnaire. The results of experts' answers confirm a good internal consistency (Cronbach's alpha α = 0.87) which indicates that AvaliaJS is correct, authentic, consistent, clear, unambiguous and flexible. However, the model will need to be validated during the process of creating a new game to ensure its usability and efficiency. In general, AvaliaJS can be used to support the team in the planning, documentation and development of artifacts and data collection in SGs, as well as in the execution of the assessment, learning measurement and constant and personalized feedback for students.

Do I Have To Be An “Other” To Be Myself? Exploring Gender Diversity In Taxonomy, Data Collection, And Through The Research Data Lifecycle

Objective: Existing studies estimate that between 0.3% and 2% of adults in the U.S. (between 900,000 and 2.6 million in 2020) identify as a nonbinary gender or otherwise gender nonconforming. In response to the RDAP 2021 theme of radical change, this article examines the need to change how datasets represent nonbinary persons and how research involving gender data should approach the curation of this data at each stage of the research lifecycle. Methods: In this article, we examine some of the known challenges of gender inclusion in datasets and summarize some solutions underway. Using a critical lens, we examine the difference between current practice and inclusive practice in gender representation, describing inclusive practices at each stage of the research lifecycle from writing a data management plan to sharing data. Results: Data structures that limit gender to “male” and “female” or ontological structures that use mapping to collapse gender demographics to binary values exclude nonbinary and gender diverse populations. Some data collection instruments attempt inclusivity by adding the gender category of “other,” but using the “other” gender category labels nonbinary persons as intrinsically alien. Inclusive change must go farther, to move from alienation to inclusive categories. We describe several techniques for inclusively representing gender in data, from the data management planning stage, to collecting data, cleaning data, and sharing data. To facilitate better sharing of gender data, repositories must also allow mapping that includes nonbinary genders explicitly and allow for ontological mapping for long-term representation of diverse gender identities. Conclusions: A good practice during research design is to consider two levels of critique in the data collection plan. First, consider the research question at hand and remove unnecessary gendering from the data. Secondly, if the research question needs gender, make sure to include nonbinary genders explicitly. Allies must take on this problem without leaving it to those who are most affected by it. Further, more voices calling for inclusionary practices surrounding data rises to a crescendo that cannot be ignored.

BEXIS2: A FAIR-aligned data management system for biodiversity, ecology and environmental data.

BackgroundObtaining fit-to-use data associated with diverse aspects of biodiversity, ecology and environment is challenging since often it is fragmented, sub-optimally managed and available in heterogeneous formats. Recently, with the universal acceptance of the FAIR data principles, the requirements and standards of data publications have changed substantially. Researchers are encouraged to manage the data as per the FAIR data principles and ensure that the raw data, metadata, processed data, software, codes and associated material are securely stored and the data be made available with the completion of the research.New informationWe have developed BEXIS2 as an open-source community-driven web-based research data management system to support research data management needs of mid to large-scale research projects with multiple sub-projects and up to several hundred researchers. BEXIS2 is a modular and extensible system providing a range of functions to realise the complete data lifecycle from data structure design to data collection, data discovery, dissemination, integration, quality assurance and research planning. It is an extensible and customisable system that allows for the development of new functions and customisation of its various components from database schemas to the user interface layout, elements and look and feel.During the development of BEXIS2, we aimed to incorporate key aspects of what is encoded in FAIR data principles. To investigate the extent to which BEXIS2 conforms to these principles, we conducted the self-assessment using the FAIR indicators, definitions and criteria provided in the FAIR Data Maturity Model. Even though the FAIR data maturity model is developed initially to judge the conformance of datasets, the self-assessment results indicated that BEXIS2 remarkably conforms and supports FAIR indicators. BEXIS2 strongly conforms to the indicators Findability and Accessibility. The indicator Interoperability is moderately supported as of now; however, for many of the lesssupported facets, we have concrete plans for improvement. Reusability (as defined by the FAIR data principles) is partially achieved.This paper also illustrates community deployment examples of the BEXIS2 instances as success stories to exemplify its capacity to meet the biodiversity and ecological data management needs of differently sized projects and serve as an organisational research data management system.

Reducing Waste in Healthcare through Occupational Safety and Health Measures: A Study of Manufacturing Industries in Taiwan.

Occupational accidents and diseases cause the loss of valuable workers and lead to high healthcare expenses. Because occupational accidents and diseases are ascribed to inadequate working conditions and work environments, they can be prevented through a well-established occupational safety and health management system, which can ensure workers’ health and reduce the expense of healthcare. The study investigated the shortage of work-related occupational safety and health (OSH) measures in medium-sized manufacturing industries. This study mainly focused on qualitative interviews with 15 labor inspectors and 25 business executives from OSH participating to investigate the problems of occupational safety and health in the manufacturing industries in Taiwan. The results of a qualitative study show that the most important problems with OSH management are employers’ negligence and workers’ insufficient knowledge about OSH management. The research results revealed the following eighteen significant shortcomings of OSH management: employers care mostly about production profit and do not care much for OSH; OSH data collection and OSH planning are not suitable for the workplace; many managers of OSH affairs are not qualified, in terms of their professional or academic backgrounds; and the repair of workplaces’ roofs often results in falling accidents, especially before or after a typhoon, because of workers’ failure to use safety belts and/or to follow OSH guidelines. In order to address the shortcomings and bottlenecks, the study also presented recommendations for how to implement and revise the OSH Act and how to research and enhance OSH management. The results of this study will not only supply the Ministry of Labor (Taiwan) with data to plan the strategy of OSH management but also will allow employers and workers to improve OSH management in the workplace in order to prevent the occurrence of occupational accidents.

Behavioural Model for Decision-Makers’ towards the Intention to Adopt Green Information Technology: A Preliminary Study

This preliminary survey investigates and validates the measurement model of factors influencing decision makers’ intentions to adopt Green information technology (Green-IT) in manufacturing sectors in Nigeria. The Norm Activation Model (NAM) and Theory of Planned Behaviour (TPB) were used to explore the factors that could influence decision-makers’ intention in adopting Green-IT. Using constructs from the NAM and TPB, this survey proposes a model for identified behavioural factors. A quantitative research approach with a data collection and analysis plan using a cross-sectional survey design was adopted. A sample of 30 decision-makers in the top three manufacturing industries in Nigeria was selected using a purposive sampling procedure for participation in the study. The data collected was analysed using Partial Least Square Structural Equation Modelling (PLS-SEM) to test the proposed model. The model was validated in two phases: (i) Initial Measurement Model and (ii) Modified Measurement Model. Findings revealed that Green-IT Attitude, Subjective Norm, Ascription of Responsibility, Awareness of Consequences, Personal Norm, Environmental Concern, and Perceive Behavioural Control were the key elements of the behavioural intention model to adopt Green-IT, with 31 indicators having factor loadings of >0.5, adequate internal consistency reliability, CR > 0.7, and Cronbach’s Alpha, >0.7. The result revealed convergent validity, and acceptable discriminant validity was assessed using AVE > 0.5 and Fornell-lacker’s criterion. The results from the full-scale study would contribute to developing a context-specific model to examine Green-IT adoption in developing nations.

How to navigate the application of ethics norms in global health research: reflections based on qualitative research conducted with people with disabilities in Uganda

BackgroundAs Canadian global health researchers who conducted a qualitative study with adults with and without disabilities in Uganda, we obtained ethics approval from four institutional research ethics boards (two in Canada and two in Uganda). In Canada, research ethics boards and researchers follow the research ethics norms of the Tri-Council Policy Statement: Ethical Conduct for Research Involving Humans (TCPS2), and the National Guidelines for Research Involving Humans as Research Participants of Uganda (NGRU) in Uganda. The preparation and implementation of this qualitative research raised specific ethical issues related to research participant privacy and the importance of availability and management of financial resources.Main bodyOur field experience highlights three main issues for reflection. First, we demonstrate that, in a global health research context, methodological and logistic adjustments were necessary throughout the research implementation process to ensure the protection of study participants’ privacy, especially that of people with disabilities, despite having followed the prescribed Canadian and Ugandan ethics norms. Data collection and management plans were adapted iteratively based on local realities. Second, securing financial support as a key aspect of financial management was critical to ensure privacy through disability-sensitive data collection strategies. Without adequate funding, the recruitment of research participants based on disability type, sex, and region or the hiring of local sign language interpreters would not have been possible. Third, although the TCPS2 and NGRU underscore the significance of participants’ privacy, none of these normative documents clearly express this issue in the context of global health research and disability, nor broadly discuss the ethical issue related to financial availability and management.ConclusionsConducting research in resource limited settings and with study participants with different needs calls for a nuanced and respectful implementation of research ethics in a global health context. We recommend a greater integration in both the TCPS2 and NGRU of global health research, disability, and responsible conduct of research. This integration should also be accompanied by adequate training which can further guide researchers, be they senior, junior, or students, and funding agencies.