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PurposeThe global research evidences indicate that the technology adoption in case of agribusiness has a potential to enhance the performance and bring operational efficiency. India is the world’s largest producer as well as consumer of milk but struggles with yield per cattle, overall productivity, low rate of technology acceptance and adoption, health detection of milching units, animal data recording and presence of dairy products in the global market. The purpose of this study is to focus on identifying the challenges of technology adoption in dairy farms and constructing a hierarchical model using soft systems methodology.Design/methodology/approachThis study uses nominal group technique-based discussion with domain experts and personal interviews with dairy farm owners/managers for the identification of challenges, fuzzy interpretative structural modeling as well as FMICMAC to develop a hierarchical model of challenging elements and to divide the identified elements into four categories based on the dominance of driving-dependence power.FindingsThis research has developed a list of 12 challenges affecting the technology adoption in a dairy farm business unit, identified through the personal interviews with 60 dairy farms across three highest milk-producing states of India in terms of annual milk output – Haryana, Punjab and Uttar Pradesh. Lack of government support followed by lack of educational opportunities in dairy-based education were found as the most crucial and high driving challenges, whereas high cost, huge investment and low acceptance of decision-maker were found as the most dependent challenges of technology adoption.Research limitations/implicationsThis research is one step ahead of interpretive structural modeling that considers the fuzzy-based dominance in the model to showcase the degree of relationship along with its existence, but it lacks to statistically validate the findings using techniques like SEM.Practical implicationsThis paper has developed a list of challenges in adoption of technology along with their inter-relationships to highlight the required focus challenge that drives or is dependent on the other challenges. The goal is to bring performance improvement and assist Indian dairy farm business stakeholders or decision-makers in formulating strategic and action plans and help policy planners to make favorable policies based on the understanding of contextual relationship between challenges.Social implicationsIn Indian context, dairy is an important part of agriculture sector, and milk is an essential item that facilitates income generation to small and rural households and a source item for several other businesses and activities. The results of this research suggested the policy planners and government to ensure subsidized and insured technologies, training support and facilities, educational opportunities and efforts for promotion of technology adoption among dairy farmers. The suggestions are purely on the basis of the relevance of challenges in the hierarchy and can play a significant role in improving the level of technology adoption and can ultimately uplift the social and economic well-being from micro-level of farmers to macro-stage concerning economic development of India.Originality/valueTo the best of the authors’ knowledge, this study is purely original and outcome of the research conducted by authors.

Introduction: The World Health Organization recommends that family planning be integrated in HIV services, to improve service offering and uptake; stakeholder involvement is crucial. The purpose of this manuscript is to share the utilization of nominal group technique (NGT) and multiple group analysis as a vehicle to ensure stakeholder involvement in the development of a strategic action plan to improve the implementation of integrated services in Ethiopia. Methods: A qualitative research design, employing a NGT, was applied as data-gathering method to develop a strategic action plan for facilitating the integration of family planning and HIV services. NGT was used to ensure the equal involvement of stakeholders in the development thereof. Twenty-four programme managers in Addis Ababa, Ethiopia--experts in family planning and HIV/AIDS programmes, working in 10 sub-city health departments--participated in the nominal groups to identify the strategies to be included in an action plan development to facilitate integrated services. Results: The first nominal group's participants identified 12 themes, derived from the 21 categories generated from 34 individual ideas. The second group identified nine themes, from 16 categories, generated from 30 individually ideas. A multiple group analysis utilizing the findings from both groups revealed the top five most important themes (leadership and management, capacity building, implementing policies and guidelines, advocacy/awareness and infrastructure) that were selected to be included in a strategic action plan to integrated family planning and HIV services in Ethiopia. Discussion: The strategic action plan developed by the researcher who took into account the findings from the multiple group analysis was validated in a face-to-face validation meeting by all the relevant stakeholder's participation. Stakeholder involvement, utilizing different nominal groups and conducting multiple nominal group analysis ensured ownership of the strategic action plan as those involved in the development, will be the individuals to implement in Ethiopia. Keywords: strategic action plan, nominal group technique, stakeholder involvement

Introduction The Nominal Group Technique (NGT) and Delphi Technique are consensus methods used in research that is directed at problem-solving, idea-generation, or determining priorities. While consensus methods are commonly used in health services literature, few studies in pharmacy practice use these methods. This paper provides an overview of the NGT and Delphi technique, including the steps involved and the types of research questions best suited to each method, with examples from the pharmacy literature. Methodology The NGT entails face-to-face discussion in small groups, and provides a prompt result for researchers. The classic NGT involves four key stages: silent generation, round robin, clarification and voting (ranking). Variations have occurred in relation to generating ideas, and how ‘consensus’ is obtained from participants. The Delphi technique uses a multistage self-completed questionnaire with individual feedback, to determine consensus from a larger group of ‘experts.’ Questionnaires have been mailed, or more recently, e-mailed to participants. When to use The NGT has been used to explore consumer and stakeholder views, while the Delphi technique is commonly used to develop guidelines with health professionals. Method choice is influenced by various factors, including the research question, the perception of consensus required, and associated practicalities such as time and geography. Limitations The NGT requires participants to personally attend a meeting. This may prove difficult to organise and geography may limit attendance. The Delphi technique can take weeks or months to conclude, especially if multiple rounds are required, and may be complex for lay people to complete.

The Nominal Group Technique (NGT) has been used to establish clinical priorities and generate guidelines within healthcare since its creation over fifty years ago. It is characterised by its five distinct stages; introduction, silent idea generation, 'round robin', clarifications and rating or ranking. A key element traditionally has been the inclusion of face-to-face discussion, however in the context of COVID-19 innovations were required. This article provides a case study illustrating an adaptation of the NGT to a virtual format (vNGT) and outlines the processes involved in a virtual NGT (vNGT), using an illustrative study exploring the rehabilitation of stroke survivors. The vNGT offers opportunities for global collaborations without the constraints of geography or incurred costs. Future studies should evaluate it's acceptability for stroke survivors to enable their participation within research. 1. This study provides a guide for the use of virtual nominal group technique (vNGT), using a freely available video-conferencing platform

Since the outbreak of COVID-19, the development of dashboards as dynamic, visual tools for communicating COVID-19 data has surged worldwide. Dashboards can inform decision-making and support behavior change. To do so, they must be actionable. The features that constitute an actionable dashboard in the context of the COVID-19 pandemic have not been rigorously assessed. The aim of this study is to explore the characteristics of public web-based COVID-19 dashboards by assessing their purpose and users (\"why\"), content and data (\"what\"), and analyses and displays (\"how\" they communicate COVID-19 data), and ultimately to appraise the common features of highly actionable dashboards. We conducted a descriptive assessment and scoring using nominal group technique with an international panel of experts (n=17) on a global sample of COVID-19 dashboards in July 2020. The sequence of steps included multimethod sampling of dashboards; development and piloting of an assessment tool; data extraction and an initial round of actionability scoring; a workshop based on a preliminary analysis of the results; and reconsideration of actionability scores followed by joint determination of common features of highly actionable dashboards. We used descriptive statistics and thematic analysis to explore the findings by research question. A total of 158 dashboards from 53 countries were assessed. Dashboards were predominately developed by government authorities (100/158, 63.0%) and were national (93/158, 58.9%) in scope. We found that only 20 of the 158 dashboards (12.7%) stated both their primary purpose and intended audience. Nearly all dashboards reported epidemiological indicators (155/158, 98.1%), followed by health system management indicators (85/158, 53.8%), whereas indicators on social and economic impact and behavioral insights were the least reported (7/158, 4.4% and 2/158, 1.3%, respectively). Approximately a quarter of the dashboards (39/158, 24.7%) did not report their data sources. The dashboards predominately reported time trends and disaggregated data by two geographic levels and by age and sex. The dashboards used an average of 2.2 types of displays (SD 0.86); these were mostly graphs and maps, followed by tables. To support data interpretation, color-coding was common (93/158, 89.4%), although only one-fifth of the dashboards (31/158, 19.6%) included text explaining the quality and meaning of the data. In total, 20/158 dashboards (12.7%) were appraised as highly actionable, and seven common features were identified between them. Actionable COVID-19 dashboards (1) know their audience and information needs; (2) manage the type, volume, and flow of displayed information; (3) report data sources and methods clearly; (4) link time trends to policy decisions; (5) provide data that are \"close to home\"; (6) break down the population into relevant subgroups; and (7) use storytelling and visual cues. COVID-19 dashboards are diverse in the why, what, and how by which they communicate insights on the pandemic and support data-driven decision-making. To leverage their full potential, dashboard developers should consider adopting the seven actionability features identified.

This article reaffirms the value and flexibility of the nominal group technique (NGT) when conducting qualitative focus groups (QFGs). In the project that will be discussed, the methods used expanded the application of the NGT into the realm of pan-disability (i.e., individuals with differing impairments) research. It provides requirements and recommendations for the full inclusion and participation of disabled people into projects where the pertinent source of qualitative data is obtained from QFGs. Furthermore, this article describes innovative additional steps to the NGT that are beneficial to researchers. This includes a method of evaluating the data that is often lost between the NGTs’ stages of initial and final rankings. These new methods ensure pertinent data are not overlooked.

Current evidence dissemination methods fall short of meeting clinical nurses' needs, hindering the implementation of evidence-based nursing practice. Large language models (LLMs), with their advanced natural language processing capabilities, offer potential as innovative tools to facilitate evidence dissemination. However, general-purpose LLMs typically lack domain-specific knowledge, are insufficient to support effective evidence dissemination in clinical contexts. It is essential to develop artificial intelligence tools tailored to nurses' needs and preferences to enhance evidence dissemination. The aim of this study is to identify the challenges and barriers clinical nurses face in disseminating evidence, examine their perspectives on the use of existing LLMs to support evidence dissemination, and explore their needs and preferences regarding an LLM-based nursing evidence question-answering system. This qualitative study used a combined method of focus group discussions and the nominal group technique (NGT). Using purposive sampling, nurses with diverse specialties, professional titles, and years of experience were recruited, resulting in a total of 22 clinical nurses who completed the entire study. A total of 2 focus group discussions were conducted online via Tencent Meeting between November and December 2024 to explore the challenges and barriers nurses face in disseminating evidence, as well as their perspectives on using existing LLMs to support evidence dissemination. The data were analyzed using qualitative content analysis following the approach of Graneheim and Lundman. Subsequently, the NGT was used between March and April 2025 to identify nurses' needs and preferences for the system to be developed. To overcome geographical constraints and participants' busy schedules, the NGT was conducted entirely online, using online questionnaires and WeChat groups. Overall, 2 rounds of voting were conducted to determine the priority ranking of the functionalities. The focus group yielded 3 main themes and 7 subthemes. Three main themes were identified as (1) pathways for evidence dissemination among nurses, (2) barriers that hinder the effective dissemination of evidence, and (3) advantages and limitations of using LLMs to support evidence dissemination. The limitations of current LLMs served as the foundation for nurses' subsequent reflections in the nominal group discussions on the desired functions of a newly developed LLM. The NGT sessions ultimately identified 9 desired functions. After prioritization, the top 3 ranked functions were evidence-based, high-quality question-answering, evidence source provision, and personalized evidence recommendation. The current evidence dissemination process faces multiple barriers. LLMs hold promise as innovative tools to support evidence dissemination, but require further refinement. Clinical nurses have identified key functional needs, guiding the development of LLMs specifically tailored to clinical nursing practice.

Through a controlled two-stage experiment, we explore the performance of solution search strategies to resolve problems of varying complexity. We validate theoretical results that collaborative group structures may search more effectively in problems of low complexity but are outperformed by nominal structures at higher complexity levels. We call into question the dominance of the nominal group technique. Further close examination of search strategies reveals important insights: the number of generated solutions, a typical proxy for good problem-solving performance, does not consistently drive performance benefits across different levels of problem complexity. The average distance of search steps and the problem space coverage also play critical roles. Moreover, their effect is contingent on complexity: a wider variety of solutions is helpful only in complex problems. Overall, we caution management about the limitations of generic, albeit common, rules of thumb, such as “generate as many ideas as possible.” This paper was accepted by Yan Chen, decision analysis.

Consensus group methods such as the Nominal Group Technique (NGT) and Delphi method are commonly used in research to elicit and synthesize expert opinions when evidence is lacking. Traditionally, the NGT involves a face-to-face interaction. However, due to the COVID-19 pandemic, many in-person meetings have moved to online settings. It is unclear to what extent the NGT has been undertaken in virtual settings. The overarching aim of this scoping review is to explore the use of the virtual NGT in research. Our specific objectives are to answer the following questions: To what extent has the NGT been used virtually? What modifications were made to accommodate this online format? What advantages and disadvantages were noted by authors in comparison with the face-to-face mode of the technique? This scoping review will follow the steps outlined by Arksey and O'Malley and the PRISMA-ScR guidelines. Several pilot searches were completed to refine inclusion and exclusion criteria. Media Synchronicity Theory will provide a conceptual framework to inform the research, including data extraction and summarizing results. As an additional extension to the literature review, online interviews with corresponding authors will be conducted to gather further information.

Background: Corruption is widespread in Nigeria’s health sector but the reasons why it exists and persists are poorly understood and it is often seen as intractable. We describe a consensus building exercise in which we asked health workers and policy-makers to identify and prioritise feasible responses to corruption in the Nigerian health sector. Methods: We employed three sequential activities. First, a narrative literature review identified which types of corruption are reported in the Nigerian health system. Second, we asked 21 frontline health workers to add to what was found in the review (based on their own experiences) and prioritise them, based on their significance and the feasibility of assessing them, by means of a consensus building exercise using a Nominal Group Technique (NGT). Third, we presented their assessments in a meeting of 25 policy-makers to offer their views on the practicality of implementing appropriate measures. Results: Participants identified 49 corrupt practices from the literature review and their own experience as most important in the Nigerian health system. The NGT prioritised: absenteeism, procurement-related corruption, underthe-counter payments, health financing-related corruption, and employment-related corruption. This largely reflected findings from the literature review, except for the greater emphasis on employment-related corruption from the NGT. Absenteeism, Informal payments and employment-related corruption were seen as most feasible to tackle. Frontline workers and policy-makers agreed that tackling corrupt practices requires a range of approaches. Conclusion: Corruption is recognized in Nigeria as widespread but often seems insurmountable. We show how a structured approach can achieve consensus among multiple stakeholders, a crucial first step in mobilizing action to address corruption.