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The goal of this research is to analyse the obstacles to the implementation of mobile health (mHealth) in India and to gain an understanding of the contextual inter-relationships that exist amongst those obstacles.

Potential barriers and their interrelationships in their respective contexts have been uncovered. Using MICMAC analysis, the categorization of these barriers was done based on their degree of reliance and driving power (DP). Furthermore, an interpretive structural modeling (ISM) framework for the barriers to mHealth activities in India has been proposed.

The study explores a total of 15 factors that reduce the efficiency of mHealth adoption in India. The findings of the Matrix Cross-Reference Multiplication Applied to a Classification (MICMAC) investigation show that the economic situation of the government, concerns regarding the safety of intellectual technologies and privacy issues are the primary obstacles because of the significant driving power they have in mHealth applications.

Promoters of mHealth practices may be able to make better plans if they understand the social barriers and how they affect each other; this leads to easier adoption of these practices. The findings of this study might be helpful for governments of developing nations to produce standards relating to the deployment of mHealth; this will increase the efficiency with which it is adopted.

At this time, there is no comprehensive analysis of the factors that influence the adoption of mobile health care with social cognitive theory in developing nations like India. In addition, there is a lack of research in investigating how each of these elements affects the success of mHealth activities and how the others interact with them. Because developed nations learnt the value of mHealth practices during the recent pandemic, this study, by investigating the obstacles to the adoption of mHealth and their inter-relationships, makes an important addition to both theory and practice.

This article examines the educational decision-making of hearing parents for their deaf children born during a period (1970–1990s) before the introduction of new-born hearing screening in New South Wales, where the study was conducted, and prior to the now near-universal adoption of cochlear implants in Australia.

We present findings from an oral history study in which parents were invited to recall how they planned for the education of their deaf children.

We propose that these oral histories shed light on how the concept, early intervention – a child development principle that became axiomatic from about the 1960s – significantly shaped the conduct of parents of deaf children, constituting both hope and burden, and intensifying a focus on early decision-making. They also illustrate ways in which parenting was shaped by two key structural shifts, one, being the increasing enrolment of deaf children in mainstream rather than separate classrooms and the other being the transformation of deafness itself by developments in hearing assistance technology.

The paper contributes to a sociological/historical literature of “parenting for education” that almost entirely lacks deaf perspectives and a specialist literature of parental decision-making for deaf children that is almost entirely focussed on the post cochlear implant generation. The paper is distinctive in its treatment of the concept of “early intervention” as a historical phenomenon rather than a “common sense” truth, and proposes that parents of deaf children were at the leading edge of late-20th and early-21st century parenting intensification.

This paper presents the systematic process framework to develop the suitable crop insurance for each agriculture farming region which has individual differences of associated crop, climate condition, including applicable technology to be implemented in crop insurance practice. This paper also studies the adoption of new insurance scheme to assess the willingness to join crop insurance program.

Crop insurance development has been performed through IDDI conceptual framework to illustrate the specific crop insurance diagram. Area-yield insurance as a type of index-based insurance advantages on reducing basis risk, adverse selection and moral hazard. This paper therefore aims to develop area-yield crop insurance, at a provincial level, focusing on rice insurance scheme for the protection of flood. The diagram demonstrates the structure of area-yield rice insurance associates with selected machine learning algorithm to evaluate indemnity payment and premium assessment applicable for Jasmine 105 rice farming in Ubon Ratchathani province. Technology acceptance model (TAM) is used for new insurance adoption testing.

The framework produces the visibly informative structure of crop insurance. Random Forest is the algorithm that gives high accuracy for specific collected data for rice farming in Ubon Ratchathani province to evaluate the rice production to calculate an indemnity payment. TAM shows that the level of adoption is high.

This paper originates the framework to generate the viable crop insurance that suitable to individual farming and contributes the idea of technology implementation in the new service of crop insurance scheme.