Games Features for Health Disciplines for Patient Learning as Entertainment

Butt, Shariq Aziz; Gochhait, Saikat; Andleeb, Shama; Adeel, Muhammad

doi:10.1007/978-981-15-9724-4_4

Cited by 5 publications

(3 citation statements)

References 30 publications

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“…Driven by the successes of the leisure game industry, the notion of games was redefined in non-gaming application areas, including learning, coaching, health care, awareness raising, strategic thinking, as well as market research (Gelperin 2011 ; Pallot et al 2012 ; Yilmaz et al 2016 ; Lamrani et al 2017 ; Westera 2017 ; Stettina et al 2018 ; Trujillo et al 2018 ; Üsfekes et al 2019 ; Lamrani and Abdelwahed 2020 ; Butt et al 2021a ; Khorram et al 2021 ). Abt ( 1970 ) coined the term “serious games” to describe games which “are not intended to be played primarily for amusement,” but are designed for educating or solving a problem.…”

Section: Theoretical and Practical Backgroundmentioning

confidence: 99%

Game-based Sprint retrospectives: multiple action research

Przybyłek

Albecka²,

Springer

et al. 2021

Empir Software Eng

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In today’s fast-paced world of rapid technological change, software development teams need to constantly revise their work practices. Not surprisingly, regular reflection on how to become more effective is perceived as one of the most important principles of Agile Software Development. Nevertheless, running an effective and enjoyable retrospective meeting is still a challenge in real environments. As reported by several studies, the Sprint Retrospective is an agile practice most likely to be implemented improperly or sacrificed when teams perform under pressure to deliver. To facilitate the implementation of the practice, some agile coaches have proposed to set up retrospective meetings in the form of retrospective games. However, there has been little research-based evidence to support the positive effects of retrospective games. Our aim is to investigate whether the adoption of retrospective games can improve retrospective meetings in general and lead to positive societal outcomes. In this paper, we report on an Action Research project in which we implemented six retrospective games in six Scrum teams that had experienced common retrospective problems. The received feedback indicates that the approach helped the teams to mitigate many of the “accidental difficulties” pertaining to the Sprint Retrospective, such as lack of structure, dullness, too many complaints, or unequal participation and made the meetings more productive to some degree. Moreover, depending on their individual preferences, different participants perceived different games as having a positive impact on their communication, motivation-and-involvement, and/or creativity, even though there were others, less numerous, who had an opposite view. The advantages and disadvantages of each game as well as eight lessons learned are presented in the paper.

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Section: Theoretical and Practical Backgroundmentioning

confidence: 99%

Game-based Sprint retrospectives: multiple action research

Przybyłek

Albecka²,

Springer

et al. 2021

Empir Software Eng

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“…A complicated evaluation of the resource allocation in a hospital department via integrating with the identical framework a queuing gadget, a compartmental version, and an evolutionary-based optimization required. The queuing device shapes the waft of sufferers through the medical institution, the compartmental version gives a feasible structure of the sanatorium branch according to the queuing characteristics, and the evolutionary paradigm offers an approach to optimize Bed-occupancy management and the aid gives the usage of a genetic set of rules approach [28][29][30]. Excess capability in hospitals has grown to be a serious trouble in terms of technical, managerial, and policy troubles similar to everywhere in the international and Iran.…”

Section: Bed Occupancymentioning

confidence: 99%

A Machine Learning Solution for Bed Occupancy Issue for Smart Healthcare Sector

Gochhait

Butt

De-la-Hoz-Franco

et al. 2021

Aut. Control Comp. Sci.

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The health care domain is a culmination and emergence of many other economic sectors that give different services from patient treatment to healing, protective, rehabilitation, and palliative care. The GDP consumes to facilitate health in terms of smart device development, clinical examinations, outsourcing, and Tele-Medication facilities. The Asian countries and less developed countries with a high population rate are facing health care services related issues. One of these countries is India. India has two types of health care services system; (i) public service system and (ii) private system. The public health system, i.e., the government, provides facilities to patients as primary health centers (PHCs) through limited secondary and tertiary health institutions like hospitals in rural areas while the private service is owned by local practitioners and institutions. Both of these service providers are facing bed occupancy issues for patients due to a highly populated country. To overcome this issue, we propose a Machine Learning solution for patient admission scheduling autonomously. The propose framework helps hospitals to enhance the decision process for bed occupancy for patients concerning their departments and their diseases. We have deployed our framework in real time environment and find that it facilitates the overall performance of bed allocation in the prescribed hospitals.

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“…Help to patients, the medicinal services framework for the old is imperative to fulfill the wellbeing administration needs to screen day-by-day exercises of the old individuals. There is meant to approve the proficiency of coordinating various advancements in recording dayby-day exercises of old individuals through gadgets such as wearable sensors in actual time [8].…”

Section: Introductionmentioning

confidence: 99%

A Smart Health Monitoring Application for Patients to Improve Health

Ariza-Colpas

Butt

Tariq

et al. 2022

Advances in Information, Communication and Cybersecurity

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Health is growing nowadays due to technological revolutions. These revolutions make health smart and easy to monitor the patient at their location. In this paper, we are suggesting and developing the smart health monitoring scenario. In our system, we are monitoring patients with the disease of frequent urine due to diabetes, stiffness of bones due to ortho disease, and heart rate monitoring due to heart disease we used some statically measured to find results from the generated data during the monitoring. Our system reveals that the scenario we created for monitoring patients at their location is more accurate and valuable during the decision-making to take appropriate action. Objective of this study is to support the elder patients for their remote health monitoring with the trustworthy scenario. We used an app development method for it. We used almost 10 patients to evaluate the results of our developed system. The study reveals that our developed system is very valuable for elder patients' health monitoring. We selected 10 patients with the mentioned diseases to monitor them and check the validity of our developed system. We find that our developed system is very efficient and useful for monitoring and generating an alarm in the case of any abnormality situations. In conclusion, there is an essential need for such systems that monitor the patient effectively and take decisions timely. In this paper, we implemented a model for elder patients to monitor the patient with different diseases such as frequent urine sugar levels, and stiffness in bones. For this, we deployed sensors in the patient's body and attached them to the mobile to transmit the data to the other ends. We also set an alarming stage in the system when there is any abnormality condition observed. The study reveals that there is a need for a more precise and decision support mechanism for disease monitoring to enhance the elder people life.

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Games Features for Health Disciplines for Patient Learning as Entertainment

Cited by 5 publications

References 30 publications

Game-based Sprint retrospectives: multiple action research

Game-based Sprint retrospectives: multiple action research

A Machine Learning Solution for Bed Occupancy Issue for Smart Healthcare Sector

A Smart Health Monitoring Application for Patients to Improve Health

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