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Article ; Online: Use of YouTube as a Source of Information for Quitting or Cutting Down Alcohol

Abdullah Al Mahmud / Anh Le / Omar Mubin

Frontiers in Public Health, Vol

2021 Volume 9

Abstract: Background: Although research has been done on considering YouTube for dissuading and encouraging unhealthy behaviours such as smoking, less focus has been placed on its role in quitting or cutting down alcohol. This study aims to analyse the alcohol ... ...

Abstract	Background: Although research has been done on considering YouTube for dissuading and encouraging unhealthy behaviours such as smoking, less focus has been placed on its role in quitting or cutting down alcohol. This study aims to analyse the alcohol cessation videos available and accessible on YouTube to gain a more in-depth insight into the ways that YouTube as a platform is being used to persuade with relation to alcohol cessation.Methods: We systematically searched for content on YouTube related to alcohol cessation and these videos were analysed and evaluated for the format, themes, specific alcohol cessation advice, and uploader.Results: The results demonstrated that the collected alcohol cessation videos included a fairly even presence of the themes of discussing the negative impacts of alcohol and the benefits of quitting or staying away from it. At the same time, however, we found the videos were not sourced from professional institutions, such as government or anti-alcohol misuse non-government organisations.Conclusion: More research is needed to investigate utilising YouTube to support those looking to quit or cut down alcohol.
Keywords	YouTube ; alcohol cessation ; content analysis ; alcohol ; social media ; human-computer interaction ; Public aspects of medicine ; RA1-1270
Subject code	020
Language	English
Publishing date	2021-12-01T00:00:00Z
Publisher	Frontiers Media S.A.
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Perceived Service Quality in HRI

Isha Kharub / Michael Lwin / Aila Khan / Omar Mubin

Frontiers in Robotics and AI, Vol

Applying the SERVBOT Framework

2021 Volume 8

Abstract: Services are intangible in nature and as a result, it is often difficult to measure the quality of the service. In the service literature, the service is usually delivered by a human to a human customer and the quality of the service is often evaluated ... ...

Abstract	Services are intangible in nature and as a result, it is often difficult to measure the quality of the service. In the service literature, the service is usually delivered by a human to a human customer and the quality of the service is often evaluated using the SERVQUAL dimensions. An extensive review of the literature shows there is a lack of an empirical model to assess the perceived service quality provided by a social robot. Furthermore, the social robot literature highlights key differences between human service and social robots. For example, scholars have highlighted the importance of entertainment value and engagement in the adoption of social robots in the service industry. However, it is unclear whether the SERVQUAL dimensions are appropriate to measure social robot’s service quality. The paper proposes the SERVBOT model to assess a social robot’s service quality. It identifies, reliability, responsiveness, assurance, empathy, and entertainment as the five dimensions of SERVBOT. Further, the research will investigate how these five factors influence emotional engagement and future intentions to use the social robot in a concierge service setting. The model was tested using student sampling, and a total of 94 responses were collected for the study. The findings indicate empathy and entertainment value as key predictors of emotional engagement. Further, emotional engagement is a strong predictor of future intention to use a social robot in a service setting. This study is the first to propose the SERVBOT model to measure social robot’s service quality. The model provides a theoretical underpinning on the key service quality dimensions of a social robot and gives scholars and managers a method to track the service quality of a social robot. The study also extends on the literature by exploring the key factors that influence the use of social robots (i.e. emotional engagement).
Keywords	human-robot interaction ; service quality ; SERVQUAL ; concierge ; retail ; Mechanical engineering and machinery ; TJ1-1570 ; Electronic computers. Computer science ; QA75.5-76.95
Subject code	629 ; 360
Language	English
Publishing date	2021-11-01T00:00:00Z
Publisher	Frontiers Media S.A.
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: COVID-19 Global Risk

Mudassar Arsalan / Omar Mubin / Fady Alnajjar / Belal Alsinglawi

International Journal of Environmental Research and Public Health, Vol 17, Iss 5592, p

Expectation vs. Reality

2020 Volume 5592

Abstract: Background and Objective : COVID-19 has engulfed the entire world, with many countries struggling to contain the pandemic. In order to understand how each country is impacted by the virus compared with what would have been expected prior to the pandemic ... ...

Abstract	Background and Objective : COVID-19 has engulfed the entire world, with many countries struggling to contain the pandemic. In order to understand how each country is impacted by the virus compared with what would have been expected prior to the pandemic and the mortality risk on a global scale, a multi-factor weighted spatial analysis is presented. Method : A number of key developmental indicators across three main categories of demographics, economy, and health infrastructure were used, supplemented with a range of dynamic indicators associated with COVID-19 as independent variables. Using normalised COVID-19 mortality on 13 May 2020 as a dependent variable, a linear regression (N = 153 countries) was performed to assess the predictive power of the various indicators. Results : The results of the assessment show that when in combination, dynamic and static indicators have higher predictive power to explain risk variation in COVID-19 mortality compared with static indicators alone. Furthermore, as of 13 May 2020 most countries were at a similar or lower risk level than what would have been expected pre-COVID, with only 44/153 countries experiencing a more than 20% increase in mortality risk. The ratio of elderly emerges as a strong predictor but it would be worthwhile to consider it in light of the family makeup of individual countries. Conclusion : In conclusion, future avenues of data acquisition related to COVID-19 are suggested. The paper concludes by discussing the ability of various factors to explain COVID-19 mortality risk. The ratio of elderly in combination with the dynamic variables associated with COVID-19 emerge as more significant risk predictors in comparison to socio-economic and demographic indicators.
Keywords	COVID-19 ; risk evaluation ; multi-weighted factor analysis ; Medicine ; R ; covid19
Subject code	300 ; 332
Language	English
Publishing date	2020-08-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: An explainable machine learning framework for lung cancer hospital length of stay prediction

Belal Alsinglawi / Osama Alshari / Mohammed Alorjani / Omar Mubin / Fady Alnajjar / Mauricio Novoa / Omar Darwish

Scientific Reports, Vol 12, Iss 1, Pp 1-

2022 Volume 10

Abstract: Abstract This work introduces a predictive Length of Stay (LOS) framework for lung cancer patients using machine learning (ML) models. The framework proposed to deal with imbalanced datasets for classification-based approaches using electronic healthcare ...

Abstract	Abstract This work introduces a predictive Length of Stay (LOS) framework for lung cancer patients using machine learning (ML) models. The framework proposed to deal with imbalanced datasets for classification-based approaches using electronic healthcare records (EHR). We have utilized supervised ML methods to predict lung cancer inpatients LOS during ICU hospitalization using the MIMIC-III dataset. Random Forest (RF) Model outperformed other models and achieved predicted results during the three framework phases. With clinical significance features selection, over-sampling methods (SMOTE and ADASYN) achieved the highest AUC results (98% with CI 95%: 95.3–100%, and 100% respectively). The combination of Over-sampling and under-sampling achieved the second-highest AUC results (98%, with CI 95%: 95.3–100%, and 97%, CI 95%: 93.7–100% SMOTE-Tomek, and SMOTE-ENN respectively). Under-sampling methods reported the least important AUC results (50%, with CI 95%: 40.2–59.8%) for both (ENN and Tomek- Links). Using ML explainable technique called SHAP, we explained the outcome of the predictive model (RF) with SMOTE class balancing technique to understand the most significant clinical features that contributed to predicting lung cancer LOS with the RF model. Our promising framework allows us to employ ML techniques in-hospital clinical information systems to predict lung cancer admissions into ICU.
Keywords	Medicine ; R ; Science ; Q
Subject code	006
Language	English
Publishing date	2022-01-01T00:00:00Z
Publisher	Nature Portfolio
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: A Preliminary Evaluation of Mobile Phone Apps to Curb Alcohol Consumption

Omar Mubin / Billy Cai / Abdullah Al Mahmud / Isha Kharub / Michael Lwin / Aila Khan

International Journal of Environmental Research and Public Health, Vol 19, Iss 135, p

2022 Volume 135

Abstract: Mobile apps have become increasingly prevalent in modern society, and persuasive technology has a broader market than ever. Mobile-based alcohol cessation apps can promote positive behaviour change in users and improve the overall health of our society. ... ...

Abstract	Mobile apps have become increasingly prevalent in modern society, and persuasive technology has a broader market than ever. Mobile-based alcohol cessation apps can promote positive behaviour change in users and improve the overall health of our society. This research aimed to understand the various features users respond to and make design recommendations for alcohol cessation apps. This paper reports on three sources of feedback (user ratings, user reviews, MARS App Quality score) provided on 20 alcohol cessation apps in the Google Play Store. Our findings suggest that self-control type apps received much greater positive user reviews than motivational apps. In addition, this trend was not observed through numeric user ratings. We also speculate on design recommendations for apps that are meant to inhibit alcohol intake.
Keywords	mobile app ; user needs ; persuasive design ; Mobile App Rating Scale (MARS) ; alcohol cessation ; Medicine ; R
Subject code	005
Language	English
Publishing date	2022-12-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Global and Temporal COVID-19 Risk Evaluation

Mudassar Arsalan / Omar Mubin / Fady Alnajjar / Belal Alsinglawi / Nazar Zaki

Frontiers in Public Health, Vol

2020 Volume 8

Abstract: The COVID-19 pandemic has caused unprecedented crisis across the world, with many countries struggling with the pandemic. In order to understand how each country is impacted by the virus and assess the risk on a global scale we present a regression based ...

Abstract	The COVID-19 pandemic has caused unprecedented crisis across the world, with many countries struggling with the pandemic. In order to understand how each country is impacted by the virus and assess the risk on a global scale we present a regression based analysis using two pre-existing indexes, namely the Inform and Infectious Disease Vulnerability Index, in conjunction with the number of elderly living in the population. Further we introduce a temporal layer in our modeling by incorporating the stringency level employed by each country over a period of 6 time intervals. Our results show that the indexes and level of stringency are not ideally suited for explaining variation in COVID-19 risk, however the ratio of elderly in the population is a stand out indicator in terms of its predictive power for mortality risk. In conclusion, we discuss how such modeling approaches can assist public health policy.
Keywords	COVID-19 ; inform index ; infectious disease vulnerability index ; mortality risk evaluation ; public health ; Public aspects of medicine ; RA1-1270 ; covid19
Subject code	330
Language	English
Publishing date	2020-08-01T00:00:00Z
Publisher	Frontiers Media S.A.
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Measurement Method for Evaluating the Lockdown Policies during the COVID-19 Pandemic

Mohammed Al Zobbi / Belal Alsinglawi / Omar Mubin / Fady Alnajjar

International Journal of Environmental Research and Public Health, Vol 17, Iss 5574, p

2020 Volume 5574

Abstract: Coronavirus Disease 2019 (COVID-19) has affected day to day life and slowed down the global economy. Most countries are enforcing strict quarantine to control the havoc of this highly contagious disease. Since the outbreak of COVID-19, many data analyses ...

Abstract	Coronavirus Disease 2019 (COVID-19) has affected day to day life and slowed down the global economy. Most countries are enforcing strict quarantine to control the havoc of this highly contagious disease. Since the outbreak of COVID-19, many data analyses have been done to provide close support to decision-makers. We propose a method comprising data analytics and machine learning classification for evaluating the effectiveness of lockdown regulations. Lockdown regulations should be reviewed on a regular basis by governments, to enable reasonable control over the outbreak. The model aims to measure the efficiency of lockdown procedures for various countries. The model shows a direct correlation between lockdown procedures and the infection rate. Lockdown efficiency is measured by finding a correlation coefficient between lockdown attributes and the infection rate. The lockdown attributes include retail and recreation, grocery and pharmacy, parks, transit stations, workplaces, residential, and schools. Our results show that combining all the independent attributes in our study resulted in a higher correlation (0.68) to the dependent value Interquartile 3 (Q3). Mean Absolute Error (MAE) was found to be the least value when combining all attributes.
Keywords	COVID-19 ; infectious disease modeling ; basic reproduction number ; machine learning ; government regulations ; spread control ; Medicine ; R ; covid19
Subject code	006
Language	English
Publishing date	2020-08-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: A Systematic Review of Adaptivity in Human-Robot Interaction

Muneeb Ahmad / Omar Mubin / Joanne Orlando

Multimodal Technologies and Interaction, Vol 1, Iss 3, p

2017 Volume 14

Abstract: As the field of social robotics is growing, a consensus has been made on the design and implementation of robotic systems that are capable of adapting based on the user actions. These actions may be based on their emotions, personality or memory of past ... ...

Abstract	As the field of social robotics is growing, a consensus has been made on the design and implementation of robotic systems that are capable of adapting based on the user actions. These actions may be based on their emotions, personality or memory of past interactions. Therefore, we believe it is significant to report a review of the past research on the use of adaptive robots that have been utilised in various social environments. In this paper, we present a systematic review on the reported adaptive interactions across a number of domain areas during Human-Robot Interaction and also give future directions that can guide the design of future adaptive social robots. We conjecture that this will help towards achieving long-term applicability of robots in various social domains.
Keywords	adaptive interactions ; adaptive social robots ; human robot interactions ; social robotics ; Technology ; T ; Science ; Q
Language	English
Publishing date	2017-07-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: The Effect of Strict State Measures on the Epidemiologic Curve of COVID-19 Infection in the Context of a Developing Country

Khalid A. Kheirallah / Belal Alsinglawi / Abdallah Alzoubi / Motasem N. Saidan / Omar Mubin / Mohammed S. Alorjani / Fawaz Mzayek

International Journal of Environmental Research and Public Health, Vol 17, Iss 6530, p

A Simulation from Jordan

2020 Volume 6530

Abstract: COVID-19 has posed an unprecedented global public health threat and caused a significant number of severe cases that necessitated long hospitalization and overwhelmed health services in the most affected countries. In response, governments initiated a ... ...

Abstract	COVID-19 has posed an unprecedented global public health threat and caused a significant number of severe cases that necessitated long hospitalization and overwhelmed health services in the most affected countries. In response, governments initiated a series of non-pharmaceutical interventions (NPIs) that led to severe economic and social impacts. The effect of these intervention measures on the spread of the COVID-19 pandemic are not well investigated within developing country settings. This study simulated the trajectories of the COVID-19 pandemic curve in Jordan between February and May and assessed the effect of Jordan’s strict NPI measures on the spread of COVID-19. A modified susceptible, exposed, infected, and recovered (SEIR) epidemic model was utilized. The compartments in the proposed model categorized the Jordanian population into six deterministic compartments: suspected, exposed, infectious pre-symptomatic, infectious with mild symptoms, infectious with moderate to severe symptoms, and recovered. The GLEAMviz client simulator was used to run the simulation model. Epidemic curves were plotted for estimated COVID-19 cases in the simulation model, and compared against the reported cases. The simulation model estimated the highest number of total daily new COVID-19 cases, in the pre-symptomatic compartmental state, to be 65 cases, with an epidemic curve growing to its peak in 49 days and terminating in a duration of 83 days, and a total simulated cumulative case count of 1048 cases. The curve representing the number of actual reported cases in Jordan showed a good pattern compatibility to that in the mild and moderate to severe compartmental states. The reproduction number under the NPIs was reduced from 5.6 to less than one. NPIs in Jordan seem to be effective in controlling the COVID-19 epidemic and reducing the reproduction rate. Early strict intervention measures showed evidence of containing and suppressing the disease.
Keywords	COVID-19 ; simulation ; SEIR ; SARS-CoV-2 ; Jordan ; SIR ; Medicine ; R ; covid19
Subject code	380
Language	English
Publishing date	2020-09-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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