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Fulltext Integrating contextual sentiment analysis in collaborative recommender systems

Osman NA, Mohd Noah SA, Darwich M, Mohd M

PLoS One, 2021;16(3):e0248695.
PMID: 33750957 DOI: 10.1371/journal.pone.0248695

Recently. recommender systems have become a very crucial application in the online market and e-commerce as users are often astounded by choices and preferences and they need help finding what the best they are looking for. Recommender systems have proven to overcome information overload issues in the retrieval of information, but still suffer from persistent problems related to cold-start and data sparsity. On the flip side, sentiment analysis technique has been known in translating text and expressing user preferences. It is often used to help online businesses to observe customers' feedbacks on their products as well as try to understand customer needs and preferences. However, the current solution for embedding traditional sentiment analysis in recommender solutions seems to have limitations when involving multiple domains. Therefore, an issue called domain sensitivity should be addressed. In this paper, a sentiment-based model with contextual information for recommender system was proposed. A novel solution for domain sensitivity was proposed by applying a contextual information sentiment-based model for recommender systems. In evaluating the contributions of contextual information in sentiment-based recommendations, experiments were divided into standard rating model, standard sentiment model and contextual information model. Results showed that the proposed contextual information sentiment-based model illustrates better performance as compared to the traditional collaborative filtering approach.
An experimental study on the performance of collaborative filtering based on user reviews for large-scale datasets

Al-Ghuribi S, Mohd Noah SA, Mohammed M

PeerJ Comput Sci, 2023;9:e1525.
PMID: 37705634 DOI: 10.7717/peerj-cs.1525

Collaborative filtering (CF) approaches generate user recommendations based on user similarities. These similarities are calculated based on the overall (explicit) user ratings. However, in some domains, such ratings may be sparse or unavailable. User reviews can play a significant role in such cases, as implicit ratings can be derived from the reviews using sentiment analysis, a natural language processing technique. However, most current studies calculate the implicit ratings by simply aggregating the scores of all sentiment words appearing in reviews and, thus, ignoring the elements of sentiment degrees and aspects of user reviews. This study addresses this issue by calculating the implicit rating differently, leveraging the rich information in user reviews by using both sentiment words and aspect-sentiment word pairs to enhance the CF performance. It proposes four methods to calculate the implicit ratings on large-scale datasets: the first considers the degree of sentiment words, while the second exploits the aspects by extracting aspect-sentiment word pairs to calculate the implicit ratings. The remaining two methods combine explicit ratings with the implicit ratings generated by the first two methods. The generated ratings are then incorporated into different CF rating prediction algorithms to evaluate their effectiveness in enhancing the CF performance. Evaluative experiments of the proposed methods are conducted on two large-scale datasets: Amazon and Yelp. Results of the experiments show that the proposed ratings improved the accuracy of CF rating prediction algorithms and outperformed the explicit ratings in terms of three predictive accuracy metrics.
Fulltext The Effectiveness of a Web-Based Health Education Tool, WESIHAT 2.0, among Older Adults: A Randomized Controlled Trial

Vanoh D, Shahar S, Razali R, Ali NM, Manaf ZA, Mohd Noah SA, et al.

J Alzheimers Dis, 2019;70(s1):S255-S270.
PMID: 31256116 DOI: 10.3233/JAD-180464

BACKGROUND: Intervention strategies, especially online based approaches, are considered to be beneficial in improving the health of the senior. The effectiveness of such approaches is yet to be determined.
OBJECTIVE: This study aims to determine the effectiveness of the web-based application, WESIHAT 2.0©, for improving cognitive function, physical fitness, biochemical indices, and psychosocial variables among older adults in Klang Valley, Malaysia. The cost analysis of WESIHAT 2.0© was also determined.
METHOD: The study utilized a two-arm randomized controlled trial with 25 subjects in each of the intervention and control groups. The participants chosen for the study included those who were 60 years and above with at least secondary education and had internet access using a computer at home. The intervention group was exposed to the website (30 minutes per day, 4 days per week) for six months, while the control group was given health education pamphlets. Activity-Based Costing method was used to determine the cost saved using WESIHAT 2.0© as compared to using the pamphlet.
RESULTS: Significant intervention effects were observed for self-perception of disability and informational support scores. WESIHAT 2.0© was able to save costs in improving the self-perception of disability score and the informational support score at MYR 6.92 and MYR 13.52, respectively, compared to the conventional method.
CONCLUSION: WESIHAT 2.0© was able to save costs in improving the self-perceived disability and informational support scores for the intervention group.
Fulltext Willingness, perceived barriers and motivators in adopting mobile applications for health-related interventions among older adults: a scoping review protocol

Ahmad NA, Mat Ludin AF, Shahar S, Mohd Noah SA, Mohd Tohit N

BMJ Open, 2020 Mar 16;10(3):e033870.
PMID: 32184309 DOI: 10.1136/bmjopen-2019-033870

INTRODUCTION: The world's older population continues to grow at an unprecedented rate. An ageing population poses a great challenge to our healthcare system that requires new tool to tackle the complexity of health services as well as the increasing expenses. Mobile health applications (mHealth app) is seen to have the potential to address these challenges, alleviating burdens on the healthcare system and enhance the quality of life for older adults. Despite the numerous benefits of mHealth apps, relatively little is known about whether older adults perceive that these apps confer such benefits. Their perspectives towards the use of mobile applications for health-related purposes have also been little studied. Therefore, in this paper, we outline our scoping review protocol to systematically review literature specific to older adults' willingness, perceived barriers and motivators towards the use of mobile applications to monitor and manage their health.
METHODS AND ANALYSIS: Arksey and O'Malley's scoping review methodology framework will guide the conduct of this scoping review. The search strategy will involve electronic databases including PubMed, Excerpta Medica Database, Cumulative Index of Nursing and Allied Health Literature, Cochrane Library, Google Scholar and ScienceDirect, in addition to grey literature sources and hand-searching of reference lists. Two reviewers will independently screen all abstracts and full-text studies for inclusion. Data will be charted and sorted through an iterative process by the research team. The extracted data will undergo a descriptive analysis and simple quantitative analysis will be conducted using descriptive statistics. Engagement with relevant stakeholders will be carried out to gain more insights into our data from different perspectives.
ETHICS AND DISSEMINATION: Since the data used are from publicly available sources, this study does not require ethical approval. Results will be disseminated through academic journals, conferences and seminars. We anticipate that our findings will aid technology developers and health professionals working in the area of ageing and rehabilitation.
Fulltext Digital technology usage among older adults with cognitive frailty: A survey during COVID-19 pandemic

Md Fadzil NH, Shahar S, Singh DKA, Rajikan R, Vanoh D, Mohamad Ali N, et al.

Digit Health, 2023;9:20552076231207594.
PMID: 37868158 DOI: 10.1177/20552076231207594

OBJECTIVE: The research aimed to study digital divide by determining the usage of digital technology among older adults with cognitive frailty (CF) in Malaysia.
METHODS: The dataset was obtained from the AGELESS trial screening phase conducted from October 2021 to March 2022, involving 476 community-dwelling Malaysian older adults (67.7 years old ± 6.1). Digital technology usage was assessed and CF was determined using Fried's criteria and Clinical Dementia Rating. A binary logistic regression was used to determine the sociodemographic factors associated with digital technology use among older adults with CF.
RESULTS: The findings suggest a digital divide between older adults with CF and robust in Malaysia. CF individuals (72.1%) were less likely to utilise digital technology, mainly smartphone than robust older adults (89.6%). More than 70% of older people owned social media on their smartphones, namely, WhatsApp. The most frequent online activities in both groups were family interaction and obtaining current news. CF older adults were less likely to play games on their smart devices. Usage of digital technology was more common among male, younger age, attained formal education more than 6 years, had a higher monthly household income, and robust participants.
CONCLUSIONS: The usage of digital technology was inversely related to CF status. CF older adults were less likely to integrate digital technology into their daily living compared to robust even though they were familiar with it. The use of digital technology should be reinforced among female, advanced age, widowers/divorcees without formal education and those from lower- or middle-income statuses, and cognitively frail older people.
Mapping the landscape: A bibliometric analysis of information and communication technology adoption by older adults with cognitive frailty or impairment

Md Fadzil NH, Shahar S, Singh DKA, Rajikan R, Vanoh D, Mohamad Ali N, et al.

Geriatr Gerontol Int, 2024 Mar;24(3):251-262.
PMID: 38329011 DOI: 10.1111/ggi.14814

The adoption of information and communication technology (ICT) by older adults with cognitive frailty and impairment is beneficial to support aging in place and promote healthy aging. However, data are scarce regarding the use of ICT by this demographic in comparison with other age groups. This bibliometric analysis was aimed at systematically mapping the literature on ICT-related research on older adults with cognitive frailty and cognitive impairment to provide insights into research trends, patterns and knowledge gaps. Data were extracted from the Web of Science database, which identified 324 publications between 1980 and 2023. Performance analysis and science mapping were carried out using Microsoft® Excel, VOSViewer and Harzing's Publish or Perish. The analysis showed an upsurge in the research output trend over time. Notable journals, authors, citations, nations and research areas have been documented. Four key clusters were identified, including: (i) caregiver concern, support and involvement; (ii) technology as a tool for cognitive training and cognitive rehabilitation; (iii) cognitive improvement; and (iv) the use of technology for prevention and self-management. The findings derived from this analysis provide an appropriate reference for future researchers to bridge the gap in ICT-related studies among this population, and distinguish the relevant articles that are required for further investigation. These include the need for further long-term research, the incorporation of ICT-based approaches to counter cognitive frailty and the importance of multidomain telehealth interventions. Geriatr Gerontol Int 2024; 24: 251-262.