Determinants of the acceptance and adoption of a digital contact tracing tool during the COVID-19 pandemic in Singapore.

The motivations that govern the adoption of digital contact tracing (DCT) tools are complex and not well understood. Hence, we assessed the factors influencing the acceptance and adoption of Singapore's national DCT tool - TraceTogether - during the COVID-19 pandemic. We surveyed 3943 visitors of Tan Tock Seng Hospital from July 2020 to February 2021 and stratified the analyses into three cohorts. Each cohort was stratified based on the time when significant policy interventions were introduced to increase the adoption of TraceTogether. Binary logistic regression was preceded by principal components analysis to reduce the Likert items. Respondents who 'perceived TraceTogether as useful and necessary' had higher likelihood of accepting it but those with 'Concerns about personal data collected by TraceTogether' had lower likelihood of accepting and adopting the tool. The injunctive and descriptive social norms were also positively associated with both the acceptance and adoption of the tool. Liberal individualism was mixed in the population and negatively associated with the acceptance and adoption of TraceTogether. Policy measures to increase the uptake of a national DCT bridged the digital divide and accelerated its adoption. However, good public communications are crucial to address the barriers of acceptance to improve voluntary uptake widespread adoption.

Sociodemographic and clinical factors, visit expectations and driving factors for emergency department attendance for uncomplicated upper respiratory tract infection.

BACKGROUND: Upper respiratory tract infections (URTIs) account for substantial non-urgent ED attendances. Hence, we explored the reasons for such attendances using a mixed-methods approach. METHODS: We interviewed adult patients with URTI who visited the second busiest adult ED in Singapore from June 2016 to November 2018 on their expectations and reasons for attendance. A structured questionnaire, with one open-ended question was used. Using the Andersen's Behavioural Model for Healthcare Utilisation, the topmost reasons for ED attendances were categorised into (1) contextual predisposing factors (referral by primary care physician, family, friends or coworkers), (2) contextual enabling factors (convenience, accessibility, employment requirements), (3) individual enablers (personal preference and trust in hospital-perceived care quality and efficiency) and (4) individual needs (perceived illness severity and non-improvement). Multivariable multinomial logistic regression was used to assess associations between sociodemographic and clinical factors, patient expectations for ED visits and the drivers for ED attendance. RESULTS: There were 717 patients in the cohort. The mean age of participants was 40.5 (SD 14.7) years, 61.2% were males, 66.5% without comorbidities and 40.7% were tertiary educated. Half had sought prior medical consultation (52.4%) and expected laboratory tests (55.7%) and radiological investigations (46.9%). Individual needs (32.8%) and enablers (25.1%) were the main drivers for ED attendance. Compared with ED attendances due to contextual enabling factors, attendances due to other drivers were more likely to be aged ≥45 years, had prior medical consultation and expected radiological investigations. Having a pre-existing medical condition (adjusted OR (aOR) 1.78, 95% CI 1.05 to 3.04) and an expectation for laboratory tests (aOR 1.64, 95% CI 1.01 to 2.64) were associated with individual needs while being non-tertiary educated (aOR 2.04, 95% CI 1.22 to 3.45) and having pre-existing comorbidities (aOR 1.79, 95% CI 1.04 to 3.10) were associated with individual enablers. CONCLUSIONS: Meeting individual needs of perceived illness severity or non-improvement was the topmost driver of ED visits for URTI, while contextual enabling factors such as convenience was the lowest. Patients' sociodemographic and clinical factors and visit expectations influence their motivations for ED attendances. Addressing these factors and expectations can alleviate the overutilisation of ED services.

Appropriateness of action prompts for hypoglycaemia and hyperglycaemia in type 2 diabetes self-management apps.

BACKGROUND: Control of blood glucose levels is needed not only to alleviate symptoms of hypoglycaemia and hyperglycaemia, but also to prevent or delay diabetes-related complications. Advice for glucose control is usually provided to patients by members of the health care team. However, many diabetes apps claim to enhance self-management of blood glucose by providing decision support to patients when an out-of-range blood glucose level is recorded. In this study, we investigated the appropriateness of action prompts provided by diabetes apps for hypoglycaemia and hyperglycaemia against evidence-based guidelines. METHODS: We used methods previously reported to identify and select diabetes apps, which were downloaded and assessed against the American Diabetes Association (ADA) guidelines. Screenshots of action prompts corresponding to low or high out-of-range blood glucose values were subjected to content analysis. RESULTS: Of 371 diabetes self-management apps evaluated, only 217 and 216 apps alerted patients about hypoglycaemia and hyperglycaemia, respectively. Of these, 20.7% (45/217) and 15.3% (33/216) also provided action prompts. We found 5.1% of apps (hypoglycaemia: 11/217; hyperglycaemia: 11/216) provided prompts that were either too general to be helpful or not aligned with ADA guidelines. Overall, only 17.9% (39/217) and 14.8% (32/216) provided appropriate action prompts for hypoglycaemia and hyperglycaemia, respectively. CONCLUSION: Less than one fifth of apps provided evidence-based steps to guide patients through hypoglycaemia and hyperglycaemia. The majority of apps failed to provide just-in-time diabetes self-management education to prevent frequent or severe episodes of hypoglycaemia and hyperglycaemia. Our findings emphasize the need for better design and quality assurance of diabetes apps.

Use of a Real-Time Locating System for Contact Tracing of Health Care Workers During the COVID-19 Pandemic at an Infectious Disease Center in Singapore: Validation Study.

BACKGROUND: In early 2020, coronavirus disease (COVID-19) emerged and spread by community and nosocomial transmission. Effective contact tracing of potentially exposed health care workers is crucial for the prevention and control of infectious disease outbreaks in the health care setting. OBJECTIVE: This study aimed to evaluate the comparative effectiveness of contact tracing during the COVID-19 pandemic through the real-time locating system (RTLS) and review of the electronic medical record (EMR) at the designated hospital for COVID-19 response in Singapore. METHODS: Over a 2-day study period, all admitted patients with COVID-19, their ward locations, and the health care workers rostered to each ward were identified to determine the total number of potential contacts between patients with COVID-19 and health care workers. The numbers of staff-patient contacts determined by EMR reviews, RTLS-based contact tracing, and a combination of both methods were evaluated. The use of EMR-based and RTLS-based contact tracing methods was further validated by comparing their sensitivity and specificity against self-reported staff-patient contacts by health care workers. RESULTS: Of 796 potential staff-patient contacts (between 17 patients and 162 staff members), 104 (13.1%) were identified by both the RTLS and EMR, 54 (6.8%) by the RTLS alone, and 99 (12.4%) by the EMR alone; 539 (67.7%) were not identified through either method. Compared to self-reported contacts, EMR reviews had a sensitivity of 47.2% and a specificity of 77.9%, while the RTLS had a sensitivity of 72.2% and a specificity of 87.7%. The highest sensitivity was obtained by including all contacts identified by either the RTLS or the EMR (sensitivity 77.8%, specificity 73.4%). CONCLUSIONS: RTLS-based contact tracing showed higher sensitivity and specificity than EMR review. Integration of both methods provided the best performance for rapid contact tracing, although technical adjustments to the RTLS and increasing user compliance with wearing of RTLS tags remain necessary.

Medication management support in diabetes: a systematic assessment of diabetes self-management apps.

BACKGROUND: Smartphone apps are becoming increasingly popular for supporting diabetes self-management. A key aspect of diabetes self-management is appropriate medication-taking. This study aims to systematically assess and characterise the medication management features in diabetes self-management apps and their congruence with best-practice evidence-based criteria. METHODS: The Google Play and Apple app stores were searched in June 2018 using diabetes-related terms in the English language. Apps with both medication and blood glucose management features were downloaded and evaluated against assessment criteria derived from international medication management and diabetes guidelines. RESULTS: Our search yielded 3369 Android and 1799 iOS potentially relevant apps; of which, 143 apps (81 Android, 62 iOS) met inclusion criteria and were downloaded and assessed. Over half 58.0% (83/143) of the apps had a medication reminder feature; 16.8% (24/143) had a feature to review medication adherence; 39.9% (57/143) allowed entry of medication-taking instructions; 5.6% (8/143) provided information about medication; and 4.2% (6/143) displayed motivational messages to encourage medication-taking. Only two apps prompted users on the use of complementary medicine. Issues such as limited medication logging capacity, faulty reminder features, unclear medication adherence assessment, and visually distracting excessive advertising were observed during app assessments. CONCLUSIONS: A large proportion of diabetes self-management apps lacked features for enhancing medication adherence and safety. More emphasis should be given to the design of medication management features in diabetes apps to improve their alignment to evidence-based best practice.

Digital Health Professions Education on Diabetes Management: Systematic Review by the Digital Health Education Collaboration.

BACKGROUND: There is a shortage of health care professionals competent in diabetes management worldwide. Digital education is increasingly used in educating health professionals on diabetes. Digital diabetes self-management education for patients has been shown to improve patients' knowledge and outcomes. However, the effectiveness of digital education on diabetes management for health care professionals is still unknown. OBJECTIVE: The objective of this study was to assess the effectiveness and economic impact of digital education in improving health care professionals' knowledge, skills, attitudes, satisfaction, and competencies. We also assessed its impact on patient outcomes and health care professionals' behavior. METHODS: We included randomized controlled trials evaluating the impact of digitalized diabetes management education for health care professionals pre- and postregistration. Publications from 1990 to 2017 were searched in MEDLINE, EMBASE, Cochrane Library, PsycINFO, CINAHL, ERIC, and Web of Science. Screening, data extraction and risk of bias assessment were conducted independently by 2 authors. RESULTS: A total of 12 studies met the inclusion criteria. Studies were heterogeneous in terms of digital education modality, comparators, outcome measures, and intervention duration. Most studies comparing digital or blended education to traditional education reported significantly higher knowledge and skills scores in the intervention group. There was little or no between-group difference in patient outcomes or economic impact. Most studies were judged at a high or unclear risk of bias. CONCLUSIONS: Digital education seems to be more effective than traditional education in improving diabetes management-related knowledge and skills. The paucity and low quality of the available evidence call for urgent and well-designed studies focusing on important outcomes such as health care professionals' behavior, patient outcomes, and cost-effectiveness as well as its impact in diverse settings, including developing countries.

Clinical relevance of smartphone apps for diabetes management: A global overview.

BACKGROUND: We assessed the number, proportion, and clinical relevance of diabetes self-management apps in major languages spoken by 10 countries with the highest number of people with diabetes. METHODS: China, India, USA, Brazil, Russian Federation, Mexico, Indonesia, Egypt, Japan, and Pakistan were identified as the 10 countries with the largest number of people with diabetes based on the latest NCD-RisC survey. Android and iOS apps in the 10 national languages were extracted with a search strategy. App titles and descriptions were systematically screened by trained reviewers, including apps specific for diabetes self-management and excluding apps for health care providers, general well-being, health and product promotion, and traditional cure. Eighteen apps in the above languages were then downloaded based on availability and popularity and assessed for clinical relevance to diabetes self-management with reference to current clinical guidelines. RESULTS: The diabetes-related search terms identified 3374 Android and 4477 iOS apps, where 1019 Android and 1303 iOS apps were screened as being relevant for diabetes self-management. Chinese and English language apps constitute above 80% of the diabetes apps, have more downloads, and more comprehensive clinically relevant functions compared with other languages. None of the apps assessed met all criteria for information provision and app functionalities nor provided information cited from accredited sources. CONCLUSIONS: Our study showed that apps could play an important role in complementing multifaceted diabetes care, but should preferably be regulated, context specific, and more tailored to users' needs with clear guidance for patients and clinicians about the choices.

eHealth in the future of medications management: personalisation, monitoring and adherence.

BACKGROUND: Globally, healthcare systems face major challenges with medicines management and medication adherence. Medication adherence determines medication effectiveness and can be the single most effective intervention for improving health outcomes. In anticipation of growth in eHealth interventions worldwide, we explore the role of eHealth in the patients' medicines management journey in primary care, focusing on personalisation and intelligent monitoring for greater adherence. DISCUSSION: eHealth offers opportunities to transform every step of the patient's medicines management journey. From booking appointments, consultation with a healthcare professional, decision-making, medication dispensing, carer support, information acquisition and monitoring, to learning about medicines and their management in daily life. It has the potential to support personalisation and monitoring and thus lead to better adherence. For some of these dimensions, such as supporting decision-making and providing reminders and prompts, evidence is stronger, but for many others more rigorous research is urgently needed. CONCLUSIONS: Given the potential benefits and barriers to eHealth in medicines management, a fine balance needs to be established between evidence-based integration of technologies and constructive experimentation that could lead to a game-changing breakthrough. A concerted, transdisciplinary approach adapted to different contexts, including low- and middle-income contries is required to realise the benefits of eHealth at scale.

Association Between Preoperative Long-Term Poor Sleep Quality and Postoperative Delirium in Elderly Patients Undergoing Cardiac Surgery: A Multi-Center Observational Study.

BACKGROUND: Delirium is a common complication in elderly patients after cardiac surgery, and sleep disorders have been suggested as a potential risk factor. However, few studies have explored the link between long-term preoperative poor sleep quality and postoperative delirium (POD) in this population. This study aimed to investigate the association between preoperative sleep quality and POD in elderly cardiac surgery patients. METHODS: The study enrolled 194 patients aged 60 years or older who underwent cardiac surgery. The Pittsburgh Sleep Quality Index (PSQI) objectively assessed preoperative sleep quality, while the Confusion Assessment Method screened for POD. The measurable outcomes encompassed the identification of risk factors associated with POD, while the secondary outcomes focused on factors influencing levels of consciousness. The statistical analysis is logistic regression analysis. RESULTS: Patients with POD had a higher prevalence of preoperative sleep disorders and higher PSQI scores than those without delirium (12.9 ± 5.1 vs 7.8 ± 3.4, P = .007). Logistic regression analysis demonstrated that the number of months with high PSQI scores and age were significantly associated with POD. The predictive ability of the number of months with high PSQI scores for POD was .762 (95% CI: .671-.854). Multivariate linear regression analysis revealed that preoperative sleep disorder was a significant predictor of exacerbation of POD (P < .05). CONCLUSION: This study suggests that long-term poor preoperative sleep quality, as assessed by the PSQI, is associated with an increased risk of POD in elderly patients undergoing cardiac surgery.

An Evidence-Based Serious Game App for Public Education on Antibiotic Use and Resistance: Randomized Controlled Trial.

BACKGROUND: The misuse and overuse of antibiotics accelerate the development of antimicrobial resistance (AMR). Serious games, any form of games that serve a greater purpose other than entertainment, could augment public education above ongoing health promotion efforts. Hence, we developed an evidence-based educational serious game app-SteWARdS Antibiotic Defence-to educate players on good antibiotic use practices and AMR through a game quest comprising 3 minigames and interaction with the nonplayer characters. OBJECTIVE: We aimed to evaluate the effectiveness of the SteWARdS Antibiotic Defence app in improving the knowledge of, attitude toward, and perceptions (KAP) of appropriate antibiotic use and AMR among the public in Singapore. METHODS: We conducted a 2-arm parallel randomized controlled trial, recruiting visitors aged 18-65 years from 2 polyclinics in Singapore. Intervention group participants had to download the SteWARdS Antibiotic Defence app (available only in English and on the Android platform) on their smartphones and complete the quest in the app. Participants took half a day to 2 weeks to complete the quest. The control group received no intervention. Knowledge questions on antibiotic use and AMR (11 binary questions) were self-administered at baseline, immediately after the intervention, and 6-10 weeks post intervention, while attitudes and perception questions (14 three-point Likert-scale questions) were self-administered at baseline and 6-10 weeks post intervention. We also collected participants' feedback on app usage. RESULTS: Participants (n=348; intervention: n=142, control: n=206) had a mean age of 36.9 years. Intervention group participants showed a statistically significant improvement in mean knowledge score (effect size: 0.58 [95% CI 0.28-0.87]) compared with controls after accounting for age, educational level, and exposure to advertisements on antibiotics and AMR. Intervention participants also showed a statistically significant improvement in mean attitude-perception scores (effect size: 0.98 (95% CI 0.44-1.52)) after adjusting for marital status and race. A majority of participants agreed that the "SteWARdS Antibiotic Defence" app improved their awareness on antibiotic use (135/142, 95.1%) and AMR (136/142, 95.8%). About 73.9% (105/142) of the participants agreed that the app is easy to use, 70.4% (100/142) agreed that the app was enjoyable, and 85.2% (121/142) would recommend the app to others. CONCLUSIONS: Our educational serious game app improves participants' KAP on appropriate antibiotic use and AMR. Public education apps should be engaging, educational, easy to use, and have an attractive user interface. Future research should assess the effectiveness of interventions in facilitating long-term knowledge retention and long-lasting behavioral change. TRIAL REGISTRATION: ClinicalTrials.gov NCT05445414; https://clinicaltrials.gov/ct2/show/NCT05445414. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.2196/45833.

Recent advances in mung bean protein: From structure, function to application.

With the surge in protein demand, the application of plant proteins has ushered in a new wave of research. Mung bean is a potential source of protein due to its high protein content (20-30 %). The nutrition, structure, function, and application of mung bean protein have always been a focus of attention. In this paper, these highlighted points have been reviewed to explore the potential application value of mung bean protein. Mung bean protein contains a higher content of essential amino acids than soybean protein, which can meet the amino acid values recommended by FAO/WHO for adults. Mung bean protein also can promote human health due to its bioactivity, such as the antioxidant, and anti-cancer activity. Meanwhile, mung bean protein also has well solubility, foaming, emulsification and gelation properties. Therefore, mung bean protein can be used as an antioxidant edible film additive, emulsion-based food, active substance carrier, and meat analogue in the food industry. It is understood there are still relatively few commercial applications of mung bean protein. This paper highlights the potential application of mung bean proteins, and aims to provide a reference for future commercial applications of mung bean proteins.

Doctors' perception on the ethical use of AI-enabled clinical decision support systems for antibiotic prescribing recommendations in Singapore.

Objectives: The increased utilization of Artificial intelligence (AI) in healthcare changes practice and introduces ethical implications for AI adoption in medicine. We assess medical doctors' ethical stance in situations that arise in adopting an AI-enabled Clinical Decision Support System (AI-CDSS) for antibiotic prescribing decision support in a healthcare institution in Singapore. Methods: We conducted in-depth interviews with 30 doctors of varying medical specialties and designations between October 2022 and January 2023. Our interview guide was anchored on the four pillars of medical ethics. We used clinical vignettes with the following hypothetical scenarios: (1) Using an antibiotic AI-enabled CDSS's recommendations for a tourist, (2) Uncertainty about the AI-CDSS's recommendation of a narrow-spectrum antibiotic vs. concerns about antimicrobial resistance, (3) Patient refusing the "best treatment" recommended by the AI-CDSS, (4) Data breach. Results: More than half of the participants only realized that the AI-enabled CDSS could have misrepresented non-local populations after being probed to think about the AI-CDSS's data source. Regarding prescribing a broad- or narrow-spectrum antibiotic, most participants preferred to exercise their clinical judgment over the AI-enabled CDSS's recommendations in their patients' best interest. Two-thirds of participants prioritized beneficence over patient autonomy by convincing patients who refused the best practice treatment to accept it. Many were unaware of the implications of data breaches. Conclusion: The current position on the legal liability concerning the use of AI-enabled CDSS is unclear in relation to doctors, hospitals and CDSS providers. Having a comprehensive ethical legal and regulatory framework, perceived organizational support, and adequate knowledge of AI and ethics are essential for successfully implementing AI in healthcare.

N-of-1 Trials of Antimicrobial Stewardship Interventions to Optimize Antibiotic Prescribing for Upper Respiratory Tract Infection in Emergency Departments: Protocol for a Quasi-Experimental Study.

BACKGROUND: Antimicrobial stewardship programs attempting to optimize antibiotic therapy and clinical outcomes mainly focus on inpatient and outpatient settings. The lack of antimicrobial stewardship program studies in the emergency department (ED) represents a gap in tackling the problem of antimicrobial resistance as EDs treat a substantial number of upper respiratory tract infection cases throughout the year. OBJECTIVE: We intend to implement two evidence-based interventions: (1) patient education and (2) providing physician feedback on their prescribing rates. We will incorporate evidence from a literature review and contextualizing the interventions based on findings from a local qualitative study. METHODS: Our study uses a quasi-experimental design to evaluate the effects of interventions over time in the EDs of 4 public hospitals in Singapore. We will include an initial control period of 18 months. In the next 6 months, we will randomize 2 EDs to receive 1 intervention (ie, patient education) and the other 2 EDs to receive the alternative intervention (ie, physician feedback). All EDs will receive the second intervention in the subsequent 6 months on top of the ongoing intervention. Data will be collected for another 6 months to assess the persistence of the intervention effects. The information leaflets will be handed to patients at the EDs before they consult with the physician, while feedback to individual physicians by senior doctors is in the form of electronic text messages. The feedback will contain the physicians' antibiotic prescribing rate compared with the departments' overall antibiotic prescribing rate and a bite-size message on good antibiotic prescribing practices. RESULTS: We will analyze the data using segmented regression with difference-in-difference estimation to account for concurrent cluster comparisons. CONCLUSIONS: Our proposed study assesses the effectiveness of evidence-based, context-specific interventions to optimize antibiotic prescribing in EDs. These interventions are aligned with Singapore's national effort to tackle antimicrobial resistance and can be scaled up if successful. TRIAL REGISTRATION: ClinicalTrials.gov NCT05451863; https://clinicaltrials.gov/study/NCT05451836. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/50417.

Correlation of T2DM and Anthropometric Measures with Total Small Bowel Length and Its Effects on Diabetes Remission After Bariatric Surgery.

BACKGROUND: The outcome of weight loss surgery is related to several factors, and for super-obese patients, the rate of weight loss failure and weight recovery after Roux-en-Y gastric bypass (RYGB) is high. Relevant studies have shown that the weight loss effect also correlates with total small bowel length (TSBL) and biliopancreatic (BP) and Roux limbs. However, there are few studies on the relationship between TSBL and anthropometric parameters, the BP limb, the Roux limb, and weight loss effect, and no relevant reports have been reported in China. OBJECTIVES: The objective was to study the relationship between the total length of the small intestine and anthropometric parameters in the Chinese population. The effect of the Roux limb/biliopancreatic limb (RL/BPL) ratio on weight loss and diabetes remission in RYGB patients 1 year after surgery was evaluated to find the appropriate ratio relationship. METHODS: In this prospective study, 148 patients between the ages of 19 and 68 years who underwent laparoscopic Roux-en-Y gastric bypass were enrolled. Height, weight, BMI, the BP limb, the Roux limb, fasting blood glucose (FBG), etc., were noted. To explore the correlation between the total length of the small intestine and these values. Subsequently, the 148 patients were followed up for 1 year after surgery. The patients diagnosed with T2DM before surgery were screened out, and 56 patients were finally identified according to the postoperative follow-up, in which BPL = 50 cm and RL = 150 cm, 175 cm, and 200 cm, respectively. RL/BPL was divided into 3, 3.5, and 4 groups according to the proportional relationship to explore the relationship between RL/BPL and diabetes remission and weight loss. RESULTS: (1) The study included 148 patients (61 women and 87 men). The mean age was 35.68 ± 10.46 years, weight = 127.46 ± 34.51 kg, height = 167.83 ± 9.16 cm, BMI = 44.94 ± 10.58 kg/m2. The average TSBL value was 714.41 ± 101.08 cm. Linear regression analysis showed that TSBL was positively correlated with height, weight, neck circumference, chest circumference, waist circumference, and Roux limb. (2) Fifty-six patients with T2DM who were followed up 1 year after surgery were divided into three groups. Group 1: BPL = 50 cm, RL = 150 cm (n = 20); group 2: BPL = 50 cm, RL = 175 cm (n = 26); group 3: BPL = 50 cm, RL = 200 cm (n = 10); RL/BPL = 3 was associated with higher weight loss than the other groups. The remission rate of diabetes did not differ between the three groups. CONCLUSIONS: TSBL was positively correlated with height, weight, neck circumference, chest circumference, waist circumference, and Roux limb. The TSBL of males was significantly higher than that of females. Among patients with T2DM who participated in the follow-up 1 year after surgery, RL/BPL = 3 (n = 20) had greater weight loss than the other groups.

Antibiotic expectation, behaviour, and receipt among patients presenting to emergency departments with uncomplicated upper respiratory tract infection during the COVID-19 pandemic.

OBJECTIVES: Pre-COVID-19 pandemic, patients who attended the emergency department (ED) for upper respiratory tract infection (URTI) were more likely to receive antibiotics if they expected them. These expectations could have changed with the change in health-seeking behaviour during the pandemic. We assessed the factors associated with antibiotics expectation and receipt for uncomplicated URTI patients in four Singapore EDs during the COVID-19 pandemic. METHODS: We conducted a cross-sectional study on adult patients with URTI from March 2021 to March 2022 in four Singapore EDs and assessed the determinants of antibiotics expectation and receipt using multivariable logistic regression models. We also assessed the reasons patients expect antibiotics during their ED visit. RESULTS: Among 681 patients, 31.0% expected antibiotics while 8.7% received antibiotics during their ED visit. Factors (adjusted odds ratio [95% confidence interval]) that significantly influenced expectation for antibiotics include: 1) prior consultation for current illness with (6.56 [3.30-13.11]) or without (1.50 [1.01-2.23]) antibiotics prescribed; 2) anticipation for COVID-19 test (1.56 [1.01-2.41]); and 3) poor (2.16 [1.26-3.68]) to moderate (2.26 [1.33-3.84]) knowledge on antibiotics use and resistance. Patients expecting antibiotics were 10.6 times (10.64 [5.34-21.17]) more likely to receive antibiotics. Those with tertiary education were twice (2.20 [1.09-4.43]) as likely to receive antibiotics. CONCLUSION: In conclusion, patients with URTI who expected antibiotics to be prescribed remained more likely to receive it during the COVID-19 pandemic. This highlights the need for more public education on the non-necessity for antibiotics for URTI and COVID-19 to address the problem of antibiotic resistance.

An Evidence-Based Serious Game App for Public Education on Antibiotic Use and Antimicrobial Resistance: Protocol of a Randomized Controlled Trial.

BACKGROUND: The misuse and overuse of antibiotics contribute to the acceleration of antimicrobial resistance (AMR), but public knowledge on appropriate antibiotic use and AMR remained low despite ongoing health promotion efforts. App gamification has gained traction in recent years for health promotion and to affect change in health behaviors. Hence, we developed an evidence-based serious game app "SteWARdS Antibiotic Defence" to educate the public on appropriate antibiotic use and AMR and address knowledge gaps. OBJECTIVE: We aim to evaluate the effectiveness of the "SteWARdS Antibiotic Defence" app in improving the knowledge of, attitude toward, and perception (KAP) of appropriate antibiotic use and AMR among the public. The primary objective is to assess the changes in KAP of antibiotic use and AMR in our participants, while the secondary objectives are to assess the extent of user engagement with the app and the level of user satisfaction in using the app. METHODS: Our study is a parallel 2-armed randomized controlled trial with a 1:1 allocation. We plan to recruit 400 participants (patients or their caregivers) aged 18-65 years from government-funded primary care clinics in Singapore. Participants are randomized in blocks of 4 and into the intervention or control group. Participants in the intervention group are required to download the "SteWARdS Antibiotic Defence" app on their smartphones and complete a game quest within 2 weeks. Users will learn about appropriate antibiotic use and effective methods to recover from uncomplicated upper respiratory tract infections by interacting with the nonplayer characters and playing 3 minigames in the app. The control group will not receive any intervention. RESULTS: The primary study outcome is the change in participants' KAP toward antibiotic use and AMR 6-10 weeks post intervention or 6-10 weeks from baseline for the control group (web-based survey). We will also assess the knowledge level of participants immediately after the participant completes the game quest (in the app). The secondary study outcomes are the user engagement level (tracked by the app) and satisfaction level of playing the game (via the immediate postgame survey). The satisfaction survey will also collect participants' feedback on the game app. CONCLUSIONS: Our proposed study provides a unique opportunity to assess the effectiveness of a serious game app in public health education. We anticipate possible ceiling effects and selection bias in our study and have planned to perform subgroup analyses to adjust for confounding factors. The app intervention will benefit a larger population if it is proven to be effective and acceptable to users. TRIAL REGISTRATION: ClinicalTrials.gov NCT05445414; https://clinicaltrials.gov/ct2/show/NCT05445414. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/45833.

A multi-institutional exploration of emergency medicine physicians' attitudes and behaviours on antibiotic use during the COVID-19 pandemic: a mixed-methods study.

BACKGROUND: The COVID-19 pandemic has changed the epidemiology of upper respiratory tract infections (URTI) and the disease profile of patients attending the emergency department (ED). Hence, we sought to explore the changes in ED physicians' attitudes and behaviours in four EDs in Singapore. METHODS: We employed a sequential mixed-methods approach (quantitative survey followed by in-depth interviews). Principal component analysis was performed to derive latent factors, followed by multivariable logistic regression to explore the independent factors associated with high antibiotic prescribing. Interviews were analysed using the deductive-inductive-deductive framework. We derive five meta-inferences by integrating the quantitative and qualitative findings with an explanatory bidirectional framework. RESULTS: We obtained 560 (65.9%) valid responses from the survey and interviewed 50 physicians from various work experiences. ED physicians were twice as likely to report high antibiotic prescribing rates pre-COVID-19 pandemic than during the pandemic (AOR = 2.12, 95% CI 1.32 to 3.41, p = 0.002). Five meta-inferences were made by integrating the data: (1) Less pressure to prescribe antibiotics due to reduced patient demand and more patient education opportunities; (2) A higher proportion of ED physicians self-reported lower antibiotic prescribing rates during the COVID-19 pandemic but their perception of the overall outlook on antibiotic prescribing rates varied; (3) Physicians who were high antibiotic prescribers during the COVID-19 pandemic made less effort for prudent antibiotic prescribing as they were less concerned about antimicrobial resistance; (4) the COVID-19 pandemic did not change the factors that lowered the threshold for antibiotic prescribing; (5) the COVID-19 pandemic did not change the perception that the public's knowledge of antibiotics is poor. CONCLUSIONS: Self-reported antibiotic prescribing rates decreased in the ED during the COVID-19 pandemic due to less pressure to prescribe antibiotics. The lessons and experiences learnt from the COVID-19 pandemic can be incorporated into public and medical education in the war against antimicrobial resistance going forward. Antibiotic use should also be monitored post-pandemic to assess if the changes are sustained.

Are physicians ready for precision antibiotic prescribing? A qualitative analysis of the acceptance of artificial intelligence-enabled clinical decision support systems in India and Singapore.

OBJECTIVES: Artificial intelligence (AI)-driven clinical decision support systems (CDSSs) can augment antibiotic decision-making capabilities, but physicians' hesitancy in adopting them may undermine their utility. We conducted a cross-country comparison of physician perceptions on the barriers and facilitators in accepting an AI-enabled CDSS for antibiotic prescribing. METHODS: We conducted in-depth interviews with physicians from the National Centre for Infectious Diseases (NCID), Singapore, and Christian Medical College Vellore (CMCV), India, between April and December 2022. Our semi-structured in-depth interview guides were anchored on Venkatesh's UTAUT model. We used clinical vignettes to illustrate the application of AI in clinical decision support for antibiotic prescribing and explore medico-legal concerns. RESULTS: Most NCID physicians felt that an AI-enabled CDSS could facilitate antibiotic prescribing, while most CMCV physicians were sceptical about the tool's utility. The hesitancy in adopting an AI-enabled CDSS stems from concerns about the lack of validated and successful examples, fear of losing autonomy and clinical skills, difficulty of use, and impediment in work efficiency. Physicians from both sites felt that a user-friendly interface, integration with workflow, transparency of output, a guiding medico-legal framework, and training and technical support would improve the uptake of an AI-enabled CDSS. CONCLUSION: In conclusion, the acceptance of AI-enabled CDSSs depends on the physician's confidence with the tool's recommendations, perceived ease of use, familiarity with AI, the organisation's digital culture and support, and the presence of medico-legal governance of AI. Progressive implementation and continuous feedback are essential to allay scepticism around the utility of AI-enabled CDSSs.

Applying Andersen's healthcare utilization model to assess factors influencing patients' expectations for diagnostic tests at emergency department visits during the COVID-19 pandemic.

Background: The uncertainties surrounding the COVID-19 pandemic led to a surge in non-urgent emergency department (ED) attendance among people presenting with upper respiratory tract infection (URTI) symptoms. These non-urgent visits, often manageable in primary care, exacerbated ED overcrowding, which could compromise the quality of ED services. Understanding patients' expectations and the reasons for these ED visits is imperative to mitigate the problem of ED overcrowding. Hence, we assessed the factors influencing patients' expectations for diagnostic tests during their ED visits for uncomplicated URTI during different phases of the pandemic. Methods: We conducted a cross-sectional study on adults with URTI symptoms seeking care at four public EDs in Singapore between March 2021 and March 2022. We segmented the study period into three COVID-19 pandemic phases-containment, transition, and mitigation. The outcome variables are whether patients expected (1) a COVID-19-specific diagnostic test, (2) a non-COVID-19-specific diagnostic test, (3) both COVID-19-specific and non-COVID-19-specific diagnostic tests, or (4) no diagnostic test. We built a multinomial regression model with backward stepwise selection and classified the findings according to Andersen's healthcare utilization model. Results: The mean age of participants was 34.5 (12.7) years. Factors (adjusted odds ratio [95% confidence interval]) influencing expectations for a COVID-19-specific diagnostic test in the ED include younger age {21-40 years: (2.98 [1.04-8.55])}, no prior clinical consultation (2.10 [1.13-3.89]), adherence to employer's health policy (3.70 [1.79-7.67]), perceived non-severity of illness (2.50 [1.39-4.55]), being worried about contracting COVID-19 (2.29 [1.11-4.69]), and during the transition phase of the pandemic (2.29 [1.15-4.56]). Being non-employed influenced the expectation for non-COVID-19-specific diagnostic tests (3.83 [1.26-11.66]). Factors influencing expectations for both COVID-19-specific and non-COVID-19-specific tests include younger age {21-40 years: (3.61 [1.26-10.38]); 41-60 years: (4.49 [1.43-14.13])}, adherence to employer's health policy (2.94 [1.41-6.14]), being worried about contracting COVID-19 (2.95 [1.45- 5.99]), and during the transition (2.03 [1.02-4.06]) and mitigation (2.02 [1.03-3.97]) phases of the pandemic. Conclusion: Patients' expectations for diagnostic tests during ED visits for uncomplicated URTI were dynamic across the COVID-19 pandemic phases. Expectations for COVID-19-specific diagnostic tests for ED visits for uncomplicated URTI were higher among younger individuals and those worried about contracting COVID-19 during the COVID-19 pandemic. Future studies are required to enhance public communications on the availability of diagnostic services in primary care and public education on self-management of emerging infectious diseases such as COVID-19.