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Abstract Artificial Intelligence (AI) is transforming systematic reviews (SRs) in health research by automating processes such as study screening, data extraction, and quality assessment. This perspective highlights recent advancements in AI tools that enhance efficiency and accuracy in SRs. It discusses the benefits, challenges, and future directions of AI integration, emphasising the need for human oversight to ensure the reliability of AI outputs in evidence synthesis and decision-making in healthcare.

Abstract The association of health-related productivity loss (HRPL) with social isolation and depressive symptoms is not well studied. We aimed to examine the association of social isolation and depressive symptoms with productivity loss. Data on employed adults aged 21 years and above were derived from the Population Health Index (PHI) study conducted by the National Healthcare Group (NHG) on community-dwelling adults, residing in the Central and Northern residential areas of Singapore. The severity of depressive symptoms and social isolation were assessed using the 9-item Patient Health Questionnaire (PHQ-9) and Lubben Social Network Scale-6 (LSNS-6) respectively. Productivity loss was assessed using the Work Productivity and Activity Impairment Questionnaire (WPAI). We used Generalised Linear Models, with family gamma, log link for the analysis. Models were adjusted for socio-demographic variables (including age, gender, ethnicity, employment status, housing type) and self-reported chronic conditions (including the presence of diabetes, hypertension, and dyslipidemia). There were 2,605 working (2,143 full-time) adults in this study. The median reported percentage of unadjusted productivity loss was 0.0%, 10.0% and 20.0% for participants with social isolation, depressive symptoms, and both, respectively. In the regression analysis, mean productivity loss scores were 2.81 times (95% Confidence Interval: 2.12, 3.72) higher in participants with depressive symptoms than those without. On the other hand, social isolation was not found to be associated with productivity loss scores (1.17, 95% Confidence Interval: 0.96, 1.42). The interaction term of depressive symptoms with social isolation was statistically significant, with an effect size of 1.89 (95% Confidence Interval: 1.04, 3.44). It appeared that productivity loss was amplified when social isolation and depressive symptoms were concomitant. Our results suggested significant associations of social isolation and depressive symptoms with productivity loss. These findings highlighted the potential impact of social isolation and depressive symptoms on work performance and drew attention to the importance of having a holistic work support system that promotes social connectedness, mental wellbeing and work productivity.

Abstract Background Medication non-adherence has become a striking problem among patients with chronic diseases worldwide. However, literature on prevalence, reasons and factors associated with medication non-adherence in Singapore general population is still lacking. This study aimed to (1) estimate the prevalence of intentional and unintentional medication non-adherence in young (aged 21–64 years) and older adults (aged ≥ 65 years), respectively; (2) identify and compare the main reasons for non-adherence; and (3) examine the association between potential factors and non-adherence in each group. Methods This study sampled 1,528 community-dwelling adults on medications (young adults:766, older adults: 762) from a cross-sectional population health survey conducted in the northern and central regions of Singapore in 2018/2019. Self-reported medication non-adherence and its reasons were collected using a modified questionnaire and compared between the two groups. Multiple logistic regressions were conducted to examine the association between potential factors (e.g., social-demographic factors, smoking and drinking status, presence of diabetes, hypertension, or dyslipidaemia, and presence of depressive symptoms) and medication non-adherence in each group. Results The prevalence of non-adherence was 38.4% and 22.3% in young and older adults, respectively, with young adults reporting higher unintentional and intentional non-adherence rates than older adults. “Afraid of developing drug dependence” was the most common reason in both groups (young:74.8% vs. old:73.5%). Compared to young adults (3.7%), “Not understanding medication labels” was more prevalent in older adults (8.8%). Presence of depressive symptoms was associated with non-adherence in both young (odds ratio [95% confidence interval]: 3.00 [1.79, 5.05]) and older adults (4.16 [2.31, 7.51]). Being employed (2.92 [1.76, 4.84]) and taking ≥ 2 medications (1.42 [1.04, 1.95]) had positive association while personal income of SGD1,000–4,000 (0.53 [0.36, 0.77]) and current smoking (0.61 [0.39, 0.95]) had inverse association with non-compliance in young adults. Diagnosis of diabetes, hypertension, or dyslipidaemia (2.63 [1.25, 5.53]) was associated with higher odds of non-compliance in older adults. Conclusions Young adults had higher prevalence of medication non-adherence than older adults. The main reasons for non-adherence reported by young and older adults were generally comparable. Presence of depressive symptoms was a risk factor of medication non-adherence in both groups.

Abstract Stratum corneum is the outermost layer of the skin preventing external substances from entering human body. Microneedles (MNs) are sharp protrusions of a few hundred microns in length, which can penetrate the stratum corneum to facilitate drug permeation through skin. To determine the amount of drug delivered through skin, in vitro drug permeation testing is commonly used, but the testing is costly and time‐consuming. To address this issue, machine learning methods were employed to predict drug permeation through the skin, circumventing the need of conducting skin permeation experiments. By comparing the experimental data and simulated results, it was found extreme gradient boosting (XGBoost) was the best among the four simulation methods. It was also found that drug loading, permeation time, and MN surface area were critical parameters in the models. In conclusion, machine learning is useful to predict drug permeation profiles for MN‐facilitated transdermal drug delivery.

Abstract Chronic low back pain, defined as low back pain lasting more than 3 months, is a globally prevalent health problem with significantly high medical and economic burden on individuals and the society. This study aimed to estimate the prevalence of chronic low back pain and examine its association with health outcomes including physical function, mental health, and quality of life among adult population in Singapore. Cross-sectional secondary data analysis was performed using baseline data of the 1941 adults (mean age: 52.6 years, range: 21–97 years) from a representative population health survey conducted in the Central region of Singapore. Those with self-reported chronic low back pain in past six months were identified. The Late-Life Function and Disability Instrument, Patient Health Questionnaire-9, and EQ-5D-5L were used to measure physical function and limitation, mental health, and health-related quality of life, respectively. Generalized Linear Regressions were used to examine the association of chronic low back pain with physical function, limitation, depressive symptoms, and health-related quality of life. There were 8.1% (n = 180) participants reporting having chronic low back pain in past six months, among whom 80.5% sought treatments at either primary care, specialist outpatient, or Traditional Chinese Medicine clinics. Individuals with chronic low back pain reported poorer physical function, more limitations in performing major life tasks and social activities, more depressive symptoms, and lower health-related quality of life (all p

Abstract Background There is a shortage of research evidence about how social isolation, social participation, and loneliness were longitudinally associated with frailty. This study was to 1) examine the associations of social isolation, social participation, and loneliness with level of frailty among community-dwelling older adults using panel data, and 2) explore the moderating effect of gender on the association of social isolation, social participation and loneliness with frailty. Methods The study included 606 participants aged 60 years and above from the longitudinal Population Health Index Survey conducted in Singapore. At each timepoint, level of frailty was determined using the Clinical Frailty Scale. Social isolation was assessed by the Lubben Social Network Scale-6, and loneliness was assessed using the three-item UCLA Loneliness Scale. Fixed-effects ordinal logistic regressions were conducted with level of frailty as the dependent variable and social isolation and loneliness as the independent variables, adjusting for time-varying socio-demographic, lifestyle, and health-related factors. Results Increase in social participation was associated with lower level of frailty (odds ratio: 0.96, 95% confidence interval: 0.93–0.99) and feeling lonely was associated with higher level of frailty (odds ratio: 2.90, 95% confidence interval: 1.44–5.84). Social isolation was not associated with frailty. Gender did not have moderating effect on these associations. Conclusions This study observed that social isolation and loneliness had differential longitudinal association with level of frailty among community-dwelling older adults and suggested that loneliness and frailty should be measured and addressed concurrently among community-dwelling older adults.

Abstract Background A valid and reliable measure is essential to assess patient engagement and its impact on health outcomes. This study aimed to examine the psychometric properties of the 8-item Altarum Consumer Engagement Measure™ (ACE Measure) among English-speaking community-dwelling adults in Singapore. Methods This cross-sectional study involved 400 randomly selected community-dwelling adults (mean age: 49.7 years, 50.0% were female, 72.3% were Chinese) who completed the English version of the 8-item ACE Measure independently. The item-level statistics were described. The internal consistency of the measure was measured by Cronbach alpha and item-rest correlations. Validity of the tool was assessed by 1) factorial validity using confirmatory factor analysis (CFA), 2) hypothesis-testing validity by correlating ACE subscales (Commitment and Navigation) with health-related outcomes, and 3) criterion validity against the Patient Activation Measure and Health Confidence Measure. Results There was no floor or ceiling effect for Commitment and Navigation subscales, and the Cronbach alpha for each subscale was 0.76 and 0.54, respectively. The two-factor structure was confirmed by CFA. In general, Commitment and Navigation subscales were positively correlated with frequency of activity participation (rho = 0.30 - 0.33) and EQ-5D visual analog scale (rho = 0.15 - 0.30). Individuals who perceived better health than peers had higher subscale scores (p

Abstract Background Frailty is frequently found to be associated with increased healthcare utilisation in western countries, but little is known in Asian population. This study was conducted to investigate the association between frailty and healthcare utilisation in different care settings among community-dwelling older adults in Singapore. Methods Data from a population health survey among community-dwelling adults were linked with an administrative database to retrieve data of healthcare utilisation (including government primary care clinic visits, specialised outpatient clinic visits, emergency department visits, day surgery and hospitalisations) occurred during a six-month look-back period and six-month post-baseline respectively. Baseline frailty status was measured using the five-item FRAIL scale, which was categorised into three groups: robust (0), pre-frail (1–2), and frail (3–5). Negative binomial regression was applied to examine the association between frailty with respective healthcare utilisation (dependent variables), controlling for other confounding variables. Results In our sample of 701 older adults, 64.8% were of robust health, 27.7% were pre-frail, and 7.6% were frail. Compared to the robust group, frail individuals had a higher rate of specialised outpatient clinic visits (incidence rate ratio (IRR): 2.8, 95% confidence interval (CI): 1.2–6.5), emergency department visits (IRR: 3.1, 95%CI: 1.1–8.1), day surgery attendances (IRR: 6.4, 95%CI: 1.3–30.9), and hospitalisations (IRR: 6.7, 95%CI: 2.1–21.1) in the six-month period prior to the baseline and in subsequent 6 months (IRR: 3.3, 95%CI: 1.6–7.1; 6.4, 2.4–17.2; 5.8, 1.3–25.8; 13.1, 4.9–35.0; respectively), controlling for covariates. Conclusions Frailty was positively associated with the number of specialised outpatient clinic visits, emergency department visits, day surgeries and hospitalisations occurred during 6 months prior to and after the baseline. As frailty is a potentially reversible health state with early screening and intervention, providing preventive activities that delay the onset or progression of frailty should have potential effect on delaying secondary and tertiary care utilisation.

Introduction Measuring health activation in general population using valid instruments is needed to facilitate the evaluation of health education and behavioral programs in community. The 13-item Patient Activation Measure was well validated in patients with different chronic diseases but rarely validated in general population. The objective of this study was to assess the psychometric properties of the Patient Activation Measure among community-dwelling adults in Singapore. Methods Data of participants having valid responses to the English-version measure (N = 824) were analyzed. The psychometric properties were assessed by demonstrating evidence for uni-dimensionality using Rasch Principal Component Analysis of Residuals, known-group validity, convergent and divergent validity, and internal consistency reliability using Cronbach’s alpha. Results The uni-dimensionality of the Patient Activation Measure was supported by the Rasch Principal Component Analysis of Residuals results. Participants having multimorbidity or polypharmacy and being inactive in physical activity had significantly lower activation scores. The activation score was positively and moderately correlated with health confidence measured by the Health Confidence Measure (r = .38, P < .001), and negatively and weakly correlated with depressive symptoms measured by the Patient Health Questionnaire (r = − .13, P < .001). The internal reliability was good with a Cronbach’s alpha of .82. Conclusion The 13-item Patient Activation Measure has acceptable construct validity and good internal consistency among community-dwelling adults. It is a potential instrument to measure health activation in this population. Further research is required to investigate the expansion of response options, validate the cut-off scores for the activation levels and examine the test-retest reliability and responsiveness.

BackgroundFor population health management, it is important to have health indices that can monitor prevailing health trends in the population. Traditional health indices are generally measurable at different geographical levels with varied number of health dimensions. The aim of this work was to develop and validate a scalable and extendable multi-dimensional health index based on individual data.MethodsWe defined health to be made up of five different domains: Physical, Mental, Social, Risk, and Healthcare utilization. Item response theory was used to develop models to compute domain scores and a health index. These were normalized to represent an individual's health percentile relative to the population (0 = worst health, 100 = best health). Data for the models came from a longitudinal health survey on 1,942 participants. The health index was validated using age, frailty, post-survey one-year healthcare utilization and one-year mortality.ResultsThe Spearman rho between the health index and age, frailty and post-survey one-year healthcare utilization were -0.571, -0.561 and -0.435, respectively, with all pConclusionThe health index can be used at the individual, program, local, regional or national level to track the state of health of the population. When used together with the domain scores, it can identify regions with poor health and deficiencies within each of the five health domains.

BackgroundWhile it is well established that skin disease places significant psychosocial burden on a patient's wellbeing, its effects have rarely been examined in Asian populations.ObjectiveEvaluate the psychosocial burden of skin disease among community-dwelling adults in Singapore.MethodsThis cross-sectional study included 1510 participants interviewed on their history of thirteen skin diseases. The Patient Health Questionnaire (PHQ-9), Lubben Social Network Scale-6 (LSNS-6), University of California Los Angeles (UCLA) Loneliness Scale, and European Quality of Life-5 Dimensions- 5 Level (EQ-5D-5L) were used as measures for depressive symptoms, social isolation, loneliness and quality of life respectively. Multiple linear regression analysis was used to examine the association of skin diseases with each of the four measured outcomes.ResultsParticipants with skin diseases reported significantly higher PHQ-9 and UCLA Loneliness scale scores, and lower LSNS-6 and EQ-5D-5L scores when compared to their healthy counterparts. The presence of skin disease was positively associated with depressive symptoms (B = 0.40, SE = 0.11), and negatively associated with quality of life (B = -0.03, SE = 0.01). As disease severity was not evaluated in this study, we were unable to ascertain the associations between disease severity and measured outcomes.ConclusionParticipants with skin diseases were more likely to have depressive symptoms, social isolation, loneliness and lower quality of life. Unemployed, single and elderly patients were at higher risk of developing depressive symptoms. More emphasis should be placed on the psychosocial aspect of care to reduce the burden of skin disease. Some considerations include monitoring patients for mood-related changes and implementing early psychosocial interventions.

Background: Chronic kidney disease (CKD) patients requiring intravenous vancomycin bear considerable risks of adverse outcomes both from the infection and vancomycin therapy itself, necessitating especially precise dosing to avoid sub- and supratherapeutic vancomycin exposure.Methods: In this retrospective study, we performed a population pharmacokinetic analysis to construct a vancomycin dose prediction model for CKD patients who do not require renal replacement therapy. The model was externally validated on an independent cohort of patients to assess its prediction accuracy. The pharmacokinetic parameter estimates and the equations were productized into a Web application (VancApp) subsequently implemented in routine care. The association between VancApp-based dosing and time-to-target concentration attainment, 30-day mortality, and nephrotoxicity were assessed postimplementation.Results: The model constructed from an initial cohort (n = 80) revealed a population clearance and volume of distribution of 1.30 L/h and 1.23 L/kg, respectively. External model validation (n = 112) demonstrated a mean absolute prediction error of 1.25 mg/L. Following 4 months of clinical implementation of VancApp as an optional alternative to usual care [VancApp (n = 22) vs. usual care (n = 21)], patients who had received VancApp-based dosing took a shorter time to reach target concentrations (median: 66 vs. 102 h, p = 0.187) and had fewer 30-day mortalities (14% vs. 24%, p = 0.457) compared to usual care. While statistical significance was not achieved, the clinical significance of these findings appear promising.Conclusion: Clinical implementation of a population pharmacokinetic model for vancomycin in CKD can potentially improve dosing precision in CKD and could serve as a practical means to improve vital clinical outcomes.

OBJECTIVES:The aims of the study were to identify the associations between multimorbidity and specific physical function domains among community-dwelling adults in Singapore, and to examine sex differences in the associations. METHODS:This study was conducted using baseline data of 1,940 participants in the Population Health Index Survey conducted in the Central Region of Singapore from November 2015 to November 2016. Physical function was assessed using the Function Component of the Late-life Function and Disability Instrument and compared between men and women. Multiple linear regressions were conducted to examine associations between multimorbidity and different physical function domains for all participants, and in men and women separately. RESULTS:The prevalence of multimorbidity in the study population was 35.0% for adults aged 21 years and above, with no differences between men and women. Multimorbidity was associated with reduced upper extremity function, basic and advanced lower extremity function, and overall function in men and women after adjusting for demographic factors. Multimorbidity had a stronger association with advanced lower extremity function and overall physical function in women than in men. CONCLUSIONS:The findings of this study indicate that multimorbidity is associated with physical function domains in men and women, and in particular advanced lower extremity for women. Effective community-based interventions need to be implemented to preserve physical function in individuals with multimorbidity to keep them functionally independent and physically active in the community. Additional focus on advanced lower extremity function for women is needed.

Background: Lower extremity amputation (LEA) is defined as the complete loss in the transverse anatomical plane of any part of the lower limb. The objective of this study is to look at the trend and mortality trend of LEA performed in diabetes patients from 2008 to 2013. Methods: All patients age 15 and above with diabetes mellitus who had undergone LEAs (both major and minor) in Tan Tock Seng Hospital, Singapore from 1 January 2008 to 31 December 2013 were included. The outcomes of interest were deaths from all causes within 30 days and within 1 year. Results: Major LEA rate has increased from 11.0 per 100,000 population in 2008 to 13.3 per 100,000 population in 2013. The 30-day mortality rate ranges from 6.0% to 11.1% and the 1-year mortality rate ranges from 24.3% to 30.6%. Minor LEA rate has increased from 10.8 per 100,000 population in 2008 to 13.9 per 100,000 population in 2013. The 30-day mortality rate ranges from 1.5% to 3.7% and the 1-year mortality rate ranges from 9.7% to 18.3%. Conclusions: The trends in major and minor LEA are increasing. The 30-day and 1-year mortality for both major and minor LEA are comparable to figures reported worldwide. There is a need to re-look at preventive strategies to reduce LEA in diabetes patients in Singapore.

To assess the relationship between various social isolation indicators and loneliness, and to examine the differential associations that social isolation indicators, loneliness have with depressive symptoms.Baseline data for 1,919 adults (aged 21 years and above) from a representative health survey in the Central region of Singapore was used for this study. The association between social isolation indicators (marital status, living arrangement, social connectedness with relatives and friends) and loneliness (the three-item UCLA Loneliness) were assessed, and their differential associations with depressive symptoms (the Patient Health Questionnaire-9) were examined using multiple linear regression, controling for relevant covariates.There was significant overlap between loneliness and social isolation. Social connectedness with relatives and friends were mildly correlated with loneliness score (|r| = 0.14~0.16). Social isolation in terms of weak connectedness with relatives and with friends and loneliness were associated with depressive symptoms even after controling for age, gender, employment status and other covariates. The association of loneliness with depressive symptoms (β = 0.33) was independent of and stronger than that of any social isolation indicators (|β| = 0.00~0.07).The results of the study establishes a significant and unique association of different social isolation indicators and loneliness with depressive symptoms in community-dwelling adults aged 21 and above.