Understanding reasons and determinants of medication non-adherence in community-dwelling adults: a cross-sectional study comparing young and older age groups.

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.

Associations of social isolation, social participation, and loneliness with frailty in older adults in Singapore: a panel data analysis.

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.

Psychometric evaluation of the 8-item Altarum Consumer Engagement (ACE) Measure™ in community-dwelling adults in Singapore.

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 < 0.01). Each subscale score had moderate and positive correlations with activation score (rho = 0.48 - 0.55) and health confidence score (rho = 0.35 - 0.47). CONCLUSIONS: The two-subscale ACE Measure demonstrated good construct validity in English-speaking Singapore community-dwelling adults. Evidence in internal consistency was mixed, indicating further investigation.

Frailty and healthcare utilisation across care settings among community-dwelling older adults in Singapore.

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.

Prevalence of frailty and its association with depressive symptoms among older adults in Singapore.

OBJECTIVES: The aims of the study were to (1) estimate the prevalence of frailty among community-dwelling older adults , and (2) investigate the independent association between level of frailty and depressive symptoms. METHODS: A total of 721 older adults (aged 60 and above ) were included in this study. Severity of frailty was determined using the Clinical Frailty Scale and further classified into four levels (CFS1-3: F1, CFS4: F2, CFS5: F3, and CFS6-7: F4). The depressive symptoms were assessed using the Patient Health Questionnaire-9. The prevalence of frailty by four levels was described and the association between level of frailty and depressive symptoms was assessed using multiple linear regression. RESULTS: The prevalence of frailty among the study population was 24.5% (F2: 14.4%, F3:3.7%, F4: 6.4%). There was no significant difference in level of frailty between male and female. With the increase in severity level of frailty, older adults reported substantially higher depressive symptom scores (p < .001), even after controlling for socio-demographics, number of non-mental chronic conditions, and number of medications taken regularly. CONCLUSIONS: Level of frailty is independently associated with depressive symptoms among community-dwelling older population, which is not fully explained by symptom overlap, socio-demographic, and comorbidity covariates.

Effects of chronic diseases on health-related quality of life and self-rated health among three adult age groups.

Little is known about whether there is any difference in associations of chronic diseases with health-related quality of life and self-rated health across age groups. The purpose of the present study was to examine the associations of one specific and multiple chronic diseases with health-related quality of life and self-rated health (measured using the 5-level EQ-5D version) in three age groups: young (21-44 years), middle-aged (45-64 years), and older adults (≥65 years). Secondary data analysis of 1932 participants in the Population Health Index Survey was performed. Linear regression results showed that different chronic diseases had a characteristic effect on health-related quality of life and self-rated health among different age groups. The presence of a single chronic disease was associated with lower health-related quality of life and self-rated health in young adults. Multi-morbidity was consistently associated with decreased health-related quality of life and self-rated health in all age groups. Our findings suggest that although young adults have a lower prevalence of chronic diseases, their impacts on health-related quality of life and self-rated health can be as significant as that in middle-aged and older adults.

Identification of novel peroxisome proliferator-activated receptor-gamma (PPARγ) agonists using molecular modeling method.

Peroxisome proliferator-activated receptor-gamma (PPARγ) plays a critical role in lipid and glucose homeostasis. It is the target of many drug discovery studies, because of its role in various disease states including diabetes and cancer. Thiazolidinediones, a synthetic class of agents that work by activation of PPARγ, have been used extensively as insulin-sensitizers for the management of type 2 diabetes. In this study, a combination of QSAR and docking methods were utilised to perform virtual screening of more than 25 million compounds in the ZINC library. The QSAR model was developed using 1,517 compounds and it identified 42,378 potential PPARγ agonists from the ZINC library, and 10,000 of these were selected for docking with PPARγ based on their diversity. Several steps were used to refine the docking results, and finally 30 potentially highly active ligands were identified. Four compounds were subsequently tested for their in vitro activity, and one compound was found to have a K i values of <5 µM.

Isorhamnetin inhibits proliferation and invasion and induces apoptosis through the modulation of peroxisome proliferator-activated receptor γ activation pathway in gastric cancer.

Gastric cancer (GC) is a lethal malignancy and the second most common cause of cancer-related deaths. Although treatment options such as chemotherapy, radiotherapy, and surgery have led to a decline in the mortality rate due to GC, chemoresistance remains as one of the major causes for poor prognosis and high recurrence rate. In this study, we investigated the potential effects of isorhamnetin (IH), a 3'-O-methylated metabolite of quercetin on the peroxisome proliferator-activated receptor γ (PPAR-γ) signaling cascade using proteomics technology platform, GC cell lines, and xenograft mice model. We observed that IH exerted a strong antiproliferative effect and increased cytotoxicity in combination with chemotherapeutic drugs. IH also inhibited the migratory/invasive properties of GC cells, which could be reversed in the presence of PPAR-γ inhibitor. We found that IH increased PPAR-γ activity and modulated the expression of PPAR-γ regulated genes in GC cells. Also, the increase in PPAR-γ activity was reversed in the presence of PPAR-γ-specific inhibitor and a mutated PPAR-γ dominant negative plasmid, supporting our hypothesis that IH can act as a ligand of PPAR-γ. Using molecular docking analysis, we demonstrate that IH formed interactions with seven polar residues and six nonpolar residues within the ligand-binding pocket of PPAR-γ that are reported to be critical for its activity and could competitively bind to PPAR-γ. IH significantly increased the expression of PPAR-γ in tumor tissues obtained from xenograft model of GC. Overall, our findings clearly indicate that antitumor effects of IH may be mediated through modulation of the PPAR-γ activation pathway in GC.

PaDEL-DDPredictor: open-source software for PD-PK-T prediction.

ADMET (absorption, distribution, metabolism, excretion, and toxicity)-related failure of drug candidates is a major issue for the pharmaceutical industry today. Prediction of PD-PK-T properties using in silico tools has become very important in pharmaceutical research to reduce cost and enhance efficiency. PaDEL-DDPredictor is an in silico tool for rapid prediction of PD-PK-T properties of compounds from their chemical structures. It is free and open-source software that, has both graphical user interface and command line interface, can work on all major platforms (Windows, Linux, and MacOS) and supports more than 90 different molecular file formats. The software can be downloaded from http://padel.nus.edu.sg/software/padelddpredictor.

An automated Pearson's correlation change classification (APC3) approach for GC/MS metabonomic data using total ion chromatograms (TICs).

A fully automated and computationally efficient Pearson's correlation change classification (APC3) approach is proposed and shown to have overall comparable performance with both an average accuracy and an average AUC of 0.89 ± 0.08 but is 3.9 to 7 times faster, easier to use and have low outlier susceptibility in contrast to other dimensional reduction and classification combinations using only the total ion chromatogram (TIC) intensities of GC/MS data. The use of only the TIC permits the possible application of APC3 to other metabonomic data such as LC/MS TICs or NMR spectra. A RapidMiner implementation is available for download at http://padel.nus.edu.sg/software/padelapc3.

Prediction of drug permeation through microneedled skin by machine learning.

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.

Selective agonism of human pregnane X receptor by individual ginkgolides.

Ginkgolide A, ginkgolide B, ginkgolide C, and ginkgolide J are structurally related terpene trilactones present in Ginkgo biloba extract. Pregnane X receptor (PXR), glucocorticoid receptor (GR), and constitutive androstane receptor (CAR) regulate the expression of genes involved in diverse biological functions. In the present study, we investigated the effects of individual ginkgolides as single chemical entities on the function of human PXR (hPXR), human GR (hGR), and human CAR (hCAR). In cell-based reporter gene assays, none of the ginkgolides activated hGR or hCAR (wild-type and its SV23, SV24, and SV25 splice variants). Concentration-response experiments showed that ginkgolide A and ginkgolide B activated hPXR and rat PXR to a greater extent than ginkgolide C, whereas ginkgolide J had no effect. As determined by a time-resolved fluorescence resonance energy transfer competitive binding assay, ginkgolide A and ginkgolide B, but not ginkgolide C or ginkgolide J, were shown to bind to the ligand-binding domain of hPXR, consistent with molecular docking data. Compared with tetraethyl 2-(3,5-di-tert-butyl-4-hydroxyphenyl)ethenyl-1,1-bisphosphonate (SR12813) (a known agonist of hPXR), ginkgolide A and ginkgolide B were considerably less potent in binding to hPXR. These two ginkgolides recruited steroid receptor coactivator-1 to hPXR and increased hPXR target gene (CYP3A4) expression, as assessed by a mammalian two-hybrid assay and real-time polymerase chain reaction, respectively. In conclusion, the individual ginkgolides regulate the function of nuclear receptors in a receptor-selective and chemical-dependent manner. This study identifies ginkgolide A and ginkgolide B as naturally occurring agonists of hPXR and provides mechanistic insight into the structure-activity relationship in ligand activation of hPXR.

Interaction of lapatinib with cytochrome P450 3A5.

Lapatinib, an oral tyrosine kinase inhibitor used for breast cancer, has been reported to cause idiosyncratic hepatotoxicity. Recently, it has been found that lapatinib forms a metabolite-inhibitor complex (MIC) with CYP3A4 via the formation of an alkylnitroso intermediate. Because CYP3A5 is highly polymorphic compared with CYP3A4 and also oxidizes lapatinib, we investigated the interactions of lapatinib with CYP3A5. Lapatinib inactivated CYP3A5 in a time-, concentration-, and NADPH-dependent manner using testosterone as a probe substrate with K(I) and k(inact) values of 0.0376 mM and 0.0226 min(-1), respectively. However, similar results were not obtained when midazolam was used as the probe substrate, suggesting that inactivation of CYP3A5 by lapatinib is site-specific. Poor recovery of CYP3A5 activity postdialysis and the lack of a Soret peak confirmed that lapatinib does not form a MIC with CYP3A5. The reduced CO difference spectrum further suggested that a large fraction of the reactive metabolite of lapatinib is covalently adducted to the apoprotein of CYP3A5. GSH trapping of a reactive metabolite of lapatinib formed by CYP3A5 confirmed the formation of a quinoneimine-GSH adduct derived from the O-dealkylated metabolite of lapatinib. In silico docking studies supported the preferential formation of an O-dealkylated metabolite of lapatinib by CYP3A5 compared with an N-hydroxylation reaction that is predominantly catalyzed by CYP3A4. In conclusion, lapatinib appears to be a mechanism-based inactivator of CYP3A5 via adduction of a quinoneimine metabolite.

3D-QSAR Study on dihydro-1,3,5-triazines and their spiro derivatives as DHFR inhibitors by comparative molecular field analysis (CoMFA).

A 3D-QSAR/CoMFA was performed for a series of triazine and its spiro derivative based DHFR inhibitors displaying IC(50) values ranging from 0.002 to 58.8 µM. Analyses resulted in a reliable computational model with the parameters of n=46, r(2)=0.986, q(2)=0.724, SE=0.164, F=275.889. It is shown that the steric and electrostatic properties predicted by CoMFA contours can be related to the DHFR inhibitory activity. The predictive ability of the resultant model was evaluated using a test set comprised of 18 molecules and the results show that the CoMFA model is able to correctly predict the poor inhibitory activities of the compounds in the testing set. This model is a significant guide to trace the features that really matter especially with respect to the design of novel compounds.

Rational design of selective organoruthenium inhibitors of protein tyrosine phosphatase 1B.

Protein tyrosine phosphatases (PTPs) belong to a large family of important regulatory enzymes involved in vital mammalian signaling pathways. Selective inhibitors of PTPs are highly valuable from a therapeutic standpoint given their association with various pathological conditions. One such target is PTP-1B which has previously been linked to diabetes and cancer. However, developing a selective inhibitor against PTP-1B has proven to be daunting because the enzyme shares a high degree of structural homology with TC-PTP, an essential PTP involved in modulating immune functions. To address this challenge, a series of organoruthenium complexes was developed to bind at the PTP substrate-binding site while simultaneously target the peripheral structural space. By capitalizing on the potential difference in the structural environment proximal to the active site between different PTPs, selectivity toward PTP-1B over TC-PTP was improved, paving the way for organoruthenium complexes as selective PTP-1B metalloinhibitors.

Consensus QSAR model for identifying novel H5N1 inhibitors.

Due to the importance of neuraminidase in the pathogenesis of influenza virus infection, it has been regarded as the most important drug target for the treatment of influenza. Resistance to currently available drugs and new findings related to structure of the protein requires novel neuraminidase 1 (N1) inhibitors. In this study, a consensus QSAR model with defined applicability domain (AD) was developed using published N1 inhibitors. The consensus model was validated using an external validation set. The model achieved high sensitivity, specificity, and overall accuracy along with low false positive rate (FPR) and false discovery rate (FDR). The performance of model on the external validation set and training set were comparable, thus it was unlikely to be overfitted. The low FPR and low FDR will increase its accuracy in screening large chemical libraries. Screening of ZINC library resulted in 64,772 compounds as probable N1 inhibitors, while 173,674 compounds were defined to be outside the AD of the consensus model. The advantage of the current model is that it was developed using a large and diverse dataset and has a defined AD which prevents its use on compounds that it is not capable of predicting. The consensus model developed in this study is made available via the free software, PaDEL-DDPredictor.

QSAR classification of metabolic activation of chemicals into covalently reactive species.

Metabolic activation of chemicals into covalently reactive species might lead to toxicological consequences such as tissue necrosis, carcinogenicity, teratogenicity, or immune-mediated toxicities. Early prediction of this undesirable outcome can help in selecting candidates with increased chance of success, thus, reducing attrition at all stages of drug development. The ensemble modelling of mixed features was used for the development of a model to classify the metabolic activation of chemicals into covalently reactive species. The effects of the quality of base classifiers and performance measure for sorting were examined. An ensemble model of 13 naive Bayes classifiers was built from a diverse set of 1,479 compounds. The ensemble model was validated internally with five-fold cross validation and it has achieved sensitivity of 67.4% and specificity of 93.4% when tested on the training set. The final ensemble model was made available for public use.

Identification of active compounds from medicinal plant extracts using gas chromatography-mass spectrometry and multivariate data analysis.

Conventional methods of drug discovery from natural products include bioassay-guided fractionation, which is tedious and has low efficiency. The aim of this work is to develop a platform method to rapidly identify bioactive compounds from crude plant extracts and their partially purified fractions using multivariate data analysis (MVDA). Soxhlet extraction and liquid-liquid fractionation were used to prepare different extracts and fractions from the leaves of a medicinal plant, Ardisia elliptica. The extracts and fractions were analysed chemically using GC-MS, and their ability to inhibit platelet aggregation was investigated. Two MVDA methods were developed and optimised to analyse the results. In the first method, compounds with the highest contribution scores for biological activity calculated by different models were listed as potential antiplatelet compounds. For the second MVDA method, a correlation of the concentrations of constituents and biological activities in the various extracts and fractions for each compound was done. Compounds with the highest correlation coefficients were identified as potential antiplatelet compounds. One of the predicted components was isolated, purified and confirmed to possess antiplatelet effects. This platform method can be developed and optimised for other plant extracts and biological activities, thus reducing time and cost of drug discovery while improving efficiency.

Automated systems to identify relevant documents in product risk management.

BACKGROUND: Product risk management involves critical assessment of the risks and benefits of health products circulating in the market. One of the important sources of safety information is the primary literature, especially for newer products which regulatory authorities have relatively little experience with. Although the primary literature provides vast and diverse information, only a small proportion of which is useful for product risk assessment work. Hence, the aim of this study is to explore the possibility of using text mining to automate the identification of useful articles, which will reduce the time taken for literature search and hence improving work efficiency. In this study, term-frequency inverse document-frequency values were computed for predictors extracted from the titles and abstracts of articles related to three tumour necrosis factors-alpha blockers. A general automated system was developed using only general predictors and was tested for its generalizability using articles related to four other drug classes. Several specific automated systems were developed using both general and specific predictors and training sets of different sizes in order to determine the minimum number of articles required for developing such systems. RESULTS: The general automated system had an area under the curve value of 0.731 and was able to rank 34.6% and 46.2% of the total number of 'useful' articles among the first 10% and 20% of the articles presented to the evaluators when tested on the generalizability set. However, its use may be limited by the subjective definition of useful articles. For the specific automated system, it was found that only 20 articles were required to develop a specific automated system with a prediction performance (AUC 0.748) that was better than that of general automated system. CONCLUSIONS: Specific automated systems can be developed rapidly and avoid problems caused by subjective definition of useful articles. Thus the efficiency of product risk management can be improved with the use of specific automated systems.

Psychometric Properties of the Patient Activation Measure in Community-Dwelling Adults in Singapore.

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.