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BackgroundThe use of mobile health (mHealth) has gained popularity globally, including for its use in a variety of health interventions, particularly through short message service (SMS) text messaging. However, there are challenges to the use of mHealth, particularly among older users who have a large heterogeneity in usability and accessibility barriers when using technology. ObjectiveIn order to better understand and conceptualize the diversity of users and give insight into their particular needs, we turned to persona creation. Personas are user archetypes created through data generated from multi-method inquiry with actual target users. Personas are an appropriate yet largely underutilized component of current mHealth research. MethodsLeveraging data from a multi-method study conducted in Singapore with an ethnically diverse population including Chinese, Malay, and Indian participants, we used a proforma to analyze data from the qualitative component (ie, 20 in-depth interviews) and quantitative component (ie, 100 interviewer-guided surveys). We then identified key characteristics, including technology use and preferences as well as adherence factors, to synthesize five personas reflective of persons over the age of 40 years in Singapore with atherosclerotic cardiovascular disease (ASCVD) or ASCVD risk factors, such as hypertension. ResultsWe present five personas typologized as (1) The Quiet Analog, (2) The Busy Grandparent, (3) The Socializer, (4) The Newly Diagnosed, and (5) The Hard-to-Reach. We report on four key characteristics: health care access, medication adherence, mobile phone technology usage (ie, ownership, access, and utilization), and interest in mHealth. Finally, we provide insights into how these personas may be used in the design and implementation of an mHealth intervention. Our work demonstrates how multi-method data can create biopsychosocial personas that can be used to explore and address the diversity in behaviors, preferences, and needs in user groups. ConclusionsWith wider adoption of mHealth, it is important that we consider user-centered design techniques and design thinking in order to create meaningful, patient-centered interventions for adherence to medications. Future research in this area should include greater exploration of how these five personas can be used to better understand how and when is best to deliver mHealth interventions in Singapore and beyond.

BackgroundCardiovascular disease, including atherosclerotic cardiovascular disease (ASCVD), is a growing public health threat globally and many individuals remain undiagnosed, untreated, and uncontrolled. Simultaneously, mobile health (mHealth) interventions using short messaging service (SMS) have gained popularity globally. There is an opportunity for innovative approaches such as mHealth to encourage and enable adherence to medications for ASCVD and its risk factors. ObjectiveThis study aimed to understand mobile technology acceptance, use, and facilitating conditions among the study population ahead of the design of an mHealth intervention. MethodsUsing data from a mixed-methods study conducted in Singapore, we conducted a cross-sectional survey with 100 participants and in-depth, semistructured interviews with 20 patients. All participants were over the age of 40 years with ASCVD or its risk factors. Interviews were conducted in English and Mandarin and if needed translated to English. Nvivo 11 (QSR International) was used for analyses. ResultsParticipants reported their perspectives on technology use and preferences, including low or sporadic mobile phone use and usability concerns including small screen and text size, among others; the benefit of previous mHealth use in creating a favorable opinion of SMS for health information; trust in both the source of mHealth SMS, as well as in treatment; the formation of habits; and fear of sequelae or death for facilitating intention to use an mHealth intervention and adhere to medication. We also highlighted a case that underscored the importance of the period after diagnosis in habit forming as an opportunity for an mHealth intervention. ConclusionsWe explored both technology- and adherence-related factors that influence a patient’s intention to use an mHealth intervention for adherence to ASCVD medication in Singapore. We highlighted the importance of identifying the right opportunity to engage with patients and promote an mHealth intervention for adherence, such as immediately following diagnosis when patients are establishing medication-taking habits.

ObjectiveIn an earlier study, several tested International Pharmaceutical Federation (FIP) pictograms did not achieve validity among older adults in Singapore. In this study, for 27 unvalidated FIP pictograms, we (1) developed variants of each pictogram, (2) elicited the most-preferred variant, and (3) assessed the validity of the most-preferred variant among older Singaporeans.MethodsIn phase 1, up to three variants of the 27 pictograms were developed, based on older adults' feedback from a previous study. In phase 2, the most-preferred variant of 26 pictograms, which had two or three variants, was selected by 100 older participants. In phase 3, the 27 most-preferred variants (including the pictogram with only one variant) were assessed for validity - transparency and translucency - among 278 older participants (10 pictograms per participant). To evaluate transparency, participants were first asked: "If you see this picture on a medicine label, what do you think it means?" for each assigned pictogram. If they responded, they were asked, "How do you know?", and if not, they were told, "Tell me everything you see in this picture". Then, participants were shown their assigned pictograms again, one by one, and the pictogram's intended meaning was revealed to evaluate translucency. Pictograms were classified as valid (≥66% participants interpreted its intended meaning correctly [transparency criterion] and ≥85% participants rated its representativeness as ≥ 5 [translucency criterion]), partially valid (only transparency criterion fulfilled) or not valid.ResultsIn phase 1, 77 variants of the 27 pictograms were developed. In phase 2, a majority of the most-preferred variants were selected by >50% participants. In phase 3, 10 (37.0%) of the 27 pictograms tested were considered valid, and five (18.5%) were partially valid. A higher proportion of pictograms portraying dose and route of administration and precautions were valid or partially valid, versus those depicting indications or side effects.ConclusionContextual redesigning and selection of pharmaceutical pictograms, which initially failed to achieve validity in a population, contributed to their validation.InnovationThe redesigned validated pictograms from this study can be incorporated into relevant patient information materials in clinical practice.

BackgroundPrescription medication labels (PMLs) predominantly dispensed in English, are an important adjunct to medication counselling. PMLs are routinely used by pharmacy staff to counsel older adults about their medications. This study sought to identify challenges that pharmacy staff observe older adults face in using their PMLs, and to identify and quantify solutions employed by pharmacy staff during medication counselling to address such challenges.MethodsTen in-depth interviews were done with primary care pharmacy staff to gather the range of challenges and solutions. Subsequently, a quantitative survey, informed by the qualitative findings, was administered to 121 pharmacy staff to assess if the reported solutions were commonly used.ResultsThe two main challenges were incongruity between PML language (English) and older adults' language proficiency, and poor PML legibility. The solutions, classified under three themes, were simplifying medication information on PMLs, supplementing PMLs with additional medication information and mitigating poor readability.ConclusionsPharmacy staff observed challenges faced by older adults in using PMLs during medication counselling. Ad-hoc improvisations by pharmacy staff to PMLs were pervasive. System-level PML improvements, such as provision of legible bilingual medication instructions, pharmaceutical pictograms and additional medication information, through patient information leaflets or using quick response (QR) codes on PMLs, should be considered. This will facilitate patient-provider communication, especially in settings with language dissonance between PMLs and patients.

BackgroundPrescription medication labels (PMLs) are an important source of written medication information for patients. However, real-world PMLs do not entirely conform with available labelling best practices and guidelines. Given this disconnect, older adults remain particularly at risk of misinterpreting their PMLs. Past studies have commonly assessed hypothetical PMLs, warranting studies that explore the lived experiences of older adults with real-world PMLs. Furthermore, the perspective of family caregivers of older adults is yet to be studied.ObjectivesThis qualitative study documented the challenges faced by older adults and their family caregivers in using real-world PMLs, their strategies to cope with these challenges, and their suggestions to improve existing PMLs.MethodsWe conducted two focus group discussions (n = 17) and 30 in-depth interviews with older adults (n = 20; including those who can read in English and those with limited English proficiency) and caregivers (n = 10) in Singapore. The data were systematically assigned to codes that were continuously refined to accommodate emergent themes.ResultsChallenges, coping strategies and suggested improvements were related to the comprehensibility, availability, readability and consistency of medication information on PMLs.ConclusionsReal-world PMLs continue to pose challenges for older adults and their caregivers, necessitating them to seek unique and personal coping strategies. The identified PML improvements, desired by older adults and their caregivers, urge healthcare systems to implement improved PMLs. Future research should explore system-level logistical, financial, and administrative barriers (or opportunities) that hinder (or facilitate) this implementation.

Background: Mild stroke affects more than half the stroke population, yet there is limited evidence characterizing cognition over time in this population, especially with predictive approaches applicable at the individual-level. We aimed to identify patterns of recovery and the best combination of demographic, clinical, and lifestyle factors predicting individual-level cognitive state at 3- and 12-months after mild stroke. Methods: In this prospective cohort study, the Montreal Cognitive Assessment (MoCA) was administered at 3–7 days, 3- and 12-months post-stroke. Raw changes in MoCA and impairment rates (defined as MoCA<24 points) were compared between assessment time-points. Trajectory clusters were identified using variations of ≥1 point in MoCA scores. To further compare clusters, additional assessments administered at 3- and 12-months were included. Gamma and Quantile mixed-effects regression were used to predict individual MoCA scores over time, using baseline clinical and demographic variables. Model predictions were fitted for each stroke survivor and evaluated using model cross-validation to identify the overall best predictors of cognitive recovery. Results: Participants' (n = 119) MoCA scores improved from baseline to 3-months (p<0.001); and decreased from 3- to 12-months post-stroke (p = 0.010). Cognitive impairment rates decreased significantly from baseline to 3-months (p<0.001), but not between 3- and 12-months (p = 0.168). Nine distinct trajectory clusters were identified. Clinical characteristics between clusters at each time-point varied in cognitive outcomes but not in clinical and/or activity participation outcomes. Cognitive performance at 3- and 12-months was best predicted by younger age, higher physical activity levels, and left-hemisphere lesion side. Conclusion: More than half of mild-stroke survivors are at risk of cognitive decline one year after stroke, even when preceded by a significantly improving pattern in the first 3-months of recovery. Physical activity was the only modifiable factor independently associated with cognitive recovery. Individual-level prediction methods may inform the timing and personalized application of future interventions to maximize cognitive recovery post-stroke. [ABSTRACT FROM AUTHOR]

Background: Telemonitoring programs have been found to be effective in improving diabetic control by promoting patients' self-management of diabetes through medication adherence, dietary modifications, and exercise. Nonetheless, few studies have assessed the cost-effectiveness of telemonitoring for the self-management of diabetes based on real-world data. Methods: A randomized controlled trial entitled Optimizing care of Patients via Telehealth In Monitoring and Augmenting their control of Diabetes Mellitus was conducted among adults with Type 2 Diabetes Mellitus in Singapore. Individuals in the intervention group (n = 159) underwent a telemonitoring program comprising of remote patient monitoring, education, individualized health coaching, and teleconsultations, whereas individuals in the control group (n = 160) received regular care. Economic evaluation was conducted from health care system and societal perspectives in 2020 in Singapore dollars, using health outcomes and costs documented at baseline and at 6 month follow-up. One-way sensitivity analyses and bootstrapping to generate scatter plot on cost-effectiveness planes were done. Results: The adjusted reduction in HbA1c scores was greater in the intervention group by −0.41 (95% confidence interval [CI], −0.65 to −0.17), while the change in utility scores was higher in the intervention group by 0.011 (95% CI, −0.016 to 0.0378). From a health care perspective, the incremental cost-effectiveness ratio (ICER) of the telemonitoring program per unit improvement in HbA1c, per additional case of well-controlled diabetes, and per unit improvement in quality adjusted life years was SGD 580.44, SGD 9100.15, and SGD 21,476.36, respectively. From a societal perspective, the ICERs were SGD 817.20, SGD 12,812.02, and SGD 30,236.36, respectively. Conclusions: The Optimizing care of Patients via Telehealth In Monitoring and Augmenting their control of Diabetes Mellitus telemonitoring program was effective and potentially cost-effective for the management and control of diabetes among patients in primary care. [ABSTRACT FROM AUTHOR]

Introduction: Children from low-income (LI) families often suffer from poor health, with sub-optimal health practices. This cross-sectional study examined the differences in health habits and health-related quality of life (HRQoL) of LI preschool children compared to non-low-income preschool peers (PPG). Method: Using data from the social-health Circle of Care-Health Development Screening Programme (CoC-HDSP) in Singapore, 118 LI children and 304 PPG children aged 18 months to 6 years old and their families were recruited from 13 government-funded preschools. Health practices examined included screen time habits, sleep, nutrition, dental health and the children's HRQoL using PedsQL 4.0 Generic Core Scales. Results: Majority of the children were aged 4-6 years in kindergarten 1 and 2. There were more Malay children in the LI than the PPG (61.9% versus [vs] 29.3%, P<0.001). Low-income children were more likely to have lower-educated parents (P<0.001). The completed vaccination rate in the LI group was lower than those in PPG (84.7% vs 98.0%, P<0.001). More in the LI group utilised emergency services for acute illnesses (P<0.05). Fewer LI children had ever visited a dentist (47.4% vs 75.4%, P<0.001), and more LI children consumed sweetened drinks daily (33.3% vs 8.6%, P<0.001). The LI group reported poorerquality sleep (48.3% vs 27.2%, P<0.001), though both groups exceeded the daily recommended screen viewing duration. The LI group scored higher in the social (mean 92.4±12.2 vs 84.3±15.3, P<0.001) and emotional (mean 85.2±15.1 vs 76.6±17.3, P<0.001) domains of the PedsQL 4.0 when compared to PPG. Conclusion: Low-income children have poorer health practices, receive less preventive paediatric care, and utilise more emergency services for acute illnesses. These findings are important for developing interventions that work towards improving the health of LI children. [ABSTRACT FROM AUTHOR]