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Health literacy (HL) skills are essential to enable self-management and shared decision-making in patients with type 2 diabetes mellitus (T2DM). Limited HL in these patients is associated with poorer outcomes. It is not clear what the burden of limited HL in patients with T2DM across countries and what factors influence it. A systematic review was conducted according to the PRISMA guidelines. The study protocol was registered with PROSPERO (CRD42017056150). We searched MEDLINE, EMBASE, PsycINFO, CINAHL and ERIC for articles published up to January 2017. Articles that measured HL levels in adult patients with T2DM; that used validated HL tools; and that were reported in English were included. Two reviewers assessed studies for eligibility and quality, and extracted the data. Prevalence of limited HL is calculated from the number of patients with less than adequate HL over the total number of patients with T2DM in the study. Meta-analysis and meta-regression analysis were conducted using the Open Meta-analyst software. Twenty-nine studies involving 13,457 patients with T2DM from seven countries were included. In total, seven different HL measurement tools were used. The prevalence of limited HL ranged from 7.3% to 82%, lowest in Switzerland and the highest in Taiwan. Meta-regression analysis of all included studies showed the country of study (p<0.001), HL tool used (p = 0.002), and the country's region (p<0.001) contributed to the variation findings. Thirteen studies in the USA measured functional HL. The pooled prevalence of inadequate functional HL among patients with T2DM in the USA was 28.9% (95% CI: 20.4-37.3), with high heterogeneity (I2 = 97.9%, p <0.001). Studies were done in the community as opposed to a hospital or primary care (p = 0.005) and populations with education level lower than high school education (p = 0.009) reported a higher prevalence of limited HL. The prevalence of limited HL in patients with T2DM varied widely between countries, HL tools used and the country's region. Pooled prevalence showed nearly one in three patients with T2DM in the USA had limited functional HL. Interactions with healthcare providers and educational attainment were associated with reported of prevalence in the USA.

ChatGPT, an artificial intelligence (AI) language model based on the GPT-3.5 architecture, is revolutionising scientific writing and medical research. Researchers employ ChatGPT for diverse tasks, including automated literature reviews, structured-outline generation and drafting/editing assistance. The tool adapts language for varied audiences, aids in citation management, supports collaborative writing and peer review and facilitates table/figure creation. While it enhances efficiency, concerns arise regarding ethics, bias, accuracy and originality. Transparent data sourcing and validation are crucial, as ChatGPT complements human efforts but does not replace critical thinking. Accordingly, researchers must uphold integrity, ensuring that AI-assisted content aligns with research principles. Acknowledgement of AI use in manuscripts, as recommended by the International Committee of Medical Journal Editors, ensures accountability. ChatGPT’s transformative potential lies in harmonising its capabilities with researchers’ expertise, fostering a symbiotic relationship that advances scientific progress and ethical standards.

There were errors in the extraction of numbers used to calculate the prevalence of limited health literacy, resulting in the incorrect extracted values for Souza, J. G., et al (2014), Kim, S. H. (2009), Chen, G. D., et al (2014), van der Heide, I., et al (2014), Aikens JE, Piette JD. (2009), Mancuso, J. M. (2010) and Wallace, A. S., et al (2010) in Table 1. The study with the highest reported prevalence of limited health literacy (76.3%) was conducted to determine the mechanism through with health literacy exerted its influence on health outcomes related to diabetes care. Meta-regression analysis identified two factors that predicted this heterogeneity, the study setting (p = 0.005) and the proportion of participants with more the high school education (p = 0.009).

ObjectiveLimited health literacy in patients with type 2 diabetes mellitus (T2DM) led to poorer diabetes knowledge, less medication adherence and increased healthcare cost. The purpose of this paper was to report the prevalence of limited health literacy in patients with T2DM and to identify factors that are associated with it.DesignA cross-sectional study was conducted from January to March 2018; data on patients’ sociodemographic characteristics, diabetes knowledge, perceived social support and health literacy level were collected. Health literacy level was measured using the European Health Literacy Survey Questionnaire (HLS-EU-Q47).SettingPatients were recruited from four primary care clinics in Perak, Malaysia.ParticipantsAdult patients diagnosed with T2DM who attended the study clinics during the study period.Primary outcome variablePatients with HLS-EU-Q47 General Index of ≤33 points were classified as having limited health literacy.ResultsThe prevalence of limited health literacy was 65.3% (n=279). In bivariate analysis, patients’ ethnicity (p=0.04), highest education level (p<0.001), monthly income (p=0.003), having health insurance (p=0.007), English language fluency (p<0.001), Malay language fluency (p=0.021), attending diabetes education sessions (p<0.001), perceived social support (p<0.001) and diabetes knowledge (p=0.019) were factors associated with limited health literacy. In logistic regression, not being fluent in English was associated with limited health literacy (OR=2.36, 95% CI 1.30 to 4.30) whereas having high perceived social support (OR=0.52, 95% CI 0.40 to 0.69) and having attended diabetes education sessions (OR=0.42, 95% CI 0.27 to 0.68) were associated with adequate health literacy.ConclusionThe prevalence of limited health literacy is high among patients with T2DM in Perak, Malaysia. Strategies to improve health literacy in these patients must consider the influences of English fluency, attendance at diabetes education sessions and social support, and may need to adopt a universal approach to addressing limited health literacy.

Background The evidence of the impact of online health information-seeking (OHIS) on health outcomes has been conflicting. OHIS is increasingly recognised as a factor influencing health behaviour but the impact of OHIS on medication adherence remains unclear. Objectives We conducted a systematic review and meta-analysis to examine the associations between OHIS and medication adherence. Methods We searched Medline, Embase, Web of Science, Scopus, CINAHL and Psychology and Behavioural Science Collection for studies published up to December 2020. The inclusion criteria were studies that reported the associations of OHIS and medication adherence, quantitative design, reported primary data only, related to any health condition where medications are used and conducted on patients either in clinical or community settings. A meta-analysis was used to examine the association between OHIS and medication adherence. Results A total of 17 studies involving 24,890 patients were included in this review. The study designs and results were mixed. In the meta-analysis, there was no significant association (n = 7, OR 1.356, 95% CI 0.793-2.322, p = 0.265), or correlation (n = 4, r = -0.085, 95% CI −0.572-0.446, p = 0.768) between OHIS and medication adherence. In the sub-group analysis of people living with HIV/AIDS, OHIS was associated with better medication adherence (OR 1.612, 95% CI 1.266-2.054, p < 0.001). Conclusions The current evidence of an association between OHIS and medication adherence is inconclusive. This review highlights methodological issues on how to measure OHIS objectively and calls for in-depth exploration of how OHIS affects health decisions and behaviour.

The last 2 decades have been a time of exponential growth and maturation for digital health, while the global burden of respiratory disease continues to grow worldwide. Leveraging digital health interventions (DHIs) to manage and mitigate respiratory disease and its adverse health effects presents itself as an obvious path forward. We aimed to understand the current digital landscape and enabling environment around respiratory health to reduce costs, avoid duplication, and understand the comprehensiveness of DHIs. This study will follow a scoping review methodology as outlined by Arksey and O'Malley, the Joanna Briggs Institute, and the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) checklist. MEDLINE, Embase, CINAHL, PsycINFO, Cochrane Library, Web of Science, PakiMedNet, and MyMedR databases will be searched along with key websites, repositories, and gray literature databases. The terms \"respiratory health,\" \"digital health,\" \"South Asia,\" and \"Southeast Asia,\" as well as related terms will be searched. The results will be screened for duplicates and then against the inclusion and exclusion criteria. For the studies included, data will be extracted, collated, and analyzed. The scoping review was started in July 2023 and will be finalized by February 2024. Results will be presented following the World Health Organization's classification of DHIs to categorize interventions in a standardized format and the mobile health evidence reporting and assessment checklist to report on the effectiveness of interventions. Further exposition of the evidence extracted will be presented through narrative synthesis. As DHIs continue to proliferate, the need to understand the current landscape becomes more pertinent. In this scoping review, we will seek to more clearly understand what digital health tools and technologies are being used in the current landscape of digital health in South and Southeast Asia for respiratory health and to what extent they are addressing the respiratory health needs of the region. The results will inform recommendations on digital health tools for respiratory health in South and Southeast Asia will help funders and implementers of DHIs leverage existing technologies and accelerate innovations that address documented gaps in the studied countries. DERR1-10.2196/52517.

Background - Recently, there have been attempts to develop mHealth applications for asthma self-management. However, there is a lack of applications that can offer accurate predictions of asthma exacerbation using the weather triggers and demographic characteristics to give tailored response to users. This paper proposes an optimised Deep Neural Network Regression (DNNR) model to predict asthma exacerbation based on personalised weather triggers. Methods - With the aim of integrating weather, demography, and asthma tracking, an mHealth application was developed where users conduct the Asthma Control Test (ACT) to identify the chances of their asthma exacerbation. The asthma dataset consists of panel data from 10 users that includes 1010 ACT scores as the target output. Moreover, the dataset contains 10 input features which include five weather features (temperature, humidity, air-pressure, UV-index, wind-speed) and five demography features (age, gender, outdoor-job, outdoor-activities, location). Results - Using the DNNR model on the asthma dataset, a score of 0.83 was achieved with Mean Absolute Error (MAE)=1.44 and Mean Squared Error (MSE)=3.62. It was recognised that, for effective asthma self-management, the prediction errors must be in the acceptable loss range (error<0.5). Therefore, an optimisation process was proposed to reduce the error rates and increase the accuracy by applying standardisation and fragmented-grid-search. Consequently, the optimised-DNNR model (with 2 hidden-layers and 50 hidden-nodes) using the Adam optimiser achieved a 94% accuracy with MAE=0.20 and MSE=0.09. Conclusions - This study is the first of its kind that recognises the potentials of DNNR to identify the correlation patterns among asthma, weather, and demographic variables. The optimised-DNNR model provides predictions with a significantly higher accuracy rate than the existing predictive models and using less computing time. Thus, the optimisation process is useful to build an enhanced model that can be integrated into the asthma self-management for mHealth application.

The pandemic created challenges for trainers and trainees, including the fear of contracting COVID-19 infection, geographical separation from their loved ones, worry about their own and family members health and uncertainty about the future.· 1 Accelerated adoption of technological advances in patient care and education was necessary to help reduce the spread of the virus while helping healthcare services to stay open and for training to continue. By implementing the core values and principles of family medicine, our centre instituted daily physical morning checkins and briefings, used a mass communication channel to disseminate information, implemented an online risk assessment for trainees exposed to the virus and continued the teaching and learning sessions by providing trainees with suitable personal protective equipment so they could continue to manage patients and by using online platforms. In this way, even with advancing technologies in patient care and education, human touch and kindness will not be lost.

The participation of general practitioners (GPs) in primary care research is variable and often poor. We aimed to develop a substantive and empirical theoretical framework to explain GPs' decision-making process to participate in research. We used the grounded theory approach to construct a substantive theory to explain the decision-making process of GPs to participate in research activities. Five in-depth interviews and four focus group discussions were conducted among 21 GPs. Purposeful sampling followed by theoretical sampling were used to attempt saturation of the core category. Data were collected using semi-structured open-ended questions. Interviews were recorded, transcribed verbatim and checked prior to analysis. Open line-by-line coding followed by focus coding were used to arrive at a substantive theory. Memoing was used to help bring concepts to higher abstract levels. The GPs' decision to participate in research was attributed to their inner drive and appreciation for primary care research and their confidence in managing their social and research environments. The drive and appreciation for research motivated the GPs to undergo research training to enhance their research knowledge, skills and confidence. However, the critical step in the GPs' decision to participate in research was their ability to align their research agenda with priorities in their social environment, which included personal life goals, clinical practice and organisational culture. Perceived support for research, such as funding and technical expertise, facilitated the GPs' participation in research. In addition, prior experiences participating in research also influenced the GPs' confidence in taking part in future research. The key to GPs deciding to participate in research is whether the research agenda aligns with the priorities in their social environment. Therefore, research training is important, but should be included in further measures and should comply with GPs' social environments and research support.

Background People are exposed to variable health information from the Internet, potentially influencing their health decision-making and behaviour. It remains a challenge for people to discern between good- and poor-quality online health information (OHI). This study explored how patients evaluate and determine trust in statin-related OHI in patients with high cardiovascular risk. Methods This qualitative study used vignettes and think-aloud methods. We recruited patients from a primary care clinic who were at least 18 years old, had high cardiovascular risk and had previously sought OHI. Participants were given two statin-related vignettes: Vignette 1 (low-quality information) and Vignette 2 (high-quality information). Participants voiced their thoughts aloud when reading the vignettes and determined the trust level for each vignette using a 5-point Likert scale. This was followed by a semi-structured interview which was audio-recorded and transcribed verbatim. The transcripts were coded and analysed using thematic analysis. Results A total of 20 participants were recruited, with age ranging from 38–74 years. Among all the high cardiovascular-risk participants, eight had pre-existing cardiovascular diseases. For Vignette 1 (low-quality information), five participants trusted it while nine participants were unsure of their trust. 17 participants (85%) trusted Vignette 2 (high-quality information). Five themes emerged from the analysis of how patients evaluated OHI: (1) logical content, (2) neutral stance and tone of OHI content, (3) credibility of the information source, (4) consistent with prior knowledge and experience, and (5) corroboration with information from other sources. Conclusion Patients with high cardiovascular risks focused on the content, source credibility and information consistency when evaluating and determining their trust in statin-related OHI. Doctors should adopt a more personalised approach when discussing statin-related online misinformation with patients by considering their prior knowledge, beliefs and experience of statin use.