Access To Health Information Research Articles

Patients with antiphospholipid antibodies preferentially seek health information from physicians: a cross-sectional online patient quantitative survey.

Little is known about how patients with antiphospholipid syndrome (APS) or antiphospholipid antibodies (aPL) access and trust health information. This research aimed to: describe the sources of information most frequently accessed/trusted by patients with APS/aPL; identify if individuals with APS/aPL perceived their health had been negatively impacted by various sources and document obstacles to accessing health information. Patients meeting Revised Sapporo Criteria for APS or with ≥1 positive aPL on ≥2 occasions were recruited to an online survey regarding their health information use at diagnosis and within 6 months preceding survey completion. McNemar tests were used to compare percentages accessing and trusting each source at diagnosis/currently. 69 patients completed the survey; 88.4% were female, mean age was 47.4 years (SD 15.1). The sources most frequently accessed at diagnosis and currently were rheumatologists/lupus specialists, hematologists, and family physicians, yet patients accessed family physicians (47.8% vs. 31.9%, difference -15.9%, 95% CI - 29.2%, -2.7%) and hematologists (47.8% vs. 31.9%, difference -15.9%, 95% CI -31.1%, -0.8%) less frequently from diagnosis to currently. The most trusted sources at diagnosis and currently were rheumatologists/lupus specialists (82.6% vs. 92.8%) and family physicians (66.7% vs. 68.1%). Few respondents reported negative impacts from advocacy organizations (4.4%), websites (5.8%) and social media (4.4%). 20.3% reported challenges communicating with healthcare providers. Patients with aPL/APS preferentially seek health information from and trust their physicians. However, 20.3% of patients felt communication with healthcare providers was an obstacle to accessing information. There is a need for enhanced patient-physician communication.

Do you think medicines can be prescribed in a more eco-directed, greener way? A qualitative study based on public and prescriber focus groups on the impact of pharmaceuticals in Scotland’s water environment

ObjectivesThis qualitative study explored public and prescriber awareness of pharmaceutical pollution in the water environment and eco-directed sustainable prescribing (EDSP) as a mitigation strategy to reduce the environmental impact of...

Mai: A Transformer Based Domain Specific Chatbot for Menstrual Health

Traditional health-seeking behaviors, particularly in menstrual health, are deeply rooted in local languages, sociocultural norms, and religious beliefs. These factors significantly influence women in South Asia and other developing regions, often proving detrimental to their physical and psychological health. Recognizing the multifaceted nature of these challenges, this paper investigates the role of generative domain-specific chatbots as a supportive mechanism to enhance menstrual health-seeking behaviors among South Asian women. Specifically, it aims to create and assess Mai, a conversational agent, which utilizes Roman-Urdu and English models to provide accurate information, thereby contributing to the broader effort of empowering women with knowledge and resources. Due to a lack of conversational data in this domain, our research involves creating a dataset from existing English sources and translating it into Roman Urdu, presenting its own set of challenges. These datasets, specifically curated for this research, addressed a wide range of menstrual health topics. Despite being an English monolingual model, DialoGPT’s transformer architecture produced favorable results when fine-tuned on a Roman Urdu dataset. While the Roman Urdu version occasionally faced challenges with contextual understanding, both models achieved promising results. Automatic evaluation metrics indicated strong performance for Mai compared to baseline models. Likewise, user evaluations yielded average ratings of 4.2 and 4.3 (out of 5) for the Roman Urdu and English chatbots, respectively, and more than half of the medical professionals surveyed expressed willingness to recommend the dialogue system. Overall, our findings highlight the transformative potential of domain-specific dialogue systems in health education, with room for improvement in overcoming cultural and linguistic barriers to women’s health information access.

Teen relevant and open access health information for building vaccine confidence

Teen relevant and open access health information for building vaccine confidence

The Influence of Health Literacy on Diabetes Prevention Behaviors in Sai Mai District Communities, Bangkok

This research aimed to 1) assess health literacy levels 2) evaluate diabetes prevention behaviors and 3) analyze the influence of health literacy on diabetes prevention behaviors among residents in Sai Mai District communities, Bangkok. This cross-sectional survey research included 317 participants aged 35 years and above, selected through stratified random sampling. Data were collected from June to September 2024 using questionnaires with content validity and reliability (Cronbach's alpha coefficient = 0.87). Data were analyzed using descriptive statistics and multiple regression analysis. The results showed that the majority of participants had moderate levels of health literacy (65.3%) and diabetes prevention behaviors (58.7%). Factors significantly influencing diabetes prevention behaviors included education level (β = .325, p < .001), health information accessibility (β = .298, p < .001), self-management (β = .276, p < .001), age (β = .245, p < .01), and income (β = .198, p < .01). These variables collectively explained 52.3% of the variance in diabetes prevention behaviors (R² = .523). The findings can be applied to develop appropriate health literacy promotion programs and diabetes prevention behaviors suitable for the community context.

Developing a Framework to Measure Health Literacy Demands of Consumer-Facing Healthcare Organization Websites

Many consumer-facing healthcare organization websites are challenging for people with low e-health literacy skills to navigate and use the information to make informed decisions. Though searchers may be familiar with how to use the Internet, navigating website designs, often referred to as eHealth literacy, can make finding health information confusing. Health literacy demands, related to eHealth literacy skills concerning the content and design, can make the difference between consumers’ frustration and success. In this study, we aimed to create a framework to measure the accessibility and usability of healthcare organization consumer-facing websites using this question, “How can the information offered, and navigation of consumer-facing healthcare organization websites be improved to increase accessibility and usability?” We scored select healthcare organizations’ consumer-facing websites including their home page and two patient education pages, using Social Cognitive Theory and Health Literacy constructs both of which promote better accessibility and usability of health information. In addition, we analyzed how the health literacy demands of these pages support or obstruct the eHealth literacy skills of consumers. Results indicated that only 50% of Social Cognitive Theory constructs and 47% of Health Literacy constructs were observed. However, by examining the missing constructs healthcare organizations can assess where to focus consumer-facing website improvement efforts. Therefore, we concluded that Social Cognitive Theory combined with Health Literacy constructs offer a viable framework for measuring and potentially improving consumer-facing healthcare websites.

Explicating college students’ COVID-19 prevention behaviors: Integrating information seeking and response efficacy into the reasoned action approach

Objective: This study investigated correlations between college students’ intentions to adopt COVID-19 prevention behaviors (i.e., handwashing, mask wearing, and social distancing) and their attitudes, perceived norms, perceived efficacy, and information seeking. Participants: Students (N = 326) from a large Midwestern university recruited via simple random sampling. Methods: Using a cross-sectional survey from mid-March to April 2021, structural equation modeling assessed intentions across behaviors. Results: Attitudes and perceived self-efficacy were variably associated with intentions. Perceived injunctive norms were linked to intention across all behaviors. Response efficacy was associated only with social distancing intentions. Information seeking was tied to attitudes, perceived injunctive norms, and perceived response efficacy, across all behaviors. Conclusions: Information seeking affected how college students evaluate prevention behaviors, emphasizing the importance of disseminating accessible and accurate health information in this context. The findings also highlight the need for future interventions to tailor to the unique barriers and motivators for different prevention behaviors.

Health literacy assessment and analysis of influencing factors in pregnant women with gestational diabetes mellitus in Southwest China.

The main objectives of our study are evaluating the health literacy level among women with gestational diabetes mellitus (GDM) in Southwest China and explore the influencing factors, using a multidimensional health literacy assessment scale (Chinese version of the HLS-14). Given that the HLS-14 has not been used in GDM previously, its reliability and validity testing was included as a secondary objective. It was a cross-sectional survey with 565 GDM pregnancies. The Maternal and child health information access questionnaire, Chinese version of the HLS-14, Perceived Social Support Scale (PSSS) and General Self-efficacy Scale (GSES) was used to collect health information access behaviors, health literacy, social support and self-efficacy levels, respectively. SPSS 21.0 was used for descriptive statistical, multiple stepwise linear regression analysis and exploratory factor analysis (EFA). Amos 26.0 was used for confirmatory factor analysis (CFA). The Chinese version of HLS-14 has good reliability and validity in GDM pregnancies. The Cronbach's α are 0.849, 0.866, 0.859, and 0.883, respectively. The exploratory factor analysis extracted three common factors with a cumulative variance contribution rate of 68.405%. The confirmatory factor analysis model fit was good (χ2/df = 2.595, RMSEA = 0.055, IFI = 0.970, TLI = 0.963, CFI = 0.970). The HL level in pregnancies with GDM was moderate with a mean score of 3.26 ± 0.41, of which 24.10% had limited HL, 41.87% had moderate HL, and 34.03% had adequate HL. Regression analysis showed that the women with higher family support (β = 0.298, p < 0.001), recording pregnancy management diary (β = 0.199, p < 0.001), higher the family income (β = 0.140, p < 0.001), lower pre-pregnancy BMI (β = -0.116, p = 0.004), longer time spent searching for health information (β = 0.111, p = 0.006), and searching for health information through a medical health information website (β = 0.093, p = 0.019) had higher HL levels. These variables explained 23.1% of the variance in HL. The Chinese version of the HLS-14 has good applicability in the GDM pregnancies. The HL level of them is moderate, needs to be improved. Healthcare professionals should focus on the GDM population with low family income and high pre-pregnancy BMI, fully mobilize their social support system, provide reliable access to information, encourage all GDM pregnancies to use pregnancy management diaries to record their self-management behaviors, and ensure the effectiveness of health education.

Examining internet use for health information seeking and influencing factors among undergraduate health science students in Southwest Ethiopia.

The Internet has become a pivotal resource for accessing health information globally, offering unprecedented convenience and breadth of resources. This cross-sectional study examines the implications of Internet use for health information seeking and the influencing factors among undergraduate health science students in Southwest Ethiopia. An institutional-based cross-sectional study was conducted from November 10 to December 10, 2023. The study enrolled 423 students. Data were collected using a pretested and structured self-administered questionnaire. Data entry and analysis were performed using EpiData V4.6 and STATA V17, respectively. Bi-variable and multivariable logistic regression analyses were conducted to identify factors associated with the outcome variable. Statistical significance was determined using a P-value of less than 0.05. A total of 423 respondents participated in this study, resulting in a 100% response rate. Among them, 67.4% (95% CI: 63.0%-72.0%) reported using the Internet for health purposes. Factors significantly associated with this usage included being a third-year student or above (AOR=2.33, 95% CI: 1.36-3.99), owning a smartphone (AOR=2.41, 95% CI: 1.14-5.10), having good awareness (AOR=2.81, 95% CI: 1.55-5.09), holding a favorable attitude (AOR=9.58, 95% CI: 5.10-18.00), and possessing adequate e-health literacy (AOR=5.25, 95% CI: 2.89-9.46). This study underscores the internet's primary role in accessing information on diseases, treatments, healthy lifestyles, and prevention. Key factors such as e-health literacy, attitude, awareness, smartphone usage, and study timing significantly influence this trend. Understanding these factors is vital for optimizing internet resources for health information dissemination.

Assessing Health Disparities in Digital Services and Technologies During and After the COVID-19 Pandemic: A Pooled Cross-Sectional Analysis Using HINTS Data.

Digital health techniques were adopted faster during COVID-19, but the gap remains. This study analyzes how the digital gap affected pandemic patient portal uptake during and after. Patient portals improve physician connections and patient health information access, increasing health outcomes. Digital divide-lack of internet, digital literacy, and SDOH-may inhibit fair adoption. One study found that the internet and IT affected people during and after the pandemic. Learn why this patient demographic uses online patient portals so much. Like finding demographic, socioeconomic, and behavioral characteristics that affect portal usage, specifically drivers and barriers for health-conscious patients. This project developed a health promotion model and implemented initiatives to increase patient portal use and reduce health inequities. In 2020 and 2022, we used Health Information National Trends Survey (HINTS) data. Patient portal use dominated. Our cross-sectional study assessed patient portal use and various predictors. Age, marital status, sex, mental health, education, income, urban/rural (urbanity), family size, trust, social media use, chronic condition, and health app use predict. We handled survey data collection biases with weighted analyses. Data was computed using survey weights for population representation. Logistic regression and weighted descriptive statistics utilized STATA SE 16.1. Demographic, socioeconomic, and behavioral characteristics significantly affect online patient portal use. Portal usage is positively correlated with health app use, urbanity, higher income, sex, Asian/Native American race/ethnicity, and hospital trust. In addition, our data shows low adoption rates across the digital divide. Patients who trust others utilize patient portals, and previously established characteristics affect self-motivation for health improvement. Access obstacles and behavioral factors affect online patient portal adoption. Addressing the digital divide is crucial, but trust and self-motivation may improve patient portal utilization. Adopting health IT can improve patient participation and access to care, supporting equitable health outcomes.

Exploring the Challenges of Sensemaking in Expectant Teenagers Accessing Health Information in Kajiado County, Kenya

Teenage pregnancy is a major public health challenge in Kenya and many developing nations. Expectant teenagers ought to access with ease reliable information in order to promote the health of both the mother and fetus. The objective of this qualitative study, anchored on a relativist-interpretivist philosophical foundation, utilizing a case study method, was to explore the lived experiences of health information seeking with specific focus on challenges of sensemaking in expectant teenagers in Kajiado County, Kenya. 14 expectant teenagers, aged 15-19, selected purposively from nearby villages, towns and medical institutions participated in the study using a semi- structured interview and three focus groups of six each for triangulation. Thematic analysis was utilized. Ethical considerations like informed consent and confidentiality were taken to account. Research assistants who are well versed with culture were recruited to help in creating rapport and rich data. To focus the study, the Health Belief Model was applied. The study points at the need to come up with interventions to help expectant teens make decisions, such as leveraging trusted community leaders and healthcare professionals, digital literacy initiatives and peer education programs all aimed at developing teens' critical thinking abilities, encouraging their trust of reliable sources, and bridging the gap between traditional and modern knowledge systems.

Move to improve - Prescribing physical activity and deprescribing paracetamol for low back pain: Protocol for a hybrid type III feasibility study

IntroductionPeople experiencing low back pain (LBP) could potentially benefit from multimedia educational resources that integrate self-management strategies and improve awareness of the benefits of staying active and about medications that...

Mapping the risk of tick-borne encephalitis in Europe for informed vaccination decisions.

Tick-borne encephalitis is increasing across Europe, yet public awareness lags. Geo-visualizations leveraging openly available data empower travellers and health authorities in making informed (vaccination) choices. We urge improved surveillance and synchronization of data for easily accessible and understandable (geo)health information, to enhance early detection of infections.

Digital Health Equity and Patient Education: A New Paradigm in Patient Empowerment

The COVID-19 pandemic significantly impacted global healthcare, heightening vigilance among individuals with chronic disease and increasing levels of fear and depression. As a response, digital technologies, especially telehealth, have emerged as promising tools to address these challenges, facilitating health information access and supporting patient education and decision-making. The digital health landscape now includes electronic health records, remote monitoring, digital therapeutics, AI, and machine learning, which together enhance patient care, improve diagnosis accuracy, and streamline healthcare operations. Digital health tools, by presenting information interactively, engage patients cognitively and foster autonomy in health management. Additionally, social media and mobile health platforms contribute to health equity by promoting healthy behaviours and reducing barriers to access. However, disparities in digital health access, termed "digital health equity," remain a challenge. Digital health equity involves addressing “digital determinants of health," including technology access, digital literacy, and infrastructure, which interact with traditional social determinants of health. In this context, e-health literacy has become a critical factor in enabling individuals to retrieve and appraise electronic health information effectively, ultimately enhancing health literacy. Health literacy, therefore, serves as a foundation for reducing health inequalities and fostering population health.

Developing and marketing mobile health applications for low-income working adults in Hong Kong

Purpose Despite the potential of mobile health applications in reducing barriers to accessing health information and facilities, the adoption and usage of such applications were low among low-income populations. This study aims to examine the use of mobile technology for health management and the perceived barriers of the use of mobile applications for health management among low-income working adults in Hong Kong. Design/methodology/approach Semi-structured interviews were conducted with 16 working adults aged 25–45 from low-income families. The interviewees were asked about their perceptions of their health, their perceptions about and use of mobile health applications and they were asked to describe their ideal mobile health management app. Findings Interviewees often suffer from physical pain and many face relationship difficulties. They seek out health information actively on the internet, often using a mobile phone. However, their use of wearables and health mobile applications is limited. The perceived barriers of using mobile health applications included perceived difficulties in downloading and registering, privacy concerns and a lack of awareness of the health apps available. They prefer internet searching to a dedicated app. Their ideal health applications should be video based with real-life narratives. They were concerned about the credibility of the health information provided and preferred apps that engage professional and authoritative sources. Research limitations/implications The study was based on a convenience sample recruited through a nonprofit organization. It has the limitation of generalizing the results for the target population. Future studies can use survey methodology to test a theoretical model linking perceived barriers and intention to use mobile health technology. Studies using experimental design can investigate perceived ease of use and perceived benefits of different mobile health app designs. Practical implications These findings can inform the government’s health department and health organizations in designing appropriate mobile health applications that target those with limited financial and time resources. Originality/value There is a lack of studies that explore perceived barriers of adoption of mobile health technology in developed societies. To the best of the authors’ knowledge, this is the one of the first qualitative studies conducted in Hong Kong among low-income working adults about their health conditions and usage of mobile health technology.

Penguatan Pengetahuan tentang Komposisi dan Tekstur MP ASI bagi Ibu

Malnutrition issues in infants, particularly related to complementary feeding (MP ASI), remain a challenge in many areas, including Pringgarata, Central Lombok Regency. Maternal knowledge about the composition and texture of MP ASI suitable for a baby’s age is crucial to prevent nutritional problems such as stunting and malnutrition. This community service aims to enhance maternal knowledge regarding the composition and texture of MP ASI through interactive training. The method used is a qualitative approach with a participatory design, involving 20 mothers with infants under 12 months old in the Pringgarata area. Activities included education using leaflets, demonstrations on preparing MP ASI, and group discussions. Evaluation was carried out using pre-test and post-test questionnaires, interviews, and direct observation of changes in MP ASI feeding behavior. Results showed a 25% increase in maternal knowledge after the training, along with positive behavioral changes in providing MP ASI according to the baby’s age. In conclusion, community-based training can effectively improve maternal knowledge and skills in providing age-appropriate MP ASI, thereby reducing the risk of malnutrition in infants in areas with limited health information access.

Paradox within the Healthcare System: An Intersectional Analysis of Health Seeking Experiences of Migrants in the U.S.

ABSTRACT This study examined the complexities surrounding migrants’ health-seeking behaviors in the United States. Using intersectionality as a guiding analytic, we conducted in-depth interviews with 15 visa-holding migrants from West African, East, and Southeast Asian countries to understand their experiences navigating healthcare in another country. Participants mentioned the convergence of three power systems: nativity/language of origin status, education status, and migration (legal) status. Based on participants’ experiences navigating these converging systems, we identified two paradoxes migrants’ experience when seeking health information: (1) the empowerment and disempowerment in the pursuit of health information and (2) the scarcity and sufficiency in the accessibility of health information. Our findings offer a more nuanced understanding of migrant health processes. In particular, we propose that more theorizing and practical interventions should consider intersectional tensions and paradoxes that emerge from individuals whose identities grant them both access and limitations when it comes to seeking healthcare information.

Leveraging AI to improve health information access in the World's largest maternal mobile health program

AbstractHarnessing the wide‐spread availability of cell phones, many nonprofits have launched mobile health (mHealth) programs to deliver information via voice or text to beneficiaries in underserved communities, with maternal and infant health being a key area of such mHealth programs. Unfortunately, dwindling listenership is a major challenge, requiring targeted interventions using limited resources. This paper focuses on Kilkari, the world's largest mHealth program for maternal and child care – with over 3 million active subscribers at a time – launched by India's Ministry of Health and Family Welfare (MoHFW) and run by the non‐profit ARMMAN. We present a system called CHAHAK that aims to reduce automated dropouts as well as boost engagement with the program through the strategic allocation of interventions to beneficiaries. Past work in a similar domain has focused on a much smaller scale mHealth program and used markovian restless multiarmed bandits to optimize a single limited intervention resource. However, this paper demonstrates the challenges in adopting a markovian approach in Kilkari; therefore, CHAHAK instead relies on non‐markovian time‐series restless bandits and optimizes multiple interventions to improve listenership. We use real Kilkari data from the Odisha state in India to show CHAHAK's effectiveness in harnessing multiple interventions to boost listenership, benefiting marginalized communities. When deployed CHAHAK will assist the largest maternal mHealth program to date.

Government Digital Transformation and the utilization of Basic Public Health Services by China’s migrant population

BackgroundThis research delves into the ramifications of Government Digital Transformation (GDT) on Basic Public Health Services (BPHS) utilization among China’s migrant populace. Within the framework of escalating digital incorporation into public services, it becomes imperative to assess how GDT initiatives could ameliorate healthcare access for migrants, a group habitually confronted with systemic obstacles. Such scrutiny is crucial for the formulation of evidence-based policies that harness digital innovations to mitigate healthcare disparities.MethodsThe analysis employs data from the 2018 China Migrants Dynamic Survey, matched with details on the National Pilot Cities for Information Benefit to the Public policy at the prefecture city level, yielding a dataset comprising 113,905 observations. To gauge BPHS utilization among migrants, two indicators were developed: the establishment of health records and registration with family doctors. The influence of GDT on BPHS access was estimated utilizing Ordinary Least Squares regression for the initial analysis, incorporating a comprehensive array of individual and household attributes, alongside province fixed effects, to ensure a thorough evaluation.ResultsBaseline regression analyses revealed that GDT is significantly correlated with an enhanced probability of migrants establishing health records and registering with family doctors, with increases of 7.53% and 2.75%, respectively. Subsequent robustness checks, including sensitivity analyses with alternate dependent variables, the Propensity Score Matching method, Double/Debiased Machine Learning method, and placebo tests, further substantiated these findings. Additionally, the analysis explored mechanisms through which GDT facilitates BPHS access, identifying health information accessibility as a significant mediator in promoting healthcare engagement among migrants. Notably, both individual and regional heterogeneity were observed in GDT’s impact: female migrants, those with lower educational levels, older individuals, and rural hukou holders experienced more pronounced benefits, while the effects of GDT were also stronger in cities with lower GDP and smaller populations. These findings suggest that GDT is particularly effective in bridging healthcare access gaps in economically or demographically constrained areas.ConclusionsThe outcomes underscore that GDT significantly enhances BPHS utilization among migrants, positioning digital governance as an instrumental mechanism in bridging healthcare access gaps. The observed differential impacts across various subgroups and regions emphasize the importance of customized digital health strategies that cater to the diverse needs of migrant communities. For instance, targeted interventions in lower-GDP or smaller cities could maximize the benefits of GDT in under-resourced areas. Contributing to the body of empirical evidence on digital governance and public health, this research advocates for the expanded deployment of GDT initiatives to foster more equitable health service provision for migrant demographics, promoting inclusivity within a rapidly urbanizing society.

Rank Ordered Design Attributes for Health Care Dashboards Including Artificial Intelligence: Usability Study.

On average, people in the United States visit a doctor 4 times a year, and many of them have chronic illnesses. Because of the increased use of technology, people frequently rely on the internet to access health information and statistics. People use health care information to make better-educated decisions for themselves and others. Health care dashboards should provide pertinent and easily understood data, such as information on timely cancer screenings, so the public can make better-informed decisions. In order to enhance health outcomes, effective dashboards should provide precise data in an accessible and easily digestible manner. This study identifies the top 15 attributes of a health care dashboard. The objective of this research is to enhance health care dashboards to benefit the public by making better health care information available for more informed decisions by the public and to improve population-level health care outcomes. The authors conducted a survey of health care dashboards with 218 individuals identifying the best practices to consider when creating a public health care dashboard. The data collection was conducted from June 2023 to August 2023. The analyses performed were descriptive statistics, frequencies, and a comparison to a prior study. From May 2023 to June 2023, we collected 3259 responses in multiple different states around the United States from 218 people aged 18 years or older. The features ranking in descending order of importance are as follows: (1) easy navigation, (2) historical data, (3) simplicity of design, (4) high usability, (5) use of clear descriptions, (6) consistency of data, (7) use of diverse chart types, (8) compliance with the Americans with Disabilities Act, (9) incorporated user feedback, (10) mobile compatibility, (11) comparison data with other entities, (12) storytelling, (13) predictive analytics with artificial intelligence, (14) adjustable thresholds, and (15) charts with tabulated data. Future studies can extend the research to other types of dashboards such as bioinformatics, financial, and managerial dashboards as well as confirm these top 15 best practices for medical dashboards with further evidentiary support. The medical informatics community may benefit from standardization to improve efficiency and effectiveness as dashboards can communicate vital information to patients worldwide on critically prominent issues. Furthermore, health care professionals should use these best practices to help increase population health care outcomes by informing health care consumers to make better decisions with better data.