Generating Utilities for the Château-Santé Base: A Novel, Generic, and Patient-Centered Health-Outcome Measure.

OBJECTIVES: We have developed a new patient-centered, preference-based generic health-outcome measure, Château-Santé Base (CS-Base), which is based on a novel multiattribute preference response (MAPR) measurement framework. This study aimed to generate a first utility set for the CS-Base, making it suitable for use in health-economic evaluations. METHODS: CS-Base comprises 12 health attributes: mobility, vision, hearing, cognition, mood, anxiety, pain, fatigue, social functioning, daily activities, self-esteem, and independence, each with 4 levels. Our methodology to generate utilities for the CS-Base was 2-fold. First, we derived coefficients from patient MAPR data to calculate CS-Base values. Subsequently, these were normalized to a 0.0 to 1.0 utility scale, in which 0.0 signifies dead. The dead position was estimated using general population data from a discrete choice experiment (discrete choice experiment + dead), using a division-value strategy, which localize the position of states better or worse than dead. RESULTS: We analyzed MAPR data from 3222 patients and discrete choice experiment + dead data from 1995 respondents. All MAPR coefficients were negative, logically ordered, and significantly different from the reference level. The dead position was denoted by a division value of -148.385. Utility values spanned from -0.071 to 1.0, and only 53 of 16 777 216 states were deemed worse than dead. CONCLUSIONS: This study introduced the first CS-Base utility set, underlining a 2-step utility derivation method. This method, blending societal and patient views, surpasses traditional preference-based approaches, yielding firmer results. However, improvement of the normalization procedure is expected. Estimating CS-Base utilities is an ongoing process that gains precision over time.

Multimorbidity prevalence and health outcome prediction: assessing the impact of lookback periods, disease count, and definition criteria in health administrative data at the population-based level.

BACKGROUND: Health administrative databases play a crucial role in population-level multimorbidity surveillance. Determining the appropriate retrospective or lookback period (LP) for observing prevalent and newly diagnosed diseases in administrative data presents challenge in estimating multimorbidity prevalence and predicting health outcome. The aim of this population-based study was to assess the impact of LP on multimorbidity prevalence and health outcomes prediction across three multimorbidity definitions, three lists of diseases used for multimorbidity assessment, and six health outcomes. METHODS: We conducted a population-based study including all individuals ages > 65 years on April 1st, 2019, in Québec, Canada. We considered three lists of diseases labeled according to the number of chronic conditions it considered: (1) L60 included 60 chronic conditions from the International Classification of Diseases (ICD); (2) L20 included a core of 20 chronic conditions; and (3) L31 included 31 chronic conditions from the Charlson and Elixhauser indices. For each list, we: (1) measured multimorbidity prevalence for three multimorbidity definitions (at least two [MM2+], three [MM3+] or four (MM4+) chronic conditions); and (2) evaluated capacity (c-statistic) to predict 1-year outcomes (mortality, hospitalisation, polypharmacy, and general practitioner, specialist, or emergency department visits) using LPs ranging from 1 to 20 years. RESULTS: Increase in multimorbidity prevalence decelerated after 5-10 years (e.g., MM2+, L31: LP = 1y: 14%, LP = 10y: 58%, LP = 20y: 69%). Within the 5-10 years LP range, predictive performance was better for L20 than L60 (e.g., LP = 7y, mortality, MM3+: L20 [0.798;95%CI:0.797-0.800] vs. L60 [0.779; 95%CI:0.777-0.781]) and typically better for MM3 + and MM4 + definitions (e.g., LP = 7y, mortality, L60: MM4+ [0.788;95%CI:0.786-0.790] vs. MM2+ [0.768;95%CI:0.766-0.770]). CONCLUSIONS: In our databases, ten years of data was required for stable estimation of multimorbidity prevalence. Within that range, the L20 and multimorbidity definitions MM3 + or MM4 + reached maximal predictive performance.

Older people's goals of care in relation to frailty status-the COOP-study.

BACKGROUND: Literature relating older people's goals of care to their varying frailty status is scarce. OBJECTIVE: To investigate goals of care in case of acute and/or severe disease in relationship to frailty status among the general older population. METHOD: Older people aged ≥70 in the Netherlands completed a questionnaire. They were divided into three subgroups based on a self-reported Clinical Frailty Scale: fit (CFS 1-3), mildly frail (CFS 4-5) and severely frail (CFS 6-8). Seven goals were graded as unimportant (1-5), somewhat important (6-7) or very important (8-10): extending life, preserving quality of life (QoL), staying independent, relieving symptoms, supporting others, preventing hospital admission and preventing nursing home admission. RESULTS: Of the 1,278 participants (median age 76 years, 63% female), 57% was fit, 32% mildly frail and 12% severely frail. Overall, participants most frequently considered preventing nursing home admission as very important (87%), followed by staying independent (84%) and preserving QoL (83%), and least frequently considered extending life as very important (31%). All frailty subgroups reported similar preferences out of the surveyed goals as the overall study population. However, participants with a higher frailty status attached slightly less importance to each individual goal compared with fit participants (Ptrend-values ≤ 0.037). CONCLUSION: Preferred goals of care are not related to frailty status, while the importance ascribed to individual goals is slightly lower with higher frailty status. Future research should prioritise outcomes related to the shared goals of fit, mildly frail and severely frail older people to improve personalised medicine for older patients.

Assessment of the Multiple Sclerosis Severity Score and the Age-Related Multiple Sclerosis Severity Score as health indicators in a population-based cohort.

BACKGROUND: People with multiple sclerosis (MS) present varying degrees of disability throughout their disease course. The Multiple Sclerosis Severity Score (MSSS) and the Age-Related Multiple Sclerosis Severity Score (ARMSSS) adjust the Expanded Disability Status Scale (EDSS) according to disease duration and age, respectively. These measures could be useful for quantifying MS severity and as health outcome indicators for benchmarking in population-based settings. The aim of this study was to describe the severity of MS in our health district using the MSSS and ARMSSS and to assess their consistency over time. METHODS: This population-based study included patients from our health district who were diagnosed with MS according to the 2010 McDonald criteria, had a disease duration of at least one year and were followed up in our MS unit. Sex, age at onset, disease duration, clinical course, age and irreversible EDSS at the last follow-up visit were collected, and the MSSS and ARMSSS were calculated at two time points: 2017 and 2020. RESULTS: One hundred seventy-seven patients were included in 2017, and 208 in 2020. The prevalence of MS was 90 and 104 per 100,000 inhabitants, respectively. The median MSSS was 1.77 (IQR 0.76-4.28) in 2017 and 2.03 (IQR 0.82-4.36) in 2020. The median ARMSSS was 2.90 (IQR 1.47-5.72) in 2017 and 2.93 (IQR 1.51-5.56) in 2020. No significant differences were found. CONCLUSIONS: According to the MSSS and ARMSSS, the severity of MS in our area is mild, and these instruments are consistent. These measures could be reliable health outcome measures.

Discrimination and health: A cross-sectional study comparing Muslims with other-religious.

AIMS: The aim of this study is to report perceived discrimination among Muslims living in Norway and to address and compare associations between perceived discrimination and health among Muslims with an immigrant background and other-religious with an immigrant background. METHOD: A representative sample of individuals with an immigrant background in Norway was used in a cross-sectional study design that included 5484 respondents aged 16 to 74 years. The respondents were sub-grouped after religious affiliation, and as immigrants and Norwegian-born. This sample is from 'The Survey on living conditions among persons with an immigrant background 2016', conducted by Statistics Norway. Multivariate logistic regression analyses were conducted to investigate the relationship between perceived discrimination and self-rated health and between perceived discrimination and mental health problems. RESULTS: Our findings show that Muslims with an immigrant background are more likely to report perceived discrimination than non-Muslims with an immigrant background. Perceived discrimination was associated with poor self-rated health and mental health problems among immigrant Muslims and Norwegian-born Muslims. Among other-religious with an immigrant background, perceived discrimination had an inverse relationship with mental health problems among immigrants, while an association between perceived discrimination and poor self-rated health was found among Norwegian-born. CONCLUSIONS: Our findings suggest that perceived discrimination does play a role in health among minorities with an immigrant background in Norway, regardless of religion. However, the association between perceived discrimination and poor health seems to be stronger among Muslims, especially Norwegian-born Muslims.

Do small effects matter more in vulnerable populations? an investigation using Environmental influences on Child Health Outcomes (ECHO) cohorts.

BACKGROUND: A major challenge in epidemiology is knowing when an exposure effect is large enough to be clinically important, in particular how to interpret a difference in mean outcome in unexposed/exposed groups. Where it can be calculated, the proportion/percentage beyond a suitable cut-point is useful in defining individuals at high risk to give a more meaningful outcome. In this simulation study we compute differences in outcome means and proportions that arise from hypothetical small effects in vulnerable sub-populations. METHODS: Data from over 28,000 mother/child pairs belonging to the Environmental influences on Child Health Outcomes Program were used to examine the impact of hypothetical environmental exposures on mean birthweight, and low birthweight (LBW) (birthweight < 2500g). We computed mean birthweight in unexposed/exposed groups by sociodemographic categories (maternal education, health insurance, race, ethnicity) using a range of hypothetical exposure effect sizes. We compared the difference in mean birthweight and the percentage LBW, calculated using a distributional approach. RESULTS: When the hypothetical mean exposure effect was fixed (at 50, 125, 167 or 250g), the absolute difference in % LBW (risk difference) was not constant but varied by socioeconomic categories. The risk differences were greater in sub-populations with the highest baseline percentages LBW: ranging from 3.1-5.3 percentage points for exposure effect of 125g. Similar patterns were seen for other mean exposure sizes simulated. CONCLUSIONS: Vulnerable sub-populations with greater baseline percentages at high risk fare worse when exposed to a small insult compared to the general population. This illustrates another facet of health disparity in vulnerable individuals.

Patient and Staff Experience of Remote Patient Monitoring-What to Measure and How: Systematic Review.

BACKGROUND: Patient and staff experience is a vital factor to consider in the evaluation of remote patient monitoring (RPM) interventions. However, no comprehensive overview of available RPM patient and staff experience-measuring methods and tools exists. OBJECTIVE: This review aimed at obtaining a comprehensive set of experience constructs and corresponding measuring instruments used in contemporary RPM research and at proposing an initial set of guidelines for improving methodological standardization in this domain. METHODS: Full-text papers reporting on instances of patient or staff experience measuring in RPM interventions, written in English, and published after January 1, 2011, were considered for eligibility. By "RPM interventions," we referred to interventions including sensor-based patient monitoring used for clinical decision-making; papers reporting on other kinds of interventions were therefore excluded. Papers describing primary care interventions, involving participants under 18 years of age, or focusing on attitudes or technologies rather than specific interventions were also excluded. We searched 2 electronic databases, Medline (PubMed) and EMBASE, on February 12, 2021.We explored and structured the obtained corpus of data through correspondence analysis, a multivariate statistical technique. RESULTS: In total, 158 papers were included, covering RPM interventions in a variety of domains. From these studies, we reported 546 experience-measuring instances in RPM, covering the use of 160 unique experience-measuring instruments to measure 120 unique experience constructs. We found that the research landscape has seen a sizeable growth in the past decade, that it is affected by a relative lack of focus on the experience of staff, and that the overall corpus of collected experience measures can be organized in 4 main categories (service system related, care related, usage and adherence related, and health outcome related). In the light of the collected findings, we provided a set of 6 actionable recommendations to RPM patient and staff experience evaluators, in terms of both what to measure and how to measure it. Overall, we suggested that RPM researchers and practitioners include experience measuring as part of integrated, interdisciplinary data strategies for continuous RPM evaluation. CONCLUSIONS: At present, there is a lack of consensus and standardization in the methods used to measure patient and staff experience in RPM, leading to a critical knowledge gap in our understanding of the impact of RPM interventions. This review offers targeted support for RPM experience evaluators by providing a structured, comprehensive overview of contemporary patient and staff experience measures and a set of practical guidelines for improving research quality and standardization in this domain.

Predictors, mortality, and health outcomes of intensive phase non-adherence to a regimen in patients with drug-susceptible tuberculosis: a nationwide linkage database.

OBJECTIVES: The clinical importance of adhering to the regimen in tuberculosis patients has been widely investigated, but most studies were conducted in controlled settings and in limited populations. We aimed to measure the level of real-world adherence during intensive phase and investigate the predictors and the risk of mortality and health outcomes of intensive phase non-adherence in tuberculosis patients. STUDY DESIGN: We conducted a nationwide cohort study by linking the Korean National Tuberculosis Surveillance System and the National Health Information Database. METHODS: We included all incident drug-susceptible tuberculosis patients who initiated the regimens recommended by the World Health Organization from 2013 to 2018. Adherence was measured using the proportion of days covered (poor [<50%], moderate [50%-79%], and high [≥80%]). We used logistic regression model to assess predictors and the Cox proportional hazard model to evaluate the risk of mortality and health outcomes with intensive phase non-adherence. RESULTS: Of 46,818 patients, there were 8% and 11% with poor and moderate adherent groups, respectively. Age ≥45 years, insulin use, and history of renal failure were predictors of non-adherence. Compared with high adherent group, poor and moderate adherent groups were associated with a substantial risk of mortality (poor: hazard ratio, 2.14 [95% confidence interval, 1.95-2.34]; moderate: 1.76 [1.62-1.92]). Similar trends were observed for health outcomes. Stratified analyses showed a higher risk of mortality in patients with medical aid, low income, and history of renal failure, systematic corticosteroids, and immunomodulators. CONCLUSIONS: Non-adherence during intensive phase increased mortality risk by twofold, underscoring targeted intervention for high-risk population, including advanced diabetes, and immunocompromised patients.

Protocol for a scoping review to map health outcomes in individuals with inducible laryngeal obstruction.

BACKGROUND: Inducible laryngeal obstruction causes narrowing of the laryngeal aperture in response to external triggers. Outcomes are measured in inducible laryngeal obstruction to monitor changes in health status over time. METHODS: This study is a scoping review based on Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology. The review will be guided by the following research question: 'What health outcomes are measured in studies including people with inducible laryngeal obstruction?' The research question was validated using the Population-Concept-Context framework according to the methodology for Joanna Briggs Institution Scoping Reviews. Relevant peer-reviewed studies and grey literature conducted over the last 40 years will be identified from electronic databases including AMED, CINAHL, Embase, EMCARE, MEDLINE, OVID, PubMed and PsycINFO. The search strings 'inducible laryngeal obstruction', 'ILO', 'vocal cord dysfunction', 'VCD', 'paradoxical vocal fold motion', 'PVFM', 'outcome', 'measure', 'measurement instrument', 'assessment', 'scale', 'questionnaire' will be combined using Boolean logic. An independent reviewer will conduct title screening; two independent reviewers will conduct abstract and full article screening, followed by data extraction by two reviewers. Analyses will be conducted appropriate to the findings. DISCUSSION: The review will document evidence of health outcomes measured in inducible laryngeal obstruction, identifying measurement characteristics and potential utility. Collating studies may identify gaps in coverage, the need for novel tools, and for standardisation for clinical and research purposes. WHAT THIS PAPER ADDS: What is already known on the subject Inducible laryngeal obstruction causes narrowing of the laryngeal aperture in response to external triggers. Outcomes are measured in inducible laryngeal obstruction to monitor changes in health status over time. Currently, there are no standardised outcome measures for measuring the effects of interventions in inducible laryngeal obstruction (ILO). What this paper adds to existing knowledge Assessment of health can be measured in a variety of ways. Physiological, radiological and biochemical measurements of impairment are more common historically but there are a lot of outcomes of other factors now including subjective measures of functional status and health-related quality of life, with data collected directly from patients. This study will allow us to scope the literature to see the health outcomes being measured in ILO to attempt to standardise and develop future health outcomes. What are the potential or actual clinical implications of this work? The review will document evidence of health outcomes measured in inducible laryngeal obstruction, identifying measurement characteristics and potential utility. Collating studies may identify gaps in coverage, the need for novel tools and for standardisation for clinical and research purposes.

Improving Methods of Identifying Anaphylaxis for Medical Product Safety Surveillance Using Natural Language Processing and Machine Learning.

We sought to determine whether machine learning and natural language processing (NLP) applied to electronic medical records could improve performance of automated health-care claims-based algorithms to identify anaphylaxis events using data on 516 patients with outpatient, emergency department, or inpatient anaphylaxis diagnosis codes during 2015-2019 in 2 integrated health-care institutions in the Northwest United States. We used one site's manually reviewed gold-standard outcomes data for model development and the other's for external validation based on cross-validated area under the receiver operating characteristic curve (AUC), positive predictive value (PPV), and sensitivity. In the development site 154 (64%) of 239 potential events met adjudication criteria for anaphylaxis compared with 180 (65%) of 277 in the validation site. Logistic regression models using only structured claims data achieved a cross-validated AUC of 0.58 (95% CI: 0.54, 0.63). Machine learning improved cross-validated AUC to 0.62 (0.58, 0.66); incorporating NLP-derived covariates further increased cross-validated AUCs to 0.70 (0.66, 0.75) in development and 0.67 (0.63, 0.71) in external validation data. A classification threshold with cross-validated PPV of 79% and cross-validated sensitivity of 66% in development data had cross-validated PPV of 78% and cross-validated sensitivity of 56% in external data. Machine learning and NLP-derived data improved identification of validated anaphylaxis events.

Varying-coefficients for regional quantile via KNN-based LASSO with applications to health outcome study.

Health outcomes, such as body mass index and cholesterol levels, are known to be dependent on age and exhibit varying effects with their associated risk factors. In this paper, we propose a novel framework for dynamic modeling of the associations between health outcomes and risk factors using varying-coefficients (VC) regional quantile regression via K-nearest neighbors (KNN) fused Lasso, which captures the time-varying effects of age. The proposed method has strong theoretical properties, including a tight estimation error bound and the ability to detect exact clustered patterns under certain regularity conditions. To efficiently solve the resulting optimization problem, we develop an alternating direction method of multipliers (ADMM) algorithm. Our empirical results demonstrate the efficacy of the proposed method in capturing the complex age-dependent associations between health outcomes and their risk factors.

Gender differences in vision health-seeking behavior and vision health outcomes among rural Chinese schoolchildren by birth order and family size.

BACKGROUND: The gender gap remains a major impediment in the path toward equality, and it is especially wide in low-income countries. Gender differences in health-seeking behaviors may be a factor. Family size and childbirth order are two critical factors affecting family resource allocation. This study examines gender differences in healthcare-seeking behaviors among children with visual impairment in rural China across different family structures (birth order and family size). METHODS: We draw on a dataset containing 19,934 observations constructed by combining data from 252 different school-level surveys spanning two provinces. The surveys were all conducted in 2012 using uniform survey instruments and data collection protocols in randomly selected schools across western provinces in rural China. The sample children range in grades from 4 to 5. Our analysis compares rural girls with rural boys regarding vision health outcome and behavior (vision examination and correction). RESULTS: The findings revealed that girls have worse vision than boys. Regarding vision health behaviors, girls have a lower overall vision examination rate than boys. There is no gender difference when the sample student is the only child or the youngest child in the family, but there is still a gender difference when the sample student is the oldest child in the family or the middle child in the birth order. When it comes to vision correction behavior, boys are more likely to own eyeglasses than girls are for groups of students with mild visual impairment, even when the sample student is the only child in the family. However, when the sample student has another brother or sister (the sample student is the youngest, the oldest child in the family, or the middle child in the birth order), the gender difference disappears. CONCLUSIONS: Gender differences in vision health outcomes are correlated with gender differences in vision health-seeking behaviors among rural children. Depending on the birth order and family size, gender disparities in visual health practices vary. In the future, consideration should be given to providing medical subsidies to reduce the cost of vision health behaviors and to provide information interventions to change gender inequality in households and promote equality in children's vision health behaviors. TRIAL REGISTRATION: The trial was approved by the Stanford University Institutional Review Board (Protocol No. ISRCTN03252665). Permission was received from local Boards of Education in each region and the principals of all schools. The principles of the Declaration of Helsinki were followed throughout. Written informed consent was obtained from at least one parent for all child participants.

The effect of shunt removal on the quality of life in patients with congenital hydrocephalus.

BACKGROUND: Although there have been reports investigating the quality of life of patients who underwent ventriculoperitoneal shunting or endoscopic third ventriculostomy (ETV) for congenital hydrocephalus, there have been no studies of the quality of life of patients after ventriculoperitoneal shunt (VPS) removal. In the present study, a survey of pediatric and congenital hydrocephalus patients was conducted to compare the quality of life of patients with a remaining VPS with that of patients who had the shunt removed. METHODS: Between February 2020 and November 2021, an outpatient survey was administered to patients 8 years of age and older who had undergone VPS due to a diagnosis of congenital hydrocephalus. The Hydrocephalus Outcome Questionnaire (HOQ) was used to assess the quality of life for this study. The HOQ scores (overall health score, physical health score, cognitive health score, and social-emotional health score) were compared among three groups: a VPS-remaining group, VPS-removed with endoscopic third ventriculostomy (ETV) group, and VPS-removed without ETV group. RESULTS: The total number of patients who underwent VPS for hydrocephalus was 71, with 47 in the VPS-remaining group, 14 in the shunt-removed with ETV group, and 10 in the shunt-removed without ETV group. The HOQ overall health score was 0.68 for the VPS-remaining group, 0.74 for the shunt-removed with ETV group, and 0.74 for the shunt-removed without ETV. There were no significant differences between the VPS-remaining group and the VPS-removed with or without ETV groups (p = 0.3255, 0.4178, respectively). CONCLUSION: There was no significant difference in the quality of life between patients with a remaining VPS and those who had their VPS removed with or without ETV.

iCHECK-DH: Guidelines and Checklist for the Reporting on Digital Health Implementations.

BACKGROUND: Implementation of digital health technologies has grown rapidly, but many remain limited to pilot studies due to challenges, such as a lack of evidence or barriers to implementation. Overcoming these challenges requires learning from previous implementations and systematically documenting implementation processes to better understand the real-world impact of a technology and identify effective strategies for future implementation. OBJECTIVE: A group of global experts, facilitated by the Geneva Digital Health Hub, developed the Guidelines and Checklist for the Reporting on Digital Health Implementations (iCHECK-DH, pronounced "I checked") to improve the completeness of reporting on digital health implementations. METHODS: A guideline development group was convened to define key considerations and criteria for reporting on digital health implementations. To ensure the practicality and effectiveness of the checklist, it was pilot-tested by applying it to several real-world digital health implementations, and adjustments were made based on the feedback received. The guiding principle for the development of iCHECK-DH was to identify the minimum set of information needed to comprehensively define a digital health implementation, to support the identification of key factors for success and failure, and to enable others to replicate it in different settings. RESULTS: The result was a 20-item checklist with detailed explanations and examples in this paper. The authors anticipate that widespread adoption will standardize the quality of reporting and, indirectly, improve implementation standards and best practices. CONCLUSIONS: Guidelines for reporting on digital health implementations are important to ensure the accuracy, completeness, and consistency of reported information. This allows for meaningful comparison and evaluation of results, transparency, and accountability and informs stakeholder decision-making. i-CHECK-DH facilitates standardization of the way information is collected and reported, improving systematic documentation and knowledge transfer that can lead to the development of more effective digital health interventions and better health outcomes.

Exploring Political Mistrust in Pandemic Risk Communication: Mixed-Method Study Using Social Media Data Analysis.

BACKGROUND: This research extends prior studies by the Finnish Institute for Health and Welfare on pandemic-related risk perception, concentrating on the role of trust in health authorities and its impact on public health outcomes. OBJECTIVE: The paper aims to investigate variations in trust levels over time and across social media platforms, as well as to further explore 12 subcategories of political mistrust. It seeks to understand the dynamics of political trust, including mistrust accumulation, fluctuations over time, and changes in topic relevance. Additionally, the study aims to compare qualitative research findings with those obtained through computational methods. METHODS: Data were gathered from a large-scale data set consisting of 13,629 Twitter and Facebook posts from 2020 to 2023 related to COVID-19. For analysis, a fine-tuned FinBERT model with an 80% accuracy rate was used for predicting political mistrust. The BERTopic model was also used for superior topic modeling performance. RESULTS: Our preliminary analysis identifies 43 mistrust-related topics categorized into 9 major themes. The most salient topics include COVID-19 mortality, coping strategies, polymerase chain reaction testing, and vaccine efficacy. Discourse related to mistrust in authority is associated with perceptions of disease severity, willingness to adopt health measures, and information-seeking behavior. Our findings highlight that the distinct user engagement mechanisms and platform features of Facebook and Twitter contributed to varying patterns of mistrust and susceptibility to misinformation during the pandemic. CONCLUSIONS: The study highlights the effectiveness of computational methods like natural language processing in managing large-scale engagement and misinformation. It underscores the critical role of trust in health authorities for effective risk communication and public compliance. The findings also emphasize the necessity for transparent communication from authorities, concluding that a holistic approach to public health communication is integral for managing health crises effectively.

Specifying the Efficacy of Digital Therapeutic Tools for Depression and Anxiety: Retrospective, 2-Cohort, Real-World Analysis.

BACKGROUND: Depression and anxiety are the main sources of work and social disabilities as well as health-related problems around the world. Digital therapeutic solutions using cognitive behavioral therapy have demonstrated efficacy in depression and anxiety. A common goal of digital health apps is to increase user digital engagement to improve outcomes. However, there is a limited understanding of the association between digital platform components and clinical outcomes. OBJECTIVE: The aim of the study is to investigate the contribution of specific digital engagement tools to mental health conditions. We hypothesized that participation in coaching sessions and breathing exercises would be associated with a reduction in depression and anxiety. METHODS: Depression and general anxiety symptoms were evaluated in real-world data cohorts using the digital health platform for digital intervention and monitoring change. This retrospective real-world analysis of users on a mobile platform-based treatment followed two cohorts of people: (1) users who started with moderate levels of depression and completed at least 2 depression assessments (n=519) and (2) users who started with moderate levels of anxiety and completed at least 2 anxiety assessments (n=474). Levels of depression (Patient Health Questionnaire-9) and anxiety (Generalized Anxiety Disorder-7) were tracked throughout the first 16 weeks. A piecewise mixed-effects model was applied to model the trajectories of the Patient Health Questionnaire-9 and the Generalized Anxiety Disorder-7 mean scores in 2 segments (1-6 weeks and 7-16 weeks). Finally, simple slope analysis was used for the interpretation of the interactions probing the moderators: coaching sessions and breathing exercises in both depression and anxiety cohorts. RESULTS: Analysis revealed a significant decrease in depression symptoms (ß=-.37, 95% CI -0.46 to 0.28; P≤.001) during the period of weeks 1-6 of app use, which was maintained during the period of 7-16 weeks. Coach interaction significantly moderated the reduction in depression symptoms during the period of weeks 1-6 (ß=-.03, 95% CI -0.05 to -0.001; P=.02). A significant decrease in anxiety symptoms (ß=-.41, 95% CI -0.50 to -0.33; P≤.001) was revealed during the period of 1-6 weeks, which was maintained during the period of 7-16 weeks. Breathing exercises significantly moderated the reduction in anxiety symptoms during the period of 1-6 weeks (ß=-.07, 95% CI -0.14 to -0.01; P=.04). CONCLUSIONS: This study demonstrated general improvement followed by a period of stability of depression and anxiety symptoms associated with cognitive behavioral therapy-based digital intervention. Interestingly, engagement with a coaching session but not a breathing exercise was associated with a reduction in depression symptoms. Moreover, breathing exercise but not engagement with a coaching session was associated with a reduction of anxiety symptoms. These findings emphasize the importance of using a personalized approach to behavioral health during digital health interventions.

Using Social Media to Help Understand Patient-Reported Health Outcomes of Post-COVID-19 Condition: Natural Language Processing Approach.

BACKGROUND: While scientific knowledge of post-COVID-19 condition (PCC) is growing, there remains significant uncertainty in the definition of the disease, its expected clinical course, and its impact on daily functioning. Social media platforms can generate valuable insights into patient-reported health outcomes as the content is produced at high resolution by patients and caregivers, representing experiences that may be unavailable to most clinicians. OBJECTIVE: In this study, we aimed to determine the validity and effectiveness of advanced natural language processing approaches built to derive insight into PCC-related patient-reported health outcomes from social media platforms Twitter and Reddit. We extracted PCC-related terms, including symptoms and conditions, and measured their occurrence frequency. We compared the outputs with human annotations and clinical outcomes and tracked symptom and condition term occurrences over time and locations to explore the pipeline's potential as a surveillance tool. METHODS: We used bidirectional encoder representations from transformers (BERT) models to extract and normalize PCC symptom and condition terms from English posts on Twitter and Reddit. We compared 2 named entity recognition models and implemented a 2-step normalization task to map extracted terms to unique concepts in standardized terminology. The normalization steps were done using a semantic search approach with BERT biencoders. We evaluated the effectiveness of BERT models in extracting the terms using a human-annotated corpus and a proximity-based score. We also compared the validity and reliability of the extracted and normalized terms to a web-based survey with more than 3000 participants from several countries. RESULTS: UmlsBERT-Clinical had the highest accuracy in predicting entities closest to those extracted by human annotators. Based on our findings, the top 3 most commonly occurring groups of PCC symptom and condition terms were systemic (such as fatigue), neuropsychiatric (such as anxiety and brain fog), and respiratory (such as shortness of breath). In addition, we also found novel symptom and condition terms that had not been categorized in previous studies, such as infection and pain. Regarding the co-occurring symptoms, the pair of fatigue and headaches was among the most co-occurring term pairs across both platforms. Based on the temporal analysis, the neuropsychiatric terms were the most prevalent, followed by the systemic category, on both social media platforms. Our spatial analysis concluded that 42% (10,938/26,247) of the analyzed terms included location information, with the majority coming from the United States, United Kingdom, and Canada. CONCLUSIONS: The outcome of our social media-derived pipeline is comparable with the results of peer-reviewed articles relevant to PCC symptoms. Overall, this study provides unique insights into patient-reported health outcomes of PCC and valuable information about the patient's journey that can help health care providers anticipate future needs. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.1101/2022.12.14.22283419.

Using Digital Tools to Study the Health of Adults Born Preterm at a Large Scale: e-Cohort Pilot Study.

BACKGROUND: Preterm birth is a global health concern. Its adverse consequences may persist throughout the life course, exerting a potentially heavy burden on families, health systems, and societies. In high-income countries, the first children who benefited from improved care are now adults entering middle age. However, there is a clear gap in the knowledge regarding the long-term outcomes of individuals born preterm. OBJECTIVE: This study aimed to assess the feasibility of recruiting and following up an e-cohort of adults born preterm worldwide and provide estimations of participation, characteristics of participants, the acceptability of questions, and the quality of data collected. METHODS: We implemented a prospective, open, observational, and international e-cohort pilot study (Health of Adult People Born Preterm-an e-Cohort Pilot Study [HAPP-e]). Inclusion criteria were being an adult (aged ≥18 years), born preterm (<37 weeks of gestation), having internet access and an email address, and understanding at least 1 of the available languages. A large, multifaceted, and multilingual communication strategy was established. Between December 2019 and June 2021, inclusion and repeated data collection were performed using a secured web platform. We provided descriptive statistics regarding participation in the e-cohort, namely, the number of persons who registered on the platform, signed the consent form, initiated and completed the baseline questionnaire, and initiated and completed the follow-up questionnaire. We also described the main characteristics of the HAPP-e participants and provided an assessment of the quality of the data and the acceptability of sensitive questions. RESULTS: As of December 31, 2020, a total of 1004 persons had registered on the platform, leading to 527 accounts with a confirmed email and 333 signed consent forms. A total of 333 participants initiated the baseline questionnaire. All participants were invited to follow-up, and 35.7% (119/333) consented to participate, of whom 97.5% (116/119) initiated the follow-up questionnaire. Completion rates were very high both at baseline (296/333, 88.9%) and at follow-up (112/116, 96.6%). This sample of adults born preterm in 34 countries covered a wide range of sociodemographic and health characteristics. The gestational age at birth ranged from 23+6 to 36+6 weeks (median 32, IQR 29-35 weeks). Only 2.1% (7/333) of the participants had previously participated in a cohort of individuals born preterm. Women (252/333, 75.7%) and highly educated participants (235/327, 71.9%) were also overrepresented. Good quality data were collected thanks to validation controls implemented on the web platform. The acceptability of potentially sensitive questions was excellent, as very few participants chose the "I prefer not to say" option when available. CONCLUSIONS: Although we identified room for improvement in specific procedures, this pilot study confirmed the great potential for recruiting a large and diverse sample of adults born preterm worldwide, thereby advancing research on adults born preterm.

Indirect positive health outcomes of COVID-19: a systematic review.

OBJECTIVES: The aim of this study was to assess the frequency of indirect positive health outcomes as a result of the COVID-19 pandemic. STUDY DESIGN: This was a systematic review. METHODS: Articles were identified from four online databases (Web of Science, Scopus, PubMed and Google Scholar) using predetermined search terms. After studies were systematically identified, the results were summarised narratively. The indirect positive health outcomes associated with the emergence of COVID-19 and measures taken for its prevention were categorised into four health dimensions (physical, mental, social and digital). RESULTS: After initial screening, 44 articles were assessed for eligibility, and 33 were included in the final sample. Of the included studies, 72.73% noted a benefit from COVID-19 prevention measures in the physical health dimension. In addition, 12.12%, 9.09%, 3.03% and 3.03% of articles reported a positive impact in the digital, mental, social and combined digital and mental health dimensions, respectively. CONCLUSIONS: Despite the catastrophic health, socio-economic and political crises associated with the COVID-19 emergency, it has also resulted in some positive health outcomes. Reduced air pollutants, improved disease prevention practices, increased digital health delivery and improved mental and social health dimensions were reported during the pandemic. Integrated and collaborative activities for the persistence of these health benefits are recommended.

Carrot and carotene and multiple health outcomes: an umbrella review of the evidence.

In recent years, the benefits of carrots and carotene in different areas of health have been examined. The purpose of this umbrella review was to identify the associations between carrots and carotene and multiple health outcomes. The review considered evidence from meta-analyses of interventional and observational studies of carrots and carotene and any health outcome. We comprehensively searched Web of Science, PubMed, and Embase. For each association, we estimated the summary effect size using random and fixed effects models and the 95% confidence interval. A total of 1329 studies were searched, and 30 meta-analyses with 26 health outcomes were identified that met the eligibility criteria. Carrot intake was associated with a lower risk of multiple cancer outcomes including breast cancer, lung cancer, pancreatic cancer, gastric cancer, urothelial cancer, and prostate cancer. Carotene intake was associated with a lower risk of fracture, age-related cataract, sunburn, Alzheimer's disease, breast cancer, lung cancer, pancreatic cancer, gastric cancer, esophageal cancer, prostate cancer, and head and neck cancer (HNC). Serum carotene was inversely associated with all-cause mortality, breast cancer, and lung cancer. Our study revealed that carrot or carotene intake could reduce the risk of various negative health outcomes. © 2023 Society of Chemical Industry.