The health of migrants with type 2 diabetes has become a public health concern. Minority populations, including migrants, are often considered ‘hard-to-reach groups’ in clinical research, as researchers face challenges in engaging, accessing and retaining participants. Previous reviews have focused on either recruitment or retention, highlighting the need to gather experiences to obtain a more comprehensive picture for improving participation in research.

To share lessons learned about the challenges of recruiting and implementing an intervention study including migrants with type 2 diabetes.

This was a descriptive study, where researchers recorded experiences in reflective diaries and held discussions with the multi-professional teams involved. Data were analysed using Pawson’s conceptual framework, evaluating four dimensions of context: individual, interpersonal, institutional and infrastructural.

The individual context concerns the time-consuming recruitment process since about half of the prospective participants did not want to participate, often due to illness, lack of time, the need to work, or having travelled abroad. In the interpersonal context, the main challenge was involving several professional groups; the greater the involvement, the less flexibility there was to meet expectations. The priorities in the institutional context were to provide care, with efficiency and productivity taking precedence over research. The infrastructural context was crucial due to a lack of staff available to support recruitment, the healthcare system’s burden caused by the pandemic, and the impact of laws and regulations in healthcare.

Recruiting and implementing clinical research studies among migrant populations is complex. Factors across all contextual levels play a role, but the main challenges are within the institutional and infrastructural contexts. Changes in infrastructure influence institutional priorities, particularly with an already strained staff situation in primary healthcare. While political and social changes are difficult to alter, fostering positive attitudes towards research at the individual and interpersonal levels is important.

The aim of this study is to investigate family physicians’ approaches to hoarseness (dysphonia), clinical decision-making, patients’ perceptions, and structural barriers in the healthcare system using qualitative methods.

Qualitative design was used. Research was reported in line with COREQ (32 items) and EQUATOR (SRQR) guidelines. Semi-structured telephone/internet interviews were conducted with 17 family physicians working primary care in Türkiye. Participants purposively sampled interviews were audio-recorded, transcribed, coded using thematic analysis, and developed themes.

The analysis revealed four main themes: clinical assessment and differential diagnosis, referral criteria and specialist referrals, patient perception and knowledge level, health system and structural barriers. Demographic analysis determined that veteran doctors were more sensitive to malignancy, junior doctors highlighted systemic deficits, female doctors highlighted patient behavior, while doctors who practiced in rural areas highlighted structural issues.

Family physicians’ handling of hoarseness is not only dependent on clinical data but also on patient opinion and the health system’s conditions. For productive primary care management of hoarseness, it is recommended to (i) design guidelines and training for family physicians, (ii) increase patient education on voice hygiene and voice health, and (iii) establish health policies enhancing specialist accessibility.

The Dutch Children’s Food Literacy Questionnaire (DCFLQ) was developed and validated to assess food literacy among children aged 8 to 12 years. The DCFLQ is structured around farm-to-fork principles, including questions on food production, distribution, consumption, waste, and sustainability.

After initial item pool creation, the DCFLQ was developed in collaboration with experts and children. The validation process included assessments of reliability and construct validity, as well as a test–retest evaluation in a subgroup of children.

The expert panel consisted of domain-related researchers, a pedagogue, a paediatrician, dietitians, and a primary school teacher. Children were recruited via primary schools and a sports club.

A total of 11 experts and 27 children participated in the development process; 608 children participated in the validation process.

The final questionnaire comprised 29 questions and demonstrated good internal consistency (Cronbach’s α = 0.80) and test-retest reliability (ICC = 0.81). DCFLQ scores positively correlated with age, indicating that food literacy is higher in older children.

The DCFLQ is a valuable tool for assessing the effectiveness of nutrition intervention programs and monitoring Dutch children’s food literacy over time. International expert consensus on developing food literacy instruments is needed, as diversity in assessment tools impedes cross-cultural comparisons.

Since 2016, the emergence of continuous glucose monitors and closed-loop systems has significantly changed the way diabetes is managed. They have reduced the number of finger pricks and optimized insulin therapy by automatically adjusting insulin doses. In this evolving context, the Haute Autorité de santé (HAS) reassessed the national coverage conditions of three categories of medical devices for self-monitoring and automated insulin therapy management.

The assessment method was based on analysis of data from: (i) a systematic review of the scientific literature; (ii) proposals from concerned stakeholders (patient associations, professional organizations, manufacturers, service providers, public health institutions); and (iii) information from international health technology assessment agencies. The HAS assessment report and the new proposed reimbursement nomenclature were validated in July 2024 by the HAS committee, which appraises medical devices with respect to their reimbursement by the French health insurance scheme.

The main changes to the coverage conditions included harmonized and extended indications for each category of device, which involved removing the previous requirement of six months of insulin pump use and the metabolic criterion (hemoglobin A1c level). The prescribing conditions were also updated, allowing prescriptions from public or private hospital or non-hospital based centers. Concerning relative clinical effectiveness, HAS concluded that there was no clinical added benefit between the devices in each category. The evaluation of specific clinical data for each device carried out by HAS remains necessary before considering coverage in France, and post-registration studies are still required for closed-loop systems.

The new HAS coverage recommendations for the three categories of connected medical devices for managing diabetes offer greater clarity and improve patient care. More patients will benefit from these systems due to the extended indications. Moreover, the post-registration studies required by HAS for each closed-loop system will allow the long-term evaluation of these systems in France.

Obesity is increasing at an alarming rate in Brazil. Beyond its strong association with chronic diseases, obesity imposes a substantial burden on the Brazilian Unified Health System (SUS). The incorporation of new treatments, including interventions for weight management, requires rigorous assessment of efficacy, safety, and cost effectiveness by the National Committee for Health Technology Incorporation (CONITEC).

This study aimed to review decisions regarding the incorporation of health technologies for obesity treatment into the SUS. A review of CONITEC recommendations was performed, utilizing reports publicly accessible on its official website. The analysis focused on the evaluation of pharmacological and procedural technologies for obesity treatment in Brazil, examining technical and economic impact assessment reports.

Between 2012 and 2022, four technologies were evaluated for obesity treatment: sibutramine, orlistat, bariatric surgery via video laparoscopy (all requested by the Ministry of Health and medical societies), and liraglutide 3 mg (requested by a pharmaceutical company). Among these, only bariatric surgery was incorporated into the SUS in 2017. Sibutramine and orlistat were rejected due to limited efficacy and unfavorable safety profiles. The evaluation of liraglutide, aimed at patients with a body mass index above 35 kg/m² and cardiovascular risk, demonstrated efficacy, but was declined due to its high cost and significant economic impact on the SUS.

The rejection of technologies by the SUS highlighted safety, efficacy, and cost concerns. These decisions aligned with the SUS priority to remain economically sustainable while promoting multidisciplinary approaches to obesity management, which are actively offered within the SUS. Given the importance of the condition for public health, it is considered that the topic has been under-prioritized in the incorporation process within the SUS.

RSV is a leading cause of lower respiratory tract illness (LRTI) among infants in Chile. Nirsevimab was recommended for infants in 2023 to address the burden of RSV-LRTI. The cost effectiveness of maternal RSVpreF with complementary nirsevimab for infants, versus nirsevimab alone, for prevention of RSV-LRTI among infants in Chile was evaluated.

A cohort model to depict clinical and economic outcomes associated with RSV-LRTI for infants from birth to one year of age and lifetime consequences of RSV-related death. Results were based on disease and case-fatality rates, effectiveness, utility and disease-related disutility, and direct and indirect costs. The price of nirsevimab was USD260.00. The RSVpreF price was based on the economically justifiable value (EJV) of RSVpreF versus no intervention at a willingness-to-pay of one times the gross domestic product per capita. Uptake was set at 90 percent. In the complementary strategy, nirsevimab was limited to infants born to unvaccinated mothers. The healthcare system and societal perspectives were used, with costs in USD for 2023 and an annual discount rate of 3 percent.

With no intervention, 10,457 patients with RSV were hospitalized (RSV-H) and 39,460 attended the emergency department (RSV-ED) in the model, with corresponding total direct and indirect costs of USD21.0 million. Nirsevimab alone would prevent 52 percent (n=5,418) of RSV-H cases and 39 percent (n=15,317) of RSV-ED cases, at a total cost of USD58.8 million. Maternal RSVpreF with complementary nirsevimab would prevent 54 percent (n=5,635) of RSV-H and 34 percent (n=13,423) of RSV-ED cases. Using an EJV of USD94.34 per dose of RSVpreF, total costs of the complementary approach were lower by USD24.1 million, with an additional nine quality-adjusted life years gained. RSVpreF with complementary nirsevimab was cost saving, compared with nirsevimab alone.

Use of RSVpreF with complementary nirsevimab would achieve a similar public health impact as nirsevimab alone and would yield substantial cost savings in Chile.

Health technology assessment (HTA) uses explicit methods to determine the value of a health technology at different stages of its life cycle. Collaboration between HTA bodies and academia is crucial for advancing methodologies and their use in practice. However, regulatory misalignment and resource constraints hinder effective partnerships. This study provided ways to facilitate structured dialogue between HTA bodies and academia.

A two-phase approach was used. Phase one involved a rapid literature review and snowballing to identify frameworks for HTA–academia collaborations. Phase two consisted of an online survey with targeted dissemination to HTA bodies across Europe and beyond through social media (35 were invited). The survey questions were informed by a rapid review and addressed collaboration types, incentives, challenges, regulatory frameworks, and HTA regulation impact. Key areas included methodological development, training, and structured partnerships. Data were analyzed in Excel using descriptive statistics to identify patterns not only across Europe, but also within distinct European areas. Results were categorized by Europe as a whole and individual countries.

We obtained responses from 17 HTA bodies of which 16 maintained academic collaborations, primarily with universities at a national level. Common structures included service contracts (n=11) and consulting agreements (n=9), enabling short-term flexibility. Current collaborations focused on assessing scientific data (n=12) and specific health technologies (n=11). Barriers included diverse research paradigms (n=5), organizational resistance to change (n=5), and liability concerns (n=5). Respondents emphasized the need for guidelines and capacity building initiatives to overcome these challenges. Methodological innovation (n=14) and capacity building and training (n=13) emerged as priority objectives for collaboration. Future collaborations are expected (n=9) to align with the European HTA Regulation.

Strengthening HTA–academia collaborations requires structured and sustainable infrastructures addressing regulatory barriers, training needs, and cultural differences across countries. Clear guidelines, strategic academic partnership selection, and incentives can enhance collaboration. Implementing these findings will contribute to improved and updated methodologies and evidence-based decision-making in HTA across Europe and beyond.

Medications for chronic degenerative and rare diseases are provided by the Brazilian Unified Health System (SUS) after health technology assessment analysis conducted by the National Committee for Health Technology Incorporation (CONITEC). Access to these medicines at an outpatient level occurs through the Specialized Component of Pharmaceutical Assistance (CEAF). This study analyzed the number of people who had access to medicines included in the CEAF from 2012 to 2023.

Administrative and national dispensing data were extracted from the Health Intelligence Open Situation Platform (SABEIS), covering the period from January 2012 to December 2023, with data updated in August 2024. SABEIS consolidates open data from Ambulatory Information System (SIA/SUS), providing anonymized, individualized data. The annual number of users receiving medications from the CEAF was evaluated over this period, starting from the establishment of CONITEC in 2012.

Findings indicated a continuous growth in CEAF users between 2012 and 2023, with a total of 10,969,433 users and 84 different clinical conditions. The number of users grew from 1,991,828 in 2012 to 3,783,957 in 2023, reflecting an approximate 90 percent increase over 12 years and an average annual increase of 163,000 new users. During 2019 and 2020, there was stabilization, with only 11,332 new users, potentially due to the impact of COVID-19 on distribution and access. From 2021 onward, growth accelerated, with annual additions of 200,000 to 350,000 users, suggesting a recovery and expansion in treatment coverage.

The data highlighted an increasing demand for specialized treatments and the impact of CONITEC’s decisions on expanding access to high-cost treatments for chronic-degenerative and rare diseases in the Brazilian SUS.

Health judicialization is an escalating issue, especially in rare diseases where high treatment costs and complex management often limit treatment access. In Brazil, the National Council of Justice created support centers to provide technical scientific reports (TRs) based on health technology assessment (HTA) for evaluating judicialized health technologies. This study aimed to describe the frequency and characteristics of TRs related to rare diseases within this framework.

This descriptive cross-sectional study was developed at the Center of HTA, Hospital Sírio-Libanês, Sao Paulo, Brazil. Data were collected from the National System of Technical Reports, which compiles evidence-based scientific information to support judicial decision-making. We included TRs submitted to the platform between 2019 and 2024. Extracted data were categorized based on the most frequent rare diseases estimated by the Orphanet database list of 2024, identified according to the International Classification of Diseases, 11th Revision coding manual. Additionally, the requested health technologies were identified, and quantitative analyses were performed to identify distribution patterns.

A total of 235,546 TRs were analyzed. The most prevalent judicialized rare diseases and their corresponding technologies were as follows: motor neuron disease (n=501), with 42 percent of requests involving riluzole or tauroursodeoxycholic acid; cystic fibrosis (n=415), with 60 percent of requests for elexacaftor, tezacaftor, and ivacaftor; muscular dystrophy (n=349), with 30 percent of requests for ataluren; Gaucher disease (n=183), with 42 percent of requests for agalsidase alfa; and amyloidosis (n=93), with 58 percent of requests for tafamidis meglumine or daratumumab.

This analysis of TRs related to rare diseases highlighted the need for targeted interventions to improve access for the most prevalent conditions. By identifying the most frequently requested health technologies, this study emphasized the importance of evidence-based decision-making in addressing the challenges posed by rare diseases within the judicial system, particularly the high costs associated with their treatment.

While mobile gaming addiction (MGA) behavior is increasingly prevalent among children and adolescents, the role of specific emotional-behavioral profiles – particularly their latent patterns – in associating with MGA behavior remains poorly understood. This study aimed to examine these associations and age-related variations.

Data were analyzed from 507,188 participants aged 6–18 years in the Children’s Growth Environment, Lifestyle, and Physical and Mental Health Development Project, conducted in Guangzhou, China, in 2020. Latent class analysis was performed on parent-reported Strengths and Difficulties Questionnaire (SDQ) data to identify subgroups with distinct emotional and behavioral problems. Associations between SDQ dimensions, latent classes, and MGA behavior were examined using logistic regression analysis.

Five latent classes were identified: ‘Low symptom’ (82.2%), ‘Internalizing’ (0.8%), ‘Peer and prosocial issues’ (4.3%), ‘High difficulties’ (5.0%), and ‘Hyperactive’ (7.6%). Compared to the ‘Low symptom’ class, all other latent classes showed significantly higher risks for MGA, with the strongest association observed in the ‘Internalizing’ class (adjusted odds ratio [AOR]: 2.84; 95% confidence interval [95% CI]: 2.67–3.02). Among SDQ subscales, conduct problems presented the highest association (AOR: 2.08; 95% CI: 2.04–2.12), though all SDQ subdimensions were significantly positively correlated with MGA behavior (all p < 0.05). Notably, these associations were consistently stronger in adolescents (aged 13–18 years) than in children (aged 6–12 years).

This study identifies specific SDQ-based risk characteristics for MGA behavior, with adolescents (aged 13–18 years) being the most vulnerable. Future longitudinal studies should verify these associations, and clinicians may prioritize early screening for internalizing and conduct-related difficulties.

Knee osteoarthritis (OA) is a prevalent and debilitating condition with a significant impact on patient quality of life and healthcare costs. Intra-articular glucocorticoid injections (IAGI) are used in Switzerland for conservative management. A systematic literature review identified one existing economic evaluation on this topic globally. Therefore, the aim of this study was to evaluate the cost effectiveness of IAGI in knee OA (relative to standard care) within the Swiss healthcare context.

A cost-utility analysis was conducted using a healthcare payer perspective. Health outcomes were measured using quality-adjusted life year (QALY) estimates. Clinical outcomes were mapped into a preference-based utility measure. The clinical data showed IAGI only improved pain at one month but not beyond. Only direct costs in 2024 CHF were considered. A time horizon of six months was used to capture differences in costs and outcomes. Given the short-term clinical improvement, only a single IAGI injection was modeled. Both costs and outcomes were discounted at three percent per annum. Both deterministic sensitivity analyses (DSA) and probabilistic sensitivity analyses (PSA) were conducted. The research project was funded by the Swiss Federal Office of Public Health.

The base case incremental cost-effectiveness ratio for IAGI in knee OA was CHF12,456 (USD15,735) per QALY gained. PSA showed a 71.9 percent probability of cost effectiveness at a hypothetical willingness-to-pay (WTP) threshold of CHF50,000 (USD63,164) per QALY gained and 75.0 percent at CHF100,000 (USD126,322). There was a 22.0 percent chance that IAGI is dominated by standard care (i.e., IAGI is more costly and less effective). The DSA identified the key model drivers as IAGI administration costs and changes in health-related quality of life post-treatment.

IAGI for knee OA appeared to be a cost-effective adjunct to standard care under hypothetical thresholds of CHF50,000 (USD63,164) and CHF100,000 (USD126,322) per QALY gained. Incorporating both DSA and PSA allowed for a robust exploration of uncertainties, highlighting critical drivers of cost effectiveness. Future research should refine long-term effectiveness estimates, particularly the impact of IAGI on progression to joint replacement, and evaluate real-world outcomes to ensure optimal resource allocation.

Health technology assessment (HTA) has increasingly shaped public health insurance reimbursement decisions across many countries during the last 10 years. As countries implement and expand their use of HTA in determining recommendations for reimbursement, patient access to new medicines is affected. This study analyzed the impact of HTA, and HTA expansion, on patient access to new medicines across OECD countries.

New medicines were identified as new active substances approved by the European Medicines Agency, the United States Food and Drug Administration, or Japan’s Pharmaceuticals and Medical Devices Agency and launched globally between 1 January 2014, and 31 December 2023. Public health insurance reimbursement was determined by reviewing HTA recommendations by the appropriate HTA bodies and public reimbursement listings in each country. Patient utilization of new medicines was measured by estimating the number of patients treated with new medicines in each country, on a per capita basis, using sales and volume data adjusted for expected treatment durations.

During the past 10 years, HTA continued to play no official role in public health insurance reimbursement decisions for new medicines in the USA but played an expanding role in other OECD countries. New medicines increasingly launched first in the USA, with patients having access through public health insurance to 85 percent of new medicines in 2023. Patients in other OECD countries were far less likely to access new medicines within a year of first launch, and on average had access through public health insurance to less than a third of new medicines in 2023.

The use of HTA contributes to patient access inequality across countries by limiting and delaying public health insurance reimbursement of new medicines. In the USA, which does not use HTA, patients have access to far more new medicines. Patients in countries where HTA bodies have become gatekeepers of determining which new medicines are cost effective tend to have worse access.

Mass casualty incidents (MCIs) in high-risk environments pose major challenges for coordinated emergency response. Training is often infrequent, resource-intensive, and lacks interagency consistency. This study explores the use of Virtual Reality (VR) simulation to train responders in the RAMP triage model across emergency services.

An observational qualitative design was used. Sixteen participants from various emergency services engaged in a VR-based MCI scenario involving 26 patients and hazardous conditions. The scenario required rapid RAMP triage based on essential cues (radial pulse and the ability to follow commands). Structured interviews followed, and data were analyzed thematically.

Three themes emerged: (1) Deficiencies in current training, including inconsistent MCI protocols, lack of guideline familiarity, and limited interagency practice; (2) VR as an effective, low-resource training method enabling repeatable and safe practice—RAMP triage was found intuitive and efficient, even for non-medical personnel; and (3) prerequisites for VR implementation, such as realistic design, technical infrastructure, and stakeholder involvement to support shared understanding.

VR-based MCI training is a feasible and effective supplement to traditional drills. It enables scalable and flexible skill-building, though it should complement and not replace live exercises.

Budget impact analyses are essential for decision-making processes regarding the incorporation of technologies into healthcare systems. Despite advancements driven by the National Committee for Health Technology Incorporation (CONITEC), the Brazilian Network for Health Technology Assessment (REBRATS), and the National Supplementary Health Agency (ANS), challenges persist in evaluating the economic impact of new technologies, including methodological inconsistencies in submitted dossiers.

Reports on the critical analysis of dossiers submitted to the ANS prepared by a health technology assessment center between December 2022 and December 2024 were analyzed. Criticisms of the submitted dossiers were categorized into eleven topics: (i) analytical model; (ii) reference scenario; (iii) alternative scenario; (iv) time horizon; (v) target population; (vi) direct costs; (vii) market behavior; (viii) sensitivity analysis; (ix) input data; (x) output data; and (xi) final decision. Descriptive and quantitative data were used to identify patterns and methodological gaps.

The critical analysis identified recurring issues, including underestimated target populations in 50 percent of cases and inadequate direct cost evaluations in 40 percent. These inadequacies were often linked to outdated data sources, such as the Painel dos Dados do TISS database. Analytical models were deemed adequate in 70 percent of cases, whereas sensitivity analyses were insufficient in 30 percent of cases. Market behavior projections were conservatively estimated in 60 percent of dossiers, affecting the accuracy of budget impact projections. These methodological inconsistencies hindered the reproducibility of analyses and compromised evidence-based decision-making.

The findings highlighted the need for methodological standardization in dossiers submitted to the ANS, emphasizing the need to update data sources and ensure transparency in budget impact calculations. These improvements could enhance evaluation validity and support better decision-making for technology incorporation. Future research should address strategies to reduce uncertainties and inconsistencies in analytical models and cost estimations.

Da Vinci robot-assisted surgery (dV-RAS) has been around for more than 20 years and has become the standard of care for select procedures in specific countries. Recently, health technology assessment agencies have used local evidence to inform their evaluation of dV-RAS. We aimed to compare global, Pan-European (Pan-EU), and Pan-Asian systematic literature reviews on dV-RAS for seven malignant procedures.

The PubMed, Scopus, and Embase databases were systematically searched through to 31 December 2022 following PRISMA and PROSPERO guidelines (CRD42023466759). Studies that compared dV-RAS with laparoscopic or video-assisted thoracoscopic surgery (lap/VATS) or open oncologic surgery and reported on relevant clinical outcomes were included. Studies were checked for the source of clinical data and categorized as being either Pan-EU or Pan-Asian. The global analysis included all eligible studies. Pooled odds ratios or mean differences were calculated for randomized, prospective, and database studies using R software and a fixed-effect or random-effects (when heterogeneity was significant) model. The revised Cochrane risk-of-bias and ROBINS-I tools were used to assess bias.

The global systematic literature review identified 230 studies (34 randomized, 74 prospective, 122 database), including 78 Pan-EU and 35 Pan-Asian studies. Results from the global and regional studies agreed on rates of conversions and blood transfusions and lengths of hospital stay. The global, Pan-EU, and Pan-Asian studies did not align on: operative time (Global: dV-RAS longer; Pan-EU: dV-RAS longer versus open; Pan-Asian: dV-RAS longer versus lap/VATS); 30-day complications (Global and Pan-Asian: dV-RAS lower; Pan-EU: dV-RAS lower versus open); 30-day readmissions (Global and Pan-EU: dV-RAS lower; Pan-Asian: dV-RAS lower versus open); 30-day reoperations (Global: dV-RAS lower versus open; Pan-EU and Pan-Asian: dV-RAS similar); 30-day mortality (Global: dV-RAS lower; Pan-EU: dV-RAS lower versus open; Pan-Asian: dV-RAS longer versus lap/VATS).

Our analysis highlighted that global and regional evidence aligned on select outcomes. The differences we observed might be associated with surgeon experience, limited evidence, or other unknown regional biases. These findings should be considered by health technology assessment agencies when looking at regional data versus global evidence.

Generative artificial intelligence (AI) is revolutionizing real-world evidence generation in health care. This study compared chemotherapy recommendations for women with breast cancer across different clinical risk profiles and Oncotype DX Breast Recurrence Score® test results, as obtained from a Delphi panel of experts, with recommendations generated by ChatGPT. The objective was to analyze concordances and differences between AI-generated and expert-driven insights.

An online survey of 10 independent breast cancer experts, blinded to each other’s responses, assessed chemotherapy recommendations for patients with early stage, node-negative breast cancer. Responses were analyzed by clinical risk (high versus low), age group (≤50 versus >50 years), and recurrence score (RS) (<11, 11 to 25, >25) from Oncotype DX. ChatGPT, using automated prompt engineering, addressed the same scenarios as agent-based oncologists. Expert recommendations were summarized as arithmetic means, while ChatGPT responses were analyzed for concordance. A one-sample t-test compared mean estimates between the Delphi panel and ChatGPT results, highlighting differences in recommendations across groups.

The Delphi panel and ChatGPT provided clinically similar chemotherapy recommendations for patients evaluated with Oncotype DX, with no statistically significant differences in eight out of 12 scenarios. Both agreed on zero percent chemotherapy for patients with low clinical risk (RS<11) and showed comparable results for high clinical risk (RS>25), including patients under 50 years (8% versus 10%) and over 50 years (6% versus 5%). The largest divergence, which was statistically significant, was observed for patients with low clinical risk (RS 11 to 25) who were over 50 years (1% versus 20%). High-risk patients consistently received strong recommendations, with near perfect agreement for those with high clinical risk (RS>25) who were under 50 years (98% versus 95%).

From a decision-making perspective, the responses from ChatGPT and the Delphi panel were very similar, suggesting that AI can effectively support the health technology assessment process. This alignment highlights AI’s potential to accelerate decision-making, offering a faster alternative to the traditional, time-consuming Delphi model while maintaining reliable chemotherapy recommendations.

Despite the significant impact of the media on individuals with mental illness, newspaper articles related to antidepressants have not been systematically studied. The present study aimed to analyze Brazilian journalistic coverage on the use of antidepressants to understand how the news presents and shapes the topic of antidepressants for its readers.

This qualitative study evaluated journalistic content on antidepressant use from Folha de São Paulo, a newspaper available in digital format. Articles published between 1 January 2019 and 31 December 2023 were collected and stored in a database for analysis. Natural language processing (NLP) techniques, combined with machine learning, were applied. The R software (version 4.3.3) with tidytext, tm, tidyverse, and stringr packages was used for the analyses. The study identified patterns and trends in language usage, focusing on frequently occurring terms to understand how antidepressants are portrayed in media content.

The initial research was conducted using the keyword “antidepressants” in the search engine of the Folha de São Paulo. Of the articles assessed for eligibility, 182 were included in the study. Across all the articles, the analysis aimed to identify the most frequently used words, resulting in a word cloud. The most used words in the text body were “treatment,” followed by “years,” “anxiety,” “women,” and “pandemic.” Regarding the most frequent words in the titles, they were “depression,” “health,” and “study.” On average, there was no significant change in the total number of n-grams used.

The findings illustrated how Brazilian media frames antidepressant use, revealing potential misinformation or stigma. Understanding these representations can guide strategies for improving public awareness and reducing stigma around mental health. By highlighting trends in journalistic narratives, this study contributes to public health policies that promote accurate, responsible communication about antidepressant use.