The study, conducted at Cerrahpaşa Medical Faculty in Istanbul and approved by the institutional review board there, retrospectively evaluated the clinical and follow-up records of patients diagnosed and managed at the centre over a ten-year period. Engin performed the skin biopsies, diagnosed and treated the patients, and led the manuscript; Yildirim assisted with follow-up and drafted the text; Erkoc classified treatments and staging and analysed the data. The work was carried out in accordance with the Declaration of Helsinki, and the authors report no conflicts of interest. As is typical for retrospective cohort analyses of rare lymphomas, the value of the dataset lies less in dramatic new findings than in the granular picture it paints of how one busy dermatology service handles a diagnostically treacherous disease over time.

Technically, mycosis fungoides belongs to the primary cutaneous lymphomas, a family of extranodal non-Hodgkin lymphomas that arise in the skin rather than in lymphoid organs. The current diagnostic framework is anchored by the 2018 update of the WHO-EORTC classification, which separates indolent entities such as early-stage mycosis fungoides from aggressive ones such as Sézary syndrome, the leukemic variant characterised by widespread erythroderma, circulating malignant T cells and a markedly worse prognosis. The International Consensus Classification of mature lymphoid neoplasms, published in 2022, further refined this landscape. Within that framework, mycosis fungoides follows a characteristic clinical course: patch-stage lesions progress to plaques, then potentially to tumours, and in a minority of patients to visceral involvement. Most patients, however, never advance beyond the early stages, which is why accurate staging at diagnosis is the single most important prognostic exercise.

That staging depends on a synthesis of clinical, histopathological and, where indicated, molecular data. Skin biopsies are examined for epidermotropism, the migration of atypical T lymphocytes into the epidermis, and for the formation of Pautrier microabscesses, small clusters of these cells that are highly characteristic though not always present. T-cell receptor gene rearrangement studies can demonstrate clonality, distinguishing a malignant population from a reactive infiltrate, but early lesions may lack convincing clonal evidence, forcing clinicians to repeat biopsies over months or years. Blood tests assess for Sézary cells, and in advanced cases, imaging and lymph node biopsy complete the tumour-node-metastasis-blood staging algorithm. The Istanbul study reflects this layered diagnostic process, with the corresponding author personally performing and interpreting the skin biopsies that anchored each patient’s diagnosis.

One of the best-documented problems in the field is diagnostic delay. A frequently cited Danish study by Skov and Gniadecki found that the histopathological diagnosis of mycosis fungoides is often delayed, with patients carrying the disease for years before a biopsy confirms it, partly because early histology is subtle and mimics spongiotic or psoriasiform dermatitis. Every additional year of misdiagnosis represents deferred access to skin-directed therapy and prolonged uncertainty for the patient. A ten-year single-centre dataset is precisely the kind of evidence that quantifies this burden in a specific population, and the Turkish authors frame their work explicitly as an evaluation of clinical and follow-up data, the raw material from which such delays and their consequences can be measured.

Treatment for mycosis fungoides is stage-adapted, and the European Organisation for Research and Treatment of Cancer issued updated consensus recommendations in 2023 that codify the current hierarchy. Early-stage disease is managed with skin-directed therapies: topical corticosteroids and retinoids, phototherapy with narrowband UVB for patches and thin plaques, psoralen plus ultraviolet A for thicker lesions, and localised radiotherapy or total skin electron beam therapy for more extensive or refractory cutaneous involvement. Advanced disease adds systemic options, including interferon-alpha, retinoids such as bexarotene, histone deacetylase inhibitors, antibody-based therapies and, in selected cases, allogeneic stem cell transplantation, the only treatment with potential for durable cure. Combination approaches, pairing a skin-directed modality with a systemic agent, are common in tumour-stage disease. The Istanbul team’s classification of treatments and staging across their cohort maps directly onto this algorithm and illustrates how a high-volume centre deploys it in practice.

Single-centre cohort studies of this kind occupy an important niche in rare-disease research. Randomised trials in mycosis fungoides are difficult to power because the disease is uncommon and its early stages progress slowly, so much of what is known about natural history, treatment patterns and outcomes comes from institutional series accumulated over years or decades. Previous examples include the retrospective analysis of 133 cutaneous lymphoma patients from a single Japanese centre published by Fujita and colleagues, which similarly documented presentation patterns and outcomes over a multi-year window. The Turkish dataset joins this tradition, offering a Mediterranean and Middle Eastern patient population whose demographic profile, referral pathways and treatment access may differ meaningfully from the Northern European and Japanese cohorts that dominate the literature.

The follow-up dimension of the study deserves particular emphasis. Mycosis fungoides can smoulder for decades, and late relapse or transformation to a more aggressive large-cell phenotype can occur years after apparent stability. Longitudinal data from a single centre, where patients are followed by the same diagnostic and therapeutic team, reduce the heterogeneity that plagues multi-site registries, though they also introduce the limitations inherent to retrospective design: reliance on recorded notes, potential loss of patients to follow-up, and the absence of a standardised prospective protocol. The authors’ explicit contribution statement, detailing who diagnosed, biopsied, treated, staged and analysed, underscores the continuity of care that gives such datasets their internal consistency.

For the wider scientific audience, the significance of this research letter lies in what it represents rather than in any single headline number. It demonstrates that cutaneous lymphoma care in Turkey is organised around internationally recognised classification and treatment frameworks, that long-term follow-up is feasible in a public hospital dermatology service, and that the diagnostic bottleneck remains the central challenge of the disease. It also reinforces a message that dermatologists have been repeating for years: persistent, treatment-resistant or unusually distributed skin lesions in adults warrant a low threshold for biopsy and, when histology is equivocal, serial re-biopsy and specialist referral. Earlier recognition will not change the biology of mycosis fungoides, but it moves patients into appropriate surveillance and stage-appropriate therapy sooner, which matters for quality of life and, in the minority who progress, for survival.

The study is available as a research letter in volume 318 of the Archives of Dermatological Research, and its full clinical tables and figures are accessible through the journal. As genomic profiling, targeted immunotherapies and biomarker-driven risk stratification enter the cutaneous lymphoma field, datasets like this one, grounded in a decade of unbroken clinical contact with patients, will serve as the historical baseline against which the next generation of diagnostics and treatments is judged. For now, the Istanbul experience stands as a reminder that in rare lymphomas of the skin, the most powerful clinical instrument remains the patient chart kept faithfully over many years.

Subject of Research: A 10-year single-centre retrospective evaluation of clinical presentation, staging, treatment and follow-up in patients with mycosis fungoides, the most common cutaneous T-cell lymphoma.

Article Title: Evaluation of clinical and follow-up data in patients with mycosis fungoides: a 10-year single-centre experience

Article References: Engin, B., Yildirim, G., & Erkoc, Y. C. (2026). Evaluation of clinical and follow-up data in patients with mycosis fungoides: a 10-year single-centre experience. Archives of Dermatological Research, 318(1), Article 449. https://doi.org/10.1007/s00403-026-04943-7

Image Credits: AI Generated

DOI: 10.1007/s00403-026-04943-7

Keywords: mycosis fungoides, cutaneous T-cell lymphoma, dermatology, WHO-EORTC classification, diagnostic delay, skin biopsy, staging, skin-directed therapy, Sézary syndrome, retrospective cohort study, Istanbul, long-term follow-up

The significance of the result lies less in the headline accuracy figure than in what it implies for the millions of people living in rapidly urbanizing regions where air quality monitoring infrastructure is thin. The Air Quality Index, or AQI, condenses the concentrations of several regulated pollutants into a single number that public health authorities use to issue warnings, close schools, and restrict traffic. Producing that number reliably normally requires continuous measurements of particulate matter, sulfur dioxide, carbon monoxide, and nitrogen dioxide from calibrated instruments. When a district has only sparse or intermittent monitoring, the index becomes unreliable exactly when residents need it most, and the health consequences of missed pollution episodes can be severe.

Akiner and Ghasri attacked the problem with a two-stage design that reflects a key insight about atmospheric data: pollution does not behave the same way under all weather conditions. In the first stage, they applied K-Means clustering, an unsupervised algorithm that groups observations by similarity without being told what the groups should be, to a combination of meteorological variables and pollutant concentrations. The algorithm partitioned the ten-year record into distinct atmospheric regimes, essentially discovering recurring weather-and-pollution patterns on its own. Each cluster corresponds to a characteristic set of conditions, such as stagnant, cold episodes in which pollutants accumulate near the surface, or windy, well-mixed periods in which concentrations disperse rapidly.

This clustering step matters because it gives the downstream model a structured picture of the atmosphere instead of forcing it to learn every relationship from raw, undifferentiated data. In the second stage, the researchers employed XGBoost, a gradient-boosted decision tree algorithm that has become a workhorse of tabular machine learning. XGBoost builds an ensemble of decision trees sequentially, with each new tree trained to correct the residual errors of the ensemble so far, and it includes regularization terms that discourage overfitting. The model was tasked with estimating AQI values from meteorological parameters together with the key pollutants PM10, PM2.5, SO2, CO, and NO2, conditioned on the regime structure identified by the clustering stage.

The crucial design choice is the framework’s reliance on widely available meteorological data to compensate for scarce pollutant measurements. Weather variables such as temperature, wind speed, humidity, and pressure are collected routinely by national meteorological services almost everywhere on Earth, and Türkiye’s General Directorate of Meteorology, together with the Ministry of Environment, Urbanization, and Climate Change, provided the database underpinning the study. Because these inputs are cheap and abundant, the framework reduces dependence on dense sensor infrastructure. In effect, the model learns how the local climate converts emissions into pollution episodes, and can then reconstruct or forecast air quality even where direct pollutant observations are limited.

The reported performance is remarkable for a real-world urban dataset. An overall accuracy of approximately 98 percent means the model reproduces the observed AQI with enough fidelity to support timely health advisories, giving authorities lead time to warn vulnerable populations, adjust traffic, or deploy inspection resources. Beyond raw accuracy, the authors used feature-importance analysis to identify which meteorological drivers dominate AQI variability in Kağıthane. This kind of interpretability is increasingly demanded of machine learning in environmental applications, because a black-box prediction is of limited use to a planner who needs to know whether ventilation, temperature inversions, or precipitation scavenging is controlling pollution on a given day.

Kağıthane itself is a fitting laboratory for the method. The district sits in a valley that channels both traffic and terrain-driven airflow, and previous research has documented elevated particulate levels in the Kağıthane Valley and the wider Istanbul metropolitan area. Istanbul combines intense vehicular emissions, a population exceeding fifteen million, complex topography, and a coastal climate whose winds and humidity strongly modulate pollutant dispersion. A model that performs well in such a demanding setting is more likely to transfer to other challenging environments than one tuned on a flat, well-monitored city.

The authors emphasize that the framework is modular and readily transferable across different geographic and temporal contexts. Both K-Means and XGBoost are standard, well-documented algorithms, and the input data are commonly available, which means a municipality does not need supercomputing resources or proprietary technology to adopt the approach. The pipeline can be retrained on local data, the clustering stage will rediscover the atmospheric regimes specific to a new location, and the boosted trees will re-weight the meteorological drivers accordingly. That scalability is the study’s central claim: a practical answer for regions facing environmental monitoring constraints, from fast-growing cities in the Global South to districts of wealthy cities where sensor coverage is uneven.

The work also arrives amid a broader shift in how air pollution is measured and modeled. Researchers worldwide are experimenting with low-cost sensor networks, satellite retrievals of aerosol optical depth, and deep learning architectures for spatiotemporal forecasting, and systematic reviews have catalogued both the promise and the pitfalls of machine learning in air pollution epidemiology. Against that backdrop, the Istanbul study makes a deliberately pragmatic argument: rather than waiting for perfect instrumentation, cities can extract far more value from the data they already possess by combining unsupervised structure discovery with powerful supervised regression. The approach complements, rather than replaces, physical dispersion models, which remain essential for source attribution and regulatory analysis.

For public health, the implications are immediate. Air pollution is linked to cardiovascular and respiratory disease, adverse birth outcomes, and growing evidence of effects on mental health and children’s cognitive development, and the burden falls disproportionately on neighborhoods with the least monitoring. A framework that turns routine weather data into near-accurate AQI forecasts can level that playing field, enabling evidence-based environmental policy in places that have historically flown blind. As urbanization accelerates and climate change alters the meteorological conditions that govern pollutant dispersion, tools like this hybrid model may become as standard a piece of civic infrastructure as the weather forecast itself, quietly translating the atmosphere’s behavior into actionable warnings for the people who live beneath it.

Subject of Research: Hybrid machine learning for air quality index forecasting in data-scarce urban environments

Article Title: Overcoming data shortages through hybrid machine learning in air quality forecasting: a case study of Kağıthane, Istanbul

Article References: Akiner, M. E., & Ghasri, M. (2026). Overcoming data shortages through hybrid machine learning in air quality forecasting: a case study of Kağıthane, Istanbul. Theoretical and Applied Climatology, 157(10), Article 609. https://doi.org/10.1007/s00704-026-06545-9

Image Credits: AI Generated

DOI: 10.1007/s00704-026-06545-9

Keywords: air quality, machine learning, XGBoost, K-Means clustering, Air Quality Index, Istanbul, Kağıthane, meteorology, urban pollution, data scarcity, public health, environmental forecasting

The study, conducted by Gozde Kugcumen of Istanbul Medipol University and Ilkay Gungor Satilmis of Istanbul University-Cerrahpasa, set out to answer a deceptively simple question: does adding a hands-on simulation session to standard online theoretical instruction actually improve what obstetric nurses and midwives know about preeclampsia care, and how confident do they feel applying that knowledge? The researchers ran the trial between February 2019 and August 2020 at a university hospital in Istanbul, registering it prospectively as a clinical trial to signal methodological transparency from the outset. In a field where educational interventions are often evaluated with before-and-after studies lacking any comparison group, the randomized design alone marks this work as a meaningful contribution.

The technical architecture of the trial reflects careful attention to the realities of clinical staffing. A total of 76 nurses and midwives were enrolled and randomized in equal halves of 38 participants per group, but the final complete-case analysis included 61 participants with full baseline and four-week outcome data—30 in the intervention group and 31 in the control group. Eligibility criteria were deliberately strict: every participant held at least a bachelor’s degree and had accumulated a minimum of six months of experience in obstetrics and delivery services. This ensured that the study measured the incremental value of simulation on top of an already educated and clinically active workforce, rather than compensating for gaps in basic training.

Crucially, both arms of the trial received the same foundation: an online theoretical training module covering the follow-up and care of pregnant women with preeclampsia. One week after completing this shared theoretical component, the intervention group took part in a simulation session built around a standardized patient—an actor trained to portray a consistent clinical scenario, allowing learners to practice history-taking, assessment, communication, and decision-making under realistic conditions. This design choice is methodologically important. Because both groups received identical theoretical content, any difference in outcomes at the four-week mark could be attributed to the simulation experience itself rather than to extra contact time or additional reading material.

The measurement battery was equally comprehensive. Knowledge was assessed with the Preeclampsia Information Assessment Form, a validated instrument probing disease-specific understanding, and with an Objective Structured Clinical Assessment Form designed to capture applied clinical performance. Self-efficacy—the psychological construct describing a person’s belief in their own capacity to execute the behaviors required for a task—was measured with the Self-Efficacy Scale in the Follow-up and Care of Pregnant Women with Preeclampsia, abbreviated as SESPWP. The learners’ experience of the education itself was evaluated with the Educational Practices Questionnaire and the Student Satisfaction and Self-Confidence in Learning Scale, two instruments widely used in simulation research to gauge whether the training environment supported engagement and confidence.

When the four-week posttest data were analyzed, the knowledge results favored simulation. Scores on the Preeclampsia Information Assessment Form were significantly higher in the intervention group than in the control group, with a p-value below 0.05, indicating that the difference was unlikely to be a statistical fluke. In practical terms, nurses and midwives who had rehearsed preeclampsia care with a standardized patient retained measurably more disease-specific knowledge a month later than peers who had received only the online lectures. For educators, this finding supports the long-standing hypothesis that active, experiential learning consolidates cognitive material more durably than passive delivery alone.

The self-efficacy story, however, is more complicated—and the authors were careful not to overstate it. Within the intervention group, SESPWP scores rose significantly from pretest to posttest, with a p-value of 0.015, suggesting that participants genuinely felt more capable of managing preeclampsia care after the simulation. Yet when the researchers adjusted for baseline differences between the groups, the between-group effect on self-efficacy was not statistically significant, and the difference in pre-to-post change between the two arms also failed to reach significance. In plain language: simulation participants gained confidence, but the control group’s confidence also shifted over the study period, and the simulation-specific increment could not be demonstrated with statistical confidence.

The authors themselves acknowledge this subtlety in their conclusions. Adding simulation-based training to shared online theoretical education was associated with higher baseline-adjusted knowledge at four weeks, they report, although the between-group difference in pre-post change was not statistically significant in sensitivity analysis, and no simulation-specific between-group effect on self-efficacy was demonstrated. This kind of transparent reporting is increasingly valued in clinical education research, where enthusiasm for simulation has sometimes outpaced the evidence. The trial’s sensitivity analyses—re-examining the primary findings under alternative statistical assumptions—reveal how fragile some between-group contrasts can be in a sample of 61 complete cases, a reminder that even well-designed trials have limits imposed by their size.

What the participants thought of the experience adds another layer to the findings. Scores on the Educational Practices Questionnaire and the Student Satisfaction and Self-Confidence in Learning Scale indicated high levels of satisfaction and positive evaluations of the simulation experience across the board. High satisfaction matters for a practical reason: educational interventions only work if clinicians are willing to complete them, and simulation formats that learners find engaging are more likely to be adopted and sustained in busy hospital environments. The consistency between the objective knowledge gains and the subjective learning experience strengthens the case that the standardized-patient session created a genuinely effective educational environment, even if its effects on confidence could not be isolated statistically.

The broader implications reach well beyond a single Istanbul hospital. Preeclampsia affects a meaningful share of pregnancies worldwide and demands rapid, coordinated recognition and management, typically initiated by bedside nurses and midwives before physicians become involved. Educational bodies have increasingly recommended simulation as a core component of obstetric emergency training, yet high-quality randomized evidence in nursing and midwifery populations has been comparatively scarce. This trial, conducted as part of a doctoral thesis in gynecologic nursing and presented orally at the 3rd International and 4th National Women’s Health Nursing Congress in May 2025, contributes precisely the kind of controlled, instrument-based evidence that such recommendations require. Its message is measured but useful: simulation appears to help clinicians retain what they learn about preeclampsia care, learners value the experience highly, and claims about self-efficacy benefits should await larger trials with the statistical power to detect them. For hospitals weighing the cost of standardized-patient programs against the return in clinical preparedness, the study offers a data point worth serious attention—and a clear template for the replication studies the field now needs.

Subject of Research: Effects of simulation-based education on nurses' and midwives' knowledge and self-efficacy in preeclampsia care

Article Title: Effects of simulation-based education on nurses’ and midwives’ knowledge and self-efficacy in preeclampsia care: a randomized controlled trial

Article References: Kugcumen, G., & Satilmis, I. G. (2026). Effects of simulation-based education on nurses’ and midwives’ knowledge and self-efficacy in preeclampsia care: a randomized controlled trial. BMC Nursing. https://doi.org/10.1186/s12912-026-05428-8

Image Credits: AI Generated

DOI: 10.1186/s12912-026-05428-8

Keywords: preeclampsia, simulation-based education, randomized controlled trial, nursing education, midwifery, self-efficacy, standardized patient, clinical training, obstetric care, BMC Nursing, Istanbul, knowledge retention

The study was led by İlknur Sayan and Didem İstafiloğlu of the Department of Health Management at Istanbul Kent University, together with independent researcher Serem Akdal. The team focused on health sciences students for a specific reason: this population represents the future healthcare workforce, the people who will eventually design, deliver, and explain digital health services to patients. If digital competency shapes how these students perceive the healthcare system, the implications could ripple outward into clinical practice, health policy, and patient education for years to come. Evidence linking e-health literacy to perceived healthcare access had remained limited in the Turkish context, and the researchers set out to fill that gap with a rigorously validated measurement approach.

Participants completed a structured questionnaire containing two established instruments. The first was the eHealth Literacy Scale, widely known as eHEALS, which measures an individual’s self-assessed ability to seek, find, and appraise health information from electronic sources. The second was a 23-item Perceived Access to Healthcare Services Scale, organized around four dimensions drawn from the classic access framework in health services research: accessibility, meaning the physical and geographic reach of services; acceptability, meaning whether services align with patients’ expectations and social norms; accommodation, meaning how well service organization fits patients’ needs, such as opening hours and appointment flexibility; and affordability, meaning the financial burden of obtaining care. The study received ethics approval from the Social and Human Sciences Ethics Committee of Istanbul Kent University, with written informed consent obtained from all participants in accordance with the Declaration of Helsinki.

The analytical machinery behind the study is where it earns its technical credibility. Rather than simply correlating two questionnaire scores, the researchers employed Confirmatory Factor Analysis to verify that the survey items actually clustered into the intended constructs, and then built a second-order Structural Equation Model in LISREL 9.3 to test whether e-health literacy predicted the higher-order construct of perceived access. The resulting model demonstrated good fit across the standard battery of indices: a chi-square to degrees-of-freedom ratio of 1.97, a Root Mean Square Error of Approximation of 0.051, a Comparative Fit Index of 0.96, a Tucker-Lewis Index of 0.95, and a Standardized Root Mean Square Residual of 0.047. For readers unfamiliar with these metrics, values in these ranges indicate that the theoretical model reproduces the observed data patterns well, rather than forcing the data into an ill-fitting structure.

The headline result is striking in its magnitude. E-health literacy was significantly and positively associated with perceived healthcare access, with a standardized path coefficient of 0.62, a p-value below 0.001, and an R-squared of 0.38. In practical terms, the model accounted for 38 percent of the variance in how students perceived their access to healthcare services, a substantial share for a social science model built on individual-level survey data. Students who felt more confident in their ability to find and evaluate health information online consistently rated the healthcare system as more accessible, more acceptable, better accommodated to their needs, and more affordable.

Within the four dimensions of access, the structural model revealed an interesting hierarchy. Acceptability, with a loading of 0.92, and accommodation, with a loading of 0.90, contributed most strongly to the higher-order access construct, while accessibility and affordability weighed somewhat less. This suggests that among young, digitally fluent students, judgments about healthcare access hinge less on geography or cost and more on whether services feel compatible with their expectations and whether the system’s organization fits their lives. It is a pattern consistent with the idea that for a generation accustomed to on-demand digital services, the friction of scheduling, communication, and service design matters as much as the location of a clinic.

The authors were careful about measurement quality, and one honest caveat emerged from their validation work. Discriminant validity, the statistical test of whether two constructs are genuinely distinct rather than measuring the same thing twice, was evaluated using both the Fornell-Larcker criterion and Heterotrait-Monotrait ratios. Most construct pairs passed cleanly. However, the acceptability and accommodation dimensions showed a Fornell-Larcker violation and an HTMT ratio of 0.916, exceeding the conservative 0.85 threshold. This indicates limited discriminant validity between these two closely related dimensions, meaning that in this sample, students may have experienced acceptability and accommodation as overlapping facets of a single impression of service fit. The team also screened for common method bias using Harman’s single-factor test, a standard safeguard when all data come from self-reported questionnaires.

The researchers themselves are explicit about the limits of what can be concluded. Because the study is cross-sectional, capturing all participants at a single point in time, the findings should be read as an association rather than evidence of a causal pathway. It is possible that higher e-health literacy genuinely improves how students perceive access to care, perhaps by giving them more tools to connect with services and more confidence in navigating them. It is equally possible that students who already view the health system favorably are more motivated to engage with digital health resources, or that some unmeasured factor, such as general digital fluency or socioeconomic background, drives both. Disentangling these possibilities requires longitudinal designs that follow students over time, and the authors recommend exactly that, alongside cross-cultural replication to test whether the pattern holds beyond Istanbul.

Even with those caveats, the practical implications are hard to ignore. The authors suggest that structured digital health competency training embedded in health sciences curricula may be a useful direction to explore further. If e-health literacy is associated with more favorable perceptions of healthcare access among the people who will soon staff hospitals, clinics, and public health agencies, then teaching those skills systematically could pay dividends not only for the professionals themselves but for the patients they will eventually guide through increasingly digital systems. Health literacy has long been recognized as a determinant of health outcomes; this study extends that logic into the digital domain, where appointment booking, prescription refills, and health information seeking increasingly live.

The study also arrives at a moment when the gap between digital haves and have-nots has become a central concern of health equity research. Although this sample consisted of university students, a relatively digitally connected population, the strong association between e-health literacy and perceived access hints at what might happen in populations with lower digital skills: if confidence with electronic health tools shapes how reachable care feels, then digital exclusion could quietly translate into perceived exclusion from healthcare itself. The Istanbul findings, published open access under a Creative Commons license and citable at DOI 10.1186/s12913-026-15732-3, offer a measured but provocative data point in that conversation, and they set a clear agenda for the longitudinal and cross-cultural studies that must now follow.

Subject of Research: The association between e-health literacy and perceived access to healthcare services among health sciences students in Istanbul, Turkey

Article Title: The impact of e-health literacy on perceived access to healthcare services: a cross-sectional study among health sciences students in Istanbul, Turkey

Article References: Sayan, İ., İstafiloğlu, D., & Akdal, S. (2026). The impact of e-health literacy on perceived access to healthcare services: a cross-sectional study among health sciences students in Istanbul, Turkey. BMC Health Services Research. https://doi.org/10.1186/s12913-026-15732-3

Image Credits: AI Generated

DOI: 10.1186/s12913-026-15732-3

Keywords: e-health literacy, healthcare access, health sciences students, structural equation modeling, eHEALS, Turkey, health services research, digital health, confirmatory factor analysis, HTMT, health equity, Istanbul

The study drew on an unusually rich observational foundation. The researchers compiled routine and special aviation weather reports issued every thirty minutes from three airports serving Istanbul: Sabiha Gökçen, identified in the study by its ICAO code LTBA, situated on the city’s Anatolian side; Istanbul Airport, coded LTFM, on the northwestern shore near the Black Sea; and Atatürk’s successor regional field LTFJ in the eastern inland part of the metropolitan area. These half-hourly reports, which record visibility, cloud base, temperature, dew point, wind, and pressure, were supplemented by radiosonde soundings that profile the vertical structure of the lower atmosphere and by microphysics satellite imagery capable of distinguishing cloud properties at night. From this combined dataset, the team applied an objective physical typing algorithm that sorts every fog event into one of five mechanistic categories: advection fog, radiation fog, precipitation fog, cloud-base lowering, and evaporation fog.

The classification matters because each fog type carries a distinct physical signature and a distinct forecasting challenge. Advection fog forms when moist air flows horizontally over a cooler surface, chilling the air to its dew point; it is the classic fog of coastal regions where warm, humid maritime air drifts across cold water or cold land. Radiation fog, by contrast, is born on clear, calm nights when the ground radiates heat skyward, cooling the air layer in contact with it until condensation begins. Precipitation fog arises when rain falls through drier air and evaporates, pumping moisture into the boundary layer. Cloud-base lowering describes stratus decks that descend until they effectively become fog at the surface, while evaporation fog forms when water evaporates from a warm surface into cooler air above. Sorting events into these categories allowed the researchers to trace each airport’s fog regime back to its thermodynamic roots.

The spatial contrasts the analysis uncovered are striking. Over the extended historical period from 2012 to 2023, the eastern inland station LTFJ logged an average of 17.2 fog days per year, more than five times the 3.2 fog days recorded annually at the southern urban station LTBA. The dominant fog mechanism also differed fundamentally between the two sites. At LTFJ, advection fog accounted for 53 percent of events, a signature of moist air being transported into the area and chilled over locally cool surfaces. At LTBA, radiation fog dominated at 55 percent, and the researchers attribute this to the interplay of urban heat island effects and topographic shielding around the airport. The urban heat island raises nighttime minimum temperatures, making it harder for the near-surface air to reach saturation, while surrounding terrain can block or channel the drainage flows and moist intrusions that feed fog elsewhere in the city.

When the analysis was restricted to the common period from 2019 to 2023, during which all three airports provided overlapping records, the three-way comparison sharpened the picture further. LTFJ recorded 52 fog-affected days over that window, LTBA just 12, and LTFM, the northern airport closest to the Black Sea coast, 57. Advection fog again led the statistics at both LTFJ, where it made up 50 percent of events, and LTFM, where it reached 56 percent. The elevated fog frequency at LTFM fits its coastal geography: proximity to the Black Sea supplies abundant low-level moisture, and the temperature contrasts between sea and land provide the cooling mechanism that advection fog requires. That two airports separated by a few dozen kilometers within the same metropolitan area can differ by nearly a factor of five in annual fog days underscores how strongly microclimate and siting control fog occurrence in complex coastal terrain.

The temporal structure of Istanbul’s fog is equally distinctive. The analysis demonstrated a pronounced winter peak, with fog activity concentrated in November and February, and a complete absence of fog during the summer months. This seasonality reflects the underlying thermodynamics. Winter brings longer nights, weaker solar heating, lower sea-surface and land-surface temperatures, and a greater supply of moist air masses moving across relatively cool waters, all of which favor the saturation of the boundary layer. Summer, with its strong insolation and warm surfaces, keeps the near-surface air well above its dew point even under maritime influence. For aviation planners and forecasters, the message is that Istanbul’s fog risk is not evenly distributed through the year but clusters sharply in the cold season, with November and February emerging as the critical months for low-visibility operations.

Perhaps the most consequential finding concerns spatial coherence. Between 2019 and 2023, the researchers evaluated how often fog occurred simultaneously at all three observation nodes, and the answer was remarkably small: only four days in five years saw all three airports shrouded at once. In other words, Istanbul’s fog is profoundly fragmented, appearing at one airport while the others remain clear. This localized fragmentation has direct operational implications. Flight diversions, holding patterns, and ground delays are typically triggered by visibility conditions at a single destination airport, so a fog climatology built on city-wide averages would badly misrepresent the actual risk. A pilot approaching one Istanbul facility may encounter dense fog while another facility across the city operates normally, a pattern that only station-specific, mechanism-aware forecasting can capture.

The study’s methodology also highlights the value of combining conventional surface observations with remote sensing. Radiosonde profiles reveal the depth and structure of the temperature inversion layers that cap and nourish radiation fog, while night microphysics satellite imagery allows researchers to track fog patches across the metropolitan area between routine observation times, confirming events that a single surface station might miss or mischaracterize. Supplementary analyses in the paper examined the distribution of fog-affected observations by cloud cover, cloud base height, runway visual range, and surface pressure, along with satellite composites of notable fog episodes in February 2019 and November 2021, building a multi-layered empirical baseline for the region.

Istanbul is far from alone in facing the forecasting puzzle of urban fog, and the study situates itself within a growing international literature. Comparable event-based climatologies have been constructed for New York City, Casablanca, Abu Dhabi, Cape Town, Belgrade, Lisbon, Perth, Shanghai Pudong, and airports across South Korea, Turkey’s northeast, and Argentina, each confirming that fog regimes are tightly bound to local geography. Recent work has pushed further, exploring machine learning approaches to low-visibility prediction, Bayesian decision networks for airport fog forecasting, and the dramatic forecast improvements that come from including irrigation effects in numerical weather prediction over northern India. The Istanbul analysis contributes a critical empirical foundation for such efforts in the eastern Mediterranean, where complex topography and competing maritime influences make statistical or machine-learning fog prediction especially dependent on high-quality, mechanism-resolved training data.

The broader significance of the work lies in what it says about fog as an urban boundary-layer phenomenon. In a megacity, the surface is a patchwork of heat-retaining concrete, vegetated hills, cool water bodies, and engineered drainage basins, and the atmosphere within the lowest few hundred meters responds to that patchwork in ways that standard synoptic-scale models struggle to resolve. By demonstrating that fog frequency varies fivefold within a single metropolitan area and that simultaneous city-wide fog is a rarity, the Istanbul study makes a compelling case for high-resolution, station-specific fog forecasting grounded in physical typing rather than raw visibility statistics. For the aviation sector, which loses millions of dollars annually to low-visibility delays worldwide, and for the growing community of researchers developing fog decision support systems, the message from Istanbul is clear: to predict fog in a megacity, one must first understand that the megacity is not a single climate but an archipelago of microclimates, each with its own fog story written in temperature, moisture, wind, and terrain.

Subject of Research: Long-term fog climatology and physical typing across three airports in the megacity of Istanbul

Article Title: A comparative long-term analysis of fog characteristics in the megacity of Istanbul

Article References: Yoğun, B., Aktaş, C., Bakır, G., Bozdemi̇r, R., Çeli̇k, Ş., & Özdemi̇r, E. T. (2026). A comparative long-term analysis of fog characteristics in the megacity of Istanbul. Theoretical and Applied Climatology, 157(10), Article 685. https://doi.org/10.1007/s00704-026-06617-w

Image Credits: AI Generated

DOI: 10.1007/s00704-026-06617-w

Keywords: fog climatology, Istanbul, boundary-layer meteorology, advection fog, radiation fog, urban heat island, aviation meteorology, METAR observations, urban microclimate, low visibility, Türkiye, Theoretical and Applied Climatology

The study recruited adults aged 18 and older who reported at least one chronic condition and direct experience of follow-up or treatment at a healthcare institution. Data were collected online between January 1 and March 15, 2026, using a self-administered structured questionnaire covering sociodemographic characteristics, healthcare access indicators, and an 18-item Turkish patient satisfaction scale. Rather than treating satisfaction as a single undifferentiated feeling, the analysis separated it into three domains: administrative aspects of care, physician-related care, and the service and environment in which care is delivered. This decomposition proved to be the study’s most revealing analytical move.

The headline numbers tell a story of qualified contentment with clear weak points. The mean overall satisfaction score was 3.43 on a scale with a standard deviation of 0.66. Physician-related satisfaction scored highest, at 3.61 plus or minus 0.75, while service and environment-related satisfaction lagged furthest behind at 3.24 plus or minus 0.72. In other words, patients in İstanbul rated the interpersonal, face-to-face quality of their medical encounters more generously than the organizational shell surrounding those encounters—the scheduling, the waiting, the physical setting, and the flow of services.

Before drawing any conclusions from these scores, the study put its measurement instrument through a demanding statistical vetting. The overall scale showed high internal consistency, with a Cronbach’s alpha of 0.95, indicating that the items hang together as a coherent measure. Exploratory factor analysis supported a three-factor structure corresponding to the administrative, physician-related, and service/environment domains, with a Kaiser-Meyer-Olkin measure of sampling adequacy of 0.946 and a significant Bartlett’s test. These are technical markers, but they matter: they signal that the satisfaction domains the study distinguishes are genuinely distinct dimensions of patient experience rather than statistical artifacts.

The core of the analysis was a robust multivariable regression on complete cases, using HC3 standard errors—a heteroscedasticity-robust estimator that guards against distorted significance when variability differs across respondents. In the primary overall model, which included 445 participants, several access-related variables emerged as significant predictors. Higher appointment waiting category was associated with lower satisfaction, with a coefficient of minus 0.09 and a p-value of 0.014. The direction is intuitive but the quantification is valuable: each step up the waiting-time ladder erodes how patients evaluate their care, independent of the other factors in the model.

Institutional context also mattered. Patients who used private hospitals reported higher satisfaction than those who used state hospitals, with a coefficient of 0.19 and a p-value of 0.013. Meanwhile, relying on public transport rather than a private vehicle was associated with lower satisfaction, at a coefficient of minus 0.21 and a p-value of 0.004. Travel time told a similar story: longer journeys were inversely associated with satisfaction, with a coefficient of minus 0.13 and a p-value of 0.048. Intriguingly, log-transformed distance showed a positive conditional association with satisfaction—a coefficient of 0.16 and a p-value of 0.011—suggesting that once travel time and transport mode are held constant, the raw geographic distance itself does not simply translate into worse experiences, a nuance that complicates any simplistic assumption that closer is always better.

Read together, these coefficients sketch a hierarchy of burden. What corrodes satisfaction most reliably is not the kilometers between home and clinic but the accumulated friction of the journey: the wait for an appointment, the dependence on public transit, and the time spent traveling. For people managing chronic conditions, who typically attend outpatient facilities repeatedly over years, this friction compounds. A patient with diabetes or hypertension who must navigate crowded buses and long appointment queues for every routine check-up is having a fundamentally different service experience from one who drives directly to a private hospital, even if the clinical encounter itself is comparable.

To test whether these patterns were fragile artifacts of missing data, the author conducted a multiple-imputation sensitivity analysis, a technique that fills in plausible values for missing responses across repeated simulated datasets and checks whether conclusions hold. The stability of the findings across this analysis strengthens confidence that the associations are not driven by which respondents happened to answer every question. The study also employed cluster analysis, which identified three distinct satisfaction profiles among the respondents—evidence that outpatient experience in this population is not evenly distributed but clusters into recognizable patterns, likely reflecting different combinations of access conditions and institutional settings.

The study’s conclusions are carefully framed. Patient satisfaction among adults with chronic conditions, the author writes, was associated with both interpersonal care and the organizational experience of accessing services. Appointment waiting, transport conditions, travel burden, and institutional context differentiated the outpatient experience, while physician-related evaluations remained comparatively favorable. This asymmetry is arguably the most policy-relevant finding: the component of care that health systems invest most heavily in training—the clinical encounter—is already the best-rated, while the surrounding infrastructure of access is where dissatisfaction concentrates.

For a megacity like İstanbul, where geography, traffic, and a mixed public-private hospital landscape shape daily life, the implications extend beyond patient surveys. The findings suggest that interventions targeting waiting times, transport accessibility, and the organization of outpatient services could shift satisfaction even without changes in clinical practice. They also highlight a measurement lesson for health services research worldwide: satisfaction scales that collapse everything into a single number risk masking the very dimensions—administrative friction and environmental quality—where improvement is most actionable. As health systems everywhere grapple with aging populations and rising chronic disease, this İstanbul study is a reminder that the road to the clinic, and the wait before it, are part of the medicine.

Subject of Research: Associations between healthcare access conditions and outpatient satisfaction among adults with chronic conditions in İstanbul

Article Title: Access, institutional context, and outpatient satisfaction among adults with chronic conditions in İstanbul: a cross-sectional study

Article References: Sönmez, K. (2026). Access, institutional context, and outpatient satisfaction among adults with chronic conditions in İstanbul: a cross-sectional study. BMC Health Services Research. https://doi.org/10.1186/s12913-026-15689-3

Image Credits: AI Generated

DOI: 10.1186/s12913-026-15689-3

Keywords: patient satisfaction, chronic disease, healthcare access, appointment waiting time, transport burden, outpatient care, İstanbul, health services research, private hospitals, public transport, cross-sectional study, Türkiye

The site could hardly be more charged. It sits at the confluence of the Kurbağalıdere stream and the Bosphorus strait, where centuries of urban encroachment have progressively channeled and enclosed a once-significant natural waterway. Kadıköy, one of Istanbul’s oldest continuously inhabited districts—ancient Chalcedon on the Anatolian shore—faces the classic pressures of rapid densification: shrinking permeable green surface, congested thoroughfares, retreating public space, and civic administrative functions scattered across multiple buildings. The proposal reinterprets these pressures not as constraints but as catalysts for urban regeneration, aligning with a global shift from property-led redevelopment toward regenerative, community-centered approaches.

The study’s most striking element is the Yeşil Yapı Kabuğu, or Green Building Shell: a vegetated roofscape of approximately 21,650 square meters that folds the planned green corridor of the Kurbağalıdere across the building’s entire programmatic mass. Functionally, the shell operates as both envelope and public terrain, providing rainwater management, thermal insulation, and biodiversity support—benefits well documented in the green-roof literature, from stormwater attenuation to urban heat island mitigation. Crucially, the entire site remains open to public use without institutional authorization or security screening, returning to citizens a public footprint equal to the building’s structural mass. It is a form of architectural compensation: a park placed on top of city hall.

The roofscape is not an arbitrary gesture but a morphology shaped by an integrated reading of site conditions—Bosphorus viewsheds, the stream corridor’s geometry, topographic gradients, adjacent rooflines, and a planned metro station at the site’s southern edge. The shell resolves into three interlocking figures. The Yamaç, or Slope, continues the green roof over the future metro station, ascending gently toward the water and mediating between ground-level ecology and elevated terrain. The Kent Terası, or Urban Terrace, hovers above the Presidential section as a contemplative civic balcony, echoing democratic precedents such as the Reichstag dome, where the public is placed in direct visual relation to the spaces of governance. The Şehir Manzaralı Tepe, or City-View Hill, rises above the surrounding rooflines as a navigational landmark and symbolic summit framing the Istanbul skyline.

Connectivity is the third structural principle of the study’s tripartite analytical framework—conceptual emergence, morphological structure, and urban connectivity—which the author, architect Günay Erdem, applies to interpret the competition entry. The building extends the Kıyı Gezinti Promenadı, the coastal promenade, by roughly 650 meters directly across its accessible roof, drawing pedestrian movement from the Bosphorus shoreline along the Kurbağalıdere banks and culminating on the roofscape itself. This dissolves the conventional boundary between architecture and public infrastructure: the building becomes simultaneously a passage, a platform, and a destination, anchoring itself within the district’s pedestrian and ecological networks.

Inside, the proposal departs equally sharply from municipal convention. The organizing device is the Belediye Hizmetleri Sokağı, the Municipal Services Street—a multi-level, light-filled interior axis around which all public-facing functions are arranged. Amphitheater seating, planted pockets, and gallery voids connect to mezzanine levels housing municipal directorates in open-plan, glazed offices. The spatial logic draws on the philosophy of Jan Gehl’s ‘life between buildings’ and on precedents such as Norman Foster’s Reichstag dome, where architecture is deliberately deployed to render governance legible. Transparency here is not merely symbolic: the physical layout allows citizens to see and navigate the structure of municipal services, reducing the distance between government and governed, while the open-plan mezzanines are designed for reconfiguration as administrative models evolve.

Two programmatic innovations push the building toward what the study terms a civic ecosystem. The Municipal Services Development Center reconfigures the traditional library into a hybrid civic laboratory, pairing the library with the Kent Konseyi—city council—so that citizens, particularly young people, can observe, critique, and co-develop municipal services through co-design workshops, real-time service performance dashboards, and structured dialogue with planning departments. The Municipal Services Exhibition Square adds a public venue for festivals, exhibitions, and civic celebrations, where departments can display initiatives and cultivate institutional accountability. The study is candid about the limits of spatial design: openness does not automatically generate engagement, and institutions may resist the cultural shift from service delivery toward co-governance unless participation is backed by frameworks giving citizen input substantive consequence.

The mobility strategy reinforces the ecological and civic logic. Two main pedestrian access points—a northern entrance beneath the shell’s highest point linking to a tramway station, and a southern entrance carved between the Slope and the Presidential wing serving metro, Metrobüs, and commuter rail—channel multimodal flows through the building. Vehicular access is confined to a single southwestern point, with four basement parking levels conceived as a transitional, residual provision while the project’s aspirational modal split prioritizes walking, cycling, and transit. This transit-oriented approach protects surface continuity, reduces heat island effects, and positions the civic institution as a node in the district’s mobility network rather than a traffic generator.

Placed against six international precedents—the High Line, Cheonggyecheon, the Oodi Central Library, Seoul Innovation Park among them—the Kadıköy proposal’s contribution becomes clear. Linear green infrastructure and stream restorations have transformed cities, and civic buildings like Oodi have transcended administrative function, but no precedent in the comparative set fuses vegetated envelope, ecological corridor restoration, and spatialized governance transparency within a single operating municipal institution. The study also distinguishes its methodological position: rather than algorithmic, simulation-driven optimization, the form emerges from a qualitatively informed, context-responsive synthesis of site data, open to future quantitative validation through energy, microclimate, stormwater, and pedestrian-flow modeling.

The implications extend well beyond Istanbul. The core strategies—accessible green roofscape as public terrain, a transparent internal civic street, and participatory governance infrastructure embedded in an institutional building—respond to conditions shared across densifying metropolitan districts in Türkiye, the Middle East, Southern Europe, and Asia: green space deficits, institutions retreating from public life, growing multimodal mobility demand, and the need for long-term institutional adaptability. As a testbed for what the study calls eco-civic urbanism, the unbuilt Kadıköy proposal suggests that the 21st-century city hall may be less a container of administration than an active facilitator of regenerative, inclusive, and participatory urban life—with the evidence base for that ambition awaiting the empirical tests of construction, post-occupancy evaluation, and comparative study that the research identifies as its next frontier.

Subject of Research: Eco-civic architectural design for urban regeneration and participatory municipal governance in Istanbul's Kadıköy district

Article Title: An integrated architectural approach to urban regeneration and public service enhancement at the Kadıköy municipality building

Article References: An integrated architectural approach to urban regeneration and public service enhancement at the Kadıköy municipality building. (n.d.). https://doi.org/10.1007/s44327-026-00372-3

Image Credits: AI Generated

DOI: 10.1007/s44327-026-00372-3

Keywords: Kadıköy, Istanbul, green infrastructure, urban regeneration, biophilic urbanism, civic architecture, participatory governance, green roof, morphology, transit-oriented development, municipal building, design research