Recruitment and Participation of Black Home Health Care Patients in Speech-Based Cognitive Research: Mixed Methods Feasibility Study
Background: Older Black adults remain underrepresented in dementia research, particularly in studies using speech-based methods for early cognitive assessment. Understanding how to effectively recruit and engage this population in research involving audio-recorded interactions is critical to ensuring equitable inclusion and developing culturally responsive study designs. However, recruiting older Black adults into dementia research remains a significant challenge. Objective: This study assessed the feasibility of recruiting older Black home health care (HHC) patients into speech-based cognitive research and examined the factors influencing participation and participants’ data collection experiences. Methods: We conducted a convergent mixed methods feasibility study using a 4-component recruitment pipeline at a nonprofit HHC agency: (1) patient identification and study introduction, (2) in-home audio-recorded cognitive assessments, (3) follow-up calls, and (4) audio-recorded patient-clinician encounters. Both patients and their corresponding clinicians were included in this study. Eligible participants were Black adults aged 60 years and older receiving HHC services in New York City. Patient demographic and clinical characteristics were compared between those who consented and those who declined using bivariate analysis. Qualitative feedback was gathered through patient questionnaires and clinician semistructured interviews and was analyzed using reflexive thematic analysis. Results: Of 246 patients contacted, 71 (28.9%) provided verbal consent and 60 (24.4%) completed cognitive assessments. Five patients were excluded due to health conditions or severe cognitive impairment, leaving 55 eligible participants. Among these participants, retention remained high across study components, including follow-up calls (48/55, 87.3%) and audio-recorded clinician visits (54/55, 98.2%). Patients who did not consent were more likely to have greater complex medical profiles, including higher pain interference (=.01), need for assistance with medication reading (=.04), and polypharmacy (≥5 medications; =.01), while no significant differences were observed for age, gender, or functional status. Qualitative findings demonstrated high acceptability and feasibility of audio recording. Patients reported strong motivation to participate, positive and engaging experiences, comfort with recording, and minimal disruption to care. Clinicians reported ease of integration into workflow, initial discomfort that diminished over time, minor technical challenges, and perceived benefits for communication and patient engagement. Conclusions: Recruiting Black older adults receiving HHC into speech-based dementia research was feasible and well accepted. Culturally tailored recruitment may enhance equitable participation and guide future research using audio-recorded speech for early cognitive detection.
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Target for Aggressive Prostate Cancer Prevention Identified in Mice
Researchers at Columbia University Irving Medical Center have identified a gene that drives the development of neuroendocrine prostate cancer (NEPC), an aggressive form of the disease. Their study showed that genetic or pharmacological inhibition of Sirtuin 1 prevents the growth of NEPC tumors in mice, laying the groundwork for future clinical studies aimed at developing new treatments for NEPC in humans.
Research lead Cory Abate-Shen, PhD, a professor at Columbia University Vagelos College of Physicians and Surgeons, is co-senior author of the researchers’ published paper in Journal of Experimental Medicine, titled “A forward genetic screen identifies Sirtuin 1 as a driver of neuroendocrine prostate cancer,” in which the team noted, “We demonstrate that expression of Sirt1 promotes NEPC while its silencing or pharmacological inhibition suppresses the NEPC phenotype.”
Prostate cancer is the most common cancer in men, and one in every six men will be affected by prostate cancer in their lifetime, the authors explained. Prostate cancer treatments have been focused on approaches to dampening androgen receptor (AR) signalling, and for men with recurrent or advanced prostate cancer the current standard of care is androgen deprivation therapy (ADT). However, it is well documented that ADT will eventually fail, leading to tumor recurrence and development of the ADT-insensitive aggressive prostate cancer variant, NEPC. “… while ADT initially leads to tumor regression, eventually tumors recur as castration-resistant prostate cancer (CRPC), so called because of its continued reliance on AR even in the absence of androgens,” the team continued.
![Positively stained NEPC markers (top) are lost when Sirt1 is silenced (bottom). [© 2026 Nunes de Almeida et al. Originally published in <em>Journal of Experimental Medicine</em>. https://doi.org/10.1084/jem.20241484]](https://www.genengnews.com/wp-content/uploads/2026/05/Low-Res_Nunes_de_Almeida_et_al_2-146x300.jpg)
The process through which ADT-responsive tumors transition towards NEPC tumors—a phenomenon known as lineage plasticity—remains unknown. “Elucidating the mechanisms governing this process may improve treatment by overcoming plasticity-associated drug resistance,” Abate-Shen added.
For their newly reported study the research team performed a Sleeping Beauty (SB) forwards genetic mutagenesis screen in mice looking for mutations that recurred across multiple independent prostate cancer tumors. They identified 75 candidate NEPC-promoting genes, the most promising of which was Sirtuin 1 (Sirt1). Sirt1 encodes an enzyme with a broad range of functions, including control of gene expression and metabolism.
The group first looked to a human prostate cancer cell line to characterize the role of Sirt1. In these cells, the induction of NEPC produced an increase in the expression of genes predicted to be activated by SIRT1 and a corresponding decrease in those predicted to be downregulated by this protein. Confirming these results, the group found that activation of Sirt1 in cells with low SIRT1 expression levels led to a robust increase in key NEPC markers.
Recapitulating their cell line data, the team found that silencing of Sirt1 profoundly reduced tumor growth in mice with NEPC, indicating that Sirt1 is indeed a promising target for NEPC treatment. They also treated the tumors with the FDA-approved SIRT1-inhibitor, Selisistat, which was originally developed for treatment of Huntington’s disease. Encouragingly, the researchers saw that Selisistat administration significantly reversed the NEPC phenotype. “Functional studies in human prostate cancer cell models and mouse organoid models using gain- and loss-of- function approaches in vitro and in vivo, as well as pharmacological inhibition, demonstrated that one of the top-ranked candidates, Sirt1, promotes NEPC,” they wrote in summary.
![Tumors surgically removed from Sirt1-silenced mice (bottom) are significantly smaller than tumors removed from mice with wild-type Sirt1 expression. [© 2026 Nunes de Almeida et al. Originally published in <em>Journal of Experimental Medicine</em>. https://doi.org/10.1084/jem.20241484]](https://www.genengnews.com/wp-content/uploads/2026/05/Low-Res_Nunes_de_Almeida_et_al_1-300x275.jpg)
“Our findings demonstrate that SIRT1 plays a pivotal role in promoting NEPC, revealing a context-dependent function that extends beyond general tumor growth to the regulation of lineage plasticity and neuroendocrine differentiation,” says Abate-Shen, adding that “this highlights SIRT1 as an attractive and clinically actionable target for lethal prostate cancer that warrants further investigation in future clinical studies.”
In their paper the team concluded, “Overall, our study establishes a generalizable computational and experimental framework that integrates SB mutagenesis with phenotypic, genomic, and transcriptomic analyses to identify novel cancer drivers … Importantly, our data suggest that targeting SIRT1 may suppress or reverse progression toward NEPC.”
The post Target for Aggressive Prostate Cancer Prevention Identified in Mice appeared first on GEN – Genetic Engineering and Biotechnology News.
Biotech exec Jeremy Levin on the industry’s strategic turning point
On this week’s episode of “The Readout LOUD,” we chat with longtime biotech executive Jeremy Levin about his new book, “Biotech in the Balance: Saving a Strategic Industry in an Age of Distrust.” That sounds alarmist, and it is in some respects, but as Levin explains, the book is also a roadmap to a brighter future for the biotech industry.
But first, we recap the week’s biotech news, including an Eli Lilly gene-editing treatment for high cholesterol, a new round of funding for a longevity startup, and a preview of the upcoming ASCO cancer research meeting.
Targeting Metabolic Mechanism Restores Chemotherapy Sensitivity in Ovarian Cancer
Although many cancers can be successfully treated using platinum-based chemotherapies, which work by damaging DNA, a subset avoid cell death by repairing their own DNA. Ovarian cancers are an example. Patients whose tumors are DNA repair proficient historically face poor prognosis and their tumors commonly recur within months.
Now data from a new study done in cells and mice points to a potential metabolic target that could prevent tumor cells from repairing their own DNA, thus overcoming their resistance. The work was done by scientists from The Wistar Institute, Temple University, and their collaborators elsewhere. Details are published in a new Nature paper titled “αKG-mediated carnitine synthesis drives DNA repair via histone acetylation.” In it, they describe a metabolic process that is altered in cancer cells that makes them resistant to DNA-damaging agents. They have also identified a drug that can inhibit the pathway that may offer a strategy for overcoming chemotherapy resistance.
Specifically, the study centers on alpha-ketoglutarate (αKG), a metabolite which accumulates in DNA repair proficient ovarian tumors. First, the scientists confirmed αKG’s role in helping ovarian cancer cells repair DNA and survive chemotherapy treatment. They did this by using a CRISPR-based approach to systematically search for the enzyme that enables αKG to repair DNA.
Previous studies on αKG focused on its role in demethylation of proteins and other molecules. Though the scientific literature pointed towards demethylases as the key enzyme, the scientists focused onTMLHE, an enzyme that initiates the synthesis of carnitine, a molecule often associated with energy metabolism. “Finding TMLHE was the moment I thought, ‘Okay, this is going to be something bigger than what we expected,’” said Katherine Aird, PhD, professor and co-leader of the molecular and cellular oncogenesis program at The Wistar Institute and senior author of the study.
The data indicated that elevated αKG activates TMLHE, which drives carnitine production. Carnitine then carries acetyl groups out of the mitochondria and into the nucleus where they are deposited onto histones. This loosens the DNA-histone complex which allows the cells repair machinery to access and fix DNA damage.
Next the team showed that when TMLHE or carnitine synthesis is blocked, histone acetylation does not occur which prevents the DNA repair machinery from doing its work. In these cases, the cells become significantly more sensitive to DNA-damaging chemotherapies. “The connection between αKG and methylation is well established—that’s what everyone studies,” said Nathaniel Snyder, PhD, associate professor in the Aging + Cardiovascular Discovery Center at Temple University School of Medicine. “What we found is that αKG is also controlling acetylation through a completely separate route, and that route turns out to be essential for DNA repair. That’s a new piece of biology that nobody had described before.”
As part of the study, the scientists tested the effects of mildronate, a carnitine synthesis inhibitor, and cisplatin, a platinum-based DNA-damaging chemotherapy drug. They found that the combination of these treatments reduced the tumor burden in mouse models of ovarian cancer, while neither drug alone produced a significant effect. Additionally, patients with high TMLHE expression in tumor tissue had significantly worse progression-free survival post chemotherapy, and higher serum acetylcarnitine levels at diagnosis correlated with faster disease progression.
That latter finding suggests that it may one day be possible to use a routine blood test for circulating acetylcarnitine to identify patients that are most likely to resist standard platinum-based cancer treatments, and to benefit from a combination therapy.
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Hormone Cell Atlas Maps Body’s Chemical Messengers
An initiative to map hormones in the human body has revealed the breadth and complexity of the endocrine system and could deliver transformative insights into disease for the creation of new therapeutics.
The Hormone Cell Atlas provides a comprehensive framework to explore the impact of these chemical messengers in health and disease, combining a system-level overview with detail at a cellular level.
Its creation incorporates transcriptome-level data from dozens of tissue types and involves the expression of hundreds of hormone and receptor genes in millions of cells and nuclei.
The research, in Science, reveal the distributed and interconnected nature of hormonal regulation, involving a wide repertoire of cell types derived from multiple cell lineages.
These cells show the potential to both synthesize or modulate hormones, with most expressing receptor genes that may integrate signals from multiple hormones.
“These findings have implications not only for understanding physiology and its perturbation in disease, but also for understanding the pleiotropic effects of hormone-based therapies,” reported Lijiang Fei, PhD, from the University of Cambridge, and co-workers.
“For example, expression of GLP1R and GIPR in cardiomyocytes and cardiac pacemaker cells raises the possibility that any cardiovascular benefits or risks of these drugs may arise from direct receptor engagement, not solely from weight loss or improvements in glycemic control.”
Hormones are secreted by endocrine glands and act across tissues and organs to coordinate physiological functions, orchestrating metabolism, growth, reproduction, and other essential physiological processes using tightly regulated synthesis and release.
Inspired by the creation of the Human Cell Atlas, which aims to map all the cells in the human body, Fei and co-workers set out to improve understanding of the synthesis and action of hormones.
Using information from that initiative, the team analyzed the expression of 379 hormone and receptor genes in a transcriptomic dataset comprising 14 million single cells and nuclei across 47 human tissues.
The team mapped the cellular architecture of hormone production and action across diverse tissues and lineages, charted long-range endocrine feedback loops, and localized the expression of genes associated with monogenic endocrine and metabolic disease at cell type resolution across a variety of tissues.
Through this, they created a comprehensive, high-resolution, browsable map that predicted hormone production at cellular resolution.
“The atlas not only recovers classical endocrine axes but also illuminates underappreciated sites of hormone production and action,” the authors pointed out.
“We highlight important principles in endocrine biology, including local modulation of steroidogenic signals in peripheral tissues, specialized vascular-endocrine niches, and the role of adipocytes as dynamic hormone-producing and -sensing cell types.”
They conclude: “This accessible, adaptable resource establishes a dynamic framework for dissecting endocrine physiology and paves the way for mechanistic and physiological studies, which together may deliver transformative insights into human endocrine disease and inform rational drug discovery.”
The post Hormone Cell Atlas Maps Body’s Chemical Messengers appeared first on Inside Precision Medicine.
How a new extraction process could unlock the world’s lithium
Researchers say they’ve found a new way to extract lithium, a crucial metal used in the lithium-ion batteries that power electric vehicles and energy storage arrays. This new technique could be more environmentally friendly and cheaper than existing ones.
The research was published today in Science, and a startup called Rock Zero is working to commercialize the process.
“At scale, we believe this will be the lowest-cost way of sourcing lithium in the world,” says Yet-Ming Chiang, one of the study authors, who is an MIT professor and a serial entrepreneur behind climate tech companies including Form Energy and Addis Energy.
The most economical way to get lithium currently is to extract it from brine, salty water that’s pulled the metal out of rock over the course of millennia. But this technique is geographically limited and currently requires vast tracts of land for massive evaporation pools. The more common tactic is hard-rock mining, where large bodies of ore are blasted apart, cooked at high temperatures, and processed using dangerous chemicals.
The researchers’ new method uses a weak acid to dissolve typically nonreactive silicate minerals. That frees not only the lithium but also other useful materials, including alumina and silica.
The origin story for this research, and the resulting company, came from another startup founded by Chiang, Sublime Systems, which makes cement using electrochemistry.
The team was trying to find a source of highly reactive silica in order to form stronger cement. One way to make reactive materials, which can bond easily with other materials, is to take a nonreactive material, dissolve it, and then allow it to become solid in a more reactive form. It’s not impossible to dissolve silicates, but the best-known way is to use hydrofluoric acid, an extremely dangerous chemical. Other fluorine-containing chemicals are candidates too, but some will produce hydrofluoric acid as a side product during reactions.
Chiang drew inspiration from a previous home renovation project involving glass, which is made of silica. “I was remodeling a shower in Framingham, Massachusetts, about 25 years ago,” he says. “So when we started this project, I remembered that glass etching cream and thought, ‘What’s in that?’”
The glass etching cream he remembered, which can be found on shelves at any craft or home improvement store, uses ammonium fluoride, a weak acid. And the MIT researchers discovered that in the right conditions, it can effectively dissolve silicate minerals without producing hydrofluoric acid in the process.
This chemistry could be useful for any silicate minerals—and there are a lot of them. But spodumene, the mineral that’s often mined for lithium, became a prime first target. (Chiang says a suggestion from Doug Wicks, one of the company’s advisors and a former ARPA-E official, pointed the team in spodumene’s direction.)
ROCK ZERO
Today, a key step in processing spodumene ore is to roast it in a kiln at super-high temperatures. This causes a phase transformation, essentially puffing up the material and making the lithium more accessible.
By avoiding the need to reach these temperatures, you could save on energy costs and potentially reduce carbon emissions as well, says Camden Hunt, one of the authors of the study and the CEO and cofounder of Rock Zero.
Avoiding the kiln could also unlock the ability to use some ores that can’t be roasted properly, Hunt adds. Ore that contains too much iron won’t go through the phase change correctly, instead melting and turning into a glassy material.
The new process relies on simple stirred plastic tanks and takes place at temperatures up to about 95 °C (200 °F). The ammonium fluoride dissolves the silicates, which in earlier experiments allowed nearly all of the lithium inside the spodumene ore to be extracted within a couple of days. The researchers have since cut this time to under 12 hours, says Benjamin Mowbray, first author of the study and the CTO and cofounder of Rock Zero.
The products (after some additional steps to clean them up) are lithium carbonate, which can be used to make batteries; alumina, which can go into a smelter to make aluminum; and cementitious silica, which can be added into concrete. And the acid can be reused in the same loop.
Chiang calls this “nose-to-tail” mining—using every part of the ore provided, like eating every part of a butchered animal.
The researchers are currently working to scale and optimize the process. The tanks in the lab in Cambridge, Massachusetts can handle three kilograms of spodumene concentrate in each batch.
They have also estimated the cost of this process once fully scaled up. Assuming that the ammonium fluoride can be recycled at a high level, they should be able to extract lithium for less than $6,000 per metric ton. (They’ve identified a potential cheap industrial source of the acid as well, as an alternative to recycling it.)
The total cost is projected to be lower than that of other processes used to extract lithium from hard-rock ore today, and it could be competitive with brine.
The team has designed a pilot plant and is looking for space to build it. The plan is to have construction done by the end of 2026 and start operating the facility in 2027. Talks are underway with potential partners in the mining industry.
One difficulty for new players in lithium extraction is the volatility of the market: Prices have seen huge swings in recent years, from a peak in 2022 to lows in late 2024 and a slow climb starting in early 2026.
Rising prices might benefit new players like Rock Zero, but there are many projects that could come online if prices continue to rise, and that could bring the market right back down, says Simon Jowitt, chair of exploration geology at the University of Nevada, Reno. “People are waiting to see what happens with the lithium price,” he says. “It’s a crowded market, and there’s some big players out there.”
And even though batteries are driving up demand for lithium, the market is still relatively small, Jowitt adds: “That means it’s going to be volatile.” New lithium extraction technologies like Rock Zero’s will have to compete with methods used by existing giants, and there’s also the potential that technological alternatives, like sodium-ion batteries that don’t need lithium, could make the market more difficult to navigate, Jowitt says. He also thinks some of the company’s economic estimates could be optimistic.
For its part, Rock Zero’s team hopes not only to scale this technology for lithium, but to use it for other minerals in the future. As Mowbray says, “The Earth’s crust is made of silicates.”
SHIMMER: Routine Clinical Data Processed Into Scalable Disease State Markers
Yes, you have a disease. No, you don’t have a disease.
There is too much complexity to human health for this simplistic, binary method of diagnosis. The phenotypic state of a disease is an ongoing process, while the genotype remains static. Even when it comes to infection, the presence or absence of a pathogen captures little of the entire dynamic biological world inside each of us.
A person’s future development can be predicted with near-certainty by an inherited mutation or chromosomal arrangement, such as cystic fibrosis, Huntington’s disease, and trisomy 21 (Down’s syndrome). Disease development is not an on/off switch. Rather, diseases progress along quantifiable biological spectrums.
The question is, how can that be done in an everyday clinical setting with routine data?
Icahn School of Medicine at Mount Sinai researchers developed a machine learning (ML)-based system that uses routine clinical data to estimate a person’s risk for multiple diseases, potentially revealing hidden illness years before diagnosis.
Published in the Cell Press journal Med, the study demonstrates that SHIMMER stands out due to its use of standard clinical measurements instead of highly specialized data. The practical use of many AI systems in medicine is limited because they require extensive imaging, genomic sequencing, or disease-specific testing. The fact that SHIMMER uses data that is already collected in regular healthcare settings instead could make it easier to implement on a larger scale.
Decoding disease states
Led by Iain S. Forrest, MD, PhD, the research team trained ML models on seven diseases—atrial fibrillation, breast cancer, coronary artery disease (CAD), migraine, rheumatoid arthritis (RA), schizophrenia, and type 2 diabetes (T2D)—using records from the BioMe Biobank in New York and the UK Biobank.
The researchers found that the disease-spectrum scores aligned closely with known risk factors and biological markers. For atrial fibrillation, rising SHIMMER scores tracked with increasing age, obesity, hypertension, and stroke risk. In T2D, the scores rose alongside glucose levels, hemoglobin A1c, triglycerides, and inflammatory markers. CAD scores correlated with smoking, high cholesterol, chronic kidney disease, and established cardiovascular risk calculations.
Importantly, these relationships were not abrupt. Instead, biological changes increased gradually across the spectrum, supporting the idea that disease develops gradually rather than suddenly at diagnosis.
Forrest and colleagues also showed that SHIMMER is capable of identifying disease severity and predicting outcomes. Higher SHIMMER scores were associated with earlier disease onset, more complications, and reduced survival. In CAD, increasing scores tracked with worsening artery blockage, heart failure, arrhythmias, and heart attacks. For RA, higher scores aligned with greater inflammation, worsening anemia, and increased use of immunosuppressive medications.
Some of the strongest findings involved diseases that traditionally lack reliable biomarkers. Schizophrenia, for example, is diagnosed largely through behavioral assessment rather than laboratory testing. However, SHIMMER found obesity, smoking, cannabis use, cardiovascular complications, and poorer survival linked to schizophrenia risk and severity. Spectrum associations were also found in migraine, another condition without biomarkers, including symptom severity and medication use.
Perhaps the most clinically intriguing result was SHIMMER’s ability to flag people who appeared biologically ill despite lacking a formal diagnosis. The researchers identified several people whose routine clinical data strongly resembled known disease profiles despite no diagnosis. One patient with a high T2D SHIMMER score had obesity, hypertension, high glucose, and classic diabetic symptoms but was never diagnosed. Similar patterns appeared for coronary artery disease and rheumatoid arthritis.
In larger undiagnosed populations, elevated SHIMMER scores still predicted abnormal biomarkers and mortality risk. That suggests the system may detect diseases that traditional healthcare pathways miss.
Not a shiny object
The findings challenge the long-standing medical convention of classifying disease in binary terms: either a patient has a condition or does not. The implications could be significant for preventive medicine and population health management. Continuous disease-spectrum scores may help healthcare systems identify high-risk patients earlier and prevent complications.
The researchers envision SHIMMER as an EHR background decision-support tool. Even if they do not meet diagnostic criteria, patients with high scores for diabetes or coronary artery disease may be prioritized for testing, monitoring, or preventive treatment. In that sense, it is complementary to genetic screening.
Still, the work remains a proof of concept rather than a ready-to-deploy clinical tool. The study was retrospective, meaning it analyzed existing records rather than prospectively following patients in real time. The researchers also note concerns about healthcare bias, uneven data quality, and the ethical implications of artificial intelligence in medicine.
Another important limitation is that SHIMMER does not provide definitive diagnoses. Its scores reflect disease burden and biological resemblance rather than calibrated predictions of future illness. Determining how clinicians should act on specific score thresholds will require further study.
The work represents a broader shift in how medicine may conceptualize disease in the AI era. Instead of fixed categories, conditions may increasingly be viewed as dynamic biological trajectories measurable through continuously updated clinical data. If confirmed in future studies, SHIMMER could turn routine medical records into early-warning systems that detect disease before symptoms appear.
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Efficacy of an e-Learning Module on Endocrine Disruptors for Family Medicine Residents: Matched Before-And-After Cohort Study
<strong>Background:</strong> Environmental factors account for 23% of global deaths and 25% of chronic diseases. In France, the Fourth National Environmental Health Plan prioritizes training health professionals in environmental health. Endocrine-disrupting chemicals (EDCs) are chemical substances that interfere with hormonal systems, contributing to a range of health effects. In 2024, the Primary Care and Environmental Health (PCEH) program at the University of Montpellier–Nîmes introduced an innovative e-learning module on EDCs for first-year family medicine residents. <strong>Objective:</strong> This study aimed to evaluate the impact of the PCEH e-learning module on participants’ satisfaction, knowledge, and self-reported behaviors regarding EDCs in household environments. <strong>Methods:</strong> This monocentric, matched before-and-after cohort study included all first-year family medicine residents at the University of Montpellier–Nîmes. The module, developed collaboratively by clinicians and educators, integrated interactive images, artificial intelligence–generated virtual rooms, short educational videos, games, and flash cards. Participants were assessed using pretraining and posttraining questionnaires administered immediately before and after the module. These questionnaires evaluated satisfaction (using a 5-point Likert scale), knowledge (using binary “yes” or “no” questions), and behaviors (using a 5-point Likert scale). Statistical analyses included the McNemar test for paired categorical variables and paired 2-tailed <i>t</i> tests for continuous variables, with a significance threshold set at a <i>P</i> value of less than .05. <strong>Results:</strong> This study aimed to evaluate the impact of an e-learning module on knowledge and behaviors related to endocrine disruptors. Our findings show significant improvements across all measured domains. Of 148 eligible residents, 78 (52.7%) completed both assessments over a 17-day period. Overall satisfaction was high (mean 4.0/5, SD 0.9), with positive ratings for the e-learning format (mean 4.1/5, SD 1.0) and module duration (mean 4.2/5, SD 1.0). Knowledge improved significantly, with a mean 55.56 (SD 13.54) increase in correct identification of EDCs across all substances (<i>P</i><.001). Self-reported behaviors improved by an average of 2.13 points (95% CI 1.71-2.56) on the 5-point scale (<i>P</i><.001), exceeding those reported in previous PCEH modules. Secondary outcomes showed high posttraining identification of at-risk populations and exposure locations, although recognition of some substances (eg, alkylphenols and phenoxyethanol) remained low. <strong>Conclusions:</strong> This innovative e-learning module significantly improved residents’ knowledge and preventive behaviors related to EDCs. These findings support the integration of environmental health training into medical curricula and highlight the potential of scalable e-learning interventions to strengthen preventive competencies in primary care.
Experiences of People With Poorly Controlled Type 2 Diabetes Using Telemonitoring: Qualitative Study Embedded in a Feasibility Trial
Background: Telemonitoring has been shown to improve glycemic control in type 2 diabetes, but the optimal design for effectively integrating self-management education remains unclear. Including patient feedback in the design process can enhance usability, increase engagement, and improve the feasibility and effectiveness of the intervention in real-world settings. Objective: This study aims to explore participants’ experiences and the acceptability of 2 different telemonitoring intervention designs and trial procedures used in a feasibility trial among people with non–insulin-dependent type 2 diabetes. Methods: Using a qualitative research design, semistructured interviews were conducted with participants who had completed the telemonitoring intervention. The interviews were analyzed using the thematic approach outlined by Braun and Clarke. Results: A total of 12 participants were interviewed. Four major themes emerged from the analysis: (1) acceptance of and experience with telemonitoring and devices, (2) structure and flow of the intervention, (3) relationship with and support from health care professionals, and (4) learning to live with diabetes. Participants found the devices easy to use, particularly self-monitoring of blood glucose, which was perceived as highly relevant and informative. Technical challenges were primarily related to the activity tracker and initial device setup. The measurement schedule supported self-management, though some participants found it inflexible and difficult to integrate into daily life. Continuous communication with health care professionals was highly valued and fostered trust. Participants reported increased insight into the relationship between lifestyle behaviors and blood glucose levels, which motivated healthier dietary choices and increased physical activity. Participants described that telemonitoring enhanced their understanding of diabetes and supported their engagement in self-management, although preferences for measurement types and frequency varied. Conclusions: Participants reported overall satisfaction, attributing it to structured monitoring and consultations with health care professionals that supported self-management. Blood glucose, physical activity, and diet were considered the most relevant data types. Tailoring the intervention to user priorities and improving the usability of devices and the intervention structure may increase engagement and motivation. Integrating continuous glucose monitoring may further reduce the burden associated with self-monitoring in future telemonitoring interventions for people with type 2 diabetes.
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