Tag: nevin manimala

Endocr Regul. 2024 Aug 9;58(1):158-167. doi: 10.2478/enr-2024-0018. Print 2024 Jan 1.

ABSTRACT

Objective. The hormonal balance is dependent on the internal and external stimuli. The baseline cortisol (BC) and thyroid stimulating hormone (TSH) levels have been observed to vary and have a predictive value in critical illness settings. Few reports have studied their variation in non-severe acute illness. The present study aims to describe the variation of BC and TSH levels and to determine the factors influencing BC and TSH levels in patients admitted with non-severe acute illness. Patients and Methods. This is a cross-sectional study of patients admitted to Infectious Diseases and Endocrinology units at the Department of Endocrinology-Diabetology and Internal Medicine at Tahar Sfar University Hospital between March 15th and September 15th, 2020. BC and TSH levels were obtained during the hospitalization. Results. A total of 143 patients were included in this study with 75 presenting with infection. All infections were community-acquired and predominantly non-severe. The BC levels were higher in patients with infection (p=0.004), especially those admitted via the emergency department (p=0.009) with a fever (p=0.015). The BC positively correlated with the temperature (p=0.002, r’=0.350), CRP levels (p=0.002, r’=0.355), neutrophil to lymphocyte ratio (p=0.045, r’=0.235), and SOFA score (p=0.023, r’=0.262). On the other hand, TSH levels were comparable in the presence of infection (p=0.400). TSH levels did not correlate with the fever, the severity of infection, or inflammation biomarkers. Both BC and TSH did not predict unfavorable outcomes in non-severe infected patients. Conclusion. In patients admitted with critical acute infections, the BC levels seem to indicate a relatively more severe infectious state. On the other hand, TSH levels did not show significant variations in these patients.

PMID:39121474 | DOI:10.2478/enr-2024-0018

JMIR Res Protoc. 2024 Aug 9;13:e55558. doi: 10.2196/55558.

ABSTRACT

BACKGROUND: Prepubertal transgender, nonbinary, and gender-diverse (TGD) children (ie, those asserting gender identity, expressing gender-role behavior outside of culturally defined norms for their sex registered at birth, or both) are presenting in greater numbers to pediatric gender clinics across the United States and abroad. A large subset of TGD children experiences gender dysphoria, that is, distress that arises from the incongruence between gender identity and sex registered at birth. A lack of consensus exists regarding care for prepubertal TGD children due, in part, to a dearth of empirical research on longitudinal developmental trajectories of gender identity, role behavior, and gender dysphoria (when present).

OBJECTIVE: The objective of this National Institutes of Health-funded study is to provide evidence to inform clinical care for prepubertal TGD children by establishing a US longitudinal cohort (N=248) of prepubertal TGD children and their caregivers that is followed prospectively at 6-month intervals across 18 months.

METHODS: At each timepoint, clinical and behavioral data are collected via web-based visit from child and caregiver reporters. Latent class analysis, among other methods, is used to identify subgroups and longitudinally characterize the gender identity and gender-role behavior of TGD children. These models will define longitudinal patterns of gender identity stability and characterize the relationship between TGD classes and mental and behavioral health outcomes, including the moderating role of social gender transition (when present), on these associations.

RESULTS: Baseline data collection (N=248) is complete, and the identification of TGD subgroups based on gender identity and expression using latent class analysis is anticipated in 2024. The completion of all 4 waves of data collection is anticipated in July 2024, coinciding with the start of a no-cost study extension period. We anticipate longitudinal analyses to be completed by winter 2024.

CONCLUSIONS: Through a longitudinal observational design, this research involving prepubertal TGD children and their caregivers aims to provide empirical knowledge on gender development in a US sample of TGD children, their mental health symptomology and functioning over time, and how family initiated social gender transition may predict or alleviate mental health symptoms or diagnoses. The research findings have promise for clinicians and families aiming to ensure the best developmental outcome for these children as they develop into adolescents.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/55558.

PMID:39121472 | DOI:10.2196/55558

Interact J Med Res. 2024 Aug 9;13:e56452. doi: 10.2196/56452.

ABSTRACT

BACKGROUND: A common challenge for individuals caring for people with Alzheimer disease and related dementias is managing the behavioral and psychological symptoms of dementia (BPSD). Effective management of BPSD will increase the quality of life of people living with dementia, lessen caregivers’ burden, and lower health care cost.

OBJECTIVE: In this review, we seek to (1) examine how indoor environmental quality parameters pertaining to light, noise, temperature, and humidity are associated with BPSD and how controlling these parameters can help manage these symptoms and (2) identify the current state of knowledge in this area, current gaps in the research, and potential future directions.

METHODS: Searches were conducted in the CINAHL, Embase, MEDLINE, and PsycINFO databases for papers published from January 2007 to February 2024. We searched for studies examining the relationship between indoor environmental quality parameters pertaining to light, noise, temperature, and humidity and BPSD.

RESULTS: A total of 3123 papers were identified in the original search in October 2020. After an additional 2 searches and screening, 38 (0.69%) of the 5476 papers were included. Among the included papers, light was the most studied environmental factor (34/38, 89%), while there were fewer studies (from 5/38, 13% to 11/38, 29%) examining the relationships between other environmental factors and BPSD. Of the 38 studies, 8 (21%) examined multiple indoor environmental quality parameters. Subjective data were the only source of environmental assessments in 6 (16%) of the 38 studies. The findings regarding the relationship between agitation and light therapy are conflicted, while the studies that examined the relationship between BPSD and temperature or humidity are all observational. The results suggest that when the environmental factors are deemed overstimulating or understimulating for an individual with dementia, the behavioral symptoms tend to be exacerbated.

CONCLUSIONS: The findings of this scoping review may inform the design of long-term care units and older adult housing to support aging in place. More research is still needed to better understand the relationship between indoor environmental quality parameters and BPSD, and there is a need for more objective measurements of both the indoor environmental quality parameters and behavioral symptoms. One future direction is to incorporate objective sensing and advanced computational methods in real-time assessments to initiate just-in-time environmental interventions. Better management of BPSD will benefit patients, caregivers, and the health care system.

PMID:39121471 | DOI:10.2196/56452

JMIR Public Health Surveill. 2024 Aug 9;10:e51242. doi: 10.2196/51242.

ABSTRACT

BACKGROUND: The incidence of herpes zoster (HZ) is rapidly increasing, causing both clinical and economic burdens in China. Very little is known about Chinese residents’ HZ vaccine preferences and willingness to pay (WTP) for each vaccination attribute.

OBJECTIVE: This study aims to elicit the preferences of Chinese urban adults (aged 25 years or older) regarding HZ vaccination programs and to calculate WTP for each vaccination attribute.

METHODS: In this study, we interviewed 2864 residents in 9 cities in China. A discrete choice experiment was conducted to investigate the residents’ preferences for HZ vaccination and to predict the uptake rate for different vaccine scenarios. A mixed logit model was used to estimate the preferences and WTP for each attribute. Seven attributes with different levels were included in the experiment, and we divided the coefficients of other attributes by the coefficient of price to measure WTP.

RESULTS: Vaccine effectiveness, protection duration, risk of side effects, place of origin, and cost were proven to influence Chinese adults’ preferences for HZ vaccination. The effectiveness of the HZ vaccine was the attribute that had the most predominant impact on residents’ preferences, followed by protection duration. The residents were willing to pay CN ¥974 (US $145) to increase the vaccine effectiveness from 45% to 90%, and they would barely pay to exchange the vaccination schedule from 2 doses to 1 dose. It is suggested that the expected uptake could be promoted the most (by 20.84%) with an increase in the protection rate from 45% to 90%.

CONCLUSIONS: Chinese urban adults made trade-offs between vaccine effectiveness, protection duration, place of origin, side effects, and cost of HZ vaccination. Vaccine effectiveness was the most important characteristic. The residents have the highest WTP (CN ¥974; US $145) for enhancing the effectiveness of vaccines. To maximize HZ vaccine uptake, health authorities should promote vaccine effectiveness.

PMID:39121469 | DOI:10.2196/51242

J Med Internet Res. 2024 Aug 9;26:e56413. doi: 10.2196/56413.

ABSTRACT

BACKGROUND: Patient complaints are a perennial challenge faced by health care institutions globally, requiring extensive time and effort from health care workers. Despite these efforts, patient dissatisfaction remains high. Recent studies on the use of large language models (LLMs) such as the GPT models developed by OpenAI in the health care sector have shown great promise, with the ability to provide more detailed and empathetic responses as compared to physicians. LLMs could potentially be used in responding to patient complaints to improve patient satisfaction and complaint response time.

OBJECTIVE: This study aims to evaluate the performance of LLMs in addressing patient complaints received by a tertiary health care institution, with the goal of enhancing patient satisfaction.

METHODS: Anonymized patient complaint emails and associated responses from the patient relations department were obtained. ChatGPT-4.0 (OpenAI, Inc) was provided with the same complaint email and tasked to generate a response. The complaints and the respective responses were uploaded onto a web-based questionnaire. Respondents were asked to rate both responses on a 10-point Likert scale for 4 items: appropriateness, completeness, empathy, and satisfaction. Participants were also asked to choose a preferred response at the end of each scenario.

RESULTS: There was a total of 188 respondents, of which 115 (61.2%) were health care workers. A majority of the respondents, including both health care and non-health care workers, preferred replies from ChatGPT (n=164, 87.2% to n=183, 97.3%). GPT-4.0 responses were rated higher in all 4 assessed items with all median scores of 8 (IQR 7-9) compared to human responses (appropriateness 5, IQR 3-7; empathy 4, IQR 3-6; quality 5, IQR 3-6; satisfaction 5, IQR 3-6; P<.001) and had higher average word counts as compared to human responses (238 vs 76 words). Regression analyses showed that a higher word count was a statistically significant predictor of higher score in all 4 items, with every 1-word increment resulting in an increase in scores of between 0.015 and 0.019 (all P<.001). However, on subgroup analysis by authorship, this only held true for responses written by patient relations department staff and not those generated by ChatGPT which received consistently high scores irrespective of response length.

CONCLUSIONS: This study provides significant evidence supporting the effectiveness of LLMs in resolution of patient complaints. ChatGPT demonstrated superiority in terms of response appropriateness, empathy, quality, and overall satisfaction when compared against actual human responses to patient complaints. Future research can be done to measure the degree of improvement that artificial intelligence generated responses can bring in terms of time savings, cost-effectiveness, patient satisfaction, and stress reduction for the health care system.

PMID:39121468 | DOI:10.2196/56413

J Med Internet Res. 2024 Aug 9;26:e58950. doi: 10.2196/58950.

ABSTRACT

BACKGROUND: Digital health research plays a vital role in advancing equitable health care. The diversity of research teams is thereby instrumental in capturing societal challenges, increasing productivity, and reducing bias in algorithms. Despite its importance, the gender distribution within digital health authorship remains largely unexplored.

OBJECTIVE: This study aimed to investigate the gender distribution among first and last authors in digital health research, thereby identifying predicting factors of female authorship.

METHODS: This bibliometric analysis examined the gender distribution across 59,980 publications from 1999 to 2023, spanning 42 digital health journals indexed in the Web of Science. To identify strategies ensuring equality in research, a detailed comparison of gender representation in JMIR journals was conducted within the field, as well as against a matched sample. Two-tailed Welch 2-sample t tests, Wilcoxon rank sum tests, and chi-square tests were used to assess differences. In addition, odds ratios were calculated to identify predictors of female authorship.

RESULTS: The analysis revealed that 37% of first authors and 30% of last authors in digital health were female. JMIR journals demonstrated a higher representation, with 49% of first authors and 38% of last authors being female, yielding odds ratios of 1.96 (95% CI 1.90-2.03; P<.001) and 1.78 (95% CI 1.71-1.84; P<.001), respectively. Since 2008, JMIR journals have consistently featured a greater proportion of female first authors than male counterparts. Other factors that predicted female authorship included having female authors in other relevant positions and gender discordance, given the higher rate of male last authors in the field.

CONCLUSIONS: There was an evident shift toward gender parity across publications in digital health, particularly from the publisher JMIR Publications. The specialized focus of its sister journals, equitable editorial policies, and transparency in the review process might contribute to these achievements. Further research is imperative to establish causality, enabling the replication of these successful strategies across other scientific fields to bridge the gender gap in digital health effectively.

PMID:39121467 | DOI:10.2196/58950

J Public Health Manag Pract. 2024 Aug 9. doi: 10.1097/PHH.0000000000001985. Online ahead of print.

ABSTRACT

OBJECTIVE: Maintaining a skilled public health workforce is essential but challenging given high turnover and that few staff hold a public health degree. Situating workforce development within existing structures leverages the strengths of different organizations and can build relationships to address public health challenges and health equity. We implemented and evaluated an innovative, sustainable model to deliver an established evidence-based public health (EBPH) training collaboratively among Prevention Research Centers (PRC), local and state health departments, and Public Health Training Centers (PHTC).

DESIGN: Quantitative data: quasi-experimental, 1-group pre-post. Qualitative data: cross-sectional. Data were collected between December 2021 and August 2022.

SETTING: Four US sites, each a partnership between a PRC, local or state health department, and a PHTC.

PARTICIPANTS: Governmental public health staff and representatives from other organizations that implement public health programs in practice settings.

MAIN OUTCOME MEASURES: Course participants completed a pre- and postcourse survey self-rating 14 skills on a 5-point Likert scale. Differences were analyzed using mixed effects linear models. In-depth interviews (n = 15) were conducted with course faculty and partners to understand: (1) resources contributed, (2) barriers and facilitators, (3) benefits and challenges, and (4) resources needed to sustain this model. Interviews were transcribed verbatim, and a thematic analysis identified themes.

RESULTS: Statistically significant increases in all skills were observed from pre- to postcourse (n = 241 at post, 90% response). The skills with the largest increases were understanding economic evaluation enough to inform decision-making (mean change = 1.22, standard error [SE] = 0.05) and developing an action plan (mean change = 1.07, SE = 0.07). Facilitators to delivering the course included having a shared goal of workforce development, existing course curricula, and dedicated funding for delivering the course.

CONCLUSIONS: Collaborative delivery of the EBPH training can ameliorate the effects of high staff turnover, strengthen academic-practice relationships, and promote population-wide health and health equity.

PMID:39121436 | DOI:10.1097/PHH.0000000000001985

Phys Rev Lett. 2024 Jul 26;133(4):047101. doi: 10.1103/PhysRevLett.133.047101.

ABSTRACT

Large deviation theory offers a powerful and general statistical framework to study the asymptotic dynamical properties of rare events. The application of the formalism to concrete experimental situations is, however, often restricted by finite statistics. Data might not suffice to reach the asymptotic regime or judge whether large deviation estimators converge at all. We here experimentally study the large deviation properties of the stochastic work and heat of a levitated nanoparticle subjected to nonequilibrium feedback control. This setting allows us to determine for each quantity the convergence domain of the large deviation estimators using a criterion that does not require the knowledge of the probability distribution. By extracting both the asymptotic exponential decay and the subexponential prefactors, we demonstrate that singular prefactors significantly restrict the convergence characteristics close to the singularity. Our results provide unique insight into the approach to the asymptotic large deviation limit and underscore the pivotal role of singular prefactors.

PMID:39121406 | DOI:10.1103/PhysRevLett.133.047101

Phys Rev Lett. 2024 Jul 26;133(4):046902. doi: 10.1103/PhysRevLett.133.046902.

ABSTRACT

We establish low-temperature resonant inelastic light scattering (RILS) spectroscopy as a tool to probe the formation of a series of moiré bands in twisted WSe_{2} bilayers by accessing collective inter-moiré-band excitations (IMBEs). We observe resonances in RILS spectra at energies in agreement with inter-moiré-band transitions obtained from an ab initio based continuum model. Transitions between the first and second moiré band for a twist angle of about 8° are reported and between the first and the third, and higher bands for a twist of about 3°. The signatures from IMBE for the latter highlight a strong departure from parabolic bands with flat minibands exhibiting very high density of states in accord with theory. These observations allow one to quantify the transition energies at the K point where the states relevant for correlation physics are hosted.

PMID:39121396 | DOI:10.1103/PhysRevLett.133.046902

Medicine (Baltimore). 2024 Aug 9;103(32):e39215. doi: 10.1097/MD.0000000000039215.

ABSTRACT

The relationship between workplace justice and nonfatal occupational accidents in a single-payer healthcare system has rarely been explored. As countries strive to achieve and sustain universal health coverage, healthcare workers’ occupational safety and health require greater concerns. We used the data from a national survey conducted on randomly sampled Taiwanese workers. One hundred forty eight males and 567 females, with a total of 715 healthcare workers aged 20 to 65, were analyzed. The workplace scale consisted of 4 subcomponents, including distributive justice, interpersonal justice, information justice, and procedural justice, and was dichotomized into low and high groups in each dimension. Logistic regression models examined the relationship between workplace justice and self-evaluated occupational accidents among healthcare employees. The prevalence of self-evaluated occupational accidents in healthcare employees was 15.54% and 11.64% for men and women, respectively. After adjusting variables such as sociodemographic variables, physical job demands, shift work status, work contract, and psychological job demands, regression analyses indicated that health employees with lower distributive justice, interpersonal justice, information justice, and procedural justice were significantly associated with self-evaluated occupational accidents both in males and females. Expanding the study to include healthcare systems in different countries could enhance the generalizability of the findings. Offering specific recommendations for policymakers and healthcare administrators to improve workplace justice and reduce occupational accidents.

PMID:39121330 | DOI:10.1097/MD.0000000000039215