Nevin Manimala

JMIR Public Health Surveill. 2025 Sep 5;11:e76708. doi: 10.2196/76708.

ABSTRACT

BACKGROUND: Content creators (CCs), like any other worker, are exposed to various occupational hazards that can affect their physical, mental, and social well-being, with psychosocial and ergonomic risks being particularly relevant. The combination of prolonged work hours, sedentary lifestyles, excessive public scrutiny, and often job insecurity and unpredictability (manifested as continuous connectivity and anticipation of sporadic tasks) presents a significant risk for the development of health issues.

OBJECTIVE: This study reviews the scientific literature to identify the potential pathological processes affecting CCs on social media.

METHODS: The scoping review method was used. Data were obtained from the following bibliographic databases: MEDLINE (via PubMed), Embase, Cochrane Library, PsycINFO, Scopus, Web of Science, and Virtual Health Library. The terms used as descriptors and in the title and abstract fields were “Content Creator” and “Pathologic Processes.” The search was conducted in May 2024. Agreement between authors for paper selection was measured using the Cohen κ coefficient. The documentary quality of the papers was assessed using the STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) questionnaire, and the level of evidence and recommendation grade were determined according to the Scottish Intercollegiate Guidelines Network recommendations. Bias was evaluated using the Risk of Bias in Non-randomized Studies of Exposures (ROBINS-E) tool.

RESULTS: Of the 1522 references retrieved, 6 papers were selected based on the inclusion and exclusion criteria. Of the 6 studies reviewed, 3 were exclusively focused on a single gender. The agreement on the relevance of the selected studies, calculated using the κ index, was 84.9% (P<.01). The study population ranged from a minimum of 6 to a maximum of 1544 participants. The STROBE scores ranged from 81.3% to 96.8%, with a median of 14.9% (IQR 2.1). According to the Scottish Intercollegiate Guidelines Network criteria, this review provided evidence level 2++ with a recommendation grade of B. ROBINS-E highlighted a higher number of biases in Domains 5, 6, and 7. All interventions were based on interviews, either conducted online or via email. Participant activities, as documented in the respective studies, comprised influencer roles (n=2), blogging (n=2), YouTube content creation (n=1), and live streaming (n=1). The design of the reviewed works comprised 4 qualitative studies and 2 mixed methods (qualitative and quantitative) studies. The reported health impacts were diverse, comprising burnout (n=2), anxiety (n=1), co-occurring anxiety and depression (n=1), eating disorder (n=1), chronic pain (n=1), and unspecified mental health issues (n=1). All studies highlighted the necessity for further investigation into potential pathological processes among CCs engaged in social media activities.

CONCLUSIONS: It was found that the most affected area was mental health, as observed in nearly all the reviewed studies. Despite the extensive documentation of mental health impact, it is necessary to identify the risk factors associated with the pathological processes of CCs to prevent the signs and symptoms identified in this literature review.

PMID:40911825 | DOI:10.2196/76708

Issues Ment Health Nurs. 2025 Sep 5:1-11. doi: 10.1080/01612840.2025.2538705. Online ahead of print.

ABSTRACT

Understanding the drivers of seclusion and physical restraint supports the work towards minimising their use in acute mental health units. However, evidence on their most important drivers remains limited and is focused mainly on individual-level features. Employing 249 days of 917 contemporaneous records of nurse de-escalation events in one adult inpatient unit in regional Australia, from January 2019 to March 2020, twenty-three features other than individual demographic, dispositional, and diagnostic factors were extracted. Bivariate statistics and supervised machine learning algorithms for feature selection (i.e. Boruta algorithm) and predictive modelling (i.e. random forest) were applied. Emerging top drivers include incidents in high observation beds, the assessed level of situational aggression before de-escalation, incidents directed towards nurses, verbal de-escalation, and distraction and redirection. These findings elevate the predictive value of contextual and interventional, rather than individual-level, features in understanding the likelihood of restrictive practices.

PMID:40911824 | DOI:10.1080/01612840.2025.2538705

J Med Internet Res. 2025 Sep 5;27:e67174. doi: 10.2196/67174.

ABSTRACT

BACKGROUND: Noncommunicable diseases are the leading cause of death, present economic challenges to health care systems worldwide, and disproportionally affect vulnerable individuals with low socioeconomic status (SES). While digital health interventions (DHIs) offer scalable and cost-effective solutions to promote health literacy and encourage behavior change, key challenges concern how to effectively reach and engage vulnerable individuals. To this end, social media influencers provide a unique opportunity to reach millions, and lasting engagement can be ensured through the design of DHIs in a manner that specifically appeals to low-SES individuals through alignment with their social background.

OBJECTIVE: The objectives of this study were 2-fold: to assess the effectiveness of leveraging influencers to reach vulnerable individuals (as measured via app downloads per stream viewers) and evaluate how the design of a DHI can improve engagement among this group (as measured via completion of the intervention).

METHODS: This study used a cross-sectional, quasi-experimental field design to assess both (1) the effectiveness of influencers in reaching vulnerable individuals and (2) the impact of specific design elements-such as gamification and storytelling-on user engagement using a stress management DHI featuring a slow-paced breathing exercise. In total, 3 differently designed versions of this DHI were developed following a fractional factorial design (StressLess, Breeze, and TragicKingdom). Reach was calculated as the number of downloads per viewers per stream and influencer. Engagement with the DHI was measured via number of conversational turns and milestone and intervention completion rates. Participants’ SES and technology acceptance were evaluated through a postintervention survey. Descriptive statistics, chi-square tests, and ANOVAs were used to examine the effects of the DHI design on reach and engagement metrics.

RESULTS: The recruitment via 8 influencers (total streams=25; total viewers=12,667) generated 220 downloads. The average reach ratio across streams amounted to 16.2% (SD 15.5%), with significant differences between conditions (ꭓ²₂=8.0, P=.02; StressLess: 8.1%, SD 9.3%; Breeze: 14%, SD 10.5%; TragicKingdom: 28.4%, SD 17.6%). The intervention completion rate across all DHI versions amounted to 7.7% (17/220), with no significant differences between conditions (P=.48).

CONCLUSIONS: This work provides the first evidence that recruitment via influencers yields high reach ratios, moving far beyond the reach of traditional social media platforms. Nonetheless, based on the data collected, the ability to leverage such platforms to recruit vulnerable individuals remains unclear. In addition, while engagement with the promoted interventions was initially high, the completion rate of the full breathing exercise was comparably low, indicating that the influencer promotion strategy cannot fully overcome the well-documented adherence barriers in digital health.

PMID:40911352 | DOI:10.2196/67174

J Am Soc Mass Spectrom. 2025 Sep 5. doi: 10.1021/jasms.5c00176. Online ahead of print.

ABSTRACT

Quantifying the similarity between two mass spectra─a known reference mass spectrum and an unidentified sample mass spectrum─is at the heart of compound identification workflows in gas chromatography-mass spectrometry (GC-MS). The reference spectrum most like the sample is assigned as its identification (provided some quantitative similarity threshold is met, e.g., 80%) and thus accurately measuring similarity is essential. Significant research has gone toward developing metrics for this purpose, each of which has attempted to improve upon existing methods by incorporating GC-MS-specific information (e.g., peak ratios or retention times) or adopting various statistical and algorithmic frameworks. While this active development has led to a plethora of similarity metrics with demonstrated value across different contexts, the unfortunate consequence has been confusion surrounding which metric should be used as a global standard. No such metric is currently accepted as the standard method because different metrics have demonstrated optimal performance in different contexts. In this work, we propose an ensemble approach to spectral similarity scoring that combines the collective information from across existing similarity metrics to form an improved, globally representative similarity metric as a step toward establishing a global standard method. The resulting ensemble metrics are evaluated on over 88,000 spectra of varying complexity and demonstrate improved abilities to accurately rank the correct reference spectrum as the top-matching candidate for a sample relative to the rankings generated by individual similarity scores.

PMID:40911348 | DOI:10.1021/jasms.5c00176

Adv Sci (Weinh). 2025 Sep 5:e15732. doi: 10.1002/advs.202415732. Online ahead of print.

ABSTRACT

Early-warning signals of delicate design are used to predict critical transitions in complex systems, which makes it possible to render the systems far away from the catastrophic state by introducing timely interventions. Traditional signals including the dynamical network biomarker (DNB), based on statistical properties such as variance and autocorrelation of nodal dynamics, overlook directional interactions and thus have limitations in capturing underlying mechanisms and simultaneously sustaining robustness against noise perturbations. This study therefore introduces a framework of causal network markers (CNMs) by incorporating causality indicators, which reflect the directional influence between variables. Actually, to detect and identify the tipping points ahead of critical transition, two markers are designed: the causal network marker from Granger causality (CNM-GC), for linear causality, and the causal network marker from transfer entropy (CNM-TE), for non-linear causality, as well as a functional representation of different causality indicators and a clustering technique to verify the system’s dominant group. Through demonstrations using computational benchmark models and real-world datasets of epileptic seizure, the framework of CNMs shows higher predictive power and accuracy than the traditional DNB. It is believed that, due to the versatility and scalability, the CNMs are suitable for comprehensively evaluating the systems. The most possible direction for application includes the identification of tipping points in clinical disease.

PMID:40911335 | DOI:10.1002/advs.202415732

JAMA Health Forum. 2025 Sep 5;6(9):e253076. doi: 10.1001/jamahealthforum.2025.3076.

ABSTRACT

IMPORTANCE: The US Inflation and Reduction Act (IRA) prohibits the Centers for Medicare & Medicaid Services (CMS) from using discriminatory methods such as cost-effectiveness analysis (CEA) that assign lower value to treating sicker and disabled persons. Generalized risk-adjusted cost- effectiveness (GRACE) provides a nondiscriminatory alternative, but the potential impact on health care budgets is unknown.

OBJECTIVE: To compare value-based drug prices based on traditional CEA with those based on IRA-compliant GRACE and assess the implications for health care budgets.

DESIGN AND SETTING: In this economic evaluation, GRACE was implemented using the direct-utility method and estimated the resulting value-based prices and total budget impact. Model inputs were derived from CEAs published by the Institute for Clinical and Economic Review (ICER) between 2014 and 2024. Data from 302 CEA results for pharmaceuticals published across 72 studies were extracted. The final analysis sample consisted of 259 observations (219 treatment-comparator pairs) across 53 distinct diseases, some of which had subgroup results.

MAIN OUTCOMES AND MEASURES: Value-based prices under GRACE and CEA were estimated. A 1-year budget impact was calculated, measured as total drug expenditures using value-based prices assuming a willingness-to-pay threshold of $150 000. The data were analyzed from October 2024 to May 2025.

RESULTS: The mean value-based prices were 7.5% higher under GRACE than under CEA (IQR, -3.9% to 9.1%). Furthermore, compared with traditional CEA, GRACE increased value-based prices for more severe diseases and decreased them for milder diseases. Twenty-four drugs (8 from the top population size quartile) cost less under GRACE; total spending was 3.3% lower under GRACE for these drugs. The remaining 45 drugs (13 from the bottom population size quartile) cost more under GRACE, resulting in 14.7% higher spending for these drugs. Taken together, GRACE increased the total budget by 2%..

CONCLUSIONS AND RELEVANCE: This economic evaluation found that although GRACE does increase value-based prices on average, the net effect on total health care spent is minimal, in part because resources are redistributed toward more severe, less prevalent illnesses.

PMID:40911330 | DOI:10.1001/jamahealthforum.2025.3076

JAMA Health Forum. 2025 Sep 5;6(9):e253020. doi: 10.1001/jamahealthforum.2025.3020.

ABSTRACT

IMPORTANCE: The concentration of poverty and multidimensional disadvantage has been shown to limit access to health care in these communities. There is a growing interest in using area-level socioeconomic indexes to address the unequal geographic distribution of health care resources. However, the association of area-level socioeconomic indexes with access to primary care-a key area in health policy-has not been determined.

OBJECTIVE: To investigate the association of Medicaid primary care utilization with the concentration of poverty and multidimensional disadvantage at the zip code level.

DESIGN, SETTINGS, AND PARTICIPANTS: This cross-sectional study used the 2019 Transformed-Medicaid Statistical Information System to identify variations in primary care utilization among Medicaid and the Children’s Health Insurance Program beneficiaries (age <65 years) by poverty and multidimensional disadvantage levels of their area of residence. Included beneficiaries were enrolled in Medicaid from January 1 to December 31, 2019, and were not dually eligible for Medicare. The zip code-level Social Vulnerability Index (SVI) was used to assess the likelihood of a beneficiary having an annual primary care visit, while controlling for individual beneficiary demographic and health characteristics. An activity-based approach was adopted to classify clinicians billing Medicaid for primary care and to identify primary care visits at federally qualified health centers (FQHCs). SVI results were compared with results using income-based poverty rates alone. Data analysis was performed from May 1, 2023, through February 28, 2025.

EXPOSURE: Zip code-level deciles of the SVI and poverty rates.

MAIN OUTCOMES AND MEASURES: Regression analysis was performed at the beneficiary level, using a binary indicator for having a primary care visit on a set of dummy variables for SVI deciles, controlling for age and sex interactions, disability status, and indicators for having been diagnosed with behavioral health or chronic physical health conditions.

RESULTS: The total population analyzed comprised 34 890 932 Medicaid beneficiaries (<65 years old; 54.2% female and 45.8% male), more than half of whom resided in the top 20% of socially vulnerable zip codes; approximately 33%, in the top 10%; and another 20%, in the ninth decile. Of the total, 68.1% had at least 1 primary care visit in 2019, at either a non-FQHC practice (61.1%) or a FQHC (12.7%). The probability of having a primary care visit was highest for children (age <18 years) but varied substantially by age. Compared to those residing in the first decile of the SVI (least socially vulnerable), beneficiaries in the tenth decile (most socially vulnerable) were 8.9 (95% CI, -9.9 to -7.9) percentage points (pp) less likely to have a primary care visit when not counting FQHC visits, but this increased to 4.7 (95% CI, -5.5 to -3.8) pp less likely when including FQHC visits. Beneficiaries in the tenth decile were 5.9 (95% CI, 4.9 to 6.8) pp more likely to have a FQHC visit than beneficiaries in the first decile. The SVI results identified more beneficiaries with disparities compared to the area-level poverty rate alone.

CONCLUSIONS AND RELEVANCE: The findings of this cross-sectional study suggest that Medicaid policy should focus on addressing geography-based disparities in access to care using new measures to target resources. The multidimensional SVI is likely a useful tool to identify small geographic areas with barriers to accessing adequate health care. The FQHC findings suggest that substantially increasing investments and support for FQHCs would address geographic inequities in access to health care.

PMID:40911326 | DOI:10.1001/jamahealthforum.2025.3020

JAMA Health Forum. 2025 Sep 5;6(9):e253035. doi: 10.1001/jamahealthforum.2025.3035.

ABSTRACT

IMPORTANCE: Access to and quality of care vary substantially by area socioeconomic status. Expanding hospital health information technology (HIT) adoption may help reduce these disparities, given hospitals’ central role in serving underserved populations.

OBJECTIVE: To examine variations in US hospital adoption of telehealth and health information exchange (HIE) functionalities by hospital service area (HSA) socioeconomic deprivation.

DESIGN, SETTING, AND PARTICIPANTS: This cross-sectional study links data from the 2018-2023 American Hospital Association Annual Survey and Information Technology Survey with HSA-level area deprivation index. Nonfederal acute care hospitals with complete data on HIT outcomes, comprising 16 646 observations for the telehealth outcomes and 9218 observations for the HIE outcomes across 6 years, were included. Data were analyzed from February 2024 to February 2025.

EXPOSURES: HSA-level area deprivation index in quartiles.

MAIN OUTCOMES AND MEASURES: Hospital adoption of treatment-stage telehealth and postdischarge telehealth services and HIE infrastructure supporting electronic data query and availability. Descriptive, regression, and Blinder-Oaxaca decomposition analyses and visualized time trends in hospital HIT adoption were used in analyses.

RESULTS: This study included 16 646 hospital-level observations and 9218 observations for health information exchange functionalities. Hospitals in the most socioeconomically deprived HSAs were significantly less likely to adopt HIT compared with those in the least deprived areas (treatment-stage telehealth: marginal effect [ME], -0.03; 95% CI, -0.06 to -0.01; postdischarge telehealth: ME, -0.03; 95% CI, -0.07 to 0.01; electronic data query capability: ME, -0.03; 95% CI, -0.06 to -0.01; electronic data availability: ME, -0.06; 95% CI, -0.11 to -0.01). Year fixed effects indicated significant increases in HIT adoption from 2018 to 2023, regardless of HSA deprivation level. Decomposition analyses showed that differences in hospital bed size, urban/rural location, and accountable care organization participation explained a substantial portion of the disparities by HSA deprivation.

CONCLUSIONS AND RELEVANCE: In this study, hospitals in more socioeconomically disadvantaged HSAs remained likely to adopt telehealth and HIE functionalities. Nevertheless, HIT adoption has grown steadily over time. Accountable care organization participation may support HIT infrastructure and help reduce geographic disparities in adoption and access to care.

PMID:40911325 | DOI:10.1001/jamahealthforum.2025.3035

JAMA Netw Open. 2025 Sep 2;8(9):e2527431. doi: 10.1001/jamanetworkopen.2025.27431.

ABSTRACT

IMPORTANCE: Preterm children face a higher risk of cardiovascular conditions, including hypertension. However, studies have not isolated the associations of prematurity with cardiovascular conditions from the associations of subsequent complications with cardiovascular conditions, especially among those admitted to a neonatal intensive care unit (NICU).

OBJECTIVE: To investigate prospective associations of prematurity and NICU complications with childhood hypertension while accounting for prenatal and perinatal factors.

DESIGN, SETTING, AND PARTICIPANTS: This cohort study analyzed longitudinal data from the Boston Birth Cohort on 2459 infants (695 preterm, 468 with NICU admission) born between January 1, 1999, and December 31, 2014. Statistical analysis was performed from January 1, 1999, to December 31, 2020.

MAIN OUTCOMES AND MEASURES: Children were categorized into 5 subgroups based on preterm birth status, NICU admission, and major complications (sepsis, chronic lung disease, necrotizing enterocolitis, and intraventricular hemorrhage). The primary end point was hypertension (episodic and persistent) per American Academy of Pediatrics guidelines, with elevated blood pressure (BP) and BP percentiles as secondary end points. Modified Poisson and proportional hazards regression were used to determine crude and adjusted relative risks (RRs) and hazard ratios (HRs). Secondary analyses used linear generalized estimating equations to assess repeated BP measurements over time, standardized to population-based BP percentiles.

RESULTS: Of the 2459 infants (695 preterm: mean [SD] gestational age, 33.2 [3.5] weeks; 358 boys [51.5%]; and 1764 full term: mean [SD] gestational age, 39.4 [1.3] weeks; 879 boys [49.7%]) in this study, 468 (19.0%) were admitted to the NICU. The incidence of persistent hypertension was higher among children born preterm compared with those born at full term (25.2% [175 of 695] vs 15.8% [278 of 1764]). Preterm infants and infants admitted to the NICU had a greater risk of developing persistent hypertension compared with full term-born children without NICU admission or neonatal complications, independent of pertinent maternal and infant characteristics. Preterm infants with an NICU stay, both with (adjusted RR, 1.87 [95% CI, 1.19-2.94]) and without (adjusted RR, 1.62 [95% CI, 1.27-2.07]) a neonatal complication, had the greatest risk for persistent hypertension. Cox proportional hazards regression analysis identified preterm infants with an NICU stay, particularly those with a complication, as having the highest risk of developing persistent hypertension (adjusted HR, 2.37 [95% CI, 1.44-3.89]). On average, infants born prematurely without an NICU admission or complication (β, 2.74 percentile points [95% CI, 0.38-5.10 percentile points]) and those born prematurely with an NICU admission but no complications (β, 4.06 percentile points [95% CI, 2.11-6.02 percentile points]) had higher systolic BP percentiles and those born prematurely with an NICU admission but no complications had higher diastolic BP percentiles (β, 4.01 percentile points [95% CI, 2.52-5.49 percentile points]) during follow-up up to 18 years of age.

CONCLUSIONS AND RELEVANCE: This prospective cohort study found incrementally stronger associations for NICU admission, prematurity, and prematurity-related complications with the risk of developing persistent hypertension in childhood. These findings support the need for hypertension screening, coordinated primary and specialist care, and cardiovascular health promotion among children born preterm.

PMID:40911310 | DOI:10.1001/jamanetworkopen.2025.27431

JAMA Netw Open. 2025 Sep 2;8(9):e2530624. doi: 10.1001/jamanetworkopen.2025.30624.

ABSTRACT

IMPORTANCE: Among men with favorable-risk (ie, low-risk or favorable intermediate-risk) prostate cancer, confirmatory testing substantially improves the detection of aggressive cancers that may merit treatment instead of conservative management. Despite guideline recommendations, confirmatory testing is inconsistently used, and more than half of men do not receive it. Value-based interventions and payment incentives may improve care quality by motivating adherence to guideline-concordant care.

OBJECTIVE: To examine the use of confirmatory testing among men with low-risk prostate cancer, after the application of a multifaceted intervention, which included physician education and a payment incentive, sponsored by a commercial payer to support its use.

DESIGN, SETTING, AND PARTICIPANTS: This cohort study used data from the Michigan Urological Surgery Improvement Collaborative on men who received a diagnosis of low-risk prostate cancer between January 1, 2017, and July 1, 2022, with a minimum 6 months of follow-up. Statistical analysis was performed from October 2024 to June 2025.

EXPOSURE: Multifaceted intervention with a payment incentive, applied specifically to men who received a diagnosis of low-risk prostate cancer between April 1, 2018, and May 30, 2019. On meeting the payment incentive’s benchmark (ie, ≥45% of men with low-risk prostate cancer complete confirmatory testing within 6 months of diagnosis), the insurer would distribute enhanced reimbursement on claims covered by commercial preferred provider organization plans.

MAIN OUTCOMES AND MEASURES: Confirmatory testing completion (ie, magnetic resonance imaging before or after diagnostic biopsy, repeat prostate biopsy, or genomics test) relative to the preincentive period among men with low-risk prostate cancer. Secondary analyses examined practices by baseline confirmatory testing completion and proportion of patients with insurance plans covered by the insurer sponsoring the payment incentive.

RESULTS: The study included 6609 patients (median age, 65 years [IQR, 60-70 years]), of whom 72.9% (n = 4818) elected for active surveillance. Confirmatory testing increased between 2017 (44.6% [725 of 1625]) and 2022 (64.3% [774 of 1203]) (P < .001). During the payment incentive period, patients had a 7.5% (95% CI, 0.0%-15.4%; P = .06) increase in the predicted probability of confirmatory testing completion relative to the preincentive period, although this change was not statistically significant (odds ratio, 1.43 [95% CI, 0.99-2.09]; P = .06).

CONCLUSIONS AND RELEVANCE: In this cohort study of men with prostate cancer, confirmatory testing completion improved over the study period. However, the payment incentive was not associated with a robust increase in its use. The results suggest collaboration between payers and physicians has the potential to improve measures of prostate cancer care quality, but also highlight the challenges associated with payment incentives and alternative payment model implementation.

PMID:40911309 | DOI:10.1001/jamanetworkopen.2025.30624