Nevin Manimala

JMIR Form Res. 2025 Sep 5;9:e71570. doi: 10.2196/71570.

ABSTRACT

BACKGROUND: Measurement-based care (MBC), including remote MBC, is increasingly being considered or implemented for mental health treatment and outcomes monitoring in routine clinical care. However, little is known about the health equity implications in real-world practice or the impact on patient-provider relationships in lower-resource systems that offer mental health treatment for diverse patients.

OBJECTIVE: This hypothesis-generating study examined the drivers of MBC implementation outcomes, the implications for health equity, and the impact of MBC on therapeutic alliance (TA). The study was conducted 1 year after the implementation of remote MBC at 3 outpatient adult clinics in a diverse, safety-net health system.

METHODS: This explanatory sequential mixed methods study used quantitative surveys and qualitative focus groups with mental health care providers. Repeated surveys were first used to understand mental health care provider experiences over a 6-month period, at least 1 year after MBC implementation. Surveys were analyzed to refine focus group prompts. Six mental health providers participated in repeated surveys over 6 months, after which the same 6 providers and 1 additional mental health provider took part in focus groups.

RESULTS: Surveys revealed stable acceptability and utility ratings, concerns that MBC was not equally benefiting patients, little endorsement that MBC improved TA, and slightly decreasing feasibility scores. In focus groups, mental health care providers shared concerns about the acceptability, appropriateness, feasibility, and equity of processes for collecting MBC data. These providers had less first-hand experience with sharing and acting upon the data but still voiced concerns about the processes for doing so. TA both impacted and was impacted by MBC in positive and negative ways. The potential drivers of the findings are discussed using qualitative data.

CONCLUSIONS: More than 1 year after the implementation of remote MBC for mental health, mental health care providers had enduring concerns about its implications for health equity as well as its bidirectional relationship with TA. These findings suggest that further study is needed to identify system-level strategies to mitigate potential negative effects of real-world MBC implementations on health equity, particularly in low-resource settings with diverse populations.

PMID:40911865 | DOI:10.2196/71570

JMIR Form Res. 2025 Sep 5;9:e67822. doi: 10.2196/67822.

ABSTRACT

BACKGROUND: Residency is a critical period in a physician’s training, characterized by significant physical, cognitive, and emotional demands that make residents highly susceptible to stress and associated negative health outcomes. While physiological signals such as heart rate have been explored as potential biomarkers of stress, their predictive utility in high-stress environments such as the intensive care unit (ICU) remains inconclusive, especially when factoring in atypical events that can further exacerbate resident stress levels.

OBJECTIVE: This study aimed to investigate the relationship between daily average heart rate (AHR) and perceived stress among ICU residents and examine the moderating effect of atypical events on this relationship.

METHODS: The TILES (Tracking Individual Performance With Sensors)-2019 dataset collected longitudinal data from 44 ICU residents who provided daily self-reported stress ratings and wore a Fitbit device to track physiological data over a 3-week period. The main predictor variables were AHR and the occurrence of atypical events (both work and life related and daily hassles). The primary outcome was the level of perceived stress measured on a 7-point Likert scale. Linear mixed models were used to analyze the relationship between AHR and stress, accounting for within-subject and between-subject variance. Interaction effects between AHR and atypical events were also examined.

RESULTS: The analysis revealed a significant positive association between AHR and perceived stress (β=0.032; P=.04) on standard days. However, this relationship was attenuated by the presence of negative atypical events (β=-0.076; P=.02). We further analyzed whether the severity of negative atypical events had an additional moderating effect but found no statistical significance.

CONCLUSIONS: AHR is a potential physiological marker for perceived stress in ICU residents, but its effect is moderated by negative atypical events. Future research should replicate these findings in more diverse cohorts, assess their generalizability to broader populations, and control for additional confounding variables. Incorporating negative atypical events into stress assessment could lead to more accurate and context-sensitive interpretations of physiological data.

PMID:40911858 | DOI:10.2196/67822

Langmuir. 2025 Sep 5. doi: 10.1021/acs.langmuir.5c02814. Online ahead of print.

ABSTRACT

In engineering applications where extreme environmental conditions are becoming increasingly prevalent, the dynamic behavior of liquid droplets on solid surfaces plays a vital role in determining system efficiency and reliability. Particularly in scenarios such as anti-icing, anticorrosion, and self-cleaning, the fabrication of micro/nanostructured surfaces with exceptional hydrophobic properties has emerged as a critical strategy. However, constrained by the technical limitations of current experimental equipment in microscale observation and the capture of transient droplet impact processes, the influence mechanism of statistical roughness parameters (skewness and kurtosis) on droplet bouncing remains underexplored. This study develops a rough surface model with controllable skewness and kurtosis using Fast Fourier Transform (FFT) and Pearson distribution transformation. The roughness model is applied as a boundary condition in a gas-liquid two-phase computational framework. Additionally, an equivalent analytical expression is introduced in CFD-Post to quantitatively extract the contact volume fraction during the spreading phase. This approach enables a systematic investigation of how statistical surface features affect droplet spreading, retraction, and detachment. Results show that, compared to a smooth surface, roughness reduces droplet contact time by up to 16.15%. Except in cases where skewness is zero and kurtosis exceeds 3, an inverse correlation is found between contact volume fraction and contact time for most parameter combinations, indicating that energy dissipation is mainly governed by the pinning effect of sharp asperities. When parameters reach extreme values, rebound is fully suppressed and spreading diminishes significantly. In contrast, kurtosis between 3 and 3.5 and skewness around ±0.2 enhance bouncing. These findings provide a theoretical basis and quantitative reference for optimizing hydrophobic microtexture design and surface postprocessing.

PMID:40911855 | DOI:10.1021/acs.langmuir.5c02814

Ann Plast Surg. 2025 Sep 1;95(3S Suppl 1):S21-S28. doi: 10.1097/SAP.0000000000004459.

ABSTRACT

BACKGROUND: Loss of breast sensation following mastectomy and reconstruction significantly impacts quality of life, influencing body image, intimacy, and overall emotional well-being. Despite advances in reconstructive techniques, sensory outcomes remain inconsistent, limiting broader clinical adoption of reinnervation strategies. This educational review synthesizes the current scope of sensory restoration in breast reconstruction, examining approaches to reinnervation, sensory outcome measures, and management of patient expectations.

METHODS: The existing literature on breast reconstruction was reviewed along with evidence on nerve repair more generally to evaluate current microsurgical techniques and identify research gaps. Data extracted included quantitative outcomes, such as Semmes-Weinstein monofilament testing and 2-point discrimination, as well as qualitative or patient-reported outcome measures like BREAST-Q or VMP-B scores. Statistical analyses were performed using R software version 4.4.1.

RESULTS: Innervated deep inferior epigastric perforator (DIEP) flaps and targeted nerve grafting serve as promising techniques, achieving improved tactile recovery in both objective and qualitative measures. However, variability in long-term recovery, the diminishing returns of meaningful recovery in longer nerve grafts (R2 = 0.986), and their impact on quality-of-life metrics remain underexplored. Moreover, the inconsistent sensory outcomes heighten the need for psychosocial support to manage patient expectations.

CONCLUSIONS: Longitudinal studies emphasizing innovative grafting strategies and integration of emerging technologies including bioengineered nerve conduits and regenerative therapies offer exciting opportunities to enhance sensory recovery. Advancing sensory restoration in reconstructive breast surgery requires a patient-centered approach to inform surgical practice by aligning clinical enthusiasm with robust evidence, ensuring meaningful and rigorous improvements in functional and emotional outcomes.

PMID:40911830 | DOI:10.1097/SAP.0000000000004459

Ann Plast Surg. 2025 Sep 1;95(3S Suppl 1):S2-S5. doi: 10.1097/SAP.0000000000004473.

ABSTRACT

BACKGROUND: Mandibular fractures are the most common facial fractures treated in the emergency setting, with significant variability in operative management across surgical specialties. Plastic and reconstructive surgery (PRS), otolaryngology (ENT), and oral and maxillofacial surgery (OMFS) each approach mandibular fracture repair with different philosophies, particularly regarding tooth extraction within the fracture line. However, few studies directly compare these practices.

OBJECTIVE: This study assessed differences in operative techniques, specifically tooth extraction and fixation strategies, across PRS, ENT, and OMFS in the treatment of isolated mandibular fractures at a level 1 trauma center.

METHODS: Following institutional review board approval, a retrospective chart review was conducted at Regional One Health from May 2019 to May 2020. Ninety patients with isolated mandibular fractures were identified using relevant Current Procedural Terminology codes. Statistical analysis included χ2 and analysis of variance testing with significance set at P < 0.05.

RESULTS: Among 90 patients (80% male; mean age, 33 years), assault was the leading cause of injury. These cases were managed by 3 specialties: ENT (24 patients), PRS (24 patients), and OMFS (42 patients). All 3 specialties utilized MMF and ORIF with similar frequency. However, OMFS demonstrated significantly higher tooth extraction rates (50%) compared with ENT (8%) and PRS (4%) (P < 0.00005). ENT had the longest average time to surgery (9 days) compared with PRS (2 days) and OMFS (1 day). No significant differences were observed in reoperation rates, operative duration, or hospital stay among the specialties.

CONCLUSIONS: Significant differences were identified in the frequency of surgical tooth extractions and time to operation for mandibular fracture repairs across different specialties. These differences may impact resource allocation and patient outcomes. Further research is needed to explore the origins of these variations and their long-term effects.

PMID:40911827 | DOI:10.1097/SAP.0000000000004473

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