Multilevel Treatment Research Articles

Multilevel analysis of the central-peripheral-target organ pathway: contributing to recovery after peripheral nerve injury.

Peripheral nerve injury is a common neurological condition that often leads to severe functional limitations and disabilities. Research on the pathogenesis of peripheral nerve injury has focused on pathological changes at individual injury sites, neglecting multilevel pathological analysis of the overall nervous system and target organs. This has led to restrictions on current therapeutic approaches. In this paper, we first summarize the potential mechanisms of peripheral nerve injury from a holistic perspective, covering the central nervous system, peripheral nervous system, and target organs. After peripheral nerve injury, the cortical plasticity of the brain is altered due to damage to and regeneration of peripheral nerves; changes such as neuronal apoptosis and axonal demyelination occur in the spinal cord. The nerve will undergo axonal regeneration, activation of Schwann cells, inflammatory response, and vascular system regeneration at the injury site. Corresponding damage to target organs can occur, including skeletal muscle atrophy and sensory receptor disruption. We then provide a brief review of the research advances in therapeutic approaches to peripheral nerve injury. The main current treatments are conducted passively and include physical factor rehabilitation, pharmacological treatments, cell-based therapies, and physical exercise. However, most treatments only partially address the problem and cannot complete the systematic recovery of the entire central nervous system-peripheral nervous system-target organ pathway. Therefore, we should further explore multilevel treatment options that produce effective, long-lasting results, perhaps requiring a combination of passive (traditional) and active (novel) treatment methods to stimulate rehabilitation at the central-peripheral-target organ levels to achieve better functional recovery.

Pharyngeal Manometry and Upper Airway Collapse During Drug-Induced Sleep Endoscopy

Drug-induced sleep endoscopy (DISE) is used to guide therapeutic management of obstructive sleep apnea (OSA), depending on the levels and patterns of pharyngeal collapse. However, the collapsibility of specific pharyngeal sites remains unknown. To assess collapse sites in patients with OSA undergoing DISE and whether number and location are associated with differences in airway collapsibility; and to quantify differences in collapsibility between primary and secondary sites in multilevel collapse. This cohort study assessed adult patients (≥18 years) with OSA undergoing DISE with manometry and positive airway pressure (PAP) titration at a tertiary care center from November 2021 to November 2023. Patients with an AHI score greater than 5 were included; those with less than 1 apnea event during DISE or incorrect catheter placement were excluded. Data were analyzed from September 28, 2022, to March 31, 2024. DISE with manometry and PAP titration. Active pharyngeal critical pressure (Pcrit-A) and pharyngeal opening pressure (PhOP) were used to quantify airway collapsibility, adjusted for covariates (age, sex, race, and body mass index [BMI]). Of 94 screened, 66 patients (mean [SD] age, 57.4 [14.3] years; BMI, 29.2 [3.9]; 51 [77.3%] males) with a mean (SD) apnea-hypopnea index (AHI) of 31.6 (19.0) were included in the analysis. Forty-seven patients (71.2%) had multilevel collapse, 10 (15.2%) had single-level nasopalatal collapse, and 9 (13.6%) had single-level infrapalatal collapse. Groups did not differ in demographic characteristics or established measures of OSA severity. The single-level nasopalatal group had substantially elevated levels of airway collapsibility (Pcrit-A and PhOP covariate adjusted mean, 2.4; 95% CI, 1.1 to 3.8; and 8.2; 95% CI, 6.4 to 9.9 cmH2O) compared to the single-level infrapalatal group (-0.9; 95% CI, -2.4 to 0.5 cmH2O; and 4.9; 95% CI, 3.0 to 6.8 cmH2O, respectively) and similar to the level among the multilevel group (1.3; 95% CI, 0.7 to 2.0; and 8.5; 95% CI, 7.7 to 9.3 cmH2O). The multilevel group had more negative inspiratory pressure (-24.2; 95% CI, -28.1 to -20.2 cmH2O) compared to the single-level nasopalatal group (-9.8; 95% CI, -18.3 to -1.28 cmH2O). In patients with multilevel collapse, airway collapsibility was significantly higher at the primary nasopalatal compared to secondary infrapalatal site (mean difference, 13.7; 95% CI, 11.3 to 16.1 cmH2O). The findings of this cohort study suggest that intervention should target the primary site of pharyngeal collapse, and secondary sites only if they are nearly as collapsible as the primary site. Future work is needed to precisely define the difference in primary and secondary collapsibility that necessitates multilevel treatment.

Nutrition Intervention and Microbiome Modulation in the Management of Breast Cancer.

Breast cancer (BC) is one of the most common cancers worldwide and a leading cause of cancer-related deaths among women. The escalating incidence of BC underscores the necessity of multi-level treatment. BC is a complex and heterogeneous disease involving many genetic, lifestyle, and environmental factors. Growing evidence suggests that nutrition intervention is an evolving effective prevention and treatment strategy for BC. In addition, the human microbiota, particularly the gut microbiota, is now widely recognized as a significant player contributing to health or disease status. It is also associated with the risk and development of BC. This review will focus on nutrition intervention in BC, including dietary patterns, bioactive compounds, and nutrients that affect BC prevention and therapeutic responses in both animal and human studies. Additionally, this paper examines the impacts of these nutrition interventions on modulating the composition and functionality of the gut microbiome, highlighting the microbiome-mediated mechanisms in BC. The combination treatment of nutrition factors and microbes is also discussed. Insights from this review paper emphasize the necessity of comprehensive BC management that focuses on the nutrition-microbiome axis.

DISE with CPAP: a useful procedure to evaluate upper airway collapsibility.

Drug-induced sleep endoscopy (DISE) is commonly performed in patients suffering obstructive sleep apnea (OSA) with continuous positive airway pressure (CPAP) intolerance. We aimed to evaluate the effects of adding CPAP to DISE to provide understanding of the reason of its failure and better guidance in future therapeutic decisions. A retrospective observational descriptive study was conducted on CPAP-intolerant patients with moderate-severe OSA. DISE was used to evaluate upper airway collapsibility, and CPAP was tested to better describe anatomical sites of obstruction and to measure the opening pharyngeal pressure. Sample size consisted of 38 patients with a mean age of 49 ± 9years. Mean BMI was 28.4 ± 2.4kg/m2, mean apnea-hypopnea index (AHI) was 35.4 events per hour ± 20.1, and mean saturation under 90% (TSat90) was 14.5%. In DISE we found a collapse at Velum in 92% of patients, at Oropharyngeal level in 89%, at tongue in 42%, and at epiglottis in 36%. In the subgroup of patients with clinical failure with CPAP, we observed 100% of epiglottic collapse and 50% of tongue obstruction. In this specific population, we recommended personalized surgery and myofunctional therapy. DISE-CPAP is a useful tool to select the treatment that better fits to each patient taking care all information available. It improves our ability to prescribe a multilevel treatment with an exhaustive topographic evaluation of upper airway collapsibility that complements CPAP classic titration, and it can be helpful to distinguish better candidates for surgery, myofunctional therapy or CPAP.

Perioperative and safety outcomes following tissue-sparing posterior cervical fusion to revise a pseudarthrosis: A multicenter retrospective review of 150 cases.

Posterior cervical fusion (PCF) with lateral mass screws is a favorable treatment option to revise a symptomatic pseudarthrosis due to reliable rates of arthrodesis; however, this technique introduces elevated risk for wound infection and hospital readmission. A tissue-sparing PCF approach involving facet fixation instrumentation reduces the rates of postoperative complications while stabilizing the symptomatic level to achieve arthrodesis; however, these outcomes have been limited to small study cohorts from individual surgeons commonly with mixed indications for treatment. One hundred and fifty cases were identified from a retrospective chart review performed by seven surgeons across six sites in the United States. All cases involved PCF revision for a pseudarthrosis at one or more levels from C3 to C7 following anterior cervical discectomy and fusion (ACDF). PCF was performed using a tissue-sparing technique with facet instrumentation. Cases involving additional supplemental fixation such as lateral mass screws, rods, wires, or other hardware were excluded. Demographics, operative notes, postoperative complications, hospital readmission, and subsequent surgical interventions were summarized as an entire cohort and according to the following risk factors: age, sex, number of levels revised, body mass index (BMI), and history of nicotine use. The average age of patients at the time of PCF revision was 55 ± 11 years and 63% were female. The average BMI was 29 ± 6 kg/m2 and 19% reported a history of nicotine use. Postoperative follow-up visits were available with a median of 68 days (interquartile range = 41-209 days) from revision PCF. There were 91 1-level, 49 2-level, 8 3-level, and 2 4±-level PCF revision cases. The mean operative duration was 52 ± 3 min with an estimated blood loss of 14 ± 1.5cc. Participants were discharged an average of 1 ± 0.05 days following surgery. Multilevel treatment resulted in longer procedure times (single = 45 min, multi = 59 min, P = 0.01) but did not impact estimated blood loss (P = 0.94). Total nights in the hospital increased by 0.2 nights with multilevel treatment (P = 0.01). Sex, age, nicotine history, and BMI had no effect on recorded perioperative outcomes. There was one instance of rehospitalization due to deep-vein thrombosis, one instance of persistent pseudarthrosis at the revised level treated with ACDF, and four instances of adjacent segment disease. In patients initially treated with multilevel ACDF, revisions occurred most commonly on the caudal level (48% of revised levels), followed by the cranial (43%), and least often in the middle level (9%). This chart review of perioperative and safety outcomes provides evidence in support of tissue-sparing PCF with facet instrumentation as a treatment for symptomatic pseudarthrosis after ACDF. The most common locations requiring revision were the caudal and cranial levels. Operative duration and estimated blood loss were favorable when compared to open alternatives. There were no instances of postoperative wound infection, and the majority of patients were discharged the day following surgery.

Network pharmacology and molecular dynamic simulation integrated strategy for the screening of active components and mechanisms of phytochemicals from Datura innoxia on Alzheimer and cognitive decline

Alzheimer’s disease (AD) ranks as the most prevalent neurodegenerative disorder with dementia and it accounts for more than 70% of all cases. Despite extensive reporting on the experimental investigation of Datura innoxia (DI) and its phytochemical components in the treatment of AD, the urgent need for elucidation of the principle of multi-mechanism and multi-level treatment of AD remains. In this research, molecular docking and network pharmacology were used to evaluate active compounds and molecular targets of DI for the treatment of AD. The phytochemical compounds of DI were obtained from the Indian Medicinal Plants, Phytochemistry, and Therapeutics (IMPPAT) as well as the Traditional Chinese Medicine System Pharmacology (TCMSP) databases. The screening includes the 28 most abundant components of DI and the Swiss Target Prediction database was used to predict targets of these compounds. The GeneCards database was used to collect AD-related genes. Both DI and AD targets were imported into a Venn diagram, and the 28 overlapped genes were identified as potential DI anti-AD targets. The results showed that Dinoxin B, Meteloidine, Scopoline, and Tropic acid had no effect on AD-related genes. Furthermore, the GO enrichment analysis indicates that DI influences molecular functions and biological processes such as learning or memory and modulation of chemical synaptic transmission as well as the membrane raft and membrane microdomain. The KEGG pathway analysis revealed that the key pathways implicated in DI's anti-AD actions include serotonergic synapse, IL-17 signaling pathway, and AGE-RAGE signaling pathway in diabetic complications. Based on the STRING and Cytoscape network-analysis platforms, the top ten anti-AD core targets include APP, CASP3, IL6, BACE1, IL1B, ACE, PSEN1, GAPDH, GSK3B and ACHE. The molecular docking and molecular dynamic simulation of the top two molecules against the top three target proteins confirmed the strong binding affinity and stability at the docked site. Overall, our findings pave the path for further research into the development and optimization of potential anti-AD agents from DI. Communicated by Ramaswamy H. Sarma

A feasibility randomised waitlist-controlled trial of a personalised multi-level language treatment for people with aphasia: The remote LUNA study.

Stroke survivors with aphasia want to improve their everyday talking (discourse). In current UK practice, 90% of speech and language therapists believe discourse assessment and treatment is part of their role but are hampered by barriers in resources, time and expertise. There is a clinical need for well-articulated discourse assessment and treatments. LUNA is a multi-level treatment targeting words, sentences and discourse macrostructure in personal stories that addresses this clinical need. This study aimed to assess the feasibility and acceptability of LUNA trial procedures in a randomised waitlist-controlled trial; and to evaluate preliminary efficacy. This paper reports a phase II, waitlist-controlled, proof-of-concept feasibility trial. Participants with chronic aphasia (n = 28) were recruited from the community and randomised to an Immediate (n = 14) or Delayed (n = 14) group. LUNA treatment was delivered twice weekly for 10 weeks via the videoconferencing technology, Zoom. Feasibility was assessed in terms of participant recruitment and retention, adherence, missing data, and treatment fidelity. Preliminary treatment efficacy was assessed in terms of between group differences in outcome measures relating to discourse, language, and psychosocial state. The remote LUNA trial was feasible: 85% of those eligible consented to the trial; trial retention was 86%; 87% of treatment sessions were delivered as scheduled, and 79% of participants completed 80%+ of the treatment programme; data was missing only for participants who withdrew; treatment fidelity was high at 92% adherence; and only one clinical outcome measure demonstrated ceiling effects. ANCOVA analysis of the clinical outcome measures revealed group differences with medium and large effect sizes, indicating, improvements in the production of words, sentences, discourse macrostructure, overall language functioning (WAB-R), and psychosocial state (VAMS) following LUNA treatment. For most outcomes measured, similar treatment benefits were suggested in a secondary, non-parametric analysis. Large-scale evaluation of the clinical efficacy and cost-effectiveness of LUNA is warranted and supported by these findings. Clinical trials registration: NCT05847023 (clinical trials.gov).

Ensuring impact of long-acting HIV therapeutics through multi-level treatment research: a view from NIH.

Ensuring impact of long-acting HIV therapeutics through multi-level treatment research: a view from NIH.

Digital health technologies for peripartum depression management among low-socioeconomic populations: perspectives from patients, providers, and social media channels

BackgroundPeripartum Depression (PPD) affects approximately 10–15% of perinatal women in the U.S., with those of low socioeconomic status (low-SES) more likely to develop symptoms. Multilevel treatment barriers including social stigma and not having appropriate access to mental health resources have played a major role in PPD-related disparities. Emerging advances in digital technologies and analytics provide opportunities to identify and address access barriers, knowledge gaps, and engagement issues. However, most market solutions for PPD prevention and management are produced generically without considering the specialized needs of low-SES populations. In this study, we examine and portray the information and technology needs of low-SES women by considering their unique perspectives and providers’ current experiences. We supplement our understanding of women’s needs by harvesting online social discourse in PPD-related forums, which we identify as valuable information resources among these populations.MethodsWe conducted (a) 2 focus groups (n = 9), (b) semi-structured interviews with care providers (n = 9) and low SES women (n = 10), and (c) secondary analysis of online messages (n = 1,424). Qualitative data were inductively analyzed using a grounded theory approach.ResultsA total of 134 open concepts resulted from patient interviews, 185 from provider interviews, and 106 from focus groups. These revealed six core themes for PPD management, including “Use of Technology/Features”, “Access to Care”, and “Pregnancy Education”. Our social media analysis revealed six PPD topics of importance in online messages, including “Physical and Mental Health” (n = 725 messages), and “Social Support” (n = 674).ConclusionOur data triangulation allowed us to analyze PPD information and technology needs at different levels of granularity. Differences between patients and providers included a focus from providers on needing better support from administrative staff, as well as better PPD clinical decision support. Our results can inform future research and development efforts to address PPD health disparities.

Realizing the untapped promise of single-session interventions for eating disorders.

Multilevel treatment barriers prevent up to 80% of individuals experiencing eating disorders (EDs) from accessing care. This treatment gap creates a critical need to identify interventions that are accessible, easily completable, and optimized for effectiveness by targeting core mechanisms linked to ED onset and maintenance. We propose single-session interventions (SSIs) as a promising path toward catalyzing innovation in the development of accessible, effective ED interventions. SSIs are structured programs that intentionally involve one encounter with a program or provider; they may serve as stand-alone or adjunctive clinical supports. All SSIs are built to acknowledge that any session might be someone's last-and that any single session can nonetheless yield meaningful clinical benefit. We define SSIs, summarize research supporting their utility for ED symptoms and other mental health problems, and recommend future directions for work in this domain. Single-session interventions may hold promise to reduce some ED symptoms and risk factors, including restrictive eating and negative body image. Steps toward realizing this promise include (1) testing whether existing evidence-based SSIs (e.g., for depression) can also reduce EDs, risk factors, and symptoms; (2) developing novel SSIs that target modifiable ED risk factors and symptoms largely unaddressed by SSIs, such as purging and binge eating; (3) studying diverse implementation pathways; (4) capitalizing on SSIs' transdiagnostic utility to broaden funding opportunities; and (5) educating ED researchers and clinicians about SSIs. Understanding the strengths and limits of mechanism-targeted SSIs for ED-related problems could be a low-risk, high-reward avenue toward reducing EDs at scale. Most individuals experiencing EDs never access any form of treatment, creating an urgent need to identify ED interventions built to overcome barriers to engaging with care. This Forum article introduces SSIs as a promising path to rapidly developing and testing accessible, evidence-based ED supports; supplementing existing ED treatment models; and reducing the individual, familial, and societal burdens of EDs at scale.

Tripartite evolutionary game study on coordination information security in prescription circulation.

To further reform the medical and health care system, regulating multi-level treatment and rationalizing the use of medicine, and securing prescription circulation information, this study explores the evolutionary behavior of three players in terms of information security collaboration under the prescription circulation policy, analyzes the evolutionary paths, and examines the influence of key parameters on evolutionary outcomes by constructing a tripartite evolutionary game model consisting of hospitals, retail pharmacies, and healthcare service platforms. The study shows the following: (1) When the information security costs of prescription circulation increase, the willingness of hospitals to promote information collaboration weakens, the probability of control and regulation by healthcare platforms will be enhanced, and the incentive for retail pharmacies to undertake prescription circulation increases and then decreases. (2) The increased profitability of prescription drug sales can cause a decrease in the likelihood of both parties working together to promote information security. Increasing the collaborative space between hospitals and retail pharmacies is conducive to improving information security in the circulation of prescriptions. (3) A bi-directional constraint relationship exists between the circulation and control subjects. The shorter the technology spillover time from the healthcare service platform is, the higher the probability that hospitals and retail pharmacies will maintain the security of prescription information. (4) In the early stages of prescription circulation, the external regulatory action of the healthcare service platform is essential to improve the coordination of information security. Finally, combined with the tripartite evolutionary game model and simulation analysis results, it offers countermeasures and suggestions for the government to realize the prescription circulation information security collaboration.

Double score matching in observational studies with multi-level treatments

While weighting methods are popular for comparing the effects of multi-level treatment in observational studies, their performance can be unstable in the presence of extreme values of the generalized propensity score (GPS). Matching methods are more resistant to GPS outliers but bear the risk of GPS model misspecification. In this article, we propose a double score matching (DSM) estimator of the pairwise average treatment effect (ATE) based on the GPS and the generalized prognostic score (GPGS) evaluated at one treatment level at a time. The de-biased DSM estimator not only maintains the advantage of matching methods but also alleviates the model dependence problem due to its double robustness: it consistently estimates the true pairwise ATE if either the GPS or the GPGS is correctly specified.

An Overview of Herbal Medicines for Idiopathic Pulmonary Fibrosis

Idiopathic pulmonary fibrosis (IPF) is a progressive interstitial lung scarring condition with the histological characteristic of typical interstitial pneumonia. Injury to alveolar epithelial cells is a critical precursor in the pathogenesis of this disease. The prevalence of IPF is growing exponentially, with substantial morbidity and mortality rates increasing the burden on economic healthcare costs. A multidisciplinary approach for diagnosis is used to rule out the alternative causes of interstitial lung disease. Pirfenidone and nintedanib, two innovative antifibrotic medicines introduced in recent years, have provided therapeutic benefits to many IPF patients, and several IPF medications are in the early phases of clinical trials. However, available medications can cause unpleasant symptoms such as nausea and diarrhoea. More efforts have been made to uncover alternative treatments towards a more personalised patient-centred care and hence improve the outcomes in the IPF patients. Through a multi-level and multi-target treatment approach, herbal medicines, such as Traditional Chinese Medicine (TCM), have been identified as revolutionary medical treatment for IPF. Due to their natural properties, herbal medicines have shown to possess low adverse effects, stable therapeutic impact, and no obvious drug dependencies. Herbal medicines have also shown anti-inflammatory and anti-fibrotic effects, which make them a promising therapeutic target for IPF. A growing number of formulas, herbal components, and various forms of Chinese herbal medicine extracts are available for IPF patients in China. This review summarises the role of herbal medicines in the prevention and treatment of IPF.

Utilizing stratified generalized propensity score matching to approximate blocked randomized designs with multiple treatment levels

ABSTRACT Conducting causal inference in settings with more than one treatment level can be challenging. Classical methods, such as propensity score matching (PSM), are restricted to only a binary treatment. To extend propensity score methods beyond a binary treatment, generalized propensity score methods have been proposed, with generalized propensity score matching (GPSM) standing as the multi-level treatment analog to PSM. One drawback of GPSM is it is only capable of emulating a completely randomized trial (CRT) design and not the more efficient blocked randomized trial design. Motivated by the desire to emulate the more efficient design, we expand on GPSM estimating literature and develop a new estimator incorporating relevant stratifying variables into the GPSM framework. We examine the variance estimation methods available for GPSM and demonstrate how to extend the estimator to one where stratifying variables are included. While it would be straightforward to include relevant stratifying variables as covariates in the propensity score estimation, our method provides for researchers to conduct retrospective analyses more consistently with the prospective experiment they would have designed if permitted. Namely, our method permits researchers to approximate a stratified randomized trial as opposed to the CRT otherwise obtainable by GPSM. We apply our proposed method to an analysis of how the number of children in a household affects systolic blood pressure in adults. We conduct a simulation study assessing how the relationship between response, treatment, and strata affect the performance of our method and compare the results to non-stratified GPSM.

Chinese Herbal Medicine in the Treatment of Depression in Parkinson's Disease: From Molecules to Systems.

Depression is one of the most common non-motor symptoms in patients with Parkinson’s disease (PD). Depression in PD (DPD) increases the disability rate and reduces the quality of life of PD patients and increases the caregiver burden. Although previous studies have explained the relationship between depression and PD through a variety of pathological mechanisms, whether depression is a precursor or an independent risk factor for PD remains unclear. Additionally, increasing evidence shows that conventional anti-PD drug therapy is not ideal for DPD. Chinese Herbal Medicine (CHM) prescriptions exhibit the characteristics of multi-target, multi-pathway, and multi-level treatment of DPD and may simultaneously improve the motor symptoms of PD patients through multiple mechanisms. However, the specific pharmacological mechanisms of these CHM prescriptions remain unelucidated. Here, we investigated the mechanisms of action of the active ingredients of single herbs predominantly used in CHM prescriptions for depression as well as the therapeutic effect of CHM prescriptions on DPD. This review may facilitate the design of new selective and effective treatment strategies for DPD.

Effective Learning During COVID-19: Multilevel Covariates Matching and Propensity Score Matching.

In large-scale observational data with a hierarchical structure, both clusters and interventions often have more than two levels. Popular methods in the binary treatment literature do not naturally extend to the hierarchical multilevel treatment case. For example, most K-12 and universities have moved to an unprecedented hybrid learning module during the COVID-19 pandemic where learning modes include hybrid and fully remote learning, while students were clustered within a class and school region. It is challenging to evaluate the effectiveness of the learning outcomes of the multilevel treatments in a hierarchically data structured. In this paper, we study a covariates matching method and develop a generalized propensity score matching method to reduce the bias of estimation in the intervention effect. We also propose simple algorithms to assess the covariates balance for each approach. We examine the finite sample performance of the methods via simulation studies and apply the proposed methods to analyze the effectiveness of learning modes during the COVID-19 pandemic.

Structural Correlates of Mental Health Support Access among Sexual Minority Youth of Color during COVID-19

ABSTRACT Many youth with mental health needs cannot access treatment, with multiply-marginalized youth, such as sexual minority youth of Color (SMYoC), experiencing both structural and identity-related barriers to care. The COVID-19 pandemic threatens to exacerbate multi-level treatment access barriers facing SMYoC youth nationwide. However, little large-scale research has examined access to mental health care among SMYoC across the United States, either during or prior to the pandemic. Such work is critical to understanding and ameliorating barriers in this domain. Using data from adolescents who self-identified as SMYoC and who endorsed a desire for mental health support during the COVID-19 pandemic (N = 470, ages 13–16, from 43 U.S. states), we examined associations between state-level, structural factors (income inequality; mental health-care provider shortage; anti-Black racism; homophobia; and the interaction between anti-Black racism and homophobia) and SMYoC mental health treatment access. Multinomial logistic regressions revealed state-level mental health-care provider shortage as the only significant predictor of SMYoC reporting they never (versus always) accessed mental health support during the COVID-19 pandemic. SMYoC living in areas with both lower homophobia and lower anti-Black racism were more likely to report always (versus sometimes) accessing mental health treatment. Results highlight the critical importance of considering diverse structural factors and applying an intersectional lens when exploring barriers to mental health treatment among multiply-marginalized youth. In locations where provider shortages are less severe, cultural stigma – including anti-Black racism and homophobia – may still pose challenges for SMYoC in need of mental health care.

Quantifying the Causal Effect of Individual Mobility on Health Status in Urban Space

How does individual mobility in the urban environment impact their health status? Previous works have explored the correlation between human mobility behaviour and individual health, yet the study on the underlying causal effect is woefully inadequate. However, the correlation analysis can sometimes be bewildering because of the confounding effects. For example, older people visit park more often but have worse health status than younger people. The common associations with age will lead to a counter-intuitive negative correlation between park visits and health status. Obtaining causal effects from confounded observations remains a challenge. In this paper, we construct a causal framework based on propensity score matching on multi-level treatment to eliminate the bias brought by confounding effects and estimate the total treatment effects of mobility behaviours on health status. We demonstrate that the matching procedure approximates a de-confounded randomized experiment where confounding variables are balanced substantially. The analysis on the directions of estimated causal effects reveals that fewer neighbouring tobacco shops and frequent visits to sports facilities are related with higher risk in health status, which differs from their correlation directions. Physical mobility behaviours and environment features have more significant estimated effects on health status than contextual mobility behaviours. Moreover, we embed our causal analysis framework in health prediction models to filter out features with superficial correlation but insignificant effects that might lead to over-fitting. This strategy achieves better model robustness with more features filtered out than L1-regularization. Our findings shed light on individual healthy lifestyle and mobility-related health policymaking.

Study on Multi-level Treatment Method of Waste Gas from Sewage Treatment Plant

Study on Multi-level Treatment Method of Waste Gas from Sewage Treatment Plant

Confounding adjustment methods for multi-level treatment comparisons under lack of positivity and unknown model specification

Imbalances in covariates between treatment groups are frequent in observational studies and can lead to biased comparisons. Various adjustment methods can be employed to correct these biases in the context of multi-level treatments (> 2). Analytical challenges, such as positivity violations and incorrect model specification due to unknown functional relationships between covariates and treatment or outcome, may affect their ability to yield unbiased results. Such challenges were expected in a comparison of fire-suppression interventions for preventing fire growth. We identified the overlap weights, augmented overlap weights, bias-corrected matching and targeted maximum likelihood as methods with the best potential to address those challenges. A simple variance estimator for the overlap weight estimators that can naturally be combined with machine learning is proposed. In a simulation study, we investigated the performance of these methods as well as those of simpler alternatives. Adjustment methods that included an outcome modeling component performed better than those that focused on the treatment mechanism in our simulations. Additionally, machine learning implementation was observed to efficiently compensate for the unknown model specification for the former methods, but not the latter. Based on these results, we compared the effectiveness of fire-suppression interventions using the augmented overlap weight estimator.