Group Members Research Articles

The impact of multilingualism and socio-economic status on academic performance: evidence from the SCAMP and the national pupil databases

ABSTRACT This study examines the impact of multilingualism and socioeconomic status on academic performance within the UK, utilising data from 3,213 pupils from the National Pupil Database who also took part in the Study of Cognition, Adolescents and Mobile Phones (SCAMP). We employed multilevel modelling to analyse the relationship between language experience, socioeconomic status and Key-Stage 2 (KS2∼11 years) and Key-Stage 4 (KS4∼16 years) performance in English, Mathematics and Science. Findings reveal that multilingual learners initially face academic challenges at KS2, particularly in English and Science, but achieve comparable results with monolingual peers by KS4, overcoming early setbacks. Notably, simultaneous multilinguals not only catch up but excel beyond their monolingual counterparts by KS4, demonstrating the significant long-term academic benefits of early multilingual exposure and /or its associated cultural factors. Further analysis indicates that multilingual group membership mitigated the adverse effects of low socioeconomic status, with pupils from these backgrounds making substantial academic strides between KS2 and KS4 compared to monolingual peers. This challenges prevalent misconceptions about multilingualism in education. These findings underscore the need for educational policies that harness linguistic diversity to foster academic equity and success, emphasising the crucial role of language experience and socioeconomic factors in shaping educational outcomes.

Latent profiles of disability in retired, community‐dwelling older adults

AbstractLater life disability poses a significant public health challenge, and while research often concentrates on physical limitations, understanding the full spectrum of disability requires a comprehensive approach. This study employs latent profile analysis (LPA), a statistical technique that identifies underlying subgroups or profiles within a larger population based on patterns of responses to multiple indicators, to classify disability. We examined one wave of existing panel data from 414 participants aged 72–106 living in retirement communities. We focus on the following disability indicators: basic and instrumental activities of daily living; physical, cognitive, and sensory impairments; and participation restrictions. Three distinct profiles emerged. The largest group (58%), “Low Disability,” exhibited minimal disability across all domains and superior psychological well‐being. The second group (38%) experienced “High Physical and Functional Disability,” with a higher prevalence among older, unmarried women. The smallest group (4%) displayed “High Cognitive‐Sensory‐Functional Disability,” marked by extensive cognitive impairment and the highest functional and sensory limitations, prevalent in advanced age with poorer psychological outcomes of all profiles. Notably, participation restrictions showed minimal variation across disability profiles. The findings emphasize the need for a data‐driven policy framework addressing disability profiles. Efficient resource allocation and targeted support are crucial, and prevention strategies should proactively address individuals at risk of transitioning into higher‐multidomain disability profile membership. Given the connection between disability and mental health, addressing these concerns can enhance overall health and well‐being. Future research should explore changes in disability group membership over time in diversified samples.

Combining propensity score methods with variational autoencoders for generating synthetic data in presence of latent sub-groups

In settings requiring synthetic data generation based on a clinical cohort, e.g., due to data protection regulations, heterogeneity across individuals might be a nuisance that we need to control or faithfully preserve. The sources of such heterogeneity might be known, e.g., as indicated by sub-groups labels, or might be unknown and thus reflected only in properties of distributions, such as bimodality or skewness. We investigate how such heterogeneity can be preserved and controlled when obtaining synthetic data from variational autoencoders (VAEs), i.e., a generative deep learning technique that utilizes a low-dimensional latent representation. To faithfully reproduce unknown heterogeneity reflected in marginal distributions, we propose to combine VAEs with pre-transformations. For dealing with known heterogeneity due to sub-groups, we complement VAEs with models for group membership, specifically from propensity score regression. The evaluation is performed with a realistic simulation design that features sub-groups and challenging marginal distributions. The proposed approach faithfully recovers the latter, compared to synthetic data approaches that focus purely on marginal distributions. Propensity scores add complementary information, e.g., when visualized in the latent space, and enable sampling of synthetic data with or without sub-group specific characteristics. We also illustrate the proposed approach with real data from an international stroke trial that exhibits considerable distribution differences between study sites, in addition to bimodality. These results indicate that describing heterogeneity by statistical approaches, such as propensity score regression, might be more generally useful for complementing generative deep learning for obtaining synthetic data that faithfully reflects structure from clinical cohorts.

Cross-Cutting Exposure in Online News Comments: The Effects of Group Identification and Uncivil Discourse on Opinion Conformity and Expression

ABSTRACT Drawing upon the social identity model of deindividuation effects, this study investigated the effects of intergroup relations and discursive quality on individuals’ responses to comments that challenge their existing beliefs on news websites. A two-session online experiment with a 2 (group membership: in-group vs. out-group) × 2 (comment tone: civil vs. uncivil) between-subjects factorial design was conducted. The results showed that exposure to counter-attitudinal comments from in-group members, compared to out-group members, led to greater opinion conformity and less expression of disagreement. Additionally, there was a significant interaction between group membership and comment tone on disagreement expression. When counter-attitudinal comments were uncivil, individuals exposed to in-group comments expressed less dissent in their replies than those exposed to out-group comments. This tendency, however, was not significant when the counter-attitudinal comments were expressed in a civil tone.

Deep learning infused SIRVD model for COVID-19 prediction: XGBoost-SIRVD-LSTM approach.

The global impact of the ongoing COVID-19 pandemic, while somewhat contained, remains a critical challenge that has tested the resilience of humanity. Accurate and timely prediction of COVID-19 transmission dynamics and future trends is essential for informed decision-making in public health. Deep learning and mathematical models have emerged as promising tools, yet concerns regarding accuracy persist. This research suggests a novel model for forecasting the COVID-19's future trajectory. The model combines the benefits of machine learning models and mathematical models. The SIRVD model, a mathematical based model that depicts the reach of the infection via population, serves as basis for the proposed model. A deep prediction model for COVID-19 using XGBoost-SIRVD-LSTM is presented. The suggested approach combines Susceptible-Infected-Recovered-Vaccinated-Deceased (SIRVD), and a deep learning model, which includes Long Short-Term Memory (LSTM) and other prediction models, including feature selection using XGBoost method. The model keeps track of changes in each group's membership over time. To increase the SIRVD model's accuracy, machine learning is applied. The key properties for forecasting the spread of the infection are found using a method called feature selection. Then, in order to learn from these features and create predictions, a model involving deep learning is applied. The performance of the model proposed was assessed with prediction metrics such as R 2, root mean square error (RMSE), mean absolute percentage error (MAPE), and normalized root mean square error (NRMSE). The results are also validated to those of other prediction models. The empirical results show that the suggested model outperforms similar models. Findings suggest its potential as a valuable tool for pandemic management and public health decision-making.

Beyond binary group categorization: towards a dynamic view of human groups

ABSTRACT Society is a composite of interacting people and groups. These groups play a significant role in maintaining social status, establishing group identity and social identity, and enforcing norms. As such, groups are essential for understanding human behavior. Nevertheless, the study of groups in everyday group life yields many diverse and sometimes contradicting theories of group behavior, and researchers tend to agree that we have yet to understand the emergence of groups out of aggregates of individuals. The current paper aims to shed new light on the convoluted interrelation between groups and individuals by focusing on individuals’ social identities and group categorization. It does so by exploring the dynamic nature of the self and its implications on identity and group membership, and introducing a framework recognizing the fluidity of groups and group categorization. Incorporating historical insights with contemporary theories, this paper argues for a flexible understanding of group dynamics that surpasses rigid in-group and out-group classifications, proposing instead that group affiliations exist along a continuum that reflects the ever-changing social landscape.

Is There a Need to Expand the Refugee Definition?

This article examines the urgency of protecting against displacement caused by climate change under international law and questions why Rohingya displacement has not been resolved even though it has been protected by international law, whether the harmonization of human rights approaches, national law, and international law towards refugees and climate refugees. This paper uses a literature review method and a normative legal approach by reviewing national and international human rights law. The findings of this paper suggest that many Rohingya continue to flee to safer countries, often taking enormous risks, including dangerous ocean crossings. The impacts of climate change can be categorized as persecution; the Refugee Convention requires that such persecution be due to race, religion, nationality, political opinion, or membership of a particular social group. Persecution alone is not enough. The difficulty is that the impacts of climate change are largely indiscriminate and not related to specific characteristics such as a person's background or beliefs. The Rohingya people have experienced violence, discrimination, and persecution for decades, and the international community has failed to protect them effectively. The international community has allowed Myanmar to carry out genocide against the Rohingya without taking any action, even though United Nations member states are obliged to protect their population from genocide, war crimes, ethnic cleansing, and crimes against humanity. National, international, and human rights laws play an important role in determining the legal status and rights of refugees in a country. All three must be embedded and integrated, starting from international law and its derivatives to national law, which contains humanitarian rights.

Determinants of livelihood vulnerability to climate change among the agrarian community: Empirical evidence from the coastal region of Indian Sundarban Biosphere Reserve

The impacts of climate change on the livelihood of agrarian households on the coast of the Indian Sundaraban Biosphere Reserve have not been addressed. Thus, it is important to identify the underlying factors for livelihood vulnerability in this region and know how climate change-related events and socio-economic conditions affect them. This work aimed to measure six major domains of livelihood vulnerability, such as overall livelihood loss, livestock loss, crop and crop area loss, fishing area loss, housing loss, and income loss. I selected the ordered probit regression and focus group discussion approaches. Results revealed that the significant determinant factors of livelihood vulnerability were early warning system, education, land holding size, social group, type of house, occupation, distance to the local market and health centre, membership of self-help group, agreement with summer temperature increased, cyclone increased, flood increased, drought in Kharif season increased. In this region, several agrarian households have taken some adaptation measures such as changing crop varieties, crop diversification, converting agriculture to fishery, and saline tolerant varieties. This approach is adaptable and can be put into practice on different levels, not just in other parts of India but also in diverse developing countries.

Group based trajectory modeling identifies distinct patterns of sympathetic hyperactivity following traumatic brain injury.

Background Paroxysmal Sympathetic Hyperactivity (PSH) occurs with high prevalence among critically ill Traumatic Brain Injury (TBI) patients and is associated with worse outcomes. The PSH-Assessment Measure (PSH-AM) consists of a Clinical Features Scale (CFS) and a Diagnosis Likelihood Tool (DLT), intended to quantify the severity of sympathetically-mediated symptoms and likelihood that they are due to PSH, respectively, on a daily basis. Here, we aim to identify and explore the value of dynamic trends in the evolution of sympathetic hyperactivity following acute TBI using elements of the PSH-AM. Methods We performed an observational cohort study of 221 acute critically ill TBI patients for whom daily PSH-AM scores were calculated over the first 14 days of hospitalization. A principled group-based trajectory modeling approach using unsupervised K-means clustering was used to identify distinct patterns of CFS evolution within the cohort. We also evaluated the relationships between trajectory group membership and PSH diagnosis, as well as PSH DLT score, hospital discharge GCS, ICU and hospital length of stay, duration of mechanical ventilation, and mortality. Baseline clinical and demographic features predictive of trajectory group membership were analyzed using univariate screening and multivariate multinomial logistic regression. Results We identified four distinct trajectory groups. Trajectory group membership was significantly associated with clinical outcomes including PSH diagnosis and DLT score, ICU length of stay, and duration of mechanical ventilation. Baseline features independently predictive of trajectory group membership included age and post-resuscitation motor GCS. Conclusions This study adds to the sparse research characterizing the heterogeneous temporal trends of sympathetic nervous system activation during the acute phase following TBI. This may open avenues for early identification of at-risk patients to receive tailored interventions to limit secondary brain injury associated with autonomic dysfunction and thereby improve TBI patient outcomes.

Positive Childhood Experiences are Associated With Alcohol Use in Adolescent and Emerging Adult Females by Adverse Childhood Experiences Dimension

PurposeExperiencing multiple adverse childhood experiences (ACEs) is associated with alcohol use in female adolescents and emerging adults. Protective and compensatory experiences (PACEs) have been theorized to off-set the health and behavioral consequences from the accumulation of ACEs throughout childhood. This study examines the association between protective experiences and subsequent alcohol and binge alcohol use frequency over one month among female adolescent and emerging adults reporting high and low levels of two ACE dimensions (household dysfunction and emotional abuse/neglect). MethodsOne hundred 43 females between the ages of 15–24 who indicated at least one binge episode in the past two weeks completed the six-item ACEs scale, the PACEs scale, and demographics at baseline. Alcohol consumption was measured prospectively over the next month during weekly appointments using the timeline follow back approach. ResultsTwo PACEs factors had significant direct associations, a source of unconditional love was associated with less frequent alcohol use (β = −0.437, 95% confidence interval [CI] -0.744, −0.131, exp(β) = 0.65, p = .005) in the context of high household dysfunction; and having a trusted adult to count on for help and advice (β = −1.373, 95% CI -2.283, −0.464, exp(β) = 0.25, p = .003) predicted fewer binge occasions in the context of high emotional abuse/neglect. Regardless of ACE dimension exposure, nonsport social group membership was associated more frequent alcohol use over the month across all ACE dimensions (β = 0.11-0.74, 95% CI -0.11, 0.74, exp(β) = 1.37 – 1.62, p ≤ .002); and having a trusted adult to count on for help and advice was associated with a 5.7 times more frequent of alcohol use among those with low household dysfunction (β = 1.74, 95% CI 0.83, 2.65, exp(β) = 5.70, p < .001). DiscussionFew PACE items are associated with direct reductions in alcohol outcomes. Indeed, there is consistently heightened risk associated with nonsport group membership for alcohol use frequency, regardless of experiences of childhood adversity. Future research should identify which protective factors have the most potential to off-set alcohol use by ACE dimension.

Determinants of smallholder membership in farmers’ groups in the pigeon pea-based farming system in Uganda

BackgroundMembership in farmers’ group (FGs) is an important social aspect of agricultural development. Little is known about the relative importance and benefits from participation in FGs in Uganda, specifically for pigeon pea smallholders in northern Uganda.MethodsWe conducted a cross-sectional survey with 257 smallholders to examine the factors that motivate farmer’s group membership and its influence on pigeon pea yield and technical efficiency (TE) in northern Uganda. We applied the Stochastic Production Frontier (SPF) model and complementary models to assess membership impact on pigeon pea yield and TE determinants, respectively. TE is defined as the degree to which smallholders use the minimum feasible farm inputs to produce a given level of pigeon pea grain.ResultsResults show that FG members were generally older and more experienced, and had better access to extension services (76%) and credit (43%) compared to non-members. Smallholders’ age, access to agricultural training, extension services, and the distance travelled to market centres were statistically significant (p < 0.05), thus limiting the likelihood of FG membership. TE for both groups was low and quite similar, at 63% and 59% for members and non-members, respectively, implying that both groups did not use the available farm resources to maximize pigeon pea yield.ConclusionOur results confirm that FG membership enhances smallholder’s access to extension, agricultural training services and credit. For northern Uganda, the study provides recommendations for increased government investment in the human, financial and physical capacity of extension agents as a strategy for rural development and improved livelihoods. In addition, policy incentives can encourage farmers to seek membership in farmers’ groups and related associations.

Free-listing and Semantic Knowledge: A Tool for Detecting Alzheimer Disease?

Impairment in semantic knowledge contributes to Alzheimer disease (AD)-related decline. However, the particulars of the impact AD has on specific domains of knowledge remain debatable. To investigate the impact of AD on specific semantic categories that are integral to daily functions-living things and man-made objects. We administered a free-listing task (written version) to 19 individuals with AD and 15 cognitively normal older adults and assessed the task's relationship with other cognitive and functional tests in clinical use. We compared the contents of the lists of salient concepts generated by the AD and control groups. Group membership (AD or control), after controlling for age, sex, formal education, and an estimate of premorbid intellectual ability, predicted the groups' performance on the free-listing task across two categories. Functional status was inversely related to performance on the free-listing task, holding demographic variables constant. Based on a comparison of the contents of the free lists that were generated by the two groups, it was possible to conclude that, in individuals with AD, conceptual knowledge central to the respective categories was well preserved, whereas the peripheral conceptual material showed evidence of degradation. The free-listing task, which is an easy-to-administer and cost-effective tool, could aid in the preliminary detection of semantic knowledge dysfunction, revealing concepts that are better preserved and, possibly, the characterization of AD. Cognitive assessment tools that can be applied across cultures are needed, and the free-listing task has the potential to address this gap.

Using an anti-racist research framework to design studies of oral human papillomavirus and oropharyngeal cancer in San Francisco: rationale and protocol for the Health Equity and Oral Health in People living with HIV (HEOHP) qualitative study

IntroductionThe goal of our research programme is to develop culturally appropriate patient-specific interventions for primary and secondary prevention of human papillomavirus (HPV)-related oropharyngeal cancer (OPC) among people living with HIV...

Workplace inclusion in higher education philanthropy

Positive workplace inclusion is important for any business today, but especially so for higher education philanthropy. Higher education philanthropy suffers from high turnover and lack of diversity, making successful workplace inclusion urgent. Higher education philanthropy exacerbates low diversity and high turnover through education bias, compensation and opportunity imbalance, work culture expectations that favour in-group members, low task interdependency, isolation from co-workers, low support from leadership, and burnout. To address the primary challenge of turnover, this paper proposes unit-level measures that higher education philanthropy offices might use to increase inclusion, promote diversity and improve work group performance and morale.

Miesize: Effect-size calculation in imputed data

In this article, I describe the miesize command for the calculation of effect sizes in imputed data. There may be situations where an effect size needs to be estimated for an intervention, an exposure, or a group membership variable but data on the independent or dependent variable are missing. Such missing data are commonly dealt with by multiply imputing plausible values. However, in this circumstance, the estimated effect size and associated standard errors will need to be pooled and estimated from the imputed dataset. The miesize command automates this process and calculates effect sizes for a binary variable from multiply imputed data in wide format. The estimates and standard errors (used to calculate the confidence intervals) are recombined using Rubin’s (1987, Multiple Imputation for Nonresponse in Surveys [Wiley]) rules. These rules are applied such that the average point estimate for the effect size is calculated from the imputed datasets. The pooled standard error, and hence confidence intervals, is calculated to account for both the variance between the imputed datasets and the variance within them. Pooled effect sizes and confidence intervals for Cohen’s (1988, Statistical Power Analysis for the Behavioral Sciences, 2nd ed. [Lawrence Erlbaum]) d, Hedges’s (1981, Journal of Educational Statistics 6: 107-128) g, and Glass’s ( Smith and Glass, 1977 , American Psychologist 32: 752-760) delta are provided by miesize.

Effects of a Manual Treatment on Lumbar Microcirculation and Tissue Stiffness Following Submaximal Eccentric Trunk Extensor Exercise: A Randomized Controlled Trial.

Recent studies have shown that the extramuscular connective tissue (ECT) is thickened and stiffened in delayed onset muscle soreness (DOMS). However, contrarily to the normal population, severe DOMS is rare in athletes or highly trained individuals. The present randomized, controlled trial therefore aimed to investigate pain as well as microcirculation and stiffness of the ECT and the erector spinae muscle following submaximal eccentric trunk extension exercise not causing DOMS. The effect of manual treatment by a therapist (myofascial release; MFR) on these parameters was to be studied. Trained healthy participants (n = 21; 31.3 ± 9.6 years; > 4 h exercise per week) performed submaximal eccentric exercise of the trunk extensors. One group was manually treated (n = 11), while the other group (n = 10) received placebo treatment with sham laser therapy. Stiffness of the ECT and the erector spinae muscle (shear wave elastography), microcirculation (white light and laser Doppler spectroscopy), palpation pain (100 mm visual analogue scale, VAS) and pressure pain threshold (indentometry, PPT) were assessed before (t0), 24 h (t24) and 48 h (t48) after conditions. Erector spinae muscle stiffness increased after eccentric exercise from t0 to t24 (0.875 m/s) and from t0 to t48 (0.869 m/s). After MFR, erector spinae muscle stiffness decreased in contrast to placebo treatment at t24 (-0.66 m/s), while ECT stiffness remained unchanged. Oxygen saturation increased (17-20.93%) and relative haemoglobin decreased (-9.1 - -12.76 AU) after eccentric exercise and MFR differed from placebo treatment at t48 (-3.71 AU). PPT differed after MFR from placebo treatment at t48 (20.69 N/mm), while VAS remained unchanged. Multiple linear regression showed that ECT stiffness and group membership predicted erector spinae muscle stiffness. MFR could have a positive effect on pain, microcirculation and muscle stiffness after submaximal eccentric exercise, suggesting better recovery, which needs to be confirmed by future work.

Caught between two worlds: Social identity change among second‐generation Afghan immigrants in Iran

AbstractThis study investigates the identity processes among second‐generation Afghans living in Iran and evaluate the relevance of the social identity model of social change (SIMIC) to understand their unique experiences. We conducted 23 in‐depth interviews and analysed the data using grounded theory method. The findings showthat Afghan youths' efforts towards integration often fail due to unfavourable responses from the host society, compounded by the perceived discriminatory environment. In addition, in line with SIMIC, the results show that participants lacks socio‐psychological resources linked to previous group membership and this leads to poorer mental health. Finally, we explore the engagement in de‐labelling, the formation of purposeful social bonds, and the development of a cosmopolitan identity among our participants as the main identity‐oriented mechanisms to navigate the challenges of being rejected by both one's and the host community.

Prevalence, Characteristics, and Selection of Bacillus cereus Subgroups from Dairy Products for Challenge Testing and Predictive Model Development

Prevalence, toxin gene profiles, lactose fermentation, and growth responses of B. cereus sensu lato subgroups in various dairy and dairy alternative products and ingredients were studied to identify relevant isolates for challenge testing and model development to predict and manage growth responses. Out of 71 examined products or ingredients, 51 B. cereus s.l. isolates were obtained from 35 positive samples (49% prevalence). These 51 isolates along with 18 additional dairy isolates and 12 B. cereus s.l. reference strains were identified using MALDI-TOF. The 81 isolates were further characterized by panC sequencing, testing for cold shock and toxin genes (cspA; hbl, nhe, CytK and ces), lactose fermentation, and study of growth rates (µmax) under various conditions (45 °C, 10 °C, 6% NaCl, pH 5.1), resulting in 298 µmax-values. These conditions were selected to differentiate mesophilic and psychrotolerant strains and to identify tolerant isolates. Dairy powders (83%), pasteurized upconcentrated cheese whey (43%), and cheeses (42%) had the highest prevalences of B. cereus s.l. and the highest concentrations in positive samples (5–100 CFU/g or ml). The panC groups II, III, IV, VI, and VIII were detected among the dairy isolates, with 97% harboring one or more toxin genes. Lactose fermentation was observed in 42% of isolates, with lactose-fermenting B. cereus s.l. isolates of panC groups III and IV dominant in dairy powders. Growth rates of B. cereus s.l. varied considerably, among and within panC groups of the dairy isolates. Based on the highest growth rates at 45 °C, 10 °C, 6% NaCl, pH 5.1, panC group membership, toxin genes profiles, and lactose fermentation ability, two cocktails of “mesophilic” or “psychrotolerant” isolates were selected. These strain cocktails can be used in future challenge testing and predictive food microbiology studies to evaluate and manage the growth of B. cereus s.l. in dairy products and ingredients.

Psychological well-being and its associations with sociodemographic characteristics, physical health, substance use and other mental health outcomes among adults in Canada.

Psychological well-being (PWB) is an important component of positive mental health (PMH) and an asset for population health. This study examined correlates of PWB among community-dwelling adults (18+ years) in the 10 Canadian provinces. Using data from the 2019 Canadian Community Health Survey Rapid Response on PMH, we conducted linear regression analyses with sociodemographic, mental health, physical health and substance use variables as predictors of PWB. PWB was measured using six questions from the Mental Health Continuum-Short Form, which asked about feelings of self-acceptance, personal growth, environmental mastery, autonomy, positive relations and purpose in life during the past month. In unadjusted and adjusted analyses, older age, being married or in a commonlaw relationship and having a BMI in the overweight category (25.00-29.99) were associated with higher PWB, while reporting a mood disorder, anxiety disorder, high perceived life stress, engaging in heavy episodic drinking and frequent cannabis use were associated with lower PWB. Sex, having children living at home, immigrant status, racialized group membership, educational attainment, household income tertile, having a BMI in the obese category (≥30.00), major chronic disease and smoking status were not significantly associated with PWB. This research identifies sociodemographic, mental health, physical health and substance use factors associated with PWB among adults in Canada. These findings highlight groups and characteristics that could be the focus of future research to promote PMH.

Centering the margins: Reimagining resilience and resistance for transgender and nonbinary people of color

AbstractBy centering the margins through intersectional and cross‐cultural perspectives, this article offers a reimagining of resilience by exploring individual versus collective (i.e., group‐level) approaches and strategies adopted by transgender and nonbinary people of color (TPOC) to resist oppression. We address the dynamics of multiple group membership and recognize the profound effects of culture on how TPOC communities navigate resilience and resistance. Utilizing an international perspective, we examine risk and resilience by considering proximal and distal minority stressors such as discrimination and internalized stigma. We also address the utility of current models used to address TPOC resilience (i.e., minority stress and resilience theory, transgender resilience intervention model). Finally, we address tensions associated with the characterization of resilience and resistance for TPOC within the social sciences and across cultures. This article thus serves as a critical foundation for reimagining research with TPOC by presenting potential avenues for further research, theory, and community action globally.