Exploring dual identification among Muslim-American emerging adults: a mixed methods study

This mixed methods study explored dual identification among Muslim-American emerging adults of immigrant origin. A closer look was taken at the relationship between American and Muslim identifications and how this relationship was influenced by experiences of discrimination, acculturative and religious practices, and whether it varied by gender. Data were gathered from 97 Muslim Americans (ages 18-25) who completed a survey and produced identity maps, a pictorial representation of hyphenated identities. The findings showed that young people found a way of allowing their Muslim and American identities to co-exist, and only a small minority of the participants seemed to experience identity conflict. While religiosity was the only predictor of Muslim identification, young peoples' identification with mainstream United States culture was predicted by discrimination-related stress and acculturative practices. Gender moderated the relationship between Muslim and American identities in both survey measures and identity maps.     

Frequency of otitis media with effusion among children aged 1–5 years presenting to immunization center of tertiary care hospitals,Rawalpindi

ObjectiveWe conducted this study to assess the etiopathogenic relation of otitis media with effusion (OME) in a group of children aged 1–5 years among the local population of Rawalpindi.MethodsThis was a cross‐sectional retrospective study. Study was conducted among the children presenting to the immunization center of three tertiary care hospitals of Rawalpindi. Otitis media was assessed by clinical examination and tympanometry from August 2019 to January 2020. Multi‐factor regression analysis was then applied to recognize the statistical significance and association of various risk factors to OME.ResultsOut of 400 children enrolled in this study, 108 (27.0%) had OME, out of which 65 (60.2%) were males and 30 (27.8%) were of age group 2–3 years. Multivariable regression analysis of risk factors associated with OME showed it was strongly associated with snoring (P < 0.001), last year symptoms (attack of ear aches with hearing loss [P = 0.002]), drugs (URTI antibiotics [P = 0.026], All 3 drugs [P = 0.013]).ConclusionsWe found out that OME is a common disease which if not identified or treated timely can lead to other hard to cure health problems. Control of its etiopathogenic factors can play a major role in its prevention.     

Reliability and Validity of the EORTC QLQ-CIPN20 (European Organization for Research and Treatment of Cancer Quality of Life Questionnaire–Chemotherapy-Induced Peripheral Neuropathy 20-Item Scale) among Thai Women with Breast Cancer Undergoing Taxane-Based Chemotherapy

Objective:The European Organization for Research and Treatment of Cancer Quality of Life Questionnaire–Chemotherapy-Induced Peripheral Neuropathy 20-item scale (EORTC QLQ-CIPN20) is the common method for determining taxane-induced peripheral neuropathy (TIPN) symptoms. However, there have been no studies on the psychometric properties of the Thai Version of EORTC QLQ-CIPN20. The aim of this study was to evaluate the test–retest reliability, concurrent validity, and contrasting group validity of the Thai Version of EORTC QLQ-CIPN20 among women with breast cancer who received taxane-based chemotherapy. Methods:Twenty-eight breast cancer patients and 28 healthy controls participated in the study. Internal consistency, test–retest reliability, and inter-rater reliability were assessed using Cronbach α and the intraclass correlation coefficient (ICC). Concurrent validity was assessed via the Spearman correlation coefficient of the total scale of the EORTC QLQ-CIPN20 and the Total Neuropathy Score clinical version (TNSc), and contrasting group validity was assessed via the Mann-Whitney U test. Results:The internal consistency, test–retest reliability, and inter-rater reliability of the Thai Version of EORTC QLQ-CIPN20 was high to excellent (Cronbach α = 0.89, ICC = 0.84–0.95 and 0.78–0.94, respectively). However, the concurrent validity between the Thai Version of EORTC QLQ-CIPN20 and TNSc was not considered statistically significant. Contrasting group validity demonstrated statistically significant differences between breast cancer patients and healthy controls. Conclusions: The results support that the Thai Version of EORTC QLQ-CIPN20 is reliable and valid in measuring TIPN symptoms in Thai women with breast cancer. The findings suggest that the Thai Version of EORTC QLQ-CIPN20 may be used to distinguish TIPN symptoms between healthy controls and women with breast cancer undergoing taxane-based chemotherapy.Key Words: Taxane, induced peripheral neuropathy, breast cancer, EORTC QLQ, CIPN20, reliability, validity     

Enhancing the design and utilization of asthma action plans through community-based participatory research in an urban African American community

BackgroundAcross the U.S., large inequities in asthma prevalence and outcomes persist, disproportionately affecting low-income, minoritized children. West Louisville is particularly impacted by these inequities due to a complex interplay of socioeconomic, historical, and industrial processes. Additionally, low health literacy and mistrust in healthcare exacerbate poor asthma self-management.ObjectiveTo engage community members and health professionals to address childhood asthma management in a marginalized community experiencing significant health inequities.Patient InvolvementAlthough prior asthma knowledge was not required, the majority of our community advisory council (CAC) members either had asthma or cared for children/grandchildren with asthma. Through facilitated decision-making using the Boot Camp Translation approach, the CAC chose to focus on improving asthma self-management in their community through enhancing the design and utilization of asthma action plans (AAPs).MethodsUpon adding inhaler images to a user-friendly AAP, the CAC developed and implemented a provider incentive program and a health communication campaign to promote the Tool’s utilization. Evaluation of the intervention consisted of a short questionnaire measuring relevant patient demographics and campaign knowledge, and phone interviews with providers to gather feedback on the incentive and Tool design.ResultsOver the short two-month intervention, a total of 8 practices with 28 providers used 153 Tools to provide asthma self-management counseling. The majority of providers preferred the enhanced Tool to other AAPs they had used. Inhaler images facilitating improved communication regarding asthma medications.DiscussionUsing a participatory approach, a community preferred intervention targeting barriers to effective asthma control increased provider utilization and community awareness of AAPs and bridged a communication gap between patients and providers.Practical ValueLeveraging community members’ (including patients/caregivers) and health professionals’ expertise led to the development of an enhanced patient-education tool and an effective provider incentive program with the potential to improve childhood asthma management in marginalized populations.     

Explainability and white box in drug discovery

Recently, artificial intelligence (AI) techniques have been increasingly used to overcome the challenges in drug discovery. Although traditional AI techniques generally have high accuracy rates, there may be difficulties in explaining the decision process and patterns. This can create difficulties in understanding and making sense of the outputs of algorithms used in drug discovery. Therefore, using explainable AI (XAI) techniques, the causes and consequences of the decision process are better understood. This can help further improve the drug discovery process and make the right decisions. To address this issue, Explainable Artificial Intelligence (XAI) emerged as a process and method that securely captures the results and outputs of machine learning (ML) and deep learning (DL) algorithms. Using techniques such as SHAP (SHApley Additive ExPlanations) and LIME (Locally Interpretable Model-Independent Explanations) has made the drug targeting phase clearer and more understandable. XAI methods are expected to reduce time and cost in future computational drug discovery studies. This review provides a comprehensive overview of XAI-based drug discovery and development prediction. XAI mechanisms to increase confidence in AI and modeling methods. The limitations and future directions of XAI in drug discovery are also discussed.