This paper considers the problem of estimation of the population total under probability proportional to size (PPS) sampling scheme when complete data is not available due to the presence of missing observations or non-response. The suggested estimators are developed based on available multi-auxiliary information for the response group and non-response group utilizing the calibration approach. The variances of the suggested estimators have been derived up to the first order of approximation. A simulation study done on a real dataset using R software also supports the performance of the suggested estimators. The empirical percentage absolute relative biases (%ARB) and percentage relative root mean squared errors (%RRMSE) are computed for the suggested estimators. The developed estimators are compared with the estimators of the population total due to the design-based Horvitz and Thompson (HT) estimator and calibration HT type estimator obtained on the available complete response units along with the design-based Hansen and Hurwitz (HH) estimator in the presence of non-response.

BACKGROUND: The advent of the hepatitis B vaccine has achieved tremendous success in eradicating and reducing the burden of hepatitis B infection, which is the main culprit for hepatocellular carcinoma-one of the most fatal malignancies globally. Response to the vaccine is achieved in about 90-95% of healthy individuals and up to only 50% in immunocompromised patients. This review aimed to provide an overview of hepatitis B vaccine non-response, the mechanisms involved, B cell amnesia, and strategies to overcome it.
METHODS: Databases, including Google Scholar, PubMed, Scopus, Cochrane, and ClinicalTrials.org, were used to search and retrieve articles using keywords on hepatitis B vaccine non-response and B cell amnesia. The PRISMA guideline was followed in identifying studies, screening, selection, and reporting of findings.
RESULTS: A total of 133 studies on hepatitis B vaccine non-response, mechanisms, and prevention/management strategies were included in the review after screening and final selection. Factors responsible for hepatitis B vaccine non-response were found to include genetic, immunological factors, and B cell amnesia in healthy individuals. The genetic factors were sex, HLA haplotypes, and genetic polymorphisms in immune response markers (cytokines). Non-response was common in conditions of immunodeficiency, such as renal failure, haemodialysis, celiac disease, inflammatory bowel disease, hepatitis C co-infection, and latent hepatitis B infection. Others included diabetes mellitus and HIV infection. The mechanisms involved were impaired immune response by suppression of response (T helper cells) or induced suppression of response (through regulatory B and T cells).
CONCLUSIONS: A comprehensive and careful understanding of the patient factors and the nature of the vaccine contributes to developing effective preventive measures. These include revaccination or booster dose, vaccine administration through the intradermal route, and the use of adjuvants in the vaccine.

UNASSIGNED: Adverse childhood experiences (ACE) encompass traumatic events occurring before age 18, with lasting impacts on health. While ACE disclosure is important for understanding these effects, some individuals decline to respond to ACE-related survey items due to sensitivity, privacy concerns, or psychological distress. This study explores the relationship between non-response to ACE items and health outcomes, shedding light on the implications for those who choose not to disclose.
UNASSIGNED: We performed a secondary analysis of the 2021 Behavioral Risk Factor Surveillance System (BRFSS)-a national telephone survey querying health behaviors and conditions. Sociodemographic factors, ACE exposure, and non-response to ACE items were analyzed.
UNASSIGNED: Individuals who decline to respond to ACE items exhibit similar patterns of health behaviors and conditions as those reporting ACE exposure. Non-response is linked to both healthier behaviors (lifetime HIV testing) and riskier behaviors (higher odds of smoking and e-cigarette use). Moreover, non-responders have higher odds of being underweight or obese, experiencing concentration difficulties, reporting poor self-rated health, and reporting multiple health diagnoses including depression, diabetes, high blood pressure, heart attack, and stroke.
UNASSIGNED: The study underscores the need to address health disparities associated with ACE, regardless of disclosure status. Healthcare interventions should target respondents and non-respondents of ACE screeners, tailoring strategies to promote healthier coping mechanisms and mitigate maladaptive behaviors. These results emphasize the importance of trauma-informed care, early intervention, and targeted public health initiatives for individuals affected by ACE, irrespective of their disclosure choices.

This paper addresses new exponential estimators for population mean in case of non-response on both the study and the concomitant variables using simple random sampling. The expressions for theoretical bias and mean square error of new estimators are derived up to first-order approximation and comparisons are made with the existing estimators. The proposed estimators are observed more efficient as compared to the considered estimators in the literature. For instance, the classical [4] unbiased estimator, the estimator of [9], and other existing estimators under the explained conditions. The theoretical results are supported numerically by using real-life data sets, under the criteria of bias, mean square error, percent relative efficiency and mathematical conditions. It is also clear from the numerical results that the suggested exponential estimators performed better than the estimators in the literature.

BACKGROUND: Owing to the evidence that as many as 30-40% of patients with vulvar lichen sclerosus (VLS) fail to report a remission of symptoms with first-line corticosteroid treatment (TCS), especially as what regards dyspareunia, we aimed to analyze patients\' satisfaction following vulvar injection of autologous platelet-rich plasma (PRP). This is intended as an adjunctive treatment, to be used following TCS, and appears to promote tissue repair. It may also possibly have immunomodulatory proprieties.
METHODS: Patients with VLS were considered eligible for this pilot study if, despite having been treated with a 3-month TCS regimen, they reported a persistence of symptoms. PRP was produced in a referral center using a manual method and a standardized protocol. Each patient received three treatments 4 to 6 weeks apart.
RESULTS: A total of 50 patients with a median age of 53 years [IQR 38-59 years] were included in the study. 6 months after the last injection of PRP all patients were either satisfied or very satisfied with the treatment (100%; 95% CI 93-100%). Median NRS scores for itching, burning, dyspareunia and dysuria were significantly reduced (p < 0.05) and FSFI, HADS and SF-12 questionnaires revealed a significant improvement in sexual function, psychological wellbeing and quality of life (p < 0.05). The number of patients reporting the need for maintenance TCS treatment was reduced by 42% (p < 0.001) and an improvement in vulvar elasticity and color was reported in all patients.
CONCLUSIONS: Following standard medical therapy, PRP may be effective not only in improving symptoms, but also in restoring function.

The advent of biologic drugs has revolutionized the treatment of Inflammatory Bowel Disease, increasing rates of response and mucosal healing in comparison to conventional therapies by allowing the treatment of corticosteroid-refractory cases and reducing corticosteroid-related side effects. However, biologic therapies (anti-TNFα inhibitors, anti-α4β7 integrin and anti-IL12/23) are still burdened by rates of response that hover around 40% (in biologic-naïve patients) or lower (for biologic-experienced patients). Moreover, knowledge of the mechanisms underlying drug resistance or loss of response is still scarce. Several cellular and molecular determinants are implied in therapeutic failure; genetic predispositions, in the form of single nucleotide polymorphisms in the sequence of cytokines or Human Leukocyte Antigen, or an altered expression of cytokines and other molecules involved in the inflammation cascade, play the most important role. Accessory mechanisms include gut microbiota dysregulation. In this narrative review of the current and most recent literature, we shed light on the mentioned determinants of therapeutic failure in order to pave the way for a more personalized approach that could help avoid unnecessary treatments and toxicities.

UNASSIGNED: H1-antihistamines (H1AH) are the first-line treatment for chronic spontaneous urticaria (CSU), but 50% of patients have inadequate disease control at standard doses.
UNASSIGNED: To assess the comorbidity burden and healthcare resource utilization (HRU) associated with non-response to H1AH-based treatments; to identify predictors of non-response.
UNASSIGNED: Optum® de-identified Electronic Health Record dataset (2007-2020) was used to identify adult patients with CSU who initiated a H1AH, alone or in combination with other oral non-biologics (index treatment). Based on twelve-month treatment patterns observed after index treatment initiation, patients were categorized as responders (continued index treatment or had only 1 next H1AH treatment without corticosteroids) or non-responders (continued corticosteroids or had 2 or more treatment switches). Patient characteristics and HRU were assessed in the 12 months before (baseline) and ≥12 months after (follow-up) index treatment initiation. Baseline predictors associated with non-response were identified using machine learning.
UNASSIGNED: There were 17 062 patients who met inclusion criteria, and 14824 (86.9%) were classified as non-responders. A higher proportion of non-responders had records of CSU-related symptoms, comorbidities, polypharmacy, and certain laboratory tests than responders at baseline. A higher proportion of non-responders than responders visited an allergist or dermatologist during follow-up (59.5% vs 53.0%). Non-responders had a larger increase in hospitalizations (15.7% vs -2.4%) than responders during follow-up vs baseline. Predictors of non-response included index and baseline treatment classes, types of specialists seen, chronic pulmonary disease, depression, and female sex.
UNASSIGNED: A large proportion of CSU patients treated with H1AH-based therapies had uncontrolled disease, contributing to increased HRU and patient burden. Non-responders had more comorbidities and HRU at baseline and follow-up, with steep increases in follow-up hospitalizations relative to baseline, highlighting an urgent need for early disease control.

Given the increasing number of studies in various disciplines using experience sampling methods, it is important to examine compliance biases because related patterns of missing data could affect the validity of research findings. In the present study, a sample of 592 participants and more than 25,000 observations were used to examine whether participants responded to each specific questionnaire within an experience sampling framework. More than 400 variables from the three categories of person, behavior, and context, collected multi-methodologically via traditional surveys, experience sampling, and mobile sensing, served as predictors. When comparing different linear (logistic and elastic net regression) and non-linear (random forest) machine learning models, we found indication for compliance bias: response behavior was successfully predicted. Follow-up analyses revealed that study-related past behavior, such as previous average experience sampling questionnaire response rate, was most informative for predicting compliance, followed by physical context variables, such as being at home or at work. Based on our findings, we discuss implications for the design of experience sampling studies in applied research and future directions in methodological research addressing experience sampling methodology and missing data.

Many adolescent health surveys ask if respondents are male or female. Non-response may be due to fear of de-anonymisation or being a gender-nonconforming youth. The present study investigates the frequency of non-response and its potential reasons. To this end, data from 54,833 adolescents aged 11-18 from six countries, participating in the 2018 Health Behaviour in School-aged Children (HBSC) study, were analysed. Respondents were divided into three groups: (1) \"Responders\" who answered both questions on age and gender, (2) \"Age non-responders\" who did not answer the question on age, and (3) \"Gender non-responders\" who answered the question on age but not the one on gender. These groups were compared regarding their non-response to other questions and regarding their health. Overall, 98.0% were responders, 1.6% were age non-responders and 0.4% were gender non-responders. On average, age non-responders skipped more questions (4.2 out or 64) than gender non-responders (3.2) and responders (2.1). Gender non-responders reported more psychosomatic complaints, more frequent substance use and lower family support than responders. This study shows that age and gender non-responders differ in their response styles, suggesting different reasons for skipping the gender question. The health disparities found between the groups suggest that further research should use a more nuanced approach, informed by LGBT+ youth\'s insights, to measure sex assigned at birth and gender identity.

Despite discussions about the replicability of findings in psychological research, two issues have been largely ignored: selection mechanisms and model assumptions. Both topics address the same fundamental question: Does the chosen statistical analysis tool adequately model the data generation process? In this article, we address both issues and show, in a first step, that in the face of selective samples and contrary to common practice, the validity of inferences, even when based on experimental designs, can be claimed without further justification and adaptation of standard methods only in very specific situations. We then broaden our perspective to discuss consequences of violated assumptions in linear models in the context of psychological research in general and in generalized linear mixed models as used in item response theory. These types of misspecification are oftentimes ignored in the psychological research literature. It is emphasized that the above problems cannot be overcome by strategies such as preregistration, large samples, replications, or a ban on testing null hypotheses. To avoid biased conclusions, we briefly discuss tools such as model diagnostics, statistical methods to compensate for selectivity and semi- or non-parametric estimation. At a more fundamental level, however, a twofold strategy seems indispensable: (1) iterative, cumulative theory development based on statistical methods with theoretically justified assumptions, and (2) empirical research on variables that affect (self-) selection into the observed part of the sample and the use of this information to compensate for selectivity.