Nevin Manimala

Sex Abuse. 2025 Sep 15:10790632251377703. doi: 10.1177/10790632251377703. Online ahead of print.

ABSTRACT

The report presents study on child sexual abuse within the Catholic Church in Poland from 1950 to 2021, using data collected in three comprehensive queries conducted between 2014 and 2021. The analysis is based on notifications reported to dioceses and male religious congregations, processed by the Institute for Catholic Church Statistics. The study categorizes cases based on the credibility of allegations and tracks the evolution of data collection methodologies, moving from handwritten questionnaires to more detailed online surveys. The research explores variables such as victim demographics (age, gender, and Church affiliation), perpetrator profiles, forms and circumstances of abuse, and reporting patterns. Over the analyzed period, 1,193 minors were identified as victims in notifications, with 1,018 credible allegations. Boys constituted 56% of victims, with an average age of abuse rising from 11 to nearly 15 years. Of 838 accused clergy, 394 were credibly implicated, primarily priests. Most offenders harmed a single victim, though 20% had multiple victims. Findings indicate a significant increase in abuse cases from the 1970s to the 1980s. Despite the detailed data, the study emphasizes limitations, including the inability to fully ascertain the prevalence of abuse due to underreporting and varied motivations for disclosure. The results highlight the need for continuous monitoring to comprehensively understand and address this issue. This research contributes to broader efforts to enhance transparency, accountability, and preventive measures within the Church.

PMID:40948096 | DOI:10.1177/10790632251377703

Clin Endocrinol (Oxf). 2025 Sep 15. doi: 10.1111/cen.70034. Online ahead of print.

ABSTRACT

OBJECTIVES: This study aims to review the long-term outcome of congenital hypothyroidism (CH) and whether patient- or treatment-related factors impact the outcomes, especially focusing on the initial Levothyroxine dose.

METHODS: This is a retrospective, cross-sectional study of the children diagnosed with CH who received Levothyroxine at Ajou University Hospital between 2003 and 2024. Comparative analysis was performed between the low (<10 mcg/kg) and high (≥10 mcg/kg) initial dose groups. Repeated-measures analysis of covariance was employed to evaluate longitudinal changes in growth outcomes, and multivariate linear regression was utilised to evaluate the effects of clinical factors on the intelligence quotient (IQ).

RESULTS: Among the study population, 84 of 144 children were prescribed an initial low dose of Levothyroxine. Most children in both initial dose groups showed appropriate growth within the normal range in the biennial growth evaluation from ages four to eight and in the Wechsler IQ exam. The initial dose seemed to not significantly affect the growth outcomes over time, as no significant differences between the low- and high-dose groups were observed (p values: 0.545, 0.609, 0.532, and 0.501 for bone age-chronological age, height z-score, weight z-score, and BMI z-score, respectively). The effect of the initial dose group on the full-scale IQ was also not statistically significant (p = 0.362).

CONCLUSION: We demonstrated the favourable long-term outcomes in linear growth and neurodevelopment among children with CH, even in lower initial Levothyroxine doses.

PMID:40948059 | DOI:10.1111/cen.70034

Brain Connect. 2025 Sep 15. doi: 10.1177/21580014251376722. Online ahead of print.

ABSTRACT

Background: Combining functional magnetic resonance imaging (fMRI) and machine learning (ML) can be used to identify therapeutic targets and evaluate the effect of repetitive transcranial magnetic stimulation (rTMS) in neural networks in tobacco use disorder. We investigated whether large-scale network connectivity can predict the rTMS effect on smoking cessation. Methods: Smoking cue exposure task-fMRI (T-fMRI) and resting-state fMRI (Rs-fMRI) scans were acquired before and after the 10 sessions of active or sham rTMS (10 Hz, 3000 pulses per session) over the left dorsal lateral prefrontal cortex in 42 treatment-seeking smokers. Five large-scale networks (default model network, central executive network, dorsal attention network, salience network [SN], and reward network) were compared before and after 10 sessions of rTMS, as well as between active and sham rTMS conditions. We performed neural network and regression analysis on the average connectivity of large-scale networks and the effectiveness of rTMS induced by rTMS. Results: Regression analyses indicated higher salience connectivity in T-fMRI and lower reward connectivity in Rs-fMRI, predicting a better outcome of TMS treatment for smoking cessation (p < 0.01, Bonferroni corrected). Neural Network analyses suggested that SN was the most important predictor of rTMS effectiveness in both T-fMRI (0.33 of feature importance) and Rs-fMRI (0.37 feature importance). Conclusions: Both T-fMRI and Rs-fMRI connectivity in SN predict a better outcome of TMS treatment for smoking cessation, but in opposite directions. The work shows that ML models can be used to target TMS treatment. Given the small sample size, all ML findings should be replicated in a larger cohort to ensure their validity.

PMID:40948026 | DOI:10.1177/21580014251376722

Scand J Caring Sci. 2025 Sep;39(3):e70115. doi: 10.1111/scs.70115.

ABSTRACT

BACKGROUND: The evaluation of nurses’ quality of care ensures that care is structured in a qualified manner.

AIMS: This study was conducted to determine the relationship between satisfaction with life in nurses and the quality of care provided by nurses.

METHODS: This descriptive and cross-sectional study included 515 nurses working in state hospitals in two provincial centres in Eastern Turkey. Data were collected using a personal information form, the Satisfaction with Life Scale, and the Caring Behaviours Inventory-24. Data analysis was performed using SPSS 25.0, AMOS 24.0, and G*Power 3.1 programmes.

RESULTS: Satisfaction with life was higher in females, married individuals, bachelor’s degree graduates, and nurses who willingly chose the profession. Working time had a significant relationship with the quality of care. The relationships between the scales were tested using structural equation modelling. All path coefficients were statistically significant (p < 0.05).

CONCLUSIONS: The mean scores of nurses’ satisfaction with life and quality of care were found to be at a moderate level. Furthermore, it was observed that as nurses’ satisfaction with life increased, their quality of care also improved. Based on these findings, it is recommended that health policies aimed at enhancing nurses’ life satisfaction be developed.

PMID:40947512 | DOI:10.1111/scs.70115

Scand J Caring Sci. 2025 Sep;39(3):e70115. doi: 10.1111/scs.70115.

ABSTRACT

BACKGROUND: The evaluation of nurses’ quality of care ensures that care is structured in a qualified manner.

AIMS: This study was conducted to determine the relationship between satisfaction with life in nurses and the quality of care provided by nurses.

METHODS: This descriptive and cross-sectional study included 515 nurses working in state hospitals in two provincial centres in Eastern Turkey. Data were collected using a personal information form, the Satisfaction with Life Scale, and the Caring Behaviours Inventory-24. Data analysis was performed using SPSS 25.0, AMOS 24.0, and G*Power 3.1 programmes.

RESULTS: Satisfaction with life was higher in females, married individuals, bachelor’s degree graduates, and nurses who willingly chose the profession. Working time had a significant relationship with the quality of care. The relationships between the scales were tested using structural equation modelling. All path coefficients were statistically significant (p < 0.05).

CONCLUSIONS: The mean scores of nurses’ satisfaction with life and quality of care were found to be at a moderate level. Furthermore, it was observed that as nurses’ satisfaction with life increased, their quality of care also improved. Based on these findings, it is recommended that health policies aimed at enhancing nurses’ life satisfaction be developed.

PMID:40947512 | DOI:10.1111/scs.70115

Health Serv Res. 2025 Sep 14:e70037. doi: 10.1111/1475-6773.70037. Online ahead of print.

ABSTRACT

OBJECTIVE: To assess the impact of increased Medicaid income eligibility during pregnancy on payment source for prenatal care and birth and on gestational age at birth (GAb).

STUDY SETTING AND DESIGN: We performed a quasi-experimental, difference-in-differences study comparing two increases in Medicaid income eligibility during pregnancy to two control states with data from 2007 to 2010: (Dyad 1) Ohio (expanded from 150% to 200% of the Federal Poverty level [FPL]) versus Pennsylvania and (Dyad 2) Wisconsin (185% to 250% FPL) versus Michigan. We performed multinomial logistic regression to assess the impact of increased Medicaid eligibility on the following key outcome variables: payment source for prenatal care and birth and GAb.

DATA SOURCES AND ANALYTIC SAMPLE: We utilized CDC Pregnancy Risk Assessment Monitoring System (PRAMS) data (2007-2010) and limited analysis to singleton, in-state live births. After re-weighting for PRAMS survey design, our analytical sample represented about 540,000 births.

PRINCIPAL FINDINGS: In the higher-income Wisconsin-Michigan dyad, increased Medicaid eligibility during pregnancy significantly increased exclusive Medicaid coverage for prenatal care (7.0%, 95% CI 2.9% to 11.1%) and birth (8.3%, 4.3% to 12.4%). Simultaneously, private insurance coverage dropped for prenatal care (-4.0%, -7.7% to -0.3%) and birth (-3.7%, -7.2% to -0.2%) while self-payment decreased only for birth (-1.8%, -3.5% to -0.2%). In the lower-income Ohio-Pennsylvania dyad, the only statistically significant effects on payment source were decreases in the likelihood of a payment source of other for prenatal care (-3.3%, -6.2% to -0.3%) and birth (-4.7%, -7.9% to -1.6%). There were no statistically significant effects on GAb across both dyads.

CONCLUSIONS: Increased Medicaid eligibility during pregnancy for individuals of higher income seems to improve utilization of exclusive Medicaid with diminished uninsurance but also less private insurance after accounting for indicators of socioeconomic advantage but has no clear impact on GAb. Medicaid policy should balance reducing uninsurance with directing scarce resources to high-risk individuals.

PMID:40947491 | DOI:10.1111/1475-6773.70037

Health Serv Res. 2025 Sep 14:e70037. doi: 10.1111/1475-6773.70037. Online ahead of print.

ABSTRACT

OBJECTIVE: To assess the impact of increased Medicaid income eligibility during pregnancy on payment source for prenatal care and birth and on gestational age at birth (GAb).

STUDY SETTING AND DESIGN: We performed a quasi-experimental, difference-in-differences study comparing two increases in Medicaid income eligibility during pregnancy to two control states with data from 2007 to 2010: (Dyad 1) Ohio (expanded from 150% to 200% of the Federal Poverty level [FPL]) versus Pennsylvania and (Dyad 2) Wisconsin (185% to 250% FPL) versus Michigan. We performed multinomial logistic regression to assess the impact of increased Medicaid eligibility on the following key outcome variables: payment source for prenatal care and birth and GAb.

DATA SOURCES AND ANALYTIC SAMPLE: We utilized CDC Pregnancy Risk Assessment Monitoring System (PRAMS) data (2007-2010) and limited analysis to singleton, in-state live births. After re-weighting for PRAMS survey design, our analytical sample represented about 540,000 births.

PRINCIPAL FINDINGS: In the higher-income Wisconsin-Michigan dyad, increased Medicaid eligibility during pregnancy significantly increased exclusive Medicaid coverage for prenatal care (7.0%, 95% CI 2.9% to 11.1%) and birth (8.3%, 4.3% to 12.4%). Simultaneously, private insurance coverage dropped for prenatal care (-4.0%, -7.7% to -0.3%) and birth (-3.7%, -7.2% to -0.2%) while self-payment decreased only for birth (-1.8%, -3.5% to -0.2%). In the lower-income Ohio-Pennsylvania dyad, the only statistically significant effects on payment source were decreases in the likelihood of a payment source of other for prenatal care (-3.3%, -6.2% to -0.3%) and birth (-4.7%, -7.9% to -1.6%). There were no statistically significant effects on GAb across both dyads.

CONCLUSIONS: Increased Medicaid eligibility during pregnancy for individuals of higher income seems to improve utilization of exclusive Medicaid with diminished uninsurance but also less private insurance after accounting for indicators of socioeconomic advantage but has no clear impact on GAb. Medicaid policy should balance reducing uninsurance with directing scarce resources to high-risk individuals.

PMID:40947491 | DOI:10.1111/1475-6773.70037

Pharm Stat. 2025 Sep-Oct;24(5):e70033. doi: 10.1002/pst.70033.

ABSTRACT

For toxicology studies, the validation of the concurrent control group by historical control data (HCD) has become requirements. This validation is usually done by historical control limits (HCL), which should cover the observations of the concurrent control with a predefined level of confidence. In many applications, HCL are applied to dichotomous data, for example, the number of rats with a tumor versus the number of rats without a tumor (carcinogenicity studies) or the number of cells with a micronucleus out of a total number of cells. Dichotomous HCD may be overdispersed and can be heavily right- (or left-) skewed, which is usually not taken into account in the practical applications of HCL. To overcome this problem, four different prediction intervals (two frequentist, two Bayesian), that can be applied to such data, are proposed. Based on comprehensive Monte-Carlo simulations, the coverage probabilities of the proposed prediction intervals were compared to heuristical HCL typically used in daily toxicological routine (historical range, limits of the np-chart, mean ± $$ pm $$ 2 SD). Our simulations reveal, that frequentist bootstrap calibrated prediction intervals control the type-1-error best, but, also prediction intervals calculated based on Bayesian generalized linear mixed models appear to be practically applicable. Contrary, all heuristics fail to control the type-1-error. The application of HCL is demonstrated based on a real life data set containing historical controls from long-term carcinogenicity studies run on behalf of the U.S. National Toxicology Program. The proposed frequentist prediction intervals are publicly available from the R package predint, whereas R code for the computation of the two Bayesian prediction intervals is provided via GitHub.

PMID:40947486 | DOI:10.1002/pst.70033

Pharm Stat. 2025 Sep-Oct;24(5):e70033. doi: 10.1002/pst.70033.

ABSTRACT

For toxicology studies, the validation of the concurrent control group by historical control data (HCD) has become requirements. This validation is usually done by historical control limits (HCL), which should cover the observations of the concurrent control with a predefined level of confidence. In many applications, HCL are applied to dichotomous data, for example, the number of rats with a tumor versus the number of rats without a tumor (carcinogenicity studies) or the number of cells with a micronucleus out of a total number of cells. Dichotomous HCD may be overdispersed and can be heavily right- (or left-) skewed, which is usually not taken into account in the practical applications of HCL. To overcome this problem, four different prediction intervals (two frequentist, two Bayesian), that can be applied to such data, are proposed. Based on comprehensive Monte-Carlo simulations, the coverage probabilities of the proposed prediction intervals were compared to heuristical HCL typically used in daily toxicological routine (historical range, limits of the np-chart, mean ± $$ pm $$ 2 SD). Our simulations reveal, that frequentist bootstrap calibrated prediction intervals control the type-1-error best, but, also prediction intervals calculated based on Bayesian generalized linear mixed models appear to be practically applicable. Contrary, all heuristics fail to control the type-1-error. The application of HCL is demonstrated based on a real life data set containing historical controls from long-term carcinogenicity studies run on behalf of the U.S. National Toxicology Program. The proposed frequentist prediction intervals are publicly available from the R package predint, whereas R code for the computation of the two Bayesian prediction intervals is provided via GitHub.

PMID:40947486 | DOI:10.1002/pst.70033