Sex, ethnic and socioeconomic inequalities and trajectories in child and adolescent mental health in Australia and the UK: findings from national prospective longitudinal studies

BACKGROUND: This study investigates the sex, ethnic and socioeconomic inequalities in emotional difficulties over childhood and adolescence using longitudinal cohort studies in the UK and Australia. Estimating cross-national differences contributes to understanding of the consistency of inequalities in mental health across contexts. METHODS: Data from 19,748 participants in two contemporary representative samples in Australia (Growing Up in Australia: The Longitudinal Study of Australian Children, n = 4,975) and UK (Millennium Cohort Study, n = 14,773) were used. Emotional difficulties were assessed using the parent-reported Strengths and Difficulties Questionnaire at ages 4/5, 6/7, 11/12 and 14/15 years and the self-reported Short Moods and Feelings Questionnaire at age 14/15. Latent Growth Curve Modelling was used to examine mental health over time. RESULTS: There were significant increases in emotional difficulties in both countries over time. Emotional difficulties were higher in Australian children at all ages. The gender gap in self-reported depressive symptoms at age 14/15 was larger in the UK (8% of UK and 13% of Australian boys were above the depression cut-off, compared with 23% of girls). Ethnic minority children had higher emotional difficulties at age 4/5 years in both countries, but over time this difference was no longer observed in Australia. In the UK, this reversed whereby at ages 11/12 and 14/15 ethnic minority children had lower symptoms than their White majority peers. Socioeconomic differences were more marked based on parent education and employment status in Australia and by parent income in the UK. UK children, children from White majority ethnicity and girls evidenced steeper worsening of symptoms from age 4/5 to 14/15 years. CONCLUSIONS: Even in two fairly similar countries (i.e. English-speaking, high-income, industrialised), the observed patterns of inequalities in mental health symptoms based on sociodemographics are not the same. Understanding country and context-specific drivers of different inequalities provides important insights to help reduce disparities in child and adolescent mental health

Prevalence and treatment implications of ICD-11 complex PTSD in Australian treatment-seeking current and ex-serving military members

Background: Despite growing support for the distinction between posttraumatic stress disorder (PTSD) and complex PTSD (CPTSD) as separate diagnoses within the ICD-11 psychiatric taxonomy, the prevalence and treatment implications of CPTSD among current and ex-serving military members have not been established. Objective: The study aims were to a) establish the prevalence of provisional ICD-11 CPTSD diagnosis relative to PTSD in an Australian sample of treatment-seeking current and ex-serving military members, and b) examine the implications of CPTSD diagnosis for intake profile and treatment response. Methods: The study analysed data collected routinely from Australian-accredited treatment programmes for military-related PTSD. Participants were 480 current and ex-serving military members in this programmes who received a provisional ICD-11 diagnosis of PTSD or CPTSD at intake using proxy measures. Measures of PTSD symptoms, disturbances in self-organisation, psychological distress, mental health and social relationships were considered at treatment intake, discharge, and 3-month follow-up. Results: Among participants with a provisional ICD-11 diagnosis, 78.2% were classified as having CPTSD, while 21.8% were classified as having PTSD. When compared to ICD-11 PTSD, participants with CPTSD reported greater symptom severity and psychological distress at intake, and lower scores on relationship and mental health dimensions of the quality of life measure. These relative differences persisted at each post-treatment assessment. Decreases in PTSD symptoms between intake and discharge were similar across PTSD (dRM = −0.81) and CPTSD (dRM = −0.76) groups, and there were no significant post-treatment differences between groups when controlling for initial scores. Conclusions: CPTSD is common among treatment-seeking current and ex-serving military members, and is associated with initially higher levels of psychiatric severity, which persist over time. Participants with CPTSD were equally responsive to PTSD treatment; however, the tendency for those with CPTSD to remain highly symptomatic post-treatment suggests additional treatment components should be considered

Adherence to COREQ Reporting Guidelines for Qualitative Research: A Scientometric Study in Nursing Social Science

Qualitative research plays an important role in helping us describe, interpret and generate theories about complex phenomena in healthcare. Complete and transparent reporting of research informs readers about the significance and rigor of the work. The aim of this scientometric study was to determine the quality of reporting of qualitative research in nursing social science. Studies were identified by manually searching the table of contents for qualitative papers published in the June (or closest subsequent) 2018 issue of 115 nursing journals. Adherence with the 32-item Consolidated Criteria for REporting Qualitative (COREQ) research was determined for each study by two researchers. Additional information about the study (e.g., sample size, field of nursing) and the publishing journal (e.g., endorsement of COREQ) were also extracted. Using established criteria, COREQ compliance was coded either good (≥ 25 items), moderate (17 to 24), poor (9 to 16), very poor (≤ 8) based on the number of items addressed in each study. One hundred and ninety-seven manuscripts were included. The quality of reporting was generally rated as either moderate (57%) or poor (38%). Journal endorsement of qualitative reporting guidelines was associated with better reporting. The reporting of qualitative research in nursing social science journals is suboptimal. Researchers, authors, reviewers and journal editors need to ensure their papers comprehensively address the requirements of COREQ to ensure comprehensive and transparent reporting of their research

Radiomics biopsy signature for predicting survival in patients with spinal bone metastases (SBMs)

STUDY DESIGN: Retrospective analysis of a registered cohort of patients treated and irradiated for metastases in the spinal column in a single institute. OBJECTIVE: This is the first study to develop and internally validate radiomics features for predicting six-month survival probability for patients with spinal bone metastases (SBM). BACKGROUND DATA: Extracted radiomics features from routine clinical CT images can be used to identify textural and intensity-based features unperceivable to human observers and associate them with a patient survival probability or disease progression. METHODS: A study was conducted on 250 patients treated for metastases in the spinal column irradiated for the first time between 2014 and 2016, at the MAASTRO clinic in Maastricht, the Netherlands. The first 150 available patients were used to develop the model and the subsequent 100 patient were considered as a test set for the model. A bootstrap (B = 400) stepwise model selection, which combines both the forward and backward variable elimination procedure, was used to select the most useful predictive features from the training data based on the Akaike information criterion (AIC). The stepwise selection procedure was applied to the 400 bootstrap samples, and the results were plotted as a histogram to visualize how often each variable was selected. Only variables selected more than 90 % of the time over the bootstrap runs were used to build the final model. A prognostic index (PI) called radiomics score (radscore) and clinical score (clinscore) was calculated for each patient. The prognostic index was not scaled, the original values were used which can be extracted from the model directly or calculated as a linear combination of the variables in the model multiplied by the respective beta value for each patient. RESULTS: The clinical model had a good discrimination power. The radiomics model, on the other hand, had an inferior performance with no added predictive power to the clinical model. The internal imaging characteristics do not seem to have a value in the prediction of survival. However, the Shape features were excluded from further analyses in our study since all biopsies had a standard shape hence no variability

Radiomics biopsy signature for predicting survival in patients with spinal bone metastases (SBMs)

Study design: Retrospective analysis of a registered cohort of patients treated and irradiated for metastases in the spinal column in a single institute. Objective: This is the first study to develop and internally validate radiomics features for predicting six-month survival probability for patients with spinal bone metastases (SBM). Background data: Extracted radiomics features from routine clinical CT images can be used to identify textural and intensity-based features unperceivable to human observers and associate them with a patient survival probability or disease progression. Methods: A study was conducted on 250 patients treated for metastases in the spinal column irradiated for the first time between 2014 and 2016, at the MAASTRO clinic in Maastricht, the Netherlands. The first 150 available patients were used to develop the model and the subsequent 100 patient were considered as a test set for the model. A bootstrap (B = 400) stepwise model selection, which combines both the forward and backward variable elimination procedure, was used to select the most useful predictive features from the training data based on the Akaike information criterion (AIC). The stepwise selection procedure was applied to the 400 bootstrap samples, and the results were plotted as a histogram to visualize how often each variable was selected. Only variables selected more than 90 % of the time over the bootstrap runs were used to build the final model.A prognostic index (PI) called radiomics score (radscore) and clinical score (clinscore) was calculated for each patient. The prognostic index was not scaled, the original values were used which can be extracted from the model directly or calculated as a linear combination of the variables in the model multiplied by the respective beta value for each patient. Results: The clinical model had a good discrimination power. The radiomics model, on the other hand, had an inferior performance with no added predictive power to the clinical model. The internal imaging characteristics do not seem to have a value in the prediction of survival. However, the Shape features were excluded from further analyses in our study since all biopsies had a standard shape hence no variability