The role of depression in subsequent infertility, miscarriage and stillbirth remains unclear. This study aimed to examine the association of a history of depression with these adverse outcomes using a longitudinal cohort study of women across their reproductive life span.

This study used data from participants in the Australian Longitudinal Study on Women’s Health who were born in 1973–1978. Participants (N = 8707) were followed up every 3 years from 2000 (aged 22–27) to 2018 (aged 40–45). Information on a diagnosis of depression was collected from each survey, and antidepressant medication use was identified through pharmaceutical prescription data. Histories of infertility, miscarriage, and stillbirth were self-reported at each survey. Time-lagged log-binomial models with generalized estimating equations were used to assess the association of a history of depression up to and including in a given survey with the risk of fertility issues in the next survey.

Women with a history of depression (excluding postnatal depression) were at higher risk of infertility [risk ratio (RR) = 1.34, 95% confidence interval (CI): 1.21–1.48], miscarriage (RR = 1.22, 95%CI: 1.10–1.34) and recurrent miscarriages (≥2; RR = 1.39, 95%CI: 1.17–1.64), compared to women without a history of depression. There were too few stillbirths to provide clear evidence of an association. Antidepressant medication use did not affect the observed associations. Estimated RRs of depression with infertility and miscarriage increased with age.

A history of depression was associated with higher risk of subsequent infertility, miscarriage and recurrent miscarriages.

Auditory verbal hallucinations (AVHs) in schizophrenia have been suggested to arise from failure of corollary discharge mechanisms to correctly predict and suppress self-initiated inner speech. However, it is unclear whether such dysfunction is related to motor preparation of inner speech during which sensorimotor predictions are formed. The contingent negative variation (CNV) is a slow-going negative event-related potential that occurs prior to executing an action. A recent meta-analysis has revealed a large effect for CNV blunting in schizophrenia. Given that inner speech, similar to overt speech, has been shown to be preceded by a CNV, the present study tested the notion that AVHs are associated with inner speech-specific motor preparation deficits.

The present study aimed to provide a useful framework for directly testing the long-held idea that AVHs may be related to inner speech-specific CNV blunting in patients with schizophrenia. This may hold promise for a reliable biomarker of AVHs.

Hallucinating (n=52) and non-hallucinating (n=45) patients with schizophrenia, along with matched healthy controls (n=42), participated in a novel electroencephalographic (EEG) paradigm. In the Active condition, they were asked to imagine a single phoneme at a cue moment while, precisely at the same time, being presented with an auditory probe. In the Passive condition, they were asked to passively listen to the auditory probes. The amplitude of the CNV preceding the production of inner speech was examined.

Healthy controls showed a larger CNV amplitude (p = .002, d = .50) in the Active compared to the Passive condition, replicating previous results of a CNV preceding inner speech. However, both patient groups did not show a difference between the two conditions (p > .05). Importantly, a repeated measure ANOVA revealed a significant interaction effect (p = .007, ηp2 = .05). Follow-up contrasts showed that healthy controls exhibited a larger CNV amplitude in the Active condition than both the hallucinating (p = .013, d = .52) and non-hallucinating patients (p < .001, d = .88). No difference was found between the two patient groups (p = .320, d = .20).

The results indicated that motor preparation of inner speech in schizophrenia was disrupted. While the production of inner speech resulted in a larger CNV than passive listening in healthy controls, which was indicative of the involvement of motor planning, patients exhibited markedly blunted motor preparatory activity to inner speech. This may reflect dysfunction in the formation of corollary discharges. Interestingly, the deficits did not differ between hallucinating and non-hallucinating patients. Future work is needed to elucidate the specificity of inner speech-specific motor preparation deficits with AVHs. Overall, this study provides evidence in support of atypical inner speech monitoring in schizophrenia.

None Declared

Under enrollment of participants in clinical research is costly and delays study completion to impact public health. Given that research personnel make decisions about which strategies to pursue and participants are the recipients of these efforts, we surveyed research staff (n = 52) and participants (n = 4,144) affiliated with SPARK (Simons Foundation Powering Autism for Knowledge) – the largest study of autism in the U.S. – to understand their perceptions of effective recruitment strategies.

In Study 1, research personnel were asked to report recruitment strategies that they tried for SPARK and to indicate which ones they would and would not repeat/recommend. In Study 2, SPARK participants were asked to indicate all the ways they heard about the study prior to enrollment and which one was most influential in their decisions to enroll.

Staff rated speaking with a SPARK-study-team member (36.5%), speaking with a medical provider (19.2%), word of mouth (11.5%), and a live TV news story (11.5%) as the most successful strategies. Participants most often heard about SPARK via social media (47.0%), speaking with a medical provider (23.1%), and an online search (20.1%). Research personnel’s and participants’ views on effective recruitment strategies often differed, with the exception of speaking with a medical provider.

Results suggest that a combination of strategies is likely to be most effective in reaching diverse audiences. Findings have implications for the selection of strategies that meet a study’s specific needs, as well as recruitment-strategy “combinations” that may enhance the influence of outreach efforts.

Population-wide restrictions during the COVID-19 pandemic may create barriers to mental health diagnosis. This study aims to examine changes in the number of incident cases and the incidence rates of mental health diagnoses during the COVID-19 pandemic.

By using electronic health records from France, Germany, Italy, South Korea and the UK and claims data from the US, this study conducted interrupted time-series analyses to compare the monthly incident cases and the incidence of depressive disorders, anxiety disorders, alcohol misuse or dependence, substance misuse or dependence, bipolar disorders, personality disorders and psychoses diagnoses before (January 2017 to February 2020) and after (April 2020 to the latest available date of each database [up to November 2021]) the introduction of COVID-related restrictions.

A total of 629,712,954 individuals were enrolled across nine databases. Following the introduction of restrictions, an immediate decline was observed in the number of incident cases of all mental health diagnoses in the US (rate ratios (RRs) ranged from 0.005 to 0.677) and in the incidence of all conditions in France, Germany, Italy and the US (RRs ranged from 0.002 to 0.422). In the UK, significant reductions were only observed in common mental illnesses. The number of incident cases and the incidence began to return to or exceed pre-pandemic levels in most countries from mid-2020 through 2021.

Healthcare providers should be prepared to deliver service adaptations to mitigate burdens directly or indirectly caused by delays in the diagnosis and treatment of mental health conditions.

SPARK launched in 2016 to build a US cohort of autistic individuals and their family members. Enrollment includes online consent to share data and optional consent to provide saliva for genomic analysis. SPARK’s recruitment strategies include social media and support of a nation-wide network of clinical sites. This study evaluates SPARK’s recruitment strategies to enroll a core study population.

Individuals who joined between January 31, 2018, and May 29, 2019 were included in the analysis. Data include sociodemographic characteristics, clinical site referral, the website URL used to join, how the participant heard about SPARK, enrollment completion (online registration, study consents, and returning saliva sample), and completion of the baseline questionnaire. Logistic regressions were performed to evaluate the odds of core participant status (completing enrollment and baseline questionnaire) by recruitment strategy.

In total, 31,715 individuals joined during the study period, including 40% through a clinical site. Overall, 88% completed online registration, 46% returned saliva, and 38% were core participants. Those referred by a clinical site were almost twice as likely to be core participants. Those who directly visited the SPARK website or performed a Google search were more likely to be core participants than those who joined through social media.

Being a core participant may be associated with the “personal” connection and support provided by a clinical site and/or site staff, as well as greater motivation to seek research opportunities. Findings from this study underscore the value of adopting a multimodal recruitment approach that combines social media and a physical presence.

Designing and conducting clinical trials is challenging for some institutions and researchers due to associated time and personnel requirements. We conducted recruitment, screening, informed consent, study product distribution, and data collection remotely. Our objective is to describe how to conduct a randomized clinical trial using remote and automated methods.

A randomized clinical trial in healthcare workers is used as a model. A random group of workers were invited to participate in the study through email. Following an automated process, interested individuals scheduled consent/screening interviews. Enrollees received study product by mail and surveys via email. Adherence to study product and safety were monitored with survey data review and via real-time safety alerts to study staff.

A staff of 10 remotely screened 406 subjects and enrolled 299 over a 3-month period. Adherence to study product was 87%, and survey data completeness was 98.5% over 9 months. Participants and study staff scored the System Usability Scale 93.8% and 90%, respectively. The automated and remote methods allowed the study maintenance period to be managed by a small study team of two members, while safety monitoring was conducted by three to four team members. Conception of the trial to study completion was 21 months.

The remote and automated methods produced efficient subject recruitment with excellent study product adherence and data completeness. These methods can improve efficiency without sacrificing safety or quality. We share our XML file for researchers to use as a template for learning purposes or designing their own clinical trials.

This study aimed to analyse surgical outcomes of paediatric patients with congenital cholesteatoma according to age.

This was a retrospective study reviewing the records of 186 children (136 boys and 50 girls) from August 1993 to January 2016. Patients were divided into three age groups (equal to or less than 3 years, over 3 and less than 7 years, and 7 to 15 years).

There were significant differences in chief complaints, location of cholesteatoma in the middle ear, computed tomography findings, operation methods, ossicular erosion and type of cholesteatoma sac among the three groups. In addition, older age, open type cholesteatoma, ossicular erosion and mastoid invasion of cholesteatoma increased the recurrence rate after surgery. However, despite higher pre-operative air–bone gap in older children, hearing can be improved enough after proper surgery with ossicular reconstruction.

Delayed detection of paediatric cholesteatoma can lead to extensive disease and the need for an aggressive operation, which can result in worse hearing outcomes and an increased recurrence risk.

A proportion of patients with bipolar disorder (BD) manifests with only unipolar mania (UM). This study examined relevant clinical features and psychosocial characteristics in UM compared with depressive-manic (D-M) subgroups. Moreover, comorbidity patterns of physical conditions and psychiatric disorders were evaluated between the UM and D-M groups.

This clinical retrospective study (N = 1015) analyzed cases with an average of 10 years of illness duration and a nationwide population-based cohort (N = 8343) followed up for 10 years in the Taiwanese population. UM was defined as patients who did not experience depressive episodes and were not prescribed adequate antidepressant treatment during the disease course of BD. Logistic regression models adjusted for relevant covariates were used to evaluate the characteristics and lifetime comorbidities in the two groups.

The proportion of UM ranged from 12.91% to 14.87% in the two datasets. Compared with the D-M group, the UM group had more psychotic symptoms, fewer suicidal behaviors, a higher proportion of morningness chronotype, better sleep quality, higher extraversion, lower neuroticism, and less harm avoidance personality traits. Substantially different lifetime comorbidity patterns were observed between the two groups.

Patients with UM exhibited distinct clinical and psychosocial features compared with patients with the D-M subtype. In particular, a higher risk of comorbid cardiovascular diseases and anxiety disorders is apparent in patients with D-M. Further studies are warranted to investigate the underlying mechanisms for diverse presentations in subgroups of BDs.

Response to lithium in patients with bipolar disorder is associated with clinical and transdiagnostic genetic factors. The predictive combination of these variables might help clinicians better predict which patients will respond to lithium treatment.

To use a combination of transdiagnostic genetic and clinical factors to predict lithium response in patients with bipolar disorder.

This study utilised genetic and clinical data (n = 1034) collected as part of the International Consortium on Lithium Genetics (ConLi+Gen) project. Polygenic risk scores (PRS) were computed for schizophrenia and major depressive disorder, and then combined with clinical variables using a cross-validated machine-learning regression approach. Unimodal, multimodal and genetically stratified models were trained and validated using ridge, elastic net and random forest regression on 692 patients with bipolar disorder from ten study sites using leave-site-out cross-validation. All models were then tested on an independent test set of 342 patients. The best performing models were then tested in a classification framework.

The best performing linear model explained 5.1% (P = 0.0001) of variance in lithium response and was composed of clinical variables, PRS variables and interaction terms between them. The best performing non-linear model used only clinical variables and explained 8.1% (P = 0.0001) of variance in lithium response. A priori genomic stratification improved non-linear model performance to 13.7% (P = 0.0001) and improved the binary classification of lithium response. This model stratified patients based on their meta-polygenic loadings for major depressive disorder and schizophrenia and was then trained using clinical data.

Using PRS to first stratify patients genetically and then train machine-learning models with clinical predictors led to large improvements in lithium response prediction. When used with other PRS and biological markers in the future this approach may help inform which patients are most likely to respond to lithium treatment.