The COVID-19 pandemic and the menstrual cycle: research gaps and opportunities

International audienceSince the beginning of the COVID-19 pandemic, discussions on social media and blogs have indicated that women have experienced menstrual changes, including altered menstrual duration, frequency, regularity, and volume (heavier bleeding and clotting), increased dysmenorrhea, and worsened premenstrual syndrome. There have been a small number of scientific studies of variable quality reporting on menstrual cycle features during the pandemic, but it is still unclear whether apparent changes are due to COVID-19 infection/illness itself, or other pandemic-related factors like increased psychological stress and changes in health behaviours. It is also unclear to what degree current findings are explained by reporting bias, recall bias, selection bias and confounding factors. Further research is urgently needed. We provide a list of outstanding research questions and potential approaches to address them. Findings can inform policies to mitigate against gender inequalities in health and society, allowing us to build back better post-COVID

Effectiveness of mental health warnings on tobacco packaging in people with and without common mental health conditions:an online randomised experiment

BACKGROUND: Health warning labels on tobacco packaging are a cost-effective means of health risk communication. However, while an extensive range of physical health risks are well-portrayed via current tobacco health warnings in the UK, there are none that currently portray the negative impact of smoking on mental health. AIMS: (i) develop novel mental health warning labels for tobacco packaging and (ii) test perceptions of these warnings in smokers and non-smokers, with and without mental health problems. METHODS: Six mental health warning labels were developed with a consultancy focus group. These warning labels were tested in an online randomised experiment, where respondents (N = 687) rated six Mental Health Warning Labels (MHWLs) and six Physical Health Warning Labels (PHWLs) on measures of perceived effectiveness, believability, arousal, valence, acceptability, reactance and novelty of information. RESULTS: MHWLs were perceived as low to moderately effective (mean = 4.02, SD = 2.40), but less effective than PHWLs (mean = 5.78, SD = 2.55, p < 0.001, η(p)(2) = 0.63). MHWLs were perceived as less believable, arousing, unpleasant, and acceptable than PHWLs. MHWLs evoked more reactance and were rated as more novel. Perceptions of MHWLs did not differ in people with and without mental health problems except for reactance and acceptability, but consistent with the PHWL literature, perceptions of MHWLs differed between non-smokers and smokers. CONCLUSION: MHWLs could be an effective means to communicate novel information about the effects of smoking on mental health. MHWLs are perceived as less effective, believable, arousing, unpleasant, and acceptable than PHWLs, but MHWLs evoke more reactance and are rated as more novel

Smoking cessation for improving mental health

Background: There is a common perception that smoking generally helps people to manage stress, and may be a form of 'self‐medication' in people with mental health conditions. However, there are biologically plausible reasons why smoking may worsen mental health through neuroadaptations arising from chronic smoking, leading to frequent nicotine withdrawal symptoms (e.g. anxiety, depression, irritability), in which case smoking cessation may help to improve rather than worsen mental health. Objectives: To examine the association between tobacco smoking cessation and change in mental health. Search Methods: We searched the Cochrane Tobacco Addiction Group's Specialised Register, Cochrane Central Register of Controlled Trials, MEDLINE, Embase, PsycINFO, and the trial registries clinicaltrials.gov and the International Clinical Trials Registry Platform, from 14 April 2012 to 07 January 2020. These were updated searches of a previously‐conducted non‐Cochrane review where searches were conducted from database inception to 13 April 2012. Selection Criteria: We included controlled before‐after studies, including randomised controlled trials (RCTs) analysed by smoking status at follow‐up, and longitudinal cohort studies. In order to be eligible for inclusion studies had to recruit adults who smoked tobacco, and assess whether they quit or continued smoking during the study. They also had to measure a mental health outcome at baseline and at least six weeks later. Data Collection and Analysis: We followed standard Cochrane methods for screening and data extraction. Our primary outcomes were change in depression symptoms, anxiety symptoms or mixed anxiety and depression symptoms between baseline and follow‐up. Secondary outcomes included change in symptoms of stress, psychological quality of life, positive affect, and social impact or social quality of life, as well as new incidence of depression, anxiety, or mixed anxiety and depression disorders. We assessed the risk of bias for the primary outcomes using a modified ROBINS‐I tool. For change in mental health outcomes, we calculated the pooled standardised mean difference (SMD) and 95% confidence interval (95% CI) for the difference in change in mental health from baseline to follow‐up between those who had quit smoking and those who had continued to smoke. For the incidence of psychological disorders, we calculated odds ratios (ORs) and 95% CIs. For all meta‐analyses we used a generic inverse variance random‐effects model and quantified statistical heterogeneity using I2. We conducted subgroup analyses to investigate any differences in associations between sub‐populations, i.e. unselected people with mental illness, people with physical chronic diseases. We assessed the certainty of evidence for our primary outcomes (depression, anxiety, and mixed depression and anxiety) and our secondary social impact outcome using the eight GRADE considerations relevant to non‐randomised studies (risk of bias, inconsistency, imprecision, indirectness, publication bias, magnitude of the effect, the influence of all plausible residual confounding, the presence of a dose‐response gradient). Main Results: We included 102 studies representing over 169,500 participants. Sixty‐two of these were identified in the updated search for this review and 40 were included in the original version of the review. Sixty‐three studies provided data on change in mental health, 10 were included in meta‐analyses of incidence of mental health disorders, and 31 were synthesised narratively. For all primary outcomes, smoking cessation was associated with an improvement in mental health symptoms compared with continuing to smoke: anxiety symptoms (SMD −0.28, 95% CI −0.43 to −0.13; 15 studies, 3141 participants; I2 = 69%; low‐certainty evidence); depression symptoms: (SMD −0.30, 95% CI −0.39 to −0.21; 34 studies, 7156 participants; I2 = 69%' very low‐certainty evidence); mixed anxiety and depression symptoms (SMD −0.31, 95% CI −0.40 to −0.22; 8 studies, 2829 participants; I2 = 0%; moderate certainty evidence). These findings were robust to preplanned sensitivity analyses, and subgroup analysis generally did not produce evidence of differences in the effect size among subpopulations or based on methodological characteristics. All studies were deemed to be at serious risk of bias due to possible time‐varying confounding, and three studies measuring depression symptoms were judged to be at critical risk of bias overall. There was also some evidence of funnel plot asymmetry. For these reasons, we rated our certainty in the estimates for anxiety as low, for depression as very low, and for mixed anxiety and depression as moderate. For the secondary outcomes, smoking cessation was associated with an improvement in symptoms of stress (SMD −0.19, 95% CI −0.34 to −0.04; 4 studies, 1792 participants; I2 = 50%), positive affect (SMD 0.22, 95% CI 0.11 to 0.33; 13 studies, 4880 participants; I2 = 75%), and psychological quality of life (SMD 0.11, 95% CI 0.06 to 0.16; 19 studies, 18,034 participants; I2 = 42%). There was also evidence that smoking cessation was not associated with a reduction in social quality of life, with the confidence interval incorporating the possibility of a small improvement (SMD 0.03, 95% CI 0.00 to 0.06; 9 studies, 14,673 participants; I2 = 0%). The incidence of new mixed anxiety and depression was lower in people who stopped smoking compared with those who continued (OR 0.76, 95% CI 0.66 to 0.86; 3 studies, 8685 participants; I2 = 57%), as was the incidence of anxiety disorder (OR 0.61, 95% CI 0.34 to 1.12; 2 studies, 2293 participants; I2 = 46%). We deemed it inappropriate to present a pooled estimate for the incidence of new cases of clinical depression, as there was high statistical heterogeneity (I2 = 87%). Authors' Conclusions: Taken together, these data provide evidence that mental health does not worsen as a result of quitting smoking, and very low‐ to moderate‐certainty evidence that smoking cessation is associated with small to moderate improvements in mental health. These improvements are seen in both unselected samples and in subpopulations, including people diagnosed with mental health conditions. Additional studies that use more advanced methods to overcome time‐varying confounding would strengthen the evidence in this area.</p

IntEgrating Smoking Cessation treAtment into usual online Psychological care for people with common mEntal illness: Protocol for an online randomised feasibility and pilot study (ESCAPE digital)

Background In the UK, smoking prevalence in people with depression (34%) and anxiety (29%) is more than double that of the general population (13%). People who stop smoking improve their mental health with comparable effect sizes found for antidepressants. In England, online psychological therapy is a standard treatment for depression and anxiety. Online therapy is an acceptable setting for smoking cessation support; however, integrated smoking and mental health support is not available. This novel study aims to assess the acceptability and feasibility of an online smoking cessation intervention, and trial procedures, offered alongside online mental health treatment as it offers increased reach to people with common mental health difficulties who smoke. Methods A two-armed; Intervention (Integrated SilverCloud smoking cessation support) and control group (SilverCloud usual care), pragmatic, randomised controlled feasibility trial. We aim to recruit 500 adult smokers eligible for online mental health treatment. Follow-up will be conducted at 3-months and 6-months. We will assess the acceptability and feasibility of the trial procedures (i.e., recruitment, data completeness, self-reported acceptability and satisfaction) and the intervention (i.e., self-reported quit attempt, engagement with the smoking cessation and mental health programs, smoking cessation medicine and e-cigarette use, self-reported acceptability and satisfaction) and pilot clinical outcomes (i.e., biologically validated smoking abstinence, anxiety, depression, quality of health). Conclusion If the Trial is successful, a randomised controlled effectiveness trial will follow to examine whether integrated smoking cessation and mental health treatment increases smoking abstinence and improves depression and anxiety compared to usual care. Trial registration: ISRCTN10612149 (https://doi.org/10.1186/ISRCTN10612149), 02/02/2023

Combining data mining and text mining for detection of early stage dementia:the SAMS framework

In this paper, we describe the open-source SAMS framework whose novelty lies in bringing together both data collection (keystrokes, mouse movements, application pathways) and text collection (email, documents, diaries) and analysis methodologies. The aim of SAMS is to provide a non-invasive method for large scale collection, secure storage, retrieval and analysis of an individual’s computer usage for the detection of cognitive decline, and to infer whether this decline is consistent with the early stages of dementia. The framework will allow evaluation and study by medical professionals in which data and textual features can be linked to deficits in cognitive domains that are characteristic of dementia. Having described requirements gathering and ethical concerns in previous papers, here we focus on the implementation of the data and text collection components

Combining mouse and keyboard events with higher level desktop actions to detect mild cognitive impairment

We present a desktop monitoring application that combines keyboard, mouse, desktop and application-level activities. It has been developed to discover differences in cognitive functioning amongst older computer users indicative of mild cognitive impairment (MCI). Following requirements capture from clinical domain experts, the tool collects all Microsoft Windows events deemed potentially useful for detecting early clinical indicators of dementia, with a view to further analysis to determine the most pertinent. Further requirements capture from potential end-users has resulted in a system that has little impact on users? daily activities and ensures data security from initial recording of events through to data analysis. We describe two experiments: firstly, volunteers were asked to perform a short set of known tasks; the second (ongoing) experiment is a longitudinal study, with the software currently successfully running on participants? computers

Supplementary materials for "Smoking cessation for improving mental health"

Supplementary materials for the Cochrane Review, 'Smoking cessation for improving mental health'. The supplemental files include the modified ROBINS-I tool (S1) employed in the risk of bias assessments and justifications for modifications made to the ROBINS-I tool (S2). Also included are the tables containing the risk of bias judgements for studies contributing to the primary outcomes (S3 - S5) and summary tables for narrative outcomes in the review (S6 - S12).For details of the review methodology, please see the associated review

Known and unknown requirements in healthcare

We report experience in requirements elicitation of domain knowledge from experts in clinical and cognitive neurosciences. The elicitation target was a causal model for early signs of dementia indicated by changes in user behaviour and errors apparent in logs of computer activity. A Delphi-style process consisting of workshops with experts followed by a questionnaire was adopted. The paper describes how the elicitation process had to be adapted to deal with problems encountered in terminology and limited consensus among the experts. In spite of the difficulties encountered, a partial causal model of user behavioural pathologies and errors was elicited. This informed requirements for configuring data- and text-mining tools to search for the specific data patterns. Lessons learned for elicitation from experts are presented, and the implications for requirements are discussed as “unknown unknowns”, as well as configuration requirements for directing data-/text-mining tools towards refining awareness requirements in healthcare applications

Height, selected genetic markers and prostate cancer risk:Results from the PRACTICAL consortium

Background: Evidence on height and prostate cancer risk is mixed, however, recent studies with large data sets support a possible role for its association with the risk of aggressive prostate cancer. Methods: We analysed data from the PRACTICAL consortium consisting of 6207 prostate cancer cases and 6016 controls and a subset of high grade cases (2480 cases). We explored height, polymorphisms in genes related to growth processes as main effects and their possible interactions. Results: The results suggest that height is associated with high-grade prostate cancer risk. Men with height 4180cm are at a 22% increased risk as compared to men with height o173cm (OR 1.22, 95% CI 1.01–1.48). Genetic variants in the growth pathway gene showed an association with prostate cancer risk. The aggregate scores of the selected variants identified a significantly increased risk of overall prostate cancer and high-grade prostate cancer by 13% and 15%, respectively, in the highest score group as compared to lowest score group. Conclusions: There was no evidence of gene-environment interaction between height and the selected candidate SNPs. Our findings suggest a role of height in high-grade prostate cancer. The effect of genetic variants in the genes related to growth is seen in all cases and high-grade prostate cancer. There is no interaction between these two exposures.</p

ICF, An Immunodeficiency Syndrome: DNA Methyltransferase 3B Involvement, Chromosome Anomalies, and Gene Dysregulation

The immunodeficiency, centromeric region instability, and facial anomalies syndrome (ICF) is the only disease known to result from a mutated DNA methyltransferase gene, namely, DNMT3B. Characteristic of this recessive disease are decreases in serum immunoglobulins despite the presence of B cells and, in the juxtacentromeric heterochromatin of chromosomes 1 and 16, chromatin decondensation, distinctive rearrangements, and satellite DNA hypomethylation. Although DNMT3B is involved in specific associations with histone deacetylases, HP1, other DNMTs, chromatin remodelling proteins, condensin, and other nuclear proteins, it is probably the partial loss of catalytic activity that is responsible for the disease. In microarray experiments and real-time RT-PCR assays, we observed significant differences in RNA levels from ICF vs. control lymphoblasts for pro- and anti-apoptotic genes (BCL2L10, CASP1, and PTPN13); nitrous oxide, carbon monoxide, NF-κB, and TNFa signalling pathway genes (PRKCH, GUCY1A3, GUCY1B3, MAPK13; HMOX1, and MAP4K4); and transcription control genes (NR2F2 and SMARCA2). This gene dysregulation could contribute to the immunodeficiency and other symptoms of ICF and might result from the limited losses of DNA methylation although ICF-related promoter hypomethylation was not observed for six of the above examined genes. We propose that hypomethylation of satellite 2at1qh and 16qh might provoke this dysregulation gene expression by trans effects from altered sequestration of transcription factors, changes in nuclear architecture, or expression of noncoding RNAs