Lesbian, gay or bisexual identity as a risk factor for trauma and mental health problems in Northern Irish students and the protective role of social support

Background: People identifying as lesbian, gay or bisexual (LGB) have been shown to experience more trauma and poorer mental health than their heterosexual counterparts, particularly in countries with discriminatory laws and policies. Northern Ireland is a post-conflict region with high rates of trauma and mental health problems, as well as significant levels of prejudice against the LGB community. To date, no studies in Northern Ireland have compared trauma exposure, social support and mental health status of LGB students to their heterosexual peers. Objective: The present study aimed to assess whether LGB status was associated with more trauma exposure and poorer mental health, and whether social support mediated these associations. Method: The sample was comprised of 1,116 university students. Eighty-nine percent (n = 993) identified as heterosexual and 11% (n = 123) identified as LGB. Path analysis was used to test the hypotheses. Results: LGB status was significantly associated with increased trauma exposure and with symptoms of PTSD, depression and anxiety, but not with problematic alcohol use. These associations were mediated by social support from family only. Conclusions: These results evidence vulnerabilities among Northern Irish students identifying as LGB in relation to trauma and mental health compared with their heterosexual peers. However, social support from family has the potential to mitigate risk. Educational initiatives should raise awareness of the importance of familial support for LGB youth, and those young people who lack family support should be considered an at-risk group, warranting particularly intensive targeting by relevant supports

Readiness to change and deception as predictors of program completion in perpetrators of intimate partner violence

PurposeIntimate partner violence (IPV) is a global problem with severe health and human rights implications. However, prevention of IPV recidivism has proved difficult, with high levels of treatment non-adherence including failure to complete IPV perpetration programs.MethodThe present study involved gathering data from the records of 169 men convicted of perpetrating intimate partner violence in Northern Ireland. Using a hierarchical binary logistic regression, motivation/readiness to change, as measured by the pre-contemplative stage of the Rhode Island Change Assessment Scale (URICA), was investigated as a predictor of IPV intervention program completion. The analysis also included deception covariates (self-deception and impression management).ResultsThe results show that higher scores on the pre-contemplative subscale of the readiness to change scale were significantly associated with failure to complete the program, with an odds ratio of OR 0.93 (inverted OR = 1.08). The covariate self-deception was also significant in the final model, with higher scores in self-deception leading to an increased chance of non-completion, with an odds ratio of 0.89 (inverted OR = 1.12). A post-hoc Chi-Square test was carried out that showed treatment completers were less likely than non-completers to breach their probation conditions χ2(1, n = 148) = 69.85, p =  < 0.001.ConclusionDue to the potentially positive impact of completing an intervention program for IPV perpetrator outcomes, the present study is important in terms of indicating that motivational stage, as well as self-deception, are relevant to treatment compliance. This finding suggests that targeting areas such as treatment readiness and self-deception may lead to improved treatment adherence and IPV perpetrator rehabilitation

Adverse experiences and mental health problems in perpetrators of intimate partner violence in Northern Ireland: A latent class analysis

Background: Trauma and adverse experiences among perpetrators of intimate partner violence (IPV) have been associated with more serious patterns of offending. Objective: To examine 1) how traumatic and adverse experiences cluster together and co-occur among IPV perpetrators, and 2) whether different patterns of trauma exposure are associated with specific mental health problems. Participants and setting: The sample consisted of 405 convicted IPV perpetrators from Northern Ireland. Methods: Data was collected between 2018 and 2019. Latent class analysis identified typologies of exposure to traumatic and adverse experiences. A series of binary logistic regression analyses explored associations between the identified classes and five categories of probable mental health problems. Results: Three adversity classes were identified: a baseline class (59.2%), characterised by relatively low levels of exposure to most types of adversity; a ‘childhood adversity’ class (32.9%), with high levels of childhood adversity; and a ‘community violence and disadvantage’ class (7.9%), which had high probabilities of endorsing adversities related to economic hardship and community violence. Regression analyses showed that the childhood adversity class was significantly associated with increased likelihood of all categories of mental health problems, except for neurodevelopmental disorders (ORs = 1.77-3.25). The community violence and disadvantage class was significantly associated with probable mood and anxiety disorder (ORs 3.92 and 8.42, respectively). Conclusions: Different patterns of exposure to adversities were associated with distinct mental health problems in the present sample. Early intervention to prevent poly-victimisation, the clustering of adversities in childhood and the resulting accumulation of risk may be a useful component of preventive responses for IPV in Northern Ireland

Formation of a type 1 diabetes young adult patient and public involvement panel to develop a health behaviour change intervention: the D1 Now study

Plain English summary Many young adults with type 1 diabetes (T1D) find it hard to control their blood glucose levels. With lots of things going on in their lives, their diabetes is often not the most important thing to them. That means they do not always take care of their T1D, for example by going to clinic appointments. Young adults with T1D do not usually get the chance to make suggestions on how to improve diabetes services. Being involved could help young adults to shape the diabetes care services that support them. Since 2014 a diabetes research team based in Galway has been looking at ways to improve how diabetes services are delivered to young adults. Eight young adults (aged 18–25 years) with T1D called the Young Adult Panel (YAP) are members of this team and have helped design the “D1 Now” intervention which aims to improve diabetes services. The YAP came up with questions to ask other young adults with T1D, their families and friends and healthcare providers about their experiences of healthcare services and how these could be improved. The YAP also shared messages from the research at national conferences and on local radio. They helped with writing sections of a grant application to take this research work forward. Our experience has shown the importance of involving young adults with T1D in helping to design research focusing on ways to improve their diabetes service that will help them and other young adults to live with diabetes in the future. Abstract Background Research indicates that young adults (18–25 year olds) with type 1 diabetes (T1D) often disengage from health services and their general diabetes management. Involving young adults with T1D in co-designing research to develop a behaviour change intervention to improve engagement with health services could potentially improve overall self management and health. A local youth mental health organisation called Jigsaw, Galway developed a very successful model for involving users in service design and development. Based on this model, the aim was to form a Young Adult Panel (YAP) of 18–25 year olds with T1D and involve them in all aspects of a study to develop an intervention to improve health and wellbeing for young adults with T1D called D1 Now. Methods Recruitment of young adults was achieved through a multimedia campaign. A consultation event was organised, followed by interviews with interested young adults. A panel of 8 members was selected. Following initial training for YAP members in committee skills and an introduction to different research methods and terms, YAP members participated in different stages of the research process. They were represented on the research study steering group and attended research meetings. They developed research materials, reviewed and interpreted research findings and helped develop the online platform to enhance engagement between young adults and their diabetes healthcare providers. They contributed to an international consensus conference on health services delivery for young adults with T1D and wrote specific sections of a further grant application to test out the new intervention. Results As a direct result of the YAP, a meaningful dialogue has opened up between healthcare providers and young adults within the D1 Now research team. Their involvement has led to a better understanding of what needs to be achieved in order to improve health service delivery. They have been active members in co-designing a health behaviour change intervention to improve engagement between young adults with T1D and healthcare providers which will be evaluated in future research. Conclusion Through the formation of the YAP, we have demonstrated that involving young adults with T1D in healthcare research is feasible and productive

Training the next generation of psychotraumatologists: COllaborative Network for Training and EXcellence in psychoTraumatology (CONTEXT)

In this paper we present a description of the Horizon2020, Marie Skłodowska-Curie Action funded, research and training programme CONTEXT: COllaborative Network for Training and EXcellence in psychoTraumatology. The three objectives of the programme are put forward, each of which refers to a key component of the CONTEXT programme. First, we summarize the 12 individual research projects that will take place across three priority populations: (i) refugees and asylum seekers, (ii) first responders, and (iii) perpetrators and survivors of childhood and gender-based violence. Second, we detail the mentoring and training programme central to CONTEXT. Finally, we describe how the research, together with the training, will contribute towards better policy, guidelines, and practice within the field of psychotraumatology

AusTraits: a curated plant trait database for the Australian flora

INTRODUCTION AusTraits is a transformative database, containing measurements on the traits of Australia’s plant taxa, standardised from hundreds of disconnected primary sources. So far, data have been assembled from > 250 distinct sources, describing > 400 plant traits and > 26,000 taxa. To handle the harmonising of diverse data sources, we use a reproducible workflow to implement the various changes required for each source to reformat it suitable for incorporation in AusTraits. Such changes include restructuring datasets, renaming variables, changing variable units, changing taxon names. While this repository contains the harmonised data, the raw data and code used to build the resource are also available on the project’s GitHub repository, http://traitecoevo.github.io/austraits.build/. Further information on the project is available in the associated publication and at the project website austraits.org. Falster, Gallagher et al (2021) AusTraits, a curated plant trait database for the Australian flora. Scientific Data 8: 254, https://doi.org/10.1038/s41597-021-01006-6 CONTRIBUTORS The project is jointly led by Dr Daniel Falster (UNSW Sydney), Dr Rachael Gallagher (Western Sydney University), Dr Elizabeth Wenk (UNSW Sydney), and Dr Hervé Sauquet (Royal Botanic Gardens and Domain Trust Sydney), with input from > 300 contributors from over > 100 institutions (see full list above). The project was initiated by Dr Rachael Gallagher and Prof Ian Wright while at Macquarie University. We are grateful to the following institutions for contributing data Australian National Botanic Garden, Brisbane Rainforest Action and Information Network, Kew Botanic Gardens, National Herbarium of NSW, Northern Territory Herbarium, Queensland Herbarium, Western Australian Herbarium, South Australian Herbarium, State Herbarium of South Australia, Tasmanian Herbarium, Department of Environment, Land, Water and Planning, Victoria. AusTraits has been supported by investment from the Australian Research Data Commons (ARDC), via their “Transformative data collections” (https://doi.org/10.47486/TD044) and “Data Partnerships” (https://doi.org/10.47486/DP720) programs; fellowship grants from Australian Research Council to Falster (FT160100113), Gallagher (DE170100208) and Wright (FT100100910), a grant from Macquarie University to Gallagher. The ARDC is enabled by National Collaborative Research Investment Strategy (NCRIS). ACCESSING AND USE OF DATA The compiled AusTraits database is released under an open source licence (CC-BY), enabling re-use by the community. A requirement of use is that users cite the AusTraits resource paper, which includes all contributors as co-authors: Falster, Gallagher et al (2021) AusTraits, a curated plant trait database for the Australian flora. Scientific Data 8: 254, https://doi.org/10.1038/s41597-021-01006-6 In addition, we encourage users you to cite the original data sources, wherever possible. Note that under the license data may be redistributed, provided the attribution is maintained. The downloads below provide the data in two formats: austraits-3.0.2.zip: data in plain text format (.csv, .bib, .yml files). Suitable for anyone, including those using Python. austraits-3.0.2.rds: data as compressed R object. Suitable for users of R (see below). Both objects contain all the data and relevant meta-data. AUSTRAITS R PACKAGE For R users, access and manipulation of data is assisted with the austraits R package. The package can both download data and provides examples and functions for running queries. STRUCTURE OF AUSTRAITS The compiled AusTraits database has the following main components: austraits ├── traits ├── sites ├── contexts ├── methods ├── excluded_data ├── taxanomic_updates ├── taxa ├── definitions ├── contributors ├── sources └── build_info These elements include all the data and contextual information submitted with each contributed datasets. A schema and definitions for the database are given in the file/component definitions, available within the download. The file dictionary.html provides the same information in textual format. Full details on each of these components and columns are contained within the definition. Similar information is available at http://traitecoevo.github.io/austraits.build/articles/Trait_definitions.html and http://traitecoevo.github.io/austraits.build/articles/austraits_database_structure.html. CONTRIBUTING We envision AusTraits as an on-going collaborative community resource that: Increases our collective understanding the Australian flora; and Facilitates accumulation and sharing of trait data; Builds a sense of community among contributors and users; and Aspires to fully transparent and reproducible research of the highest standard. As a community resource, we are very keen for people to contribute. Assembly of the database is managed on GitHub at traitecoevo/austraits.build. Here are some of the ways you can contribute: Reporting Errors: If you notice a possible error in AusTraits, please post an issue on GitHub. Refining documentation: We welcome additions and edits that make using the existing data or adding new data easier for the community. Contributing new data: We gladly accept new data contributions to AusTraits. See full instructions on how to contribute at http://traitecoevo.github.io/austraits.build/articles/contributing_data.html