pathway: Psychology

My research investigates the links between music listening, mood and mental health. I’m using the ‘Mood Music’ dataset collected at the University of Bristol, which consists of music streaming histories from Spotify, Ecological Momentary Assessment of mood, and mental health survey data. The music streaming data and time-sensitive mood data form two parallel time series, which is a novel combination of music and mood data allowing for causal analyses. I will investigate causal links between music and mood, how this may be influenced by personality or mental health, and other factors such as lyrical sentiment.

My research centres around social and moral development in children and adolescents, focusing on the development of speciesism, that being the varying treatment of animals based on species membership. Adults appear to be speciesist, for example having some animals as pets whilst eating others, but little work has investigated how children and adolescents view different animal species. My PhD research will investigate these concepts and uncover whether children and adolescents differ from adults in this regard.

Autistic individuals are more vulnerable to sexual abuse (SA) and rape and serious sexual offences (RaSSO) than non-autistic individuals, yet the extent to which factors predict this is unclear. Also, autistic victim-survivors’ experiences with the criminal justice system (CJS) are unknown. Aims: identify factors predicting autistic people’s vulnerability to RaSSO/SA; understand the experiences of autistic victim-survivors from multiple perspectives; and co-produce materials to improve CJS outcomes. Methods: a review identifying factors contributing to RaSSO in autistic individuals; a comparison of abuse recognition between autistic and non-autistic individuals; interviews with autistic victim-survivors, their parents/supporters, and CJS professionals; co-production to develop materials.

I will investigate the development of cognitive processes in children that support attention management, planning and problem-solving, called Executive Functions (EFs). Three key EFs are working memory, inhibitory control and shifting (or cognitive flexibility). I will explore how they develop and interact, evaluating the overall structure of EF. To do this, I will develop new cognitive tasks that combine visual and sound prompts to measure different kinds of EF in pre-school age children. I am hoping to gain new insight into how EF develops and is structured, informing more effective early strategies supporting learning and socialising in young children.

My research explores how cannabis use contributes to the development of psychosis using a new, standardised measure of cannabis exposure: Standard THC Units. Similar to standard alcohol units, this metric enables consistent assessment of cannabis use across studies. I apply it to quantify the risk of developing psychotic-like experiences in the general population and first-episode psychosis in clinical samples. Combining large-scale data analysis with interviews of individuals with psychosis, my work examines the transition from early symptoms to clinical disorder. This research aims to guide clinicians, support evidence-based policy, and establish safer cannabis use guidelines worldwide.

My name is Mohsen Rajabi, a doctoral researcher at the Department of Psychology at the University of Bath. My PhD research explores how caregivers and peers influence refugee children’s recovery from PTSD in resource-poor settings in low- and middle-income countries (LMICs). Trauma-exposed children often rely on social support, mainly from parents and peers, to cope with trauma-related distress. While evidence from high-income countries shows that caregiver responses impact child PTSD, little is known about these dynamics in socio-economically disadvantaged areas. Using qualitative interviews and a longitudinal assessment of refugee caregivers, my study aims to further understand parental and peer influences on children’s post-trauma recovery and inform culturally appropriate support strategies.

My research responds to the urgent need for climate action by investigating relationships between individuals’ efficacy beliefs and diverse types of pro-environmental behaviour. While current efforts prioritize consumer behaviours, my research explores typically overlooked influence and citizenship behaviours, like talking about climate change and activism. Drawing on social psychological theories, I aim to provide a comprehensive understanding of the relationships between different types of efficacy and climate actions, considering sociodemographic and contextual influences. Using findings from focus groups and surveys, I will develop and test interventions that increase efficacy and foster more effective, fairer climate action amongst different sociodemographic groups.

My research explores the menstrual experiences of people with trauma and/or mental illness using a feminist, survivor led approach. Mental and menstrual health are known to be closely interrelated. Additionally, suffering trauma is linked to higher incidence of menstrual disorders, problematic experiences and early menarche. However, there is a lack of qualitative research considering lived experiences at the intersections of menstruation, mental illness and trauma. Through my PhD, I will use mixed methods, including photographic and creative research methods, to research the lived experience of menstruation, trauma and mental illness.

Despite UK government efforts to promote inclusion, autistic children often face unfair treatment in schools. This research examines if and how educators hold biases towards autistic students. First, I will assess how educator bias is mediated by educators’ self-esteem and how this bias may impact decision-making around support for autistic children. Second, I will analyse the language used in autism teacher training programs and consider teachers’ and autistic young peoples’ perspectives of language used in schools to discuss and describe autistic children. This research aims to identify and address biases in education, to improve health and education outcomes for autistic children.

My research focuses on understanding and improving human memory by enhancing police lineup procedures with AI. I will conduct studies to explore ways to create fairer lineups that reduce biases and misidentifications common in traditional methods. To support this, I’m deveoping a Python module called pyWitnessAI, which can handle tasks like generating lineups using various AI-related strategies. The work aims to make a more controllable and unbiased system, promoting open and transparent science, ultimately benefiting individuals and our society.