Intergenerational Relations

This study evaluates the effectiveness of "ReFrame-R," a communication training program designed to help older adults in Hong Kong navigate intergenerational challenges. By focusing on enhancing communication competence and clarifying role boundaries within parent-child relationships, the research seeks to determine if this specialized intervention can improve the mental well-being of both older and younger generations. The study asks whether participating in the "ReFrame-R" curriculum leads to measurable improvements in how families interact, hypothesizing that older adults in the training group will demonstrate significantly better communication quality and a stronger sense of meaning compared to those in a control group. This study also aims to evaluate the program's overall feasibility and acceptability.

Generation Victoria (GenV) is a longitudinal, population-based study of Victorian children and their parents that will bring together data on a wide range of conditions ,exposures and outcomes. GenV blends study-collected, study-enhanced and linked data. It will be multi-purpose, supporting observational, interventional, health services and policy research within the same cohort. It is designed to address physical, mental and social issues experienced during childhood, as well as the antecedents of a wide range of diseases of ageing. It seeks to generate translatable evidence (prediction, prevention, treatments, services) to improve future wellbeing and reduce the future disease burden of children and adults. The GenV Cohort 2020s is open to all children born over a two-year period, and their parents, residing in the state of Victoria Australia. The GenV Cohort 2020s is preceded by an Advance Cohort of children born between 5 Dec 2020 and 3 October 2021, and their parents. This comprises all families recruited at GenV's Vanguard hospital (Joan Kirner Women's and Children's) and at birthing hospitals throughout Victoria as GenV scaled up to commence recruiting for the GenV Cohort 2020s. The Advance Cohort have ongoing and full participation in GenV for their lifetime unless they withdraw but may have less complete data and biosamples.

Gestational diabetes mellitus (GDM) is a transient hyperglycemic condition identified during pregnancy in women without a history of chronic diabetes. Evidence indicates that GDM can lead to various adverse health outcomes, including preterm birth, progression to pre-diabetes, and type 2 diabetes after delivery in mothers. Notably, GDM is becoming increasingly prevalent among Asian pregnant women due to rising rates of overweight and obesity, as well as genetic susceptibility. Despite growing recognition of GDM, its treatment efficiency and efficacy remain poor, primarily due to its heterogeneity, which is underpinned by various pathophysiological mechanisms. Therefore, a better understanding of GDM heterogeneity can aid clinicians in providing more targeted treatment and follow-up strategies for GDM mothers. This study aims to define GDM phenotypes based on in vivo cardio-metabolic profiles and treatment response during pregnancy, utilizing advanced technologies such as continuous glucose profiling and untargeted metabolite profiling. In this proposed 3-year pregnancy cohort study, the investigators will recruit 800 overweight or obese Asian pregnant women in early pregnancy, without a history of diabetes, and follow them through to delivery. The goal of the study is to develop systematic antenatal and postnatal screening, treatment, and intervention guidelines for mothers with GDM.

Older adult participants will engage in exercise videos twice a week for 8 weeks either while paired with a peer (same age group) or paired with a younger adult with the ability to simultaneously video chat while exercising.

The purpose of this work is to investigate how post-graduate doctors in training (PGDiTs) experience generational diversity with their colleagues in the workplace. The investigators want to explore and understand how PGDiTs perceive and experience generational diversity in the workplace and look into where these differences between generations could come from. The research team wants to do this by running focus groups. These focus groups would be made up of PGDiTs that are working within one hospital. The doctors will be split into the different generations (i.e. generation X, Y and Z). A set list of questions will be used to prompt and guide the focus group conversations. Each focus group will be audio-recorded using an electronic device and then analysed with the aid of computer software. The investigators will then generate themes from the data and use this to create an overall story of the data. It is hoped that this research can help inform supervisors and employers of the impact of generational diversity on on PGDiTs. This may be used to help develop ways of improving working relationships for PGDiTs with their supervisors and employers.