To develop and validate the Internalised Stigma Scale for Gestational Diabetes Mellitus (ISS-GDM), a questionnaire measuring self-reported internalised stigma among women with prior gestational diabetes mellitus (GDM). We hypothesised that internalised GDM stigma could be reliably and validly assessed through a short psychometric instrument.

Cross-sectional validation study.

Follow-up data from the Danish, multicentre Face-it trial for women with prior GDM and their families.

In total, 248 women completed the ISS-GDM approximately 1 year after their GDM affected pregnancy.

The primary outcome was psychometric properties of the ISS-GDM, assessed using Cronbach’s alpha, confirmatory factor analysis (CFA) and Rasch analysis (RA). Secondary outcomes included identification of item anomalies (local response dependence, differential item functioning).

A large proportion of respondents endorsed statements reflecting self-disappointment, self-blame and an altered self-perception. Less endorsed statements included feeling inferior to other mothers or guilt towards family members due to GDM. The ISS-GDM demonstrated satisfactory psychometric properties. CFA indicated that item 2 assessing self-perceived capabilities as a mother did not load onto the main factor, while CFA and RA identified local response dependence and differential item functioning by body mass index. After adjustments, a two-factor solution supported calculating a sum score of items 1 and 3–11, with item 2 retained as a stand-alone indicator of perceived parenting capabilities. The 10-item scale demonstrated acceptable reliability (Cronbach’s alpha=0.78).

The ISS-GDM is a reliable and valid tool for assessing internalised stigma among women with prior GDM. Our findings further suggest that a substantial proportion of women with prior GDM experience self-blame and an altered self-perception due to their diagnosis. The ISS-GDM scale enables research into its prevalence, severity and consequences.

Mental health issues such as depression and anxiety are highly and disproportionally prevalent among university students. Beyond the academic rigour, stressors imposed by a new environment result in them being vulnerable to the onset and manifestation of mental health symptomatology. Leveraging smartphones and wearables for digital phenotyping capabilities is an innovative approach for monitoring and intervening in the mental health conditions of university students. This provides a unique opportunity to collect and identify digital and behavioural biomarkers, subsequently enabling the development of predictive models to identify university students at risk.

This study—Brightline—will employ an observational study design over a 6-month period, recruiting 500 students from a major public university in Singapore. Passive data collection will occur continuously throughout the monitoring period through a wearable device (Fitbit Charge 6) and smartphone sensors via the Brightline app, which uses a digital phenotyping data collection platform. Active data collection will consist of self-report questionnaires to be completed at the beginning of the study and follow-up assessments at 1, 3 and 6 months after. The passive and active data collected will be analysed to identify the digital biomarkers associated with depression, anxiety, stress, loneliness and affect among university students. Predictive models of these mental health issues will also be developed.

This study was approved by the Nanyang Technological University Institutional Review Board (IRB-2023-894). Findings from this study will be published in peer-reviewed journals and presented at academic conferences.

NCT06770075.