The AI-PROGNOSIS project explores the critical impact of sex and gender on Parkinson’s disease (PD), aiming to enhance diagnostic and treatment approaches by considering these important factors.

Sex differences, as biological aspects of a human being, have been found in numerous areas pertaining to disease presentation and provision of care. Research has found sex differences in symptoms and treatment complications. More severe and common symptoms for women are restless legs, pain, loss of taste and smell, fatigue, depression, constipation, weight change, and excessive sweating (Hyperhidrosis) (Martinez-Martin et al., 2012).

• Even though PD is 1.5 more common for men (Moisan et al., 2015), women have a more benign phenotype, possibly related to female estrogens, menopause and fertile life span, and with increased expectance of tremor (67%). Women have a higher risk of treatment-related complications, lower chances of effective treatment (Picillo et al., 2017), and faster disease progression (Dahodwala et al., 2018). There are known sex-related neurological differences in cortical thickness and connectivity in Parkinson's disease, which may have implications for diagnosis and treatment (Yadav et al., 2016). Further, motor symptoms such as tremor as initial symptom, reduced rigidity, and postural instability emerge later for females (Cerri et al., 2019).

• Sex, as well as gender considerations regarding social constructs such as expectations and behaviours stemming from sex differences, also impact the provision of care, when influencing patient-provider communication and non-pharmacological disease management (Göttgens et al., 2020). 

• There has been minimal sex and gender consideration in mHealth randomised controlled trials for chronic medical conditions like PD (Wang et al., 2020). Hence, such characteristics are important parameters for predictive models within the AI-PROGNOSIS project, and future sex differences will be identified to ensure inclusivity.

For the ideation and co-creation process for needs mapping, the inclusion of sex and gender-balanced groups has so far been considered when recruiting people with Parkinson's disease (PwPs), healthcare professionals (HCPs), and people without Parkinson's disease (PwoPs) for the AI-PROGNOSIS patient panel, as well as for interviews, workshops, and focus groups.

Demographics from collected data will also be considered when analysing the data, with a focus on sex and/or gender-shaped characteristics such as different needs, adherence, relationships, or other relevant behaviours stemming from gender or sex differences.