Abstract

Literature suggests that patients from deprived backgrounds are less likely to adhere to their treatments, continue to expose themselves to risk factors and, as a result, have poorer health outcomes. It is therefore crucial to identify these vulnerable populations early on, in order to provide them with tailored and reinforced care. The primary aim of this research is to construct and validate a systematic screening tool for identifying patients at highest risk of social vulnerability due to deprivation, through the use of psychometric techniques. This tool is intended to be easily used by healthcare professionals, to provide tailored and targeted care throughout the patient's journey. This study involves the development and assessment of a screening tool, along with a self-questionnaire and a decision support tool incorporating an artificial neural network. It is a prospective, monocentric, 2-stage psychometric validation study. This study has demonstrated the successful development of the self-questionnaire using psychometric methodology. The tool was found a good performance in screening social vulnerabilities. This validated self-questionnaire is an easy-to-use tool, allowing systematic screening for social vulnerabilities for cancer patients. This early identification allows to reinforce patient's pathway in order to avoid disruption. The integration of the tool in an artificial neuron network system allows to automate and disseminate this method of deprived patients' detection, while limiting the workload for the staff.

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.