Project Background and Description

Oral cancer is a major public health problem in India. It is estimated 267 million people in India use tobacco in some form with approximately 199 million people being users of smokeless tobacco alone. In 2018, India accounted for one-third of the global burden of oral cancer (OC) cases and mortality with 119,992 new cases and 72,616 deaths. More OC screenings are needed due to the high alcohol and tobacco consumption rates. Prevention, early detection through screenings, and timely and appropriate referrals to treatment are the most effective approaches to reducing OC morbidity and mortality. The most frequent risk factors for OC are frequent tobacco consumption (SLT or smoking), alcohol consumption, dietary deficiencies, positive family history of OC, viral infections like HPV, and poor oral hygiene.

OC-DETECT will provide a low-cost solution focused on improving education and providing family educators with skills to support a home-based screening for early OC detection for at-risk individuals. Innovative components include simple mHealth screenings for early detection. Screenings for tobacco and alcohol use, as well as signs and symptoms of OC, will be delivered via mobile devices and administered periodically by family members using a checklist screening instrument. The mobile app will provide a step-by-step guide for a family member to take multiple images of the oral cavity. These images will be stitched together to create a virtual 3D image of the patient’s mouth. Using an algorithm that incorporates the screening results in combination with the oral cavity photos, OC-DETECT will display a risk assessment (binary: low and high). All patients will be required to visit the doctor for an in-person appointment after this to confirm the diagnosis. OC-DETECT will also support education using microlearning content and provide in-app reminders to patients and family members to conduct routine screenings.

Project Scope

We have successfully developed low-fidelity wireframes for OCDETECT catering to three distinct end users: students (family members of at-risk individuals), clinicians, and community health workers (CHWs). To take our design to the next level, we are looking to collaborate with SpringBoard designers to enhance our existing low-fidelity wireframes and transform them into high-fidelity/interactive wireframes for user testing and development.

Preferred Team Member experience

1.    Team member has experience in wireframes design 

2.    Team member has experience in an educational domain or related project in area

3.    Team member with experience in concept design and creative thinking

4.    Individuals should be available during standard business hours, Monday-Friday ET, in order to attend these meetings (45 min/week other than the first meeting which will be 90 minutes long)

Deliverables

● Improved Low-fidelity Wireframes in Figma

● Interactive Wireframes in Figma

● Design system and style guides 

We will give them thorough background information on the project details and orient them with the project scope and deliverables. We will create a space where team members can communicate with Benten staff to clarify existing hurdles and questions.

 We will also conduct two meetings per week

• Status/Q&A Meeting (15 minutes): Schedule early in the week (Monday or Tuesday). This brief meeting will be held to discuss the goals for the week and address any questions or concerns. It will serve as an opportunity for everyone to stay updated on the progress and ensure alignment.
• Presentation and Feedback Meeting (30 minutes): Scheduled later in the week (Thursday or Friday). This meeting will provide an opportunity for you to present your work. It will allow for in-depth discussions and constructive feedback to refine further and improve the current system design