You’re an experienced data scientist or programmer? Help to improve wellbeing at scale.

Role: one-time gigs or part-time (amount of hours flexible), remote or Berlin/London
Salary: Volunteering, if that is not possible, up to 1.000 USD per sub-task available
Application Form (only 3 fields!)

Summary

You can apply within <5 min here.

We, at Rethink Wellbeing, are looking for programmers to help out with small tasks related to automating our data collection and data-analysis. At present, we provide participants with information about their mental health status and any progress they make. We would now also like to create overviews for facilitators and other admins to track the effectiveness of each session/program/cohort (i.e., how engaging peers found the content, whether peers felt supported).

Should You Apply?

Are you interested in improving community mental health? Then, apply now!

Due to our non-profit nature, we are looking for someone to donate a similar system, or to donate their time to help us set a new system up. If this is not possible, compensation is available.

We are looking for someone who is fairly confident they can set this up; we can’t provide any (non-emotional :) ) support, so this probably isn’t a good fit for people looking for their first or second project. If you have any further questions, please reach out to: contact@rethinkwellbeing.org

Why we think this role is high-impact

Rethink Wellbeing aims to improve welldoing by improving wellbeing. To achieve this, we use engaging, proven, and low-cost online programs with weekly sessions. Our programs use evidence-based psychological methods to help participants increase their mental health and productivity. We are currently in the process of automating the way in which we analyse quantitative and qualitative participant feedback for different sessions, programs, and groups of participants. This will improve the cost-effectiveness and quality of our programs.

Your Role

This is outdated, but there are similar tasks available.
Moving forward, we would like to automate the analysis of the session feedback. In other words, we would like to generate two separate reports detailing:

Group session feedback to be sent to the facilitator after the session (i.e., a summary of how individuals found the session). Reports should:
1. Summarise quantitative scores to show progress over time,
2. Highlight participants with scores that indicate a personal check-in is needed (i.e., they report low satisfaction or high distress in a session)
Facilitator feedback to be sent to their supervisor (i.e., how each facilitator found their group and how they think they did). Reports should:
1. Summarise quantitative scores to show progress over time,
2. Flag any concerning scores (i.e., if the facilitator thinks they performed poorly, if they were distressed during the session)

To be concrete, every week we send out two surveys (one to each peer, one to each facilitator). Responses are a mix of qualitative answers and numeric ones (i.e., likert scales). We want a system that analyses the quantitative responses, outputting a legible summary that can be used to improve the sessions, support facilitators and track progress. To clarify, an MVP would contain tables, whilst an ideal version would contain graphical representations of the data as well as standard descriptives (i.e., mean scores).

Ideally, the automation would be similar to our current system which was set up to analyse the surveys participants fill out before and after the program. It:

Records responses from a Google Form in a Google Sheet
Analyses the responses in the Google Sheet
Sends a PDF report by email to participants summarising their results

That said, if other tools would work better, we are open to adopting them. In the best case, we would have this system up and running by the end of May. Support maintaining our current system may also be requested, if this is the case more details will be provided, this would be optional.

Is this you?

We are excited to get to know you!

Apply here.

Thank you to Yonatan Cale for providing helpful feedback on this post.