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A Python email automation system 📧 for sending customizable reminders to participants at different timepoints throughout a study

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📧 Automate Reminder Emails for Research Participants

AutoRemind is a Python email automation system for sending customizable reminders to participants at different timepoints throughout a study.

Check out AutoCalendar too!

⭐ Most Ideal For

This code was written for a very specific study protocol after a personally exasperating experience of manually emailing participants 😄 This system will be useful if your study is longitudinal and comprises of

  • Screening participants for eligibility
  • Sending different reminder emails for several sessions across a period of time

💡 Features

  1. Sends emails to inform participants of their eligibility
  2. Sends emails to participants to seek confirmation of their session slots
  3. Sends reminder emails to scheduled participants one day before each session
  4. Sends reminder emails to scheduled participants on the day of the session
    • The message template in autoremind.py has this as an email reminder to complete a health and travel declaration form on the morning of the experiment.

🎉 Try it Yourself

The example csv files in this repository are meant to facilitate trial-and-error with AutoRemind. Simply change the email entries in the csv files to your own email address to receive templates of the messages as laid out in autoremind.py. You would also need to have a secret.py file containing your gmail credentials. If an authentication error occurs, it is most likely because you have to change the settings in your gmail account to allow access to less secure apps.

In summary, you should have

  • Two separate files containing information of participants who are eligibile vs. ineligible (example_eligible.csv and example_ineligible.csv respectively)

    • Columns required for email customization:
      • Name
      • Email
  • One file containing information of scheduled participants:

    • Columns required for email customization:
      • Participant Name
      • Email
      • Phone
      • Session 1 Details: Date_Session1, Timeslot_Session1, Location_Session1
      • Session 2 Details: Date_Session2, Timeslot_Session2, Location_Session2
      • Timeslots Confirmed

If you have more than two sessions in your experiment, you can customize your own code to include them.

Code Structure

  • Extract participants:
    • get_new(): extracts email addresses of unread emails
    • get_participants(): imports csv files for eligible, non-eligible, and scheduled participants
  • Filter participants:
    • target_eligibility() identifies participants to be informed for being eligibility or non-eligible, with the ability to exclude participants who were already informed before.
    • target_confirmation() identifies participants who have been scheduled and need to be confirmed of their slots (if the column Timeslots Confirmed is No)
    • target_participants() identifies participants that need to be sent reminders today or tomorrow.
  • Execute Sending
    • send_research_info(): send emails to new email addresses regarding research participation information
    • send_inform_eligible(): send emails to participants based on whether they were eligible or not
    • send_session_confirmation(): send emails to seek confirmation of session slots from participants
    • send_session_reminder(): send reminder email one day before respective sessions (for now, the code accommodates only Session 1 and Session 2)
    • send_declaration_form(): send health and travel (for COVID-19) declaration forms on the day of the session

Execute It

These functions are then wrapped in autoremind(), which you can choose to control the sending of a certain type of emails. Running autoremind.py will mass send the desired mails to your participants together with printed feedback on how many subjects and exactly who were contacted, like so:

  • For example, if you only want to send one-day-prior and on-the-day reminders, and eligibility information, set send_reminders, send_eligible and send_forms to True. Once you're happy with the customization, you can execute the sending.
autoremind(participants_list, silent=False, send_research=False, send_eligible=True, send_reminders=True, send_forms=True)

### Printed feedback ###
2 eligible participants contacted.
3 ineligible participants contacted.
Sending successful eligibility outcome to: ['Subject11', 'Subject12']
Sending unsuccessful eligibility outcome to: ['Subject19', 'Subject20', 'Subject21']
one day before: No session 1 participants to be contacted.
one day before: 1 participants to be contacted for session 2.
Sending reminder emails to: ['Subject_3'].
experiment day: No session 1 participants to be contacted.
experiment day: 2 participants to be contacted for session 2.
Sending health and travel declaration forms to: ['Subject_1', 'Subject_2']
  • On the other hand, if you only want to send recruitment information to new email addresses (whose emails are still unread), set just send_research=True.
    • IMPORTANT: this is assuming ALL unread emails are indeed seeking recruitment information. Filter your inbox appropriately first e.g., make sure you read and reply to other types of emails.
autoremind(participants_list, silent=False, send_research=True, send_eligible=False, send_reminders=False, send_forms=False)

### Printed feedback ###
Retrieving unread emails
Sending research recruitment information to: ['[email protected]', '[email protected]']

✔️ Potential New Features for AutoRemind

  • Participants Scheduling
    • I have not yet thought of how best to automate the scheduling of participants for multiple sessions, assuming that the interval between these sessions needs to be within a certain range i.e., Session 1 must be a week before Session 2. If anyone has any ideas, feel free to open an issue in this repo!
  • Sending out Emails at Designated time
    • Not sure if I can do this with GitHub actions
  • Safety feature
    • Script to include parameters that allow True or False to activate only certain types of email actions. Defaults to False otherwise.

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