ALL Metrics
-
Views
-
Downloads
Get PDF
Get XML
Cite
Export
Track
Software Tool Article

Software for web-based tic suppression training

[version 1; peer review: 3 approved with reservations]
PUBLISHED 19 Dec 2017
Author details Author details
OPEN PEER REVIEW
REVIEWER STATUS

This article is included in the Tics collection.

Abstract

Exposure and response prevention (ERP) is a first-line behavior therapy for obsessive-compulsive disorder, and has also been tested in Tourette syndrome (TS). However, ERP for tic disorders requires intentional tic suppression, which for some patients is difficult even for brief periods. Additionally, practical access to behavior therapy is difficult for many patients, especially those in rural areas. The authors present a simple, working web platform (TicTrainer) that implements a strategy called reward-enhanced exposure and response prevention (RE–ERP). This strategy sacrifices most expert therapist components of ERP, focusing only on increasing the duration of time for which the user can suppress tics through automated differential reinforcement of tic-free periods (DRO). RE–ERP requires an external tic monitor, such as a parent, during training sessions. The user sees increasing digital rewards for longer and longer periods of successful tic suppression, similar to a video game score. TicTrainer is designed with security in mind, storing no personally identifiable health information, and has features to facilitate research, including optional masked comparison of tics during DRO vs. noncontingent reward conditions. A working instance of TicTrainer is available from https://tictrainer.com/

Keywords

behavior therapy, software, tic disorders, Tourette syndrome, reward

Introduction

Recent years have seen increasing evidence for and acceptance of behavior therapies for tic disorders such as Tourette syndrome (Capriotti et al., 2014). Tic suppression plays a key role in these therapies (Specht et al., 2014). One of these is exposure and response prevention (ERP), a first-line treatment for obsessive-compulsive disorder. ERP also showed similar tic reduction efficacy to the most extensively studied behavior therapy for tics in a randomized, controlled trial (Verdellen et al., 2004). However, tic suppression, an essential component of ERP, is difficult or frustrating for some tic patients. Fortunately, we showed that even children with recent-onset tic disorders could suppress tics when brief tic-free periods were rewarded immediately by small tokens (Greene et al., 2015). Our experience with that study, and in an unrelated project, suggested to us that automating the process of immediate rewards for tic-free intervals might facilitate ERP, even in those who at first could suppress tics only for a few seconds at a time (Black et al., 2017; Miller et al., 2015).

Here we present a simple, web-based tool to facilitate training intended to allow increasing periods of tic suppression. Design goals included using this program to record tics, to provide rewards for tic suppression in a video-game-like format that many children would be familiar with, to gradually increase rewards for increasing periods of tic suppression, to respect confidentiality, to gather anonymous information that can be used to assess use patterns and initial information about efficacy and safety, and to provide features that facilitate research use, i.e. creation of research subject accounts that can be assigned to different reward schedules at different points in time.

Methods

Implementation

The TicTrainer server is written in JavaScript, using the Node.js runtime.

Account registration and anonymity

The system is designed to ensure security of users’ personally identifying information. Instead of recording a name, each user is assigned a simple account ID used to log on. To track the collective age of users and to allow potential individualized training dependent on age, the user is asked his or her birth month and year. However, the system saves only a randomly chosen birthdate within 45 days of the 15th day of the month supplied.

Administrative accounts also can be created. Admins can flag certain users as research participants and assign them to receive rewards differently from regular users. They can also view system and session log files, or create another admin account.

Storing data

Each user and trainer account has its own text-based account data file on the server. This is a simple way to store modest amounts of data without using a database, at the possible expense of keeping numerous files open simultaneously if traffic to a single site becomes very heavy. System design may need to change if the number of users increases very substantially.

Logging on

A user’s ID, password, and other account information are sent back and forth as needed between client and server. When a user types his ID and password into the “Manage Account” sign in page, for example, the server sends back a unique web page that includes the credentials, as he/she provided them, and some information loaded from his/her account data. If he/she edits something in his/her account, those same credentials are sent back to the server for authentication along with the new data.

Any page on the website that has information specific to a signed-in user is created dynamically by the server. These dynamic web pages are stored as .dynh files on the server. (“.dynh” is a custom extension which stands for DYNamic Html.) These files have designated locations for the server to inject the required unique fields (usually these include the user’s ID and password) before sending the edited page back to the client. Almost every page involved in a training session is stored and generated this way by the server, so as to preserve the user’s credentials as he/she typed them at the beginning of the session.

During a session, the server mediates between the user and trainer via a session log file. When the trainer records a user’s tic, the trainer’s page sends an XMLHttpRequest asking the server to write a line to the log file. On the other side, the user’s page continually checks the session log file on the server for changes, so it can reset the rewards when the user tics and end the session when the trainer leaves. At the end of a session, the log file is archived with the end time in the filename.

Operation

TicTrainer runs on a node.js server. Users need a web browser that supports javascript. The program may not function properly on browsers that do not support HTML5, and currently does not work with Microsoft browsers.

Setting up

A visitor to TicTrainer first registers an account. User and trainer accounts are created separately. Either one next goes to the “Manage Account” page and links to another account. Specifically, trainers specify the users they train, and users specify the trainers that can train them.

Training sessions

During a session, the trainer is presented with two buttons: “Tic Detected,” and “End Session.” When “Tic Detected” is pressed, the server logs a tic. Trainers also see a 1-minute timer progressing continuously next to an “I’m Here” button, which restarts that timer (as does the “Tic Detected” button). If the trainer presses “End Session,” closes the page, or lets the “I’m Here” timer elapse, the session ends. The timer helps ensure that the trainer stays engaged in watching and recording the user’s tics.

The user’s session page displays a large counter for their current point total, followed by a superscript number indicating the current point accrual rate. Each time the user refrains from ticcing for a number of seconds equal to his/her level, their point total increases by the current rate, and the rate then increases by the square of the current level (rate is capped at 10 × levels2). Finally, a user “levels up” when his/her points exceed 1000 × levels2. He/she then also receives “coins” equal to the square of the previous level. The coins can be traded in for digital medals at an online store. Parents or clinicians may choose to provide tangible rewards for the digital coins or medals. The medals are displayed during training sessions and on the user’s “Manage Account” page. In total, this reward strategy is intended to provide users increasing incentives to suppress their tics for increasingly long intervals.

For potential use in controlled trials, research participant accounts can also be assigned to an alternative (control) reward strategy, noncontingent reward (Greene et al., 2015; Himle et al., 2008). In this case the admin user can set the initial mean frequency of rewards. This frequency may be set based on the participant’s previously recorded tic frequency, to better mask the treatment allocation. Thereafter the frequency of rewards increases automatically based on the subject’s achieved “level,” with the intention of approximately matching reward frequency with the two methods.

Use cases

Figure 1 shows a “user” window (for the person with tics) and a “trainer” window as they might appear during a session. Normally the two windows would appear on separate devices. This user is currently on level one, with 958 points, and is accruing 5 points for every second during which no tics are detected. This user has not yet earned any coins.

a62ace29-0186-45de-9536-c2d3a0ad6139_figure1.gif

Figure 1. Screenshots from a TicTrainer.com session.

Left: the “user” window (person with tics). Right: the “trainer” window (clinician or other trained observer). Typically the two windows would appear on separate devices.

Supplementary File 1 is a session log file for a test session (no human subjects were observed). Admin users can view or download these session log files, from which they can compute for each session any of the following:

  • measures of tic frequency and tic suppression, e.g.

    • mean frequency of tics

    • longest tic-free interval

    • number of 10-second tic-free intervals

  • number of rewards

  • other metrics, e.g.

    • tests of whether inter-tic intervals fit a fractal pattern (Peterson & Leckman, 1998)

    • tests of the timing of tics vis-à-vis timing of rewards

Conclusions

This simple web-based platform is available at TicTrainer.com, and provides features that allow prospective trials including with different reward schedules. Features that could yet be implemented include adding self-report (and/or trainer-report) measures of inter-session tic severity or of other symptoms, or measures of premonitory sensations/urge intensity before, during or after sessions (Himle et al., 2007; Specht et al., 2014; Verdellen et al., 2008).

Software availability

TicTrainer available from: https://tictrainer.com/

Source code available from https://github.com/jonkb/TicTrainer-node

Archived source code as at time of publication: http://doi.org/10.5281/zenodo.1098270 (Black, 2017).

License: MIT

Comments on this article Comments (0)

Version 2
VERSION 2 PUBLISHED 19 Dec 2017
Comment
Author details Author details
Competing interests
Grant information
Copyright
Download
 
Export To
metrics
Views Downloads
F1000Research - -
PubMed Central
Data from PMC are received and updated monthly.
- -
Citations
CITE
how to cite this article
Black JK and Black KJ. Software for web-based tic suppression training [version 1; peer review: 3 approved with reservations]. F1000Research 2017, 6:2150 (https://doi.org/10.12688/f1000research.13460.1)
NOTE: If applicable, it is important to ensure the information in square brackets after the title is included in all citations of this article.
track
receive updates on this article
Track an article to receive email alerts on any updates to this article.

Open Peer Review

Current Reviewer Status: ?
Key to Reviewer Statuses VIEW
ApprovedThe paper is scientifically sound in its current form and only minor, if any, improvements are suggested
Approved with reservations A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.
Not approvedFundamental flaws in the paper seriously undermine the findings and conclusions
Version 1
VERSION 1
PUBLISHED 19 Dec 2017
Views
15
Cite
Reviewer Report 15 Mar 2018
Cara W.J Verdellen, PsyQ Nijmegen, Nijmegen, The Netherlands 
Approved with Reservations
VIEWS 15
TicTrainer is developed to support exposure and response prevention (ERP) in the behavioral treatment of tics. ERP is considered a firstline intervention for tic disorders according to European Guidelines (Roessner et al; Verdellen et al, ESSTS, 2011). Patients are encouraged ... Continue reading
CITE
CITE
HOW TO CITE THIS REPORT
Verdellen CWJ. Reviewer Report For: Software for web-based tic suppression training [version 1; peer review: 3 approved with reservations]. F1000Research 2017, 6:2150 (https://doi.org/10.5256/f1000research.14616.r30608)
NOTE: it is important to ensure the information in square brackets after the title is included in all citations of this article.
  • Author Response (F1000Research Advisory Board Member) 06 Aug 2018
    Kevin J Black, Washington University School of Medicine, St. Louis, 63110, USA
    06 Aug 2018
    Author Response F1000Research Advisory Board Member
    TicTrainer is developed to support exposure and response prevention (ERP) in the behavioral treatment of tics. ERP is considered a firstline intervention for tic disorders according to European Guidelines (Roessner ... Continue reading
COMMENTS ON THIS REPORT
  • Author Response (F1000Research Advisory Board Member) 06 Aug 2018
    Kevin J Black, Washington University School of Medicine, St. Louis, 63110, USA
    06 Aug 2018
    Author Response F1000Research Advisory Board Member
    TicTrainer is developed to support exposure and response prevention (ERP) in the behavioral treatment of tics. ERP is considered a firstline intervention for tic disorders according to European Guidelines (Roessner ... Continue reading
Views
14
Cite
Reviewer Report 05 Mar 2018
Davide Martino, Department of Clinical Neurosciences, Cumming School of Medicine, Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada 
Approved with Reservations
VIEWS 14
The concept of the TicTrainer is highly valuable. Unfortunately I was unable to review the current version of the TicTrainer website directly due to issues with registration (it won’t accept ID – if crucial for this peer review, please provide ... Continue reading
CITE
CITE
HOW TO CITE THIS REPORT
Martino D. Reviewer Report For: Software for web-based tic suppression training [version 1; peer review: 3 approved with reservations]. F1000Research 2017, 6:2150 (https://doi.org/10.5256/f1000research.14616.r30850)
NOTE: it is important to ensure the information in square brackets after the title is included in all citations of this article.
  • Author Response (F1000Research Advisory Board Member) 06 Aug 2018
    Kevin J Black, Washington University School of Medicine, St. Louis, 63110, USA
    06 Aug 2018
    Author Response F1000Research Advisory Board Member
    The concept of the TicTrainer is highly valuable. Unfortunately I was unable to review the current version of the TicTrainer website directly due to issues with registration (it won’t accept ... Continue reading
COMMENTS ON THIS REPORT
  • Author Response (F1000Research Advisory Board Member) 06 Aug 2018
    Kevin J Black, Washington University School of Medicine, St. Louis, 63110, USA
    06 Aug 2018
    Author Response F1000Research Advisory Board Member
    The concept of the TicTrainer is highly valuable. Unfortunately I was unable to review the current version of the TicTrainer website directly due to issues with registration (it won’t accept ... Continue reading
Views
17
Cite
Reviewer Report 02 Feb 2018
Christine A. Conelea, Department of Psychiatry, University of Minnesota, Minneapolis, MN, USA 
Approved with Reservations
VIEWS 17
This paper describes TicTrainer, a newly created software program designed to track tic occurrences and deliver reward for successful suppression during live observation. Tic suppression contingent reward has reliably been shown to acutely enhance tic suppression in laboratory settings, but ... Continue reading
CITE
CITE
HOW TO CITE THIS REPORT
Conelea CA. Reviewer Report For: Software for web-based tic suppression training [version 1; peer review: 3 approved with reservations]. F1000Research 2017, 6:2150 (https://doi.org/10.5256/f1000research.14616.r30166)
NOTE: it is important to ensure the information in square brackets after the title is included in all citations of this article.
  • Author Response (F1000Research Advisory Board Member) 06 Aug 2018
    Kevin J Black, Washington University School of Medicine, St. Louis, 63110, USA
    06 Aug 2018
    Author Response F1000Research Advisory Board Member
    This paper describes TicTrainer, a newly created software program designed to track tic occurrences and deliver reward for successful suppression during live observation. Tic suppression contingent reward has reliably been ... Continue reading
  • Author Response (F1000Research Advisory Board Member) 07 Aug 2018
    Kevin J Black, Washington University School of Medicine, St. Louis, 63110, USA
    07 Aug 2018
    Author Response F1000Research Advisory Board Member
    Oops, that sentence should have read:
    "Higher levels give higher reward magnitude, but reward frequency is slower."
    Competing Interests: No competing interests were disclosed.
COMMENTS ON THIS REPORT
  • Author Response (F1000Research Advisory Board Member) 06 Aug 2018
    Kevin J Black, Washington University School of Medicine, St. Louis, 63110, USA
    06 Aug 2018
    Author Response F1000Research Advisory Board Member
    This paper describes TicTrainer, a newly created software program designed to track tic occurrences and deliver reward for successful suppression during live observation. Tic suppression contingent reward has reliably been ... Continue reading
  • Author Response (F1000Research Advisory Board Member) 07 Aug 2018
    Kevin J Black, Washington University School of Medicine, St. Louis, 63110, USA
    07 Aug 2018
    Author Response F1000Research Advisory Board Member
    Oops, that sentence should have read:
    "Higher levels give higher reward magnitude, but reward frequency is slower."
    Competing Interests: No competing interests were disclosed.

Comments on this article Comments (0)

Version 2
VERSION 2 PUBLISHED 19 Dec 2017
Comment
Alongside their report, reviewers assign a status to the article:
Approved - the paper is scientifically sound in its current form and only minor, if any, improvements are suggested
Approved with reservations - A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.
Not approved - fundamental flaws in the paper seriously undermine the findings and conclusions
Sign In
If you've forgotten your password, please enter your email address below and we'll send you instructions on how to reset your password.

The email address should be the one you originally registered with F1000.

Email address not valid, please try again

You registered with F1000 via Google, so we cannot reset your password.

To sign in, please click here.

If you still need help with your Google account password, please click here.

You registered with F1000 via Facebook, so we cannot reset your password.

To sign in, please click here.

If you still need help with your Facebook account password, please click here.

Code not correct, please try again
Email us for further assistance.
Server error, please try again.