Can a Smartphone App That Includes a Chatbot-based Coachi... | NCT03384550

Status Module

Name	Class
CSS health insurance	UNKNOWN

Description Module

Detailed Description

Just-in-time adaptive interventions (JITAIs) have recently been proposed as framework for health interventions that exploit the potential of mobile health information and sensing technologies. By obtaining contextual information for example from smartphone sensors (e.g. location, time of day), a JITAI adapts the provision of interventions over time with the goal to deliver support when the person needs it most (state of vulnerability) and is most likely to be receptive (state of receptivity).

To facilitate the development of a JITAI for physical activity, the present study has the following objectives:

To quantify main effects and interactions of three intervention components of Ally, a mHealth intervention for physical activity.
To identify moderators for these intervention components to formulate evidence-based decision rules.
To train machine learning models that predict the user's state of receptivity

A micro-randomized trial design is used to meet the objectives of the study. Customers of a large Swiss health insurance company will use Ally over a 10-day baseline and a 6-week study period. During the baseline period, participants only have access to the dashboard of the app and no interventions are administered. During the intervention period, Ally provides daily personalized step goals and different interventions via an interactive chatbot interface based on the MobileCoach system (www.mobile-coach.eu). We investigate the following intervention components as between-subject or within-subject experimental factors during the intervention period: daily self-regulation coaching (two levels, within-subjects), a weekly planning intervention (3 levels, within-subjects) and different incentive strategies (3 levels, between-subjects).

Primary outcome will be the difference in achievement of the daily personalized step goal between intervention and control conditions for all intervention components. We expect all intervention components to increase the probability of goal achievement. Sensitivity analyses will be conducted for per protocol analysis and adjustment for covariates. Moderators of intervention components will be investigated exploratively.

To reach objective 3, we will collect a wide range of smartphone sensor data as well as usage logs of the Ally app throughout the study.

Arms/Interventions Module

Arm Groups

Label	Type	Description	Intervention Names
Control	Active Comparator	Participants in this arm receive no incentives. As all participants, participants in this arm receive self-regulation coaching on 50% of the days during the intervention period. For each participant, days during the intervention period are randomly allocated to a coaching or a no coaching condition using an allocation ratio of 1:1. As all participants, participants in this arm also receive either an action planning, a coping planning or no planning condition each Sunday during the intervention period. Participants are randomized to one out of nine sequences of planning interventions according to a uniform and strongly balanced intervention schedule	Behavioral: Self-regulation coaching Behavioral: Planning
Financial Incentives	Experimental	Participants in this arm receive financial incentives. As all participants, participants in this arm receive self-regulation coaching on 50% of the days during the intervention period. For each participant, days during the intervention period are randomly allocated to a coaching or a no coaching condition using an allocation ratio of 1:1. As all participants, participants in this arm also receive either an action planning, a coping planning or no planning condition each Sunday during the intervention period. Participants are randomized to one out of nine sequences of planning interventions according to a uniform and strongly balanced intervention schedule	Behavioral: Self-regulation coaching Behavioral: Planning Behavioral: Financial Incentives
Charity Incentives	Experimental	Participants in this receive charity incentives. As all participants, participants in this arm receive self-regulation coaching on 50% of the days during the intervention period. For each participant, days during the intervention period are randomly allocated to a coaching or a no coaching condition using an allocation ratio of 1:1. As all participants, participants in this arm also receive either an action planning, a coping planning or no planning condition each Sunday during the intervention period. Participants are randomized to one out of nine sequences of planning interventions according to a uniform and strongly balanced intervention schedule

Interventions

Name	Type	Description	Arm Group Labels	Other Names
Self-regulation coaching	Behavioral	Short (2-5 min.) dialogue with the digital coach who provides information relevant for behavioral self-regulation, such as a goal reminder, the distance between the current step count and the goal and strategies to increase daily steps. Participants are randomized to self-regulation coaching or control (no coaching) on a daily basis.

Measure	Description	Time Frame
Daily goal achievement	Goal achievement will be assessed daily by comparing participants daily step count to the respective individualized step goal	seven weeks

Measure	Description	Time Frame
Steps per day	Steps will be measured daily via the GoogleFit or Apple Health application using the smartphone's built-in accelerometer	seven weeks
Behavioral regulation in physical activity

Eligibility Module

Name	Affiliation	Role
Tobias Kowatsch, PhD	University of St.Gallen	Principal Investigator

Facility	Status	City	State	ZIP	Country	Contacts
Center for Digital Health Interventions		Sankt Gallen		9000	Switzerland

References Module

Citations

PubMed Identifier	Type	Citation	Retractions
32182353	Derived	Kramer JN, Kunzler F, Mishra V, Smith SN, Kotz D, Scholz U, Fleisch E, Kowatsch T. Which Components of a Smartphone Walking App Help Users to Reach Personalized Step Goals? Results From an Optimization Trial. Ann Behav Med. 2020 Jun 12;54(7):518-528. doi: 10.1093/abm/kaaa002.
30702430	Derived	Kramer JN, Kunzler F, Mishra V, Presset B, Kotz D, Smith S, Scholz U, Kowatsch T. Investigating Intervention Components and Exploring States of Receptivity for a Smartphone App to Promote Physical Activity: Protocol of a Microrandomized Trial. JMIR Res Protoc. 2019 Jan 31;8(1):e11540. doi: 10.2196/11540.

IPD Sharing Statement Module

Behavioral regulation in physical activity will be measured using the second version of the Behavioral Regulation in Exercise Questionnaire (BREQ-2). The BREQ-2 consists of five subscales which represent different forms of regulation along the extrinisc-intrinsic continuum of motivation. Because the external regulation subscale in the BREQ-2 exclusively relates to external regulation by other people, it is substituted by the corresponding sub-scale of the Situational Motivation Scale (SIMS). Scores will be reported for each subscale separately. Answers are given on a five-point likert scale with the endpoints 0-not true for me and 4-very true for me.

Scores range from 0 to 16 for the subscales amotivation, external regulation, identified regulation and intrinsic regulation and from 0-12 for the subscale introjected regulation with higher scores representing a stronger manifestation of the respective form of regulation.