Systematic Review of Health App Gamification for Lifestyle Intervention Adherence

November 17, 2020 updated by: John Sievenpiper, University of Toronto

Use of Gamification in Health Apps for Lifestyle Intervention: A Systematic Review

Health behaviour applications (also referred to as "apps") have the potential to provide several advantages for motivating behaviour change for health and well-being. Finding ways to increase and sustain health promoting behaviour changes has been a challenge during health app development. Gamification, which is the use of game elements in a non-game situation, shows promise and has proven effective in many fields. However, key questions remain concerning how to use gamification in apps to modify health behaviour, especially to support adherence to dietary pattern recommendations. To investigate and summarize the current evidence, a systematic review of the totality of evidence from clinical trials and observational studies will be conducted to capture and distinguish the types of gamification strategies that may be most effective in improving and sustaining health promoting behaviours to inform future health behaviour app development.

Study Overview

Status

Unknown

Intervention / Treatment

Detailed Description

Background: Studies on health behaviours such as physical activity and smoking cessation (behaviour change) have indicated that gamification is an effective tool for engagement and behaviour change, especially when multiple different competitive elements are used including: a ranking system, badges and achievements, points, social media interaction, and leveling up. Gamification is the use of game elements in a non-game environment to invoke behaviour change. The majority of health-focused gamification investigations are currently conducted using web or mobile-based delivery platforms in adults focusing on physical activity. Access to these web and mobile based applications through smartphones, tablets and computers has grown rapidly. In 2016, 94% of Canadians had home internet access, with 88% reporting that they use a smartphone for personal use. Moreover, a recent survey in the US found that 73% of those with, or at risk of cardiovascular disease, have a smartphone and 43% use a health-related application to track progress towards a health goal. While research on mobile-based app use for modifying diet is promising, the effectiveness of using gamification in apps for sustaining dietary pattern adherence is unclear. An investigation and summary of the current types of gamification strategies that may be most effective is important to inform and aid future app development. The ultimate aim of this research investigation is to inform the development of the PortfolioDiet.app, a dietary pattern adherence application for reducing LDL-cholesterol in individuals at risk for cardiovascular disease.

Objective: To conduct a systematic review investigating the gamification strategies used in applications for long term behaviour change, with a specific focus on dietary pattern adherence in adults.

Design: A systematic review of the literature will be conducted according to the Cochrane Handbook for Systematic Reviews of Interventions and reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA).

Data sources: MEDLINE, EMBASE, and The Cochrane Central Register of Controlled Trials (Clinical Trials; CENTRAL) will be searched using appropriate search terms supplemented by hand searches of references of included studies.

Study selection: The investigators will include prospective cohort studies and controlled trials. Studies will be included if they are >= 2-months in duration and assess the relation of different gamification strategies used in health behaviour applications with adherence to the health intervention, participant engagement with using the application, and/or the intended health outcome. There will be no language restrictions.

Data extraction: Two or more investigators will independently extract relevant data and assess risk of bias using the Cochrane Risk of Bias Tool. All disagreements will be resolved by consensus.

Outcomes: The primary outcome will be adherence to the intervention associated with use of the application, such as, but not limited to: physical activity, smoking cessation, increasing fruit and vegetable intake, improving healthy food index score. Secondary outcomes will include participant engagement with use of the application. This adherence to using the application may be determined based on number of using days using the application compared to intended number of days of application usage. Observation of a significant change in the intended health outcome, such as, blood glucose, HbA1c, blood lipids, weight change [BMI, body weight, waist circumference, will also be assessed.

Data Synthesis: A Microsoft Excel spreadsheet will be used to track the extractions and summarize the qualitative and quantitative data from each study.

Risk of Bias (Quality) Assessment: The risk of bias of each included study will be assessed using the Cochrane Handbook for Systematic Reviews of Interventions. This will be done in relation to evaluating the criteria for assessing risk as either low, high or uncertain risk of bias as identified in the Risk of Bias tool.

Knowledge translation plan: The results will be disseminated through interactive presentations at local, national and international scientific meetings and publication. As well as utilized in a publically available web-based application hosted on the Canadian Cardiovascular Society website.

Significance: Gamification has been identified as a promising tool for health promotion. While research directly comparing gamified interventions to non-gamified controls has found beneficial effects on physical activity, or more recently mental health, there is a lack of evidence on investigating gamification for dietary change. As poor health behaviours (i.e. unhealthy diet, smoking, sedentary behaviour) have been repeatedly identified as major contributors to disease burden in Canada and globally, interventions which can target and improve these behaviours over a long term are required. Furthermore, as the generations who have grown up with the internet and app technology begin to age they will seek engaging digital tools to improve health outcomes, and therefore the need for digital health interventions that are effective at improving and sustaining beneficial health behaviours will only continue to grow.

Study Type

Observational

Enrollment (Anticipated)

100

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Locations

    • Ontario
      • Toronto, Ontario, Canada, M5C 2T2
        • Clinical Nutrition and Risk Factor Modification Centre, St. Michael's Hospital

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

14 years and older (Adult, Older Adult)

Accepts Healthy Volunteers

No

Genders Eligible for Study

All

Sampling Method

Probability Sample

Study Population

All adults (>=18 years), regardless of health status.

Description

Inclusion Criteria for controlled trials:

  • Randomized and non-randomized controlled intervention studies in humans
  • Gamification intervention
  • Presence of an adequate comparator, such as standard of care or an application without gamification components
  • Intervention duration >=2 months
  • Viable outcome data

Inclusion Criteria for prospective cohort studies:

  • Prospective cohort studies
  • Duration >= 2-months
  • Assessment of the exposure of gamification used in a health behaviour application
  • Ascertainment of viable outcome data by level of exposure

Exclusion Criteria for controlled trials:

  • Lack of an adequate comparator
  • Non-health behaviour application

Exclusion Criteria for prospective cohort studies:

  • Ecological, cross-sectional, or retrospective observational studies
  • Intervention studies

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

  • Observational Models: Other
  • Time Perspectives: Prospective

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Adherence to the intervention
Time Frame: At least 2 months
Percentage change
At least 2 months

Secondary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Participant app engagement
Time Frame: At least 2 months
Adherence to using the app based on number of using days using the app compared to intended number of days of app usage
At least 2 months
Health outcome - body weight
Time Frame: At least 2 months
Weight change
At least 2 months
Health outcome - BMI
Time Frame: At least 2 months
BMI change
At least 2 months
Health outcome - body fat
Time Frame: At least 2 months
Body fat change
At least 2 months
Health outcome - waist circumference
Time Frame: At least 2 months
Waist circumference
At least 2 months
Health outcome - HbA1c
Time Frame: At least 2 months
HbA1c change
At least 2 months
Health outcome - fasting plasma glucose (FPG)
Time Frame: At least 2 months
FPG change
At least 2 months
Health outcome - LDL-cholesterol (LDL-C)
Time Frame: At least 2 months
LDL-C change
At least 2 months
Health outcome - non-HDL-cholesterol (non-HDL-C)
Time Frame: At least 2 months
Non-HDL-C change
At least 2 months
Health outcome - apoB
Time Frame: At least 2 months
ApoB change
At least 2 months
Health outcome - HDL-cholesterol (HDL-C)
Time Frame: At least 2 months
HDL-C change
At least 2 months
Health outcome - triglycerides
Time Frame: At least 2 months
Triglycerides change
At least 2 months
Health outcome - systolic blood pressure (SBP)
Time Frame: At least 2 months
SBP change
At least 2 months
Health outcome - diastolic blood pressure (DBP)
Time Frame: At least 2 months
DBP change
At least 2 months

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Publications and helpful links

The person responsible for entering information about the study voluntarily provides these publications. These may be about anything related to the study.

General Publications

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

November 5, 2020

Primary Completion (Anticipated)

November 1, 2021

Study Completion (Anticipated)

November 1, 2022

Study Registration Dates

First Submitted

November 9, 2020

First Submitted That Met QC Criteria

November 16, 2020

First Posted (Actual)

November 18, 2020

Study Record Updates

Last Update Posted (Actual)

November 19, 2020

Last Update Submitted That Met QC Criteria

November 17, 2020

Last Verified

November 1, 2020

More Information

Terms related to this study

Other Study ID Numbers

  • CCS-Health Apps 2020

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

No

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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