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The use of health and fitness apps has been on the rise to monitor personal fitness and health parameters. However, recent research discovered that many users discontinue using these apps after only a few months. Gamification has been suggested as a technique to increase users’ interactions with apps. Nevertheless, it is still not clear how gamification mechanisms encourage continued use and inspire user self-management.
The main objective of this study was to articulate how gamification mechanisms in studies of designing and using health and fitness apps can contribute to the realization of information technology (IT) identity and positive behavioral outcomes. The broader goal was to shed light on how gamification mechanisms will translate into positive use behaviors in the context of mobile health apps.
Data were collected from 364 users of health and fitness apps through an online survey to empirically examine the proposed model.
Based on identity theories, this study suggests the fully mediating role of IT identity to describe how gamification elements can lead to continued intention to use health and fitness apps, and increase users’ tendency for information sharing through the apps. The findings indicate that perceived gamification can increase users’ IT identity. In turn, a higher IT identity would encourage users to continue using the apps and share more personal health information with others through the apps.
The results of this study can have practical implications for app designers to use gamification elements to increase users’ dependency, relatedness, and emotional energy associated with health apps. Moreover, the findings can have theoretical contributions for researchers to help better articulate the process in which gamification can be translated into positive use behaviors.
In recent years, many companies have invested in developing mobile health (mHealth) apps. The concept of mHealth is defined as a medical and public health practice supported by mobile devices and applications [
Different health-related apps have attempted to leverage various techniques to attract and retain more users and enhance user interactions. One of the frequently used methods is creating a gameful design for health app services [
As the mHealth market size is booming, gamification is now recognized as an influential factor affecting self-engagement in care management. However, approximately 80% of apps that use gamified elements will fail due to the poor design of gamification mechanisms [
Using self-management tools to monitor health information is consistent with the premises of patient-centered health models, which consider more control and responsibilities for patients as an important stakeholder in the health care ecosystem [
Previous studies have examined the topic of IT and identity and their relationship using different approaches [
The main objective of this study was to examine how gamification mechanisms in studies of designing and using health and fitness apps can contribute to the realization of IT identity and positive behavioral outcomes. IT identity may provide a possible foundation for answering questions about how individuals become more likely to continue using the apps and share their personal health information with others using a gamified health app. The main hypothesis of the study is that gamified health apps will lead to positive use behaviors only when a strong IT identity related to the apps is activated. Consistent with the study objective, a research model was developed by drawing on the recent appearance of the IT identity concept in the information systems literature, which was adapted for using health and fitness apps. In short, this study addresses the following questions: (1) Can gamification mechanisms influence users’ continued intention to use apps and their information-sharing tendency? (2) Does IT identity fully mediate the relationship between perceived gamification and positive use behaviors?
According to Werbach [
Gamification is composed of two subcategories: structural and content gamification. Using structural gamification, designers leverage some game elements (such as digital badges and leaderboards) to encourage users to achieve a goal [
Badges are used to identify and reward individual achievements. Users can achieve badges by completing the task described. Gamified apps use a dashboard to provide a summary of all badges obtained by users. Digital badges enable users to visualize their performance and review their personal progress [
Points and leveling systems are implemented to inform the user of their level of familiarity, and reward continued expertise and knowledge using the system. Progress bars are also a standard feature of points and levels, where users can monitor how many points they have already attained along a continuum and how many more points they need to obtain to move up to the next level [
Previous studies suggest that using IT can expand the actual self along with the meanings and insights related to the self [
IT identity represents the extent to which the use of a target IT contributes to the sense of self and self-identification [
The main proposal of this study is that gamified features of health and fitness apps influence individuals’ self-identification with a target technology. Theory on IT identity suggests that technologies with broad application across social situations (eg, mobile devices and software applications) are most highly expected to enact IT identity [
There is evidence to support that self-identification of individuals with material objects that they can manipulate are more likely to be activated than with those they are less likely to exercise control over [
Previous research indicates that individuals need some degree of internal gratification to initiate and continue a job [
H1: Perceived gamification mechanisms used in health and fitness apps positively influence users’ IT identity.
Recent studies recognize a need for alternative theoretical perspectives to examine technological and individual factors in the postadoption stage of using IT [
IT identity affects how people use the various features of personal health devices in different situations [
H2: IT identity attached to health and fitness apps positively influences continued intention to use the apps.
A feeling of dependency and enthusiasm in relation to mHealth apps can result in continuous, effective, and long-term use [
Positive emotional energy between users and a health app may empower them to discover previously unused features [
IT identity can stimulate users to explore more resources and capabilities offered by the health and fitness apps. For example, IT identity holders who were unaware of remote care and medical surveillance afforded by a health and fitness app will attempt to reveal more personal data to explore these capabilities and add these services to their to-do list. Thus, attraction toward the app may encourage individuals to share more personal data to find new situations to apply the apps in the daily roles they maintain. Individuals with a strong IT identity may actively involve collecting more facts about an IT’s features to use them for additional tasks [
H3: IT identity attached to health and fitness apps positively influences information-sharing tendency.
The related literature indicates that gamified features of mHealth apps are necessary but not sufficient to motivate users to keep up with the apps or encourage them to share their personal health information [
H4a: IT identity attached to health and fitness apps fully mediates the relationships between perceived gamification mechanisms and continued intention to use them.
H4b: IT identity attached to health and fitness apps fully mediates the relationships between perceived gamification mechanisms and information-sharing tendency.
According to the theoretical rationale for the proposed causal relationships, the research model presented in
Research model. IT: information technology.
It should be mentioned that, consistent with prior studies, IT identity is considered as a second-order construct with three reflective factors [
To achieve this study’s objective, an online survey was administered to examine the proposed relationships between gamification mechanisms, IT identity, and positive use behaviors. First, a scenario was designed about why people are attached to their health and fitness apps by describing the “IT identity” and “gamification” concepts. One screening question limited the participants to those who used a gamified health app to monitor, control, and track health data for physical activities, weight loss, fitness, or diet purposes. Respondents were then asked to fill out the survey considering one health or fitness app (with gamification aspects) that they used. For instance, when a respondent named MyFitnessPal as the app that they used, they would answer all questions with consideration of that particular app. The logic behind this filter was to measure perceived gamification mechanisms and IT identity in relation to a target IT (ie, a specific mHealth app). This enabled examining the roles of gamification and IT identity in shaping positive use behavior (ie, continued use and information-sharing tendency) associated with that particular app.
Moreover, respondents were asked to describe how long and how often they used the app and to what extent they were familiar with the particular app they mentioned. In the second section of the survey, respondents were asked to think about the scenario that they read in the survey, and express their perceptions about the gamification mechanism designed for the app, IT identity in relation to the app, continued intention to use the app, and willingness to share information with the app. The next section of the survey was dedicated to demographic variables and general IT experience questions.
The approach used to measure the variables of the research model was based on existing literature. The survey items were adapted from previously validated surveys with slight changes made to fit the context of this study. The description of the proposed variables and the sources used to develop the questionnaire are provided in
Operationalization of constructs.
Construct | Construct definition | Source |
Perceived gamification mechanism | The extent to which an app uses gamification elements (such as badges, leaderboards, points, challenges, and social engagement) in its design | Miller et al [ |
ITa identity | “The extent to which an individual views use of an IT as integral to his or her sense of self” | Carter and Grover [ |
Continued intention to use the app | The extent to which an individual is willing to continue using an app | Karahanna et al [ |
Information-sharing tendency | The extent to which an individual is likely to disclose his/her personal health information through an app | Bansal and Gefen [ |
aIT: information technology.
Once the initial questionnaire was developed, six professionals in the health app domain were consulted to improve the content validity of the study, and finalize the gamification mechanisms and the questions used in this study. Consistent with the experts’ suggestions, the terms used to define gamification were modified, and the scenario and questions were improved to ensure that they were sufficiently transparent and easy to understand for the public. Face validity was then performed with 23 students (6 PhD candidates, 7 with Master’s degrees in information systems, and 10 undergraduate students) to ensure that the readability and wording of the questions were acceptable and consistent with the objectives of the study. Thus, some ambiguous terms were reworded, and technical language and jargon were removed so as to describe the scenario in the most understandable way. Finally, prior to the main data collection, a pilot test was performed with 152 undergraduate students at a large university in the southeastern United States to ensure that the instrument had acceptable reliability and validity. The Cronbach α was computed for each construct (ie, perceived gamification mechanism α=.91, IT identity α=.90, continued intention to use the app α=.94, and information-sharing tendency α=.90). All Cronbach α values were above the cut-off point of .70, indicating that the instrument was internally consistent [
Data collection was performed in October 2020 through Amazon’s Mechanical Turk (MTurk). Previous studies have provided strong evidence to show that MTurk is a suitable survey tool to collect individual-level data [
Several studies have compared MTurk to conventional data collection methods in the health and medical literature. The vast majority of these studies support the use of MTurk for a variety of academic purposes (eg, in health care research) [
As reported in previous studies, one main concern in online data collection is that subjects choose answers randomly or participate with less attention [
Confirmatory factor analysis was performed using IBM SPSS AMOS (Version 22) to find evidence for convergent validity and discriminant validity. The results of model fit indices for the measurement model demonstrated a good fit (goodness of fit index χ22.92=0.83, adjusted goodness of fit index=0.80, comparative fit index=0.90, normed-fit index=0.91, incremental fit index=0.90, standardized root mean square residual=0.02, and root mean square error of approximation=0.03), all meeting their respective common acceptance levels.
Multicollinearity was checked by computing the variance inflation factor (VIF). The VIF values ranged between 1.218 and 1.551, which were below the cut-off value of 5 [
According to Gefen et al [
Discriminant validity analysis of the constructs was also performed. In
Results of convergent validity.
Construct |
Standardized factor loading (>0.70) | Composite reliability (>0.70) | AVEa (>0.50) | |||||
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0.914 | 0.679 | ||||
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REL1 | 0.82 |
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REL2 | 0.80 |
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REL3 | 0.83 |
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REL4 | 0.86 |
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REL5 | 0.81 |
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0.921 | 0.699 | ||||
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EMO1 | 0.83 |
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EMO2 | 0.85 |
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EMO3 | 0.84 |
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EMO4 | 0.82 |
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EMO5 | 0.84 |
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0.915 | 0.682 | ||||
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DEP1 | 0.82 |
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DEP2 | 0.81 |
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DEP3 | 0.82 |
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DEP4 | 0.85 |
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DEP5 | 0.83 |
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0.907 | 0.619 | |||||
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PEG1 | 0.80 |
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PEG2 | 0.77 |
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PEG3 | 0.79 |
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PEG4 | 0.79 |
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PEG5 | 0.81 |
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PEG6 | 0.76 |
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0.875 | 0.638 | |||||
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CIU1 | 0.73 |
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CIU2 | 0.81 |
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CIU3 | 0.83 |
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CIU4 | 0.82 |
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0.875 | 0.636 | |||||
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IST1 | 0.72 |
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IST2 | 0.72 |
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IST3 | 0.78 |
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IST4 | 0.80 |
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aAVE: average variance extracted.
Results of the discriminant validity test.a
Construct | Mean (SD) | ITI-RELb | ITI-EMOc | ITI-DEPd | PEGe | CIUf | ISTg |
ITI-REL | 3.664 (0.890) |
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0.514 | 0.523 | 0.311 | 0.371 | 0.338 |
ITI-EMO | 3.865 (0.823) | 0.514 |
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0.598 | 0.369 | 0.114 | 0.319 |
ITI-DEP | 3.937 (0.798) | 0.523 | 0.598 |
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0.301 | 0.125 | 0.248 |
PEG | 3.639 (0.904) | 0.311 | 0.369 | 0.301 |
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0.431 | 0.374 |
CIU | 3.938 (0.889) | 0.371 | 0.114 | 0.125 | 0.431 |
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0.372 |
IST | 3.820 (0.853) | 0.338 | 0.319 | 0.248 | 0.374 | 0.372 |
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aDiagonals in italics (construct compared with itself) represent the square root of the average variance extracted; off-diagonals are the correlation values.
bITI-REL: information technology identity-relatedness.
cITI-EMO: information technology identity-emotional energy.
dITI-DEP: information technology identity-dependence.
ePEG: perceived gamification mechanism.
fCIU: continued intention to use the app.
gIST: information-sharing tendency.
Regarding experience with general technology, the respondents were mostly familiar with mobile devices, with the majority (92%) rating themselves as either “extremely” or “very” familiar with mobile devices (such as phones and tablets). Concerning familiarity with health care technologies, approximately 73% of the respondents reported that they were either “extremely” or “very” familiar with mHealth apps. Finally, the majority of respondents participated in an online health community (eg, information sharing or posting comments).
Sample characteristics (N=364).
Variable | Participants, n (%) | |
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Male | 204 (56.0) |
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Female | 160 (44.0) |
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<20 | 15 (4.1) |
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20-29 | 84 (23.1) |
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30-39 | 146 (40.1) |
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40-49 | 66 (18.1) |
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50-59 | 33 (9.1) |
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≥60 | 22 (6.0) |
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<25,000 | 55 (15.1) |
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25,000-49,000 | 76 (20.9) |
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50,000-74,999 | 124 (34.1) |
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75,000-99,999 | 58 (15.9) |
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100,000-150,000 | 36 (10.0) |
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>150,000 | 15 (4.1) |
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Less than high school | 4 (1.1) |
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High school graduate | 33 (9.1) |
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Some college | 95 (26.1) |
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2-year degree | 40 (11.0) |
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Bachelor’s degree | 135 (37.1) |
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Master’s degree | 47 (12.9) |
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Doctorate | 11 (3.0) |
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Employed full time | 251 (69.0) |
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Employed part time | 51 (14.0) |
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Unemployed | 40 (11.0) |
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Retired | 15 (4.1) |
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Student | 7 (1.9) |
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White | 189 (51.9) |
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African American | 84 (23.1) |
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Asian | 22 (6.0) |
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Hispanic | 58 (15.9) |
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Mixed | 7 (1.9) |
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Other | 4 (1.1) |
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Fitocracy | 142 (39.0) |
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Fooducate | 66 (18.1) |
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MyFitnessPal | 51 (14.0) |
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My Diet Coach | 44 (12.1) |
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RunKeeper | 33 (9.1) |
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Strava | 18 (4.9) |
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JEFIT Workout | 11 (3.0) |
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Less than 6 months | 36 (9.9) |
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6 months to 1 year | 167 (45.9) |
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1-2 years | 135 (37.1) |
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More than 2 years | 25 (6.9) |
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Daily | 186 (51.1) |
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Weekly | 138 (37.9) |
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Monthly | 40 (11.0) |
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Extremely experienced | 153 (42.0) |
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Very experienced | 131 (36.0) |
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Moderately experienced | 66 (18.1) |
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Slightly experienced | 15 (4.1) |
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Extremely familiar | 244 (67.0) |
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Very familiar | 91 (25.0) |
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Moderately familiar | 25 (6.9) |
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Slightly familiar | 4 (1.1) |
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Extremely familiar | 153 (42.0) |
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Very familiar | 113 (31.0) |
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Moderately familiar | 66 (18.1) |
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Slightly familiar | 33 (9.1) |
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Yes | 244 (67.0) |
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No | 120 (33.0) |
IBM SPSS AMOS (Version 22) was used to test the hypotheses within a structural equation modeling framework. According to Ho [
Model paths. IT: information technology. **
Consistent with a previous study [
Path coefficients were examined to assess the structural model. The results of the hypotheses testing are summarized in
Finally, the model explained 74% of the variance in IT identity, 60% of the variance in continued intention to use the app, and 53% of the variance in the information-sharing tendency. These R2 values suggested that the model provides relatively strong explanatory power to predict the variance in the positive use behaviors associated with health and fitness apps.
Structural equation modeling results.
Hypothesis | Path | Standardized β coefficient (SE) | Critical ratio | Results | |
H1 | PEGa to ITIb | .862 (.078) | <.001 | 11.160 | Supported |
H2 | ITI to CIUc | .779 (.068) | <.001 | 10.812 | Supported |
H3 | ITI to ISTd | .732 (.073) | <.001 | 10.847 | Supported |
H4a | PEG to ITI to CIU (Mediating role of ITI) | .172 (.081) | .009 | 2.625 | Supported |
H4b | PEG to ITI to IST (Mediating role of ITI) | .236 (.094) | .003 | 2.471 | Supported |
aPEG: perceived gamification mechanism.
bITI: information technology identity.
cCIU: continued intention to use the app.
dIST: information-sharing tendency.
Many companies and vendors have developed various mHealth apps with the use of gamification principles. Building a gamified health and fitness app requires substantial investment. However, a highly competitive market and misalignment of gamification mechanisms with main users’ motivations could result in switching or discontinuance uses [
This study further contributes to knowledge by shedding light on how gamification mechanisms will translate into positive use behaviors for regular users of mHealth apps. The findings highlight that gamification itself does not necessarily encourage users to share their personal data and keep up with health and fitness apps. Based on the fully mediating role of IT identity, gamified designs will be a successful technique to encourage meaningful interactions with the apps only if gamified elements can enact users’ emotional responses to thinking about themselves in relation to health and fitness apps. This could be a plausible reason for the insufficient effectiveness in the design of many gamified health and fitness apps to attract and keep their users. Previous studies have mentioned that infective gamification may lead to the users’ discontinuance intention in the context of health and fitness apps [
Previous studies indicate that gamification directly influences personal information disclosure [
Focusing on pure gamification mechanisms to increase market share can be a quick fix for the designers of mHealth apps. Using various gamified elements (such as badges, leaderboards, and points) can inspire individuals to use the apps, but they cannot automatically motivate them to stay with the apps. This is consistent with previous studies suggesting that gamified designs (such as using badges) should not be used alone because users may not be excited enough to continue to use the apps without further motivation and reinforcement [
This finding could be a practical contribution to mHealth designers by demonstrating that gamified features that are not consistent with the apps’ main purposes will not act as a meaningful incentive. This is in line with previous studies highlighting that putting too much emphasis on gamification mechanisms may negatively affect users’ experience with the apps [
Robust gamification mechanisms will help shape IT identity only when an individual has confidence in using their app to complete various tasks in different situations that can actualize intrinsic benefits and emotional rewards. The findings imply that effective rewards and incentives (eg, points and badges) accessible through gamified health and fitness apps should first create durable enjoyment, reliance, and connection with the apps. Otherwise, these gamified features may not motivate users to identify the self with the apps. If users do not consider the apps as an integral part of the self (due to lack of emotional responses), they may use the apps for a while but are very likely to switch to other alternatives supporting their self-concept. The results suggest that app designers may not increase feature use behaviors and enhanced use behaviors through gamification alone, but use behaviors can be improved through positive self-identification. Therefore, gamified incentives that foster self-identification by creating self-confirming sense, positive energy, and emotion associated with mHealth apps are more likely to encourage current users to keep up with them. Effective gamification mechanisms accompanied by a strong IT identity can reinforce health and fitness apps’ usability, encourage continued use, and inspire patient self-management.
Finally, these findings have important practical implications for those tasked with the responsibility of developing health and fitness apps. There are several active alternatives and a wide range of health and fitness apps on the mHealth market [
First, in this study, data were collected from a sample of respondents from the United States. The culture of using health and fitness apps is diverse among different countries. Therefore, caution should be exercised when generalizing the results. It is recommended that future studies consider subjects from other geographical locations such as other developed countries and developing countries with different technology infrastructure.
Second, it is important to mention that a general limitation with cross-sectional or short-term gamification studies is the study duration. Thus, longitudinal studies can provide a clearer understanding of the long-term effects of gamification on behavior outcome, user engagement, and continued use behavior.
Third, this study used a self-rated sample through an online survey to recruit participants digitally. Although several measures were taken to provide clear definitions, there is still a small chance that some respondents were not completely aware of the gamification mechanisms and may have formed their own perceptions of the IT artifact. For this reason, perceptions (perceived gamification mechanisms) were included in the research model to tackle this issue. Further studies should use an alternative method (eg, experiment) to ensure that subjects are knowledgeable about gamification to measure this construct more accurately.
Fourth, current users of gamified health and fitness apps were recruited for this study; focusing on a population of engaged users can also limit the generalizability of the findings. The role of IT identity may apply to this population but may be different in nonapp users. Thus, these findings are applicable among regular users of mHealth apps. This study calls for more research to improve generalizability by using a more comprehensive user status (such as current users, potential users, previous users, and nonusers).
Fifth, data were collected from respondents of some gamified health and fitness apps. All of the mentioned apps shared a combination of the most commonly used gamification mechanisms in mHealth apps (such as badges, challenges, points, levels, and feedback), which can satisfy this study’s objectives. As suggested previously [
Sixth, using an online survey may generate a sample selection bias. Data were collected only from people who could access a computer, mobile devices, and the internet to participate in the online survey. Future studies can use other data collection means and sampling strategies to recruit a sample that is generalizable to a wide range of health care consumers. Seventh, this study did not focus on a specific brand of health and fitness app. It would be interesting to examine whether alternative mHealth brands could influence verification of IT identity and, in turn, shape positive use behaviors.
Finally, consistent with this study’s purpose, the main goal was to develop and test a research model centered on the IT identity concept. Thus, many other widely used constructs from technology adoption models were not included in the research model. Future studies can incorporate other constructs that may enhance the amount of variance in IT identities, such as social influence, performance expectancy, and effort expectancy. Further research can also use objective measures to analyze the continued intention and positive use behaviors, such as usage frequency or number and the recency of sharing personal information via health and fitness apps.
Given the increasing importance of gamification and its impacts on the continuance of usage among regular users of health and fitness apps, this study proposes a model centered on the IT identity lens to fill current research gaps. Based on IT identity theories, it is proposed that effective gamification mechanisms embedded in health and fitness apps can activate users’ IT identity and improve postadoption behaviors. The results suggest that an appropriate mix of gamified elements helps users emotionally connect to health and fitness apps and have more control over their feature set. These feelings foster their self-identification in relation to the apps, and in turn, they will be more likely to engage in information sharing and enhance use behaviors. Based on the results of this empirical study, it is proposed that IT identity fully mediates the effects of gamification on positive use behaviors. On the same basis, only gamified elements that effectively activate individuals’ IT identity will result in continuous interactions with the apps and enhanced information sharing. Gamified features that better communicate the purpose of a health app and help users identify themselves with the app are more likely to foster active information sharing and continued intention to use. The findings propose theoretical implications to the gamification literature by demonstrating the mediating role of IT identity in shaping positive use behaviors. This study contributes more in-depth knowledge to the gamification principles in the context of mHealth apps and provides useful insights into the design of an effective gamified application platform. With a deeper understanding of IT identity and its relationship with gamification, mHealth app developers may be better positioned to design gamified features supportive of IT identity to improve postadoption use behaviors.
Online survey.
average variance extracted
information technology
mobile health
Amazon's Mechanical Turk
variance inflation factor
None declared.