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Participants will take part in a 4-week study consisting of two in-person sessions. During the first session, participants will complete a demographic form and baseline questionnaire, after which the study application will be installed on their preferred device. A research team member will provide a brief introduction to the application, guide participants through the registration process, and schedule the second session. Participants will then be randomly assigned to one of two study conditions, with each group receiving a different version of the application's mental health content.
Over the following four weeks, participants may use the application freely and at their own discretion. The application will send weekly reminders based on participants' preferred day and time, but no further contact will be initiated by the research team unless participants require assistance or wish to withdraw. Depending on their assigned condition, participants will either access standard mental health content or content delivered through a virtual agent that introduces weekly themes and recommends resources based on individual interests. The application will automatically record user interactions, such as content viewed, duration of use, and navigation patterns, for research analysis.
At the end of the study period, participants will attend a second in-person session where they will complete a follow-up questionnaire and participate in a short semi-structured interview. The questionnaires and interview will assess participants' perceptions of the application, including therapeutic alliance, perceived usefulness, and intention to continue using it. The interview will also provide additional insights to help interpret participants' usage patterns and experiences with the application. Participants will receive compensation upon completion of the study.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Intervention | Experimental | The intervention group used an application whose design was guided by digital working alliance. |
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| Control | Active Comparator | The control group used a standard digital well-being resource available to students through the university's well-being office. |
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| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| MyPocketPal | Other | The intervention app, MyPocketPal, is a digital mental health literacy application designed for university students and informed by the digital working alliance framework. The app aims to enhance mental health knowledge and engagement through personalized, contextually relevant content tailored to students' interests and experiences. It includes six modules covering mental health information, personal stories, self-help tools, wellness resources, support services, and additional resources. A virtual agent introduces weekly content and provides recommendations based on user preferences. Interactive features such as guided breathing exercises, meditation, journaling, and mental health screening tools are incorporated to promote engagement, while content is released progressively to reduce information overload and encourage sustained use. |
| Measure | Description | Time Frame |
|---|---|---|
| Perceived Usefulness, Attitude and Intention to Use from Technology Acceptance Model | 9 Items used to measure the Technology Acceptance Model constructs of Perceived Usefulness, Attitude and Intention to Use were adapted from were adapted from Klopping and McKinney (2004), Yu and Yu (2010), and Ahadzadeh, Sharif (2015). The measurements were taken utilizing a 7 point Likert scale where 1 represented Strongly Disagree and 7 represented Strongly Agree | Scores were collected prior to starting the study and at the end of the 4 week study during follow up. |
| Changes in scores from Baseline in Digital Working Alliance Inventory at the end of 4 week intervention. | 6 Items used to measure the constructs of Shared Goals, Task Relevance, Bonds and Digital Working Alliance were adapted from Goldberd et al. (2022) The measurements were taken utilizing a 7 point Likert scale where 1 represented Strongly Disagree and 7 represented Strongly Agree | Scores were collected prior to starting the study and at the end of the 4 week study during follow up. |
| Changes in scores from Baseline in Technological Self-Efficacy and Task Technology Fit at the end of 4 week intervention. | 6 Items measuring were used to measure the constructs of Technological Self-Efficacy and Task Technology Fit were adapted from Becker (2016). The measurements were taken utilizing a 7 point Likert scale where 1 represented Strongly Disagree and 7 represented Strongly Agree. | Scores were collected prior to starting the study and at the end of the 4 week study during follow up. |
| Number of Logins Per Week | Participants were advised to log in once per week. To track adherence, the number of logins to the application (where the application was launched and brought to the foreground) was collected. This data was collected automatically by the application. The value ranges from 0 to X where 0 represents no logins and X where X is an integer representing the number of logins and will be used to understand a participants weekly adherence and engagement. |
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Inclusion Criteria:
Exclusion Criteria:
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| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Nanyang Technological University | Singapore | Singapore |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 25700481 | Background | Ahadzadeh AS, Pahlevan Sharif S, Ong FS, Khong KW. Integrating health belief model and technology acceptance model: an investigation of health-related internet use. J Med Internet Res. 2015 Feb 19;17(2):e45. doi: 10.2196/jmir.3564. | |
| Background | Yu TK, Yu TY. Modelling the factors that affect individuals' utilisation of online learning systems: An empirical study combining the task technology fit model with the theory of planned behaviour. British Journal of Educational Technology. 2010;41(6):1003-17. | ||
| Background | Klopping IM, McKinney E. Extending the technology acceptance model and the task-technology fit model to consumer e-commerce. Information Technology, Learning & Performance Journal. 2004;22(1). | ||
| 34000843 |
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| Control | Other | The control application consisted of a digital mental health resource that presented general well-being content commonly available to university students. Content included articles, infographics, videos, event listings, support contacts, and links to external mental health tools covering topics such as stress management, sleep hygiene, mindfulness, and overall well-being. Information was organized into browsable categories and updated regularly. |
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| From enrollment to the end of treatment at 4 weeks |
| Number of Minutes Spent in the Application Per Week | To track engagement, the number of minutes spent in the application was collected. Users were considered to be spending time in the application when the application was launched and in the foreground of the mobile device. This data was collected automatically by the application. The value ranges from 0 to X where 0 represents 0 minutes spent in the application and X is an integer representing the total number of minutes spent in the application, and will be used to understand a participant's weekly engagement. | From enrollment to the end of treatment at 4 weeks |
| Background |
| Goldberg SB, Baldwin SA, Riordan KM, Torous J, Dahl CJ, Davidson RJ, Hirshberg MJ. Alliance With an Unguided Smartphone App: Validation of the Digital Working Alliance Inventory. Assessment. 2022 Sep;29(6):1331-1345. doi: 10.1177/10731911211015310. Epub 2021 May 18. |
| Background | Becker D. Acceptance of mobile mental health treatment applications. Procedia Computer Science. 2016;98:220-7. |