| dc.description.abstract | Mental health is a critical aspect of overall well-being and affects a large proportion of the world’s population. The first step of identifying possible issues in an individual is often using assessment method such as surveys, forms, or questionnaires. However, traditional assessment methods such as self-assessment questionnaires yield challenges and limitations like social desirability and response bias. These traditional assessment methods rely heavily on the patient’s recollection of events, feelings, and current psychological state to work as intended. The emergence of ubiquitous wearable technology shows promise that it can help mitigate the mentioned issue. These devices promise to collect data reliably and can be used to get an objective representation of the physiological state of a patient. In addition, it might lead to better response rates and a more enhanced patient experience. However, thorough testing and evaluation is needed when integrating these emerging technologies. This thesis research the pressing need to improve these traditional assessment methods used in mental health by leveraging the potential of wearable technology. Moreover, the aim is to demonstrate how wearable technology can be integrated into self-assessment questionnaires through the development of an artifact that promotes reuse and interoperability. It consists of three general components: the questionnaire, the corresponding response, and the wearable data collection process for specific domains through digital biomarkers. The evaluation process involved a semi-structured interview, object-based evaluation experiment, and a user acceptance survey of the artifact. Based on this, our artifact poses as a viable solution and can be used as a starting point for future research in the problem domain. | |
