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Measuring Interests Not Minutes: Development and Validation of the Adolescents' Digital Technology Interactions and
Megan A Moreno1, Kole Binger1, Qianqian Zhao2
1Department of Pediatrics, University of Wisconsin-Madison, Madison, WI, United States.
Background:
Interactive digital technology use is integral to adolescents' lives and has been associated with both health benefits and risks. Previous studies have largely focused on measuring the quantity of technology use or understanding the use of specific platforms. To better understand adolescents' interactive digital technology use, we need new approaches that consider technology interactions and their importance.
Objective:
This study aimed to develop an assessment tool to evaluate adolescents' digital technology interactions and their perceived importance.
Methods:
We used a validated scale development approach comprising 2 initial steps to create an item pool: item pool development and item pool refinement. These steps relied upon empirical literature review and an expert convening. We then evaluated the item pool using a Web-based survey. Data were collected via Qualtrics panel recruitment from a national sample of 12- to 18-year-olds. Participant data were randomly split into a development subsample for exploratory factor analysis (EFA) and a test subsample for confirmatory factor analysis (CFA). We assessed Cronbach alpha as well as model fit characteristics including root mean square error of approximation (RMSEA) and comparative fit index (CFI).
Results:
Our initial item pool had 71 items and the refined item pool contained 40. A total of 761 adolescents assessed the item pool via Web-based survey. Participants had a mean age of 14.8 (SD 1.7) years and were 52.8% (402/761) female and 77.5% (590/761) white. The EFA analysis included 500 participants and an 18-item draft scale was created. The CFA included 261 participants to test the draft scale. Adequate model fit for the scale was indicated by an RMSEA of 0.063 and a CFI of 0.95. The final scale included 18 items in a 3-factor model, with Cronbach alpha for the 3 factors of .87 (factor 1), .90 (factor 2) and .82 (factor 3). The 3 factors were named (1) technology to bridge online and offline experiences, (2) technology to go outside one's identity or offline environment, and (3) technology for social connection.
Conclusions:
The resulting Adolescents' Digital Technology Interactions and Importance (ADTI) scale is a promising and psychometrically validated tool for identifying the importance of distinct technology interactions. The scale is informed by relevant theory and expert input. The 3 subscales have utility for future studies to understand whether certain subscale score ranges are associated with health or well-being outcomes.
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