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The primary objective of this study is to examine whether an ecological momentary intervention (EMI), combining behavioral self-monitoring (screen time screenshot uploads) and structured reflection, can enhance metacognitive awareness and metacognitive regulation in the context of recreational screen time among young adults.
A secondary objective is to investigate whether improvements in metacognitive processes are associated with subsequent changes in behavioral and psychological outcomes, including recreational screen time (RST), stress, and life satisfaction.
Furthermore, this study aims to elucidate the underlying mechanisms through which the intervention exerts its effects by integrating a randomized controlled trial (RCT) design with intensive longitudinal (daily diary) data.
Specifically, the study addresses the following research questions:
RQ1 (Primary Intervention Effect on Metacognition): Does the EMI lead to higher levels of daily metacognitive awareness and metacognitive regulation (planning, monitoring, and evaluation) compared to the control group? RQ2 (Within-person Associations): At the within-person level, do day-to-day fluctuations in metacognitive awareness and regulation predict same-day and next-day changes in recreational screen time, stress, and life satisfaction? RQ3 (Mediating Mechanism): Do increases in metacognitive awareness and regulation mediate the effects of the EMI on recreational screen time, stress, and life satisfaction? RQ4 (Between-person Effects): At the between-person level, do individuals in the intervention group exhibit higher average levels of metacognitive awareness and regulation, as well as lower recreational screen time and stress and higher life satisfaction, compared to those in the control group?
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Ecological Momentary Intervention Group | Experimental | Participants in the intervention group will receive a composite ecological momentary intervention that integrates behavioral self-monitoring and metacognitive reflection. Specifically, each day participants will:
(1) total recreational screen time, (2) usage contexts (e.g., situations or triggers), (3) awareness of potential overuse, and (4) use of regulation strategies (e.g., planning, monitoring, evaluation). In addition, participants will complete daily measures of metacognitive awareness, metacognitive regulation, stress, and life satisfaction. |
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| Control Group | No Intervention | Participants in the control group will complete the same daily diary measures of metacognitive awareness, metacognitive regulation, stress, and life satisfaction, but will not engage in screen time self-monitoring (i.e., no screenshot uploads) and will not receive any structured reflection prompts. |
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Ecological momentary intervention | Behavioral | A composite ecological momentary intervention that integrates behavioral self-monitoring and metacognitive reflection. Specifically, each day participants will:
(1) total recreational screen time, (2) usage contexts (e.g., situations or triggers), (3) awareness of potential overuse, and (4) use of regulation strategies (e.g., planning, monitoring, evaluation). |
| Measure | Description | Time Frame |
|---|---|---|
| Daily Metacognitive Awareness | Daily Metacognitive Awareness assesses the extent to which participants were consciously aware of their motivations and tendencies regarding recreational screen use on that day, which adapted from metacognitive awareness dimension in Metacognition about Regulating Recreational Screen Time Scale (McRST). Sample items include: "Today, I was aware of why I wanted to use my device for recreational purposes." Items are rated on a 5-point Likert scale (1 = strongly disagree to 5 = strongly agree). Higher scores indicate greater daily metacognitive awareness. | 14-day dairy |
| Daily Recreational Screen Time | Daily Recreational Screen Time is assessed using both subjective self-reports and objective device-recorded data in order to enhance measurement validity and reduce recall bias. Recreational screen time is defined as non-work and non-study device use, including activities such as social media browsing, video streaming, gaming, and other entertainment-related engagement. | 14-day dairy |
| Metacognitive skills | Metacognitive skills will be assessed using the Metacognition about Regulating Recreational Screen Time Scale (Mc-RST). The scale captures individuals' knowledge, beliefs, and perceived efficacy regarding their ability to regulate recreational screen use. Participants rated on a 5-point Likert scale, with higher scores indicating stronger metacognitive awareness and perceived regulatory capacity. | baseline, day 15 (t1) |
| Measure | Description | Time Frame |
|---|---|---|
| Daily Stress | Daily Stress is assessed using brief items adapted to capture day-specific perceived stress. Participants indicate the extent to which statements such as "Today, I felt stressed," "Today, I felt overwhelmed," and "Today, I found it difficult to cope with daily demands" describe their experience. Responses are rated on a 5-point scale ranging from 1 (not at all) to 5 (very much), with higher scores indicating greater daily stress. |
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Inclusion Criteria:
Participants must meet all of the following criteria:
Exclusion Criteria:
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| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Shiyun Chen, PhD Candidate | Contact | 052-46744938 | shiyun.chen@connect.polyu.hk |
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| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| The Hong Kong Polythechnic University | Recruiting | Hong Kong | Select An Option… | Hong Kong |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 33971499 | Background | Zhou H, Dang L, Lam LW, Zhang MX, Wu AMS. A cross-lagged panel model for testing the bidirectional relationship between depression and smartphone addiction and the influences of maladaptive metacognition on them in Chinese adolescents. Addict Behav. 2021 Sep;120:106978. doi: 10.1016/j.addbeh.2021.106978. Epub 2021 May 4. | |
| 30859387 |
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Individual participant data (IPD) will not be publicly shared due to the sensitive nature of the data, which includes detailed daily behavioral records and potentially identifiable digital usage patterns. Although all data will be de-identified, the granularity of longitudinal diary data and screen time records may still pose a risk of re-identification. In addition, data sharing is restricted by institutional ethical approval and participant consent agreements, which limit the use of the data to the current research purposes only. Aggregated data and study materials can be made available upon reasonable request.
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| ID | Term |
|---|---|
| D000068356 | Self-Control |
| ID | Term |
|---|---|
| D012919 | Social Behavior |
| D001519 | Behavior |
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The study adopts a randomized controlled trial (RCT) design consisting of three phases: baseline assessment (T0), a 14-day daily diary phase, and post-assessment (T1). Participants will be randomly assigned (1:1 allocation) to either the intervention group (EMI condition) or the control group. During the 14-day period, participants will complete a daily survey each evening (10:00 PM-11:59 PM) via an online platform. Automated reminders will be sent to enhance compliance. Participants in the intervention group will receive a composite ecological momentary intervention that integrates behavioral self-monitoring and metacognitive reflection and complete daily measures of metacognitive awareness, metacognitive regulation, stress, and life satisfaction. Participants in the control group will complete the same daily diary measures of metacognitive awareness, metacognitive regulation, stress, and life satisfaction, but will not engage in screen time self-monitoring.
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| 14-day dairy |
| Daily Life Satisfaction | Daily Life Satisfaction captures participants' cognitive evaluation of their day. Participants respond to items such as "Overall, I was satisfied with today," "Today was close to my ideal day," and "I feel positive about how today went." Responses are rated on a 5-point scale ranging from 1 (strongly disagree) to 5 (strongly agree). Higher scores indicate greater daily life satisfaction. | 14-day dairy |
| Internet addiction | Internet addiction will be measured using the revised Chinese Internet Addiction Scale (CIAS-R; Bai & Fan, 2005), which assesses core symptoms and related problems of excessive Internet use, including compulsive use, withdrawal, tolerance, interpersonal difficulties, and time management issues. Participants responded to items based on their experiences over the past year using a 4-point scale, with higher scores indicating greater levels of problematic Internet use. | baseline, day 15 (t1) |
| Short-form video addiction | Short-form video addiction will be assessed using the Bergen Short Video Addiction Scale (Qu et al., 2024), which captures key components of addictive behavior, including salience, mood modification, tolerance, withdrawal, conflict, and relapse. Items were rated on a 5-point frequency scale, with higher scores indicating more severe short-form video addiction. | baseline; day 15(t1) |
| Depressive symptoms | Depressive symptoms will be measured using the Patient Health Questionnaire-9 (PHQ-9; Leung et al., 2020), which assesses the frequency of depressive symptoms over the past two weeks. Each item was rated on a 4-point scale, with higher total scores indicating more severe depressive symptoms. | baseline; day 15(t1) |
| Anxiety symptoms | Anxiety symptoms will be assessed using the Generalized Anxiety Disorder-7 scale (GAD-7; He et al., 2010), which evaluates the frequency of anxiety-related symptoms over the past two weeks. Items were rated on a 4-point scale, with higher scores indicating higher levels of anxiety. | baseline; day 15(t1) |
| Perceived stress | Perceived stress will be measured using the Chinese version of the Perceived Stress Scale (CPSS; Yang & Huang, 2003), which assesses the extent to which individuals perceive their lives as unpredictable, uncontrollable, and overloaded. Participants rated items on a 5-point scale, with higher scores indicating higher perceived stress. | baseline; day 15(t1) |
| Self-control | Self-control will be assessed using the Chinese version of the Self-Control Scale (SCS; Unger et al., 2016), which measures individuals' ability to regulate impulses and maintain goal-directed behavior. Items were rated on a 6-point scale, and higher average scores indicate stronger self-control capacity. | baseline; day 15(t1) |
| Life satisfaction | Life satisfaction will be measured using the Satisfaction with Life Scale (SWLS; Diener et al., 1985), which assesses global cognitive judgments of one's life satisfaction. Participants rated five items on a 7-point Likert scale, with higher scores indicating greater life satisfaction. | baseline; day 15(t1) |
| Fear of missing out (FoMO) | Fear of missing out (FoMO) will be assessed using a validated FoMO scale (Przybylski et al., 2013; Li et al., 2019), which captures individuals' anxiety related to missing rewarding experiences or social interactions. Items were rated on a 5-point scale, with higher scores indicating higher levels of FoMO. | baseline; day 15(t1) |
| Twenge JM, Campbell WK. Media Use Is Linked to Lower Psychological Well-Being: Evidence from Three Datasets. Psychiatr Q. 2019 Jun;90(2):311-331. doi: 10.1007/s11126-019-09630-7. |
| 30406005 | Background | Twenge JM, Campbell WK. Associations between screen time and lower psychological well-being among children and adolescents: Evidence from a population-based study. Prev Med Rep. 2018 Oct 18;12:271-283. doi: 10.1016/j.pmedr.2018.10.003. eCollection 2018 Dec. |
| 18509902 | Background | Shiffman S, Stone AA, Hufford MR. Ecological momentary assessment. Annu Rev Clin Psychol. 2008;4:1-32. doi: 10.1146/annurev.clinpsy.3.022806.091415. |
| 37081557 | Background | Santos RMS, Mendes CG, Sen Bressani GY, de Alcantara Ventura S, de Almeida Nogueira YJ, de Miranda DM, Romano-Silva MA. The associations between screen time and mental health in adolescents: a systematic review. BMC Psychol. 2023 Apr 20;11(1):127. doi: 10.1186/s40359-023-01166-7. |
| 27663578 | Background | Nahum-Shani I, Smith SN, Spring BJ, Collins LM, Witkiewitz K, Tewari A, Murphy SA. Just-in-Time Adaptive Interventions (JITAIs) in Mobile Health: Key Components and Design Principles for Ongoing Health Behavior Support. Ann Behav Med. 2018 May 18;52(6):446-462. doi: 10.1007/s12160-016-9830-8. |
| 30688984 | Background | Madigan S, Browne D, Racine N, Mori C, Tough S. Association Between Screen Time and Children's Performance on a Developmental Screening Test. JAMA Pediatr. 2019 Mar 1;173(3):244-250. doi: 10.1001/jamapediatrics.2018.5056. |
| 19575624 | Background | Curran PJ, Bauer DJ. The disaggregation of within-person and between-person effects in longitudinal models of change. Annu Rev Psychol. 2011;62:583-619. doi: 10.1146/annurev.psych.093008.100356. |
| Background | Howard, S. J., Hayes, N., Mallawaarachchi, S., Johnson, D., Neilsen-Hewett, C., Mackenzie, J., ... & White, S. L. (2025). A meta-analysis of self-regulation and digital recreation from birth to adolescence. Computers in Human Behavior, 163, 108472. |
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| 36360887 | Background | Haddock A, Ward N, Yu R, O'Dea N. Positive Effects of Digital Technology Use by Adolescents: A Scoping Review of the Literature. Int J Environ Res Public Health. 2022 Oct 27;19(21):14009. doi: 10.3390/ijerph192114009. |
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| Background | Ellis, D. A., Davidson, B. I., Shaw, H., & Geyer, K. (2019). Do smartphone usage scales predict behavior? International Journal of Human-Computer Studies, 130, 86-92. https://doi.org/10.1016/j.ijhcs.2019.05.004 |
| 40120187 | Background | Donati MA, Padovani M, Iozzi A, Primi C. Prevention of problematic smartphone use among adolescents: A preliminary study to investigate the efficacy of an intervention based on the metacognitive model. Addict Behav. 2025 Jul;166:108332. doi: 10.1016/j.addbeh.2025.108332. Epub 2025 Mar 19. |
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