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Objective:
The investigators want to see if a WeChat program can help college students use the internet less and feel better.
Methods:
The investigators picked 226 students who use the internet too much. The investigators put 113 in a group that used a special WeChat program for six weeks. The other 113 did nothing different. The investigators checked how much they used the internet, slept, and how they felt before and after.
Interventions:
The WeChat program gave students info, motivation, and skills to cut down on internet use. It sent them articles and videos every two days.
Data Collection and Outcome Measures:
The investigators used a test to see how much students were addicted to the internet. The investigators also looked at their internet time, sleep, and feelings. The investigators used math tricks to see if the program worked.
Brief Summary:
This study checks if a WeChat program can help students with internet addiction. It teaches them about their habits and how to change them.
Background:
With the rise of digital technology, internet addiction has become a significant concern among college students, affecting their academic performance and mental health. The Information-Motivation-Behavioral Skills (IMB) model has shown promise in understanding and addressing health behaviors, including addiction.
Objective:
The primary objective of this study is to evaluate the effectiveness of a WeChat public account intervention based on the IMB model in reducing internet addiction among college students. The study also aims to explore the underlying mechanisms that lead to changes in addictive behaviors, contributing to the development of a new online treatment model for internet addiction.
Methods:
A total of 226 college students diagnosed with internet addiction were recruited and randomly assigned to either an intervention group (n=113) or a control group (n=113) using stratified randomization based on gender. The intervention group participated in a structured six-week program that leveraged a WeChat public account to deliver content designed to educate about internet addiction, identify triggers, enhance motivation to change, and improve behavioral skills. The control group maintained their regular routines without any intervention. Data were collected before and after the intervention period using standardized measures, including the Internet Addiction Test (IAT), and assessed for internet usage time, sleep duration, sleep quality, and somatic-psychological symptoms.
Interventions:
The intervention was structured around three modules: information, motivation, and behavioral skills. Participants in the intervention group received automated push notifications with articles or videos every two days through the WeChat public account. The content was designed to provide knowledge about internet addiction, strategies to cope with cravings, and methods to enhance self-efficacy and access to support. The intervention was monitored through the account's backend data to track engagement.
Data Collection and Outcome Measures:
The main outcome measure was the IAT scale score, which assesses the severity of internet addiction. Secondary outcomes included changes in internet usage time, sleep duration, sleep quality, and somatic-psychological symptoms. Data were analyzed using Generalized Linear Mixed Models (GLMM) and Generalized Estimating Equations (GEE) to evaluate the impact of the intervention and to identify differences pre- and post-intervention.
Significance:
The findings of this study could provide valuable insights into the effectiveness of digital interventions for internet addiction and contribute to the development of targeted prevention and treatment strategies for college students.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Intervention group | Experimental | Intervention group: A six-week intervention leveraging an online WeChat public account was implemented, integrating the IMB (Information-Motivation-Behavioral Skills) model into its design. Drawing from literature analysis, the intervention plan was structured into three distinct modules: information, motivation, and behavioral skills. The comprehensive intervention encompassed disseminating knowledge on Internet addiction, identifying and avoiding triggers, fostering withdrawal motivation, imparting coping strategies for cravings and challenging situations, enhancing self-efficacy, and facilitating access to personal and social support. Participants who followed the WeChat public account received automated push notifications containing articles or videos every two days. Throughout the intervention period, engagement was monitored by tracking the readership of the sent content through the WeChat public account's backend data. |
|
| Control group | No Intervention | Control group: without any intervention, maintain normal life and study state. |
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Intervention Name: WeChat Intervention Based on the IMB Model | Behavioral | A six-week intervention leveraging an online WeChat public account was implemented, integrating the IMB (Information-Motivation-Behavioral Skills) model into its design. Drawing from literature analysis, the intervention plan was structured into three distinct modules: information, motivation, and behavioral skills. The comprehensive intervention encompassed disseminating knowledge on Internet addiction, identifying and avoiding triggers, fostering withdrawal motivation, imparting coping strategies for cravings and challenging situations, enhancing self-efficacy, and facilitating access to personal and social support. Participants who followed the WeChat public account received automated push notifications containing articles or videos every two days. Throughout the intervention period, engagement was monitored by tracking the readership of the sent content through the WeChat public account's backend data. |
| Measure | Description | Time Frame |
|---|---|---|
| Internet Addiction | Internet Addiction Measurement Tool: 20-item Internet Addiction Test (IAT) Description: Scores range from 20 to 100, with higher scores indicating a more severe level of internet addiction (20-39: no addiction, 40-69: mild addiction, ≥70: moderate to severe addiction). | From enrollment to the end of treatment at 6 weeks |
| Measure | Description | Time Frame |
|---|---|---|
| Internet Usage Time | Internet Time Measurement: Minutes Description: Higher values indicate longer internet usage time. | From enrollment to the end of treatment at 6 weeks |
| Sleep Duration | Sleep Duration Measurement: Minutes Description: Higher values indicate longer sleep time |
| Measure | Description | Time Frame |
|---|---|---|
| Knowledge of Internet Addiction (Information) | Knowledge of Internet Addiction (Information) Measurement Tool: Self-designed questionnaire based on "Knowledge and Attitude of Internet Addiction" by Huang Yurong et al. Description: Comprises 10 judgment questions with a scoring system (1 point for correct, 0 for incorrect/unclear), including reverse scoring for items 3, 4, 7, and 9 to minimize bias. Total score ranges from 0 to 10, with higher scores indicating better knowledge. |
Inclusion Criteria:
Exclusion Criteria:
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| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Anhui Medical University | Hefei | Anhui | 230032 | China |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 37977269 | Background | Bai Y, Qu J, Li D, Yin H. Neural basis underlying the relation between internet addiction tendency and sleep quality: The intrinsic default-mode network connectivity pathways. Int J Psychophysiol. 2024 Jan;195:112264. doi: 10.1016/j.ijpsycho.2023.112264. Epub 2023 Nov 15. | |
| 38242916 | Background | Aziz M, Chemnad K, Al-Harahsheh S, Abdelmoneium AO, Bagdady A, Hassan DA, Ali R. The influence of adolescents essential and non-essential use of technology and Internet addiction on their physical and mental fatigues. Sci Rep. 2024 Jan 19;14(1):1745. doi: 10.1038/s41598-024-51655-x. |
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| ID | Term |
|---|---|
| D000082424 | Internet Addiction Disorder |
| ID | Term |
|---|---|
| D000088942 | Technology Addiction |
| D016739 | Behavior, Addictive |
| D003192 | Compulsive Behavior |
| D007175 | Impulsive Behavior |
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Intervention Group: Intervention based on the IMB model through WeChat official account
Control Group: No intervention, maintaining normal life and study status
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| From enrollment to the end of treatment at 6 weeks. |
| Sleep Quality | Sleep Quality Measurement Tool: Pittsburgh Sleep Quality Index (PSQI) Description: Scores range from 0 to 3, with higher scores indicating poorer sleep quality. This RCT includes only the components of sleep quality and sleep duration. | From enrollment to the end of treatment at 6 weeks. |
| Somatic-Psychological Symptoms | Somatic-Psychological Symptoms Measurement Tool: Symptom Checklist Description: Binary outcomes indicating the presence or absence of specific symptoms, including Dizziness, Eye Discomfort, Gastrointestinal Problems, Low Mood, and Anxiety. | From enrollment to the end of treatment at 6 weeks. |
| From enrollment to the end of treatment at 6 weeks. |
| Motivation for Internet Addiction Improvement (Motivation) | Motivation for Internet Addiction Improvement (Motivation): Measurement Tool: Treatment Self-Regulation Questionnaire (TSRQ), Chinese version by Zhou Chenxi et al. Description: 15-item questionnaire with a 7-point Likert scale, scoring from 15 to 105. Higher scores indicate stronger motivation for treatment. | From enrollment to the end of treatment at 6 weeks. |
| Internet Control Self-Efficacy (Behavioral Skills) | Internet Control Self-Efficacy (Behavioral Skills) Measurement Tool: Internet Control Self-Efficacy Questionnaire (ICSQ) by Luo et al. Description: 12-item questionnaire focusing on time management, task control, and purpose clarity. 4-point Likert scale, total score from 12 to 48. Higher scores indicate greater self-efficacy in controlling internet use. | From enrollment to the end of treatment at 6 weeks. |
| 42398925 | Derived | Yang H, Geng A, Ruan W, Yang Y, Xu F, Shi H, Xu W, Jiang K, Guo H, Wang S, Hu Z, Man M, Zhang Z. Effectiveness of WeChat Public Account Intervention Based on the Information-Motivation-Behavioral Skills Model Among College Students With Internet Addiction: Randomized Controlled Trial. J Med Internet Res. 2026 Jul 3;28:e84664. doi: 10.2196/84664. |
| D001519 |
| Behavior |