A Guided Web-Based Intervention Targeting Procrastination in College Students: Protocol for an Open Trial
Bibliographic record
Abstract
BACKGROUND: Academic procrastination is a widespread problem among college students. It is linked to poor academic performance and increased college dropout intentions, as well as several mental health problems such as depression, anxiety, and stress. Guided web-based interventions can help reduce procrastination. However, guidance by professional clinicians draws upon valuable and limited societal resources, and a more efficient, scalable form of guidance is needed. Guidance by trained clinical psychology students has not yet been examined. OBJECTIVE: The aim of this open trial is to examine the feasibility and acceptability of a web-based procrastination intervention for college students under the guidance of student digital coaches (e-coaches). METHODS: We developed a single-arm trial of a guided web-based intervention targeting procrastination for the Dutch student population. Guidance is delivered by trained clinical psychology students asynchronously in the form of textual feedback on intervention progress, with the aim of supporting and motivating the participant. Participants are recruited at 7 Dutch universities. Primary outcomes are intervention satisfaction, usability, and adherence, which are assessed by the Client Satisfaction Scale (CSQ-8), System Usability Scale (SUS-10), and number of completed modules, respectively. The primary outcomes will be examined by calculating descriptive statistics. Secondary outcomes are e-coach satisfaction and changes to procrastination, depression, stress, and quality of life from pre- to posttest and follow-up. RESULTS: The project was funded in 2019, and recruitment began in January 2021. As of May 2023, a total of 985 participants were enrolled, of which 372 had completed the posttest and 192 had completed the follow-up. The expected date of analysis and publication of the results is 2024. CONCLUSIONS: The results are expected to contribute to the body of literature regarding eHealth in 3 ways. First, we will examine whether students who procrastinate adhere to and are satisfied with an eHealth intervention targeting this problem. Second, we will explore whether an intervention targeting procrastination can also decrease depression and stress. Lastly, we will investigate whether trained psychology students can effectively guide their peers in web-based interventions. Given the shortage of licensed psychologists, exploring alternative sources of guidance is much needed in order to provide students with the mental health support they need. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/44907.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.032 | 0.033 |
| Meta-epidemiology (narrow) | 0.006 | 0.003 |
| Meta-epidemiology (broad) | 0.010 | 0.004 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.009 | 0.008 |
| Insufficient payload (model declined to judge) | 0.068 | 0.014 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".