Characterizing problematic internet use in a sample of heavy drinking emerging adults.
Bibliographic record
Abstract
OBJECTIVE: Problematic internet use (PIU) is characterized by excessive or poorly controlled internet use resulting in impairment or distress. PIU is most prevalent during emerging adulthood, a period marked by an increase in psychiatric disorders, including substance use disorders (SUDs). In a sample of high-risk emerging adults, the aim of this study was to examine the relationship between PIU and quality of life (QoL), psychiatric disorders, and impulsivity. METHODS: Participants were a community sample of heavy drinking emerging adults in Hamilton, Ontario (N = 709). Measures included: PIU, QoL, eight psychiatric indicators, and three domains of impulsivity. All variables that were significantly associated with PIU were subsequently examined concurrently in structural equation models. RESULTS: PIU was negatively associated with physical QoL (β = -0.27, p < .01) and social QoL (β = -0.20, p < .01), but positively associated with environmental QoL (β = 0.17, p < .01). For psychiatric conditions, PIU was positively associated with internalizing disorders (β = 0.42, p < .01) but not SUD (β = -0.01, p = .90). For impulsivity, PIU was positively associated with Lack of Perseverance (β = 0.16, p < .01) and Negative Urgency (β = 0.23, p < .01) but no other indicators. CONCLUSIONS: This study provides further evidence that PIU is associated with lower quality of life, selectively co-occurs with internalizing psychopathology, and is associated with certain impulsive traits. Lack of associations with SUD challenges conceptualizations of PIU as an alternative manifestation of externalizing psychopathology. (PsycInfo Database Record (c) 2022 APA, all rights reserved).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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 teacher head, 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".