Effects of decision making and impulsivity on the addictive features of non-suicidal self-injury behaviors in adolescents with depressive disorder
Bibliographic record
Abstract
BACKGROUND: Non-suicidal self-injury (NSSI) behaviors pose a significant threat to the physical and psychological well-being of adolescents. Recent research suggests that persistent, uncontrollable and repetitive NSSI can be conceptualized as a behavioral addiction. The addictive feature of NSSI behavior can be assessed using Ottawa self-injury inventory (OSI), the higher addiction score indicates the more serious NSSI behavior. This study aims to explore the relationship of impulsivity and decision-making on the addictive features of NSSI in adolescents with depressive disorder, to explore the influencing factors of behavioral addictive features of NSSI and to predict the addictive features of NSSI. METHODS: Using a cross-sectional design, a total of 126 adolescent outpatients and inpatients with a mean age of 15.49 years old (M = 15.49, SD = 1.56), male students (n = 28, 22.2%) and female students (n = 98, 77.8%) diagnosed with depressive disorders were recruited according to the criteria of the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5), and clinical interviews were completed by two psychiatrists. NSSI addictive features according to the OSI's addictive features items. The final group was categorized into three groups: depression without NSSI (n = 42), depression with NSSI without addictive features (n = 44), and depression with NSSI and addictive features (n = 40). The present study employed the Hamilton Depression Scale (HAMD-24), Chinese Revised Barratt Impulsiveness Scale Version 11 (BIS-11), OSI, and the Adolescent Non-Suicidal Self-Injury Questionnaire (ANSSIQ). Cognitive decision-making abilities were assessed using the Iowa Gambling Task (IGT). RESULTS: The depression with NSSI addictive features group had significantly lower total net scores and net scores of block3, block4, and block5 in the IGT than the depression without NSSI group, whereas there was no statistically significant difference between the two in net scores of block1 and block2. Lower scores mean more unfavorable decisions and strategy adjustments. The addictive features of NSSI behaviors were significantly and positively correlated with the severity of NSSI behaviors, depression, and cognitive impulsiveness, and significantly and negatively correlated with the total net score of the IGT. The severity of NSSI behaviors, severity of depression, cognitive impulsiveness positively predicts the addictive features of NSSI behaviors, the total net score of the IGT negatively predicted the addictive features of NSSI behaviors. CONCLUSION: Adolescents with depressive disorders with NSSI behavioral addictive features had higher severity of depression, exhibited higher cognitive impulsivity, and made more unfavorable decisions when making choices.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".