Revision of the non<b>-</b>suicidal self<b>-</b>injury behavior scale for adolescents with mental disorder.
Bibliographic record
Abstract
OBJECTIVES: Adolescents are at high risk of non-suicidal self-injury (NSSI). Currently, there is no clinical assessment tool for adolescent NSSI behaviors measurement with global consistency. The Ottawa Self-injury Inventory (OSI) is considered as a relatively comprehensive assessment tool for NSSI, but the questionnaire is discussed with excessive content and timecostly, which may affect the reliability of the measurement results for adolescent.Thus, this study, based on OSI, aims to revise the assessment tool for adolescent with NSSI that is suitable for both clinically and scientifically, referring to the diagnostic criteria for NSSI in the 5th Diagnostic and Statistical Manual of Mental Disorder (DSM-5). METHODS: This study was led by the Second Xiangya Hospital of Central South University and collaborated with 6 mental health service institutions in China from August to December 2020. Adolescent aged from 12 to 24 years old who had self-injury behavior and met the DSM-5 diagnostic criteria for NSSI were continuously recruited in the psychiatric outpatient department or ward. After clinical diagnosis by an experienced attending psychiatrist or above, the general information and OSI were collected by questionnaires. SPSS 24.0 and AMOS structural equation model statistical softwares were used to conduct item analysis and exploratory factor analysis on the obtained data to complete the revision of the scale. Cronbach's alpha coefficient, split-half reliability, test-retest reliability, and content validity and structure validity were performed to analyze the reliability and validity and confirmatory factor analysis was carried out to test the structure validity for the revised scale. RESULTS: A total of 234 adolescent with NSSI were enrolled, including 33 (14.1%) males and 201 (85.9%) females with the mean age of (16.2±2.6) years old. The most common clinical diagnoses were depression disorder (57.4%), bipolar disorder (20.9%), adolescent mood disorder (17.1%), etc. Nine items (item 2, 7, 11, 13, 23, 24, 10, 17, 18) in the functional scale of OSI were deleted according to extreme grouping method, correlation analysis, and principal component analysis in exploratory factor analysis. The revised functional scale for NSSI consisted of 15 items. The reliability analysis showed that the Cronbach's alpha coefficients of NSSI thought and behavior frequency, addiction characteristics, and function scales were 0.799, 0.798, and 0.835, respectively, and the split-half coefficients were 0.714, 0.727, and 0.852, respectively. The test-retest coefficients of the latter 2 scales were 0.466 and 0.560, respectively. The correlation coefficient between sub-items and total scores in each part of the scale showed good content validity. The exploratory factor analysis showed that a component was extracted from the frequency of thoughts and behaviors of NSSI, one component was extracted from the addictive characteristics, and three components were extracted from the functional part. The three functional subscales were social influence, external emotion regulation, and internal emotion regulation. The factor load of each item was >0.400. CONCLUSIONS: The revised Chinese version OSI targeted the adolescent patients with mental disorders has relatively ideal reliability and validity. The scale shows high stability, dependability, and a reasonable degree of fit. It is a suitable assessment tool for clinical and scientific research on adolescent with NSSI.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| 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 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".