Psychometric Properties of the Inventory of Personality Organization for Adolescents
Bibliographic record
Abstract
Background and Goals: Despite general agreement that personality disorders (PDs) have their roots in childhood and adolescence, diagnosing PDs in adolescence remains a topic of debate. Reluctance to diagnose PDs in youth has been supported by the paucity of adapted measures of adolescent personality and by findings suggesting that a PD diagnosis may be less stable and reliable in adolescence. However, despite the reported instability of categorically defined diagnoses, there is increasing evidence that early maladaptive personality traits are predictive of future personality functioning. A more dimensional approach for the assessment of personality pathology in adolescence as well as new assessment measures are thus needed. The aim of this study was to examine the psychometric properties of the adolescent version of the Inventory of Personality Organization (IPO-A), a measure that allows both a categorical and dimensional approach to personality assessment. Moreover, potential differences between adolescents and young adults regarding specific dimensions of personality organization were investigated. Method: Participants included 430 adolescents (M = 16 years old) and 448 young adults (M = 24 years old) from the community. Exploratory structural equation modeling analyses were conducted on both samples. Results: Results suggest that the IPO-A is a valid and reliable instrument for assessing personality functioning in adolescents. Adolescents also reported significantly higher scores on four of the five dimensions, indicating more severe identity disturbance; more impaired reality testing; more aggression; and poorer moral functioning than adults. Significant differences were also observed among adolescents of different age groups as well as between boys and girls in terms of the five identified factors of the IPO-A. Adolescent girls experienced significantly more difficulties with regard to an unstable sense of self and others, and had poorer moral functioning than adolescent boys. Conclusion: From a developmental point of view, a narcissistic reaction may be solicited in the context of the developmental challenges of adolescence and emerging adulthood, which may not necessarily be a part of an enduring stance and pathological narcissism. Keywords: Personality organization, personality assessment, personality disorders, adolescence, narcissism.
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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 | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 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".