From Misconception To Clarity: Assessing The Knowledge And Perceptions Regarding OCPD Among Higher Education Learners
Bibliographic record
Abstract
Background: Obsessive-Compulsive Personality Disorder (OCPD) is a mental health illness whereby the sufferer is oriented towards intense orderliness, perfectionism, and control, all of which creates an unfavorable influence of their daily life and relationships. Aim: This research assesses and evaluates the perceptions and knowledge about OCPD among higher level educational learners. The purpose is to contribute to a better understanding of OCPD in the context of higher education, as well as to give insights that can help to build more effective support systems and educational initiatives for people with OCPD. Methods: Convenience and purposive sampling were employed to collect data from 240 respondents using a structured questionnaire. Results and Conclusion: The research analysis and findings highlighted that there were no notable variations based on demographic factors via descriptive statistics and ANOVA testing. Factor analysis, further revealed that OCPD as an anxiety disorder, treatment options, impact on personal and academic life, perfectionism and emotional challenges, discomfort caused by disrupted routines and high expectations, and control requirements were the key characteristics as understood and perceived by learners. To address the misunderstandings faced by the learners regarding the explored mental health illness and to provide greater clarity, and raise awareness, the research suggests focused educational initiatives through a more informed and supportive institutional environment.
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 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 | 0.005 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".