The Relationship between Self-esteem, Anxiety and Depression among UniversityStudents in Lagos, Nigeria
Bibliographic record
Abstract
Previous studies showed negative significant correlations between self-esteem, and emotional states such as anxiety and depression among adolescents especially when studying in a higher institution. This study was, therefore, designed to investigate the prevalence of self-esteem, anxiety and depression, their sociodemographic correlates and the relationships between self-esteem, anxiety, and depression. Methods A cross-sectional design was employed for this study with the participation of 236 students at a university in Lagos, Nigeria. A structured questionnaire was applied to ask about the sociodemographic characteristics of the participants. They were also asked to complete the Rosenberg Self-esteem Scale, and the Hospital Anxiety and Depression Scale (HADS) to determine their levels of self-esteem and probable anxiety and depression and their statistical relationships. Results The findings on the reported levels of self-esteem showed that 22 (9.3%) had low self-esteem and only 12 (5.1%) experienced higher self-esteem. The males had lower self-esteem compared to the female participants. The majority of the participants 154 (65.2%) experienced probable anxiety while about one-third of them 101 (32.8%) manifested with probable depression. There were negative correlations between self-esteem, anxiety and depression -.403 and -.438. Conclusions This study showed that self-esteem negatively correlated with anxiety and depression. This negative association could significantly affect students’ educational achievements and quality of life. There is a need for tertiary institutions to routinely determine the self-esteem of students and also provide psychological interventions aimed at proactively increasing students’ self-esteem to prevent the existence of comorbid psychological and academic distress.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".