Impact of Outcome Expectations on Junior Secondary Students’ Willingness to Self-Disclose During Counseling in Anaocha LGA, Anambra State
Bibliographic record
Abstract
The willingness of junior secondary students to self-disclose during counseling sessions has been a growing concern, despite the increasing presence of guidance and counseling departments in Nigerian schools. This study used a descriptive survey design to examine the impact of outcome expectations on junior secondary school students' willingness to self-disclose during counseling in Anaocha LGA, Anambra State. The target population included all JSS1–JSS3 students in government-approved secondary schools, with a total sample of 398 students selected through multistage and stratified sampling. Data was collected using the Outcome Expectations and Self-Disclosure Scale (OESDS), which was validated by academic experts and found to have high reliability. Descriptive statistics and multiple regression analysis (SPSS version 25) were used for data analysis. The findings revealed that that outcome expectation variables during counseling sessions in Anaocha Local Government Area exhibited moderate levels for emotional openness (29.91), stigma tolerance (11.12), anticipated risk (13.51), and anticipated utility (13.47). Social support (59.38) and attitude toward self-disclosure (78.58) were higher. Girls had slightly higher emotional openness (30.02) and stigma tolerance (11.59), while boys had higher anticipated risk (13.65) and anticipated utility (13.84). The correlation analysis revealed significant relationships, with emotional openness showing moderate positive correlations with social support (0.33) and attitude toward self-disclosure (0.32). Stigma had a strong positive correlation with anticipated risk (0.90). Finally, the regression analysis indicated that social support, anticipated utility, and anticipated risk were significant predictors of attitudes toward self-disclosure, with R-values of 0.375 (F = 80.59), 0.443 (F = 34.35), 0.499 (F = 34.01), and 0.526 (F = 19.16), respectively. The study concludes that addressing these factors, along with improving counselors' multicultural competencies, is essential to fostering a more open counseling environment in schools. Based on these findings, it is recommended that school counselors undergo regular professional development, focusing on cultural competence, and that counseling programs incorporate strategies to reduce stigma and enhance social support for students.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".