Development and Validation of the Career Counseling Outcome Questionnaire in Two Clinical Settings
Bibliographic record
Abstract
This study reports the development and initial validation of the Career Counseling Outcome Questionnaire (CCOQ) in two individual career counseling settings using a college sample ( n = 1,140) and a community sample ( n = 161). Exploratory and confirmatory factor analyses revealed five correlated factors in both samples: (a) knowledge of the career decision-making process (4 items), (b) knowledge of the self (3 items), (c) knowledge of career information (3 items), (d) anxiety towards career decision-making (3 items), and (e) career undecidedness (2 items). The CCOQ scale scores changed in the expected theoretical direction during the career counseling interventions and did not change when clients were not receiving counseling. Except for anxiety, all CCOQ subscales predicted satisfaction with the career decision twelve months after counseling. The CCOQ total score predicted satisfaction with the decision twelve months after counseling, over and beyond a widely used instrument assessing sources of career decision difficulties (i.e. the Career Decision Difficulties Questionnaire; CDDQ). Career counselors could use the CCOQ to monitor the effectiveness of their interventions in complement to diagnostic measures such as the CDDQ.
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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 | 0.017 | 0.036 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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".