Client Characteristics and the Effectiveness of Embedded Counseling Services in a College of Veterinary Medicine
Bibliographic record
Abstract
Despite the widespread implementation of embedded counseling models in veterinary training programs, limited information is available about veterinary students and house officers who seek help, and researchers have not evaluated the effectiveness of counseling services. This study sought to describe clients' characteristics, presenting concerns, and mental health histories, in addition to determining if participating in counseling was associated with decreases in psychological distress. The sample included 437 Doctor of Veterinary Medicine (DVM) students and house officers receiving embedded counseling services between August 2016 and March 2024 at a public university in the Midwestern United States. Approximately half were first-year students when they initially accessed services. The most common presenting concerns included stress, anxiety, depression, academic performance, perfectionism, self-esteem/confidence, attention/concentration difficulties, mood instability, sleep difficulties, adjustment, family issues, career concerns, eating/body image concerns, and specific relationship problems. DVM students and house officers reported higher scores on some, but not all, measures of psychological distress prior to participating in counseling, compared with a normative sample of college students seeking counseling at university counseling centers. However, these differences tended to be small in magnitude. Participating in counseling was associated with meaningful improvements in depression, generalized anxiety, social anxiety, academic distress, eating concerns, frustration/anger, family distress, substance use, suicidal ideation, and overall psychological distress. Clients who reported improvements in depression and anxiety also tended to report reductions in academic distress, which underscores the value of embedded counseling services in improving the well-being and academic retention of DVM students and house officers. Implications for outreach, research, and clinical practice are discussed.
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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 | 0.002 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".