Correlates of a University Counseling Center’s Perceived Service Promptness
Bibliographic record
Abstract
The overall goal of this study was to explore the usefulness of a Perceived Service Promptness (PSP) measure for University Counseling Centers (UCCs). As UCCs compete for university resources, helping a client as quickly as possible or PSP can help to support a UCC’s documented ability to meet increasing client demands. Since no prior empirical research was found measuring PSP at a UCC, a four-item measure, adapted from a more general quality of service scale, was used. From August 2014 to May 2016, one hundred and seventeen non-urgent undergraduate students seeking counseling services filled out an online survey measuring demographics, client perceptions, wait measures, PSP and recommending the university. Confirmatory factor analysis and scale reliability data psychometrically supported the PSP scale. Correlational analyses showed that both wait time and wait bother experience were each significantly negatively related to PSP. However, hierarchical regression analyses showed that wait bother experience, but not wait time, significantly explained PSP beyond prior controlled-for demographic and client perception variables. In addition, PSP positively explained recommending the university beyond demographic, client perception and wait measures. Research limitations and future research issues 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 | 0.003 | 0.023 |
| 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 | 0.001 |
| Open science | 0.000 | 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".