Development and Psychometric Testing of the Supportive Supervisory Scale
Bibliographic record
Abstract
PURPOSE: To describe the development and psychometric testing of the Supportive Supervisory Scale (SSS). METHODS: The development of the items of the scale was based on Winnicott's relationship theory and on focus groups with 26 healthcare aides (HCAs) and 30 supervisors from six long-term care (LTC) facilities in Ontario, Canada. Content validity of the 15-item instrument was established by a panel of experts. Based on a secondary analysis of data collected from 222 HCAs in 10 LTC facilities in Ontario, Canada, the SSS was subjected to principal components analysis with oblique rotation. FINDINGS: A two-factor solution was accepted, which is consistent with the theoretical conceptualization of the instrument. Factor I was labeled Respects Uniqueness and Factor II was labeled Being Reliable. Internal consistency of Factor I was .95, and that of Factor II was .91. Discriminant validity was also established. The focus groups revealed that "being available to staff" while "recognizing the HCA as an individual, and taking a moment to get to know them" was essential to feeling supported by their supervisor. CONCLUSIONS: The SSS is a reliable and valid measure of supervisory support of supervisors working in LTC facilities. At the core of supportive supervision is the supervisor's ability to develop and maintain positive relationships with each HCA. It is through respecting the uniqueness of each HCA and being reliable that supervisor-HCA relationships can flourish. CLINICAL RELEVANCE: Supportive leadership in LTC settings is a major contributor to HCAs' job satisfaction and retention and to quality of patient care. Therefore, a tool developed and tested to measure supervisors' supportive capacities in LTC is primal to evaluate the effectiveness of supervisors in these environments.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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".