Evaluation of a collective reflective coaching device to sustain early childhood education managers well-being during covid-19
Bibliographic record
Abstract
Background. \nWork well-being of early childhood education and care (ECEC) managers is essential to provide educational quality services to children (Corr et al., 2017). If some factors are known to influence work well-being, such as job stress, burnout, depressive symptoms, self-compassion, and work engagement (Cumming & Wong, 2019; Rothmann, 2008; Zessin, 2015), COVID-19 pandemic appears to be deleterious (Bigras et al., 2021), particularly because of the frequent adjustments induced by public health measures and staffing shortages. In a previous study, ECEC managers expressed a need for support to face the challenges encountered during the pandemic (Bigras et al., 2021). To meet their need and support their work well-being, a professional coaching process, through a collective reflexive group, had been implemented (Bigras et al., 2021). Coaching modalities involving reflective practice were included to ensure its effectiveness, considering its value for dealing with complex problems, as ECEC managers did since the pandemic (Susman-Stillman et al., 2020). \n \nObjective. \nThis study aims to evaluate the effects of a collective reflective coaching device intended for ECEC managers on the factors linked with work well-being (self-compassion, work-related stress, burnout, depressive symptoms, and work engagement) during the pandemic. Methods. This research uses a quasi-experimental design (pre-post) with a control group. Experimental group involves 39 ECEC managers from some regional areas in Quebec (Canada) and was recruited with the help of the regional grouping of ECEC of Monteregie. The experimental group, divided in four subgroups, met for three hours every four weeks between February and June 2021. The meetings focused on topics based on managers' needs to support their work well- \nbeing (e.g., stress, self-compassion, self-care). Control group involves 43 ECEC managers from the same regional areas recruited by email. Quantitative data were collected with an online questionnaire (LimeSurvey) completed before the first meeting and after the last one for both experimental and \ncontrol groups. Social desirability was measured for the two groups, at both pre and post times. \n \nResults. \nANCOVA analyses controlling for pre-test scores were conducted. Since the control group (M = 0.71, SD= 0.19) had higher pre-test score on social desirability than the experimental group (M = 0.61; SD =0.16), t(79.115)=-2.561, p=0.012, we controlled for this variable. Preliminary results indicated that each variable is explained by the pre-test scores (p>0.001). Also, the descriptive data at pre-test indicated that participants in experimental group had lower pre-test scores and that they tended to reach the means score of control group on post-test scores for each variable. \n \nConclusion. \nPreliminary results suggest that reflective support system could be beneficial to improve well-being of ECEC managers through COVID-19 because theirs scores improved between the beginning and the end of the meetings. It is possible that participants in the experimental group joined the program because they needed support for their well-being. Nevertheless, since managers must perform their job with high quality in ECEC, it seems imperative to ensure that they receive all the support and resources they need to mitigate negative influences of the pandemic on their well-being.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".