The use of theoretical models in psychology supervisor development research from 1994 to 2010: A systematic review.
Bibliographic record
Abstract
Training in supervision is becoming an increasingly important component of professional psychology programs. To assist students in developing supervisory competencies, knowledge of relevant research and effective training methods is required and, ideally, such knowledge should be derived from an empirical literature comprising good quality, theory-based research. To evaluate the nature of the empirical literature on supervisor development, a systematic review was conducted to determine the extent to which theoretical models have been used in this literature. Psyclnfo, Medline, CINAHL, and ERIC were searched for articles published between 1994 and 2010. Initially 3,248 abstracts were reviewed, 25 of which met the criteria of being empirical, focused on supervisor development, and having participants with graduate training in counselling or professional psychology. Of these studies, only half drew upon models of supervisory development in the conceptualisation, design, or interpretation of the research study. The most often used model was Watkins' Supervisor Complexity Model (Watkins, 1990, 1993, 1994). Approximately one third of studies examined the influence of past training and experience in supervision on current supervision practices. For competency-based training in supervision to advance, the theoretically informed evidence base needs to be greatly expanded, and much more research is needed that explicitly applies and/or evaluates models of supervisory development.Keywords: practicum supervision, professional supervision, clinical psychology, counselling psychology, systematic reviewClinical supervision has two main purposes: to ensure the integrity of clinical services and to develop service provision competence in the supervisee (Falender & Shafranske, 2004). Although many definitions of clinical supervision have been proposed, Milne's (2007) refinement of Bernard and Goodyear's widely cited work (2004) is the most comprehensive and detailed presented thus far in the literature:The formal provision, (i.e., sanctioned by relevant organisation/s) by senior/qualified health practitioners (or similarly experienced staff), of an intensive education (general problem solving capacity; developing capability) and/or training (competence enhancement) that is casefocused and which supports, directs, and guides (including restorative and/or normative topics, addressed by means of professional methods, including objective monitoring, feedback and evaluation) the work of junior colleagues (supervisees).In Canada, competency in supervision is required for licensure by some provincial or territorial regulatory bodies (see http:// www.cpa.ca/documents/MRA.pdf). Similarly, the American Psychological Association (APA) has stated that clinical supervision should be regarded as a distinct professional competency (American Psychological Association, 2006). Clinical supervision is also recognised as a key component of prelicensure training in Canada, as accreditation of professional psychology graduate programs requires doctoral students to have instruction in clinical supervision, and internship accreditation requires that interns acquire knowledge and skills in supervision (Canadian Psychological Association, 2011). As the provision of supervision is likely to be a component of future practice for many professional psychologists, graduate programs should provide training in supervision that is, ideally, built on a solid evidence base, as is the case in other areas of professional training (Hunsley & Barker, 2011).Current perspectives on graduate training in professional psychology emphasise a competency-based approach, with competency being broadly defined as the knowledge, skills, and values required to practice effectively (Falender et al., 2004). The task for educators, then, is to identify the knowledge, skills, and values that constitute a required competency such as supervision and, further, to effectively train students and professionals to develop the competency. …
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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 | 0.041 | 0.129 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.006 | 0.007 |
| Bibliometrics | 0.041 | 0.028 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.005 | 0.007 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".