Insecure Attachment in Clinical Supervisory Relationships: Balancing Personal with Professional
Bibliographic record
Abstract
Background: The clinical supervisory relationship (SR) between counsellors-in-training and established psychologists has been considered by counsellor trainees, researchers, and the profession to be one of the most crucial and influential aspects of the training process. Accordingly, more positive and strongly bonded SRs have yielded a higher amount and magnitude of positive supervision outcomes in supervisees’ observed and felt sense of professional development and competencies. In the past few decades, an attachment theory lens has been applied to the SR to help explain relational dynamics that can enhance or hinder the quality and strength of the alliance. Within this literature base, insecure (as opposed to secure) supervisory attachments (ISAs) have been demonstrated to interfere with the SR and thus, the training process and its positive outcomes. Ethically speaking, part of a supervisor’s professional responsibilities is to work through relationship barriers or ruptures that occur within the SR that have the potential to impede training. However, addressing attachment concerns often involves more personal, rather than professional, interactions and conversations which can cross professional boundaries, take time away from other training activities, and create more emotionally intimate relationships. Overcoming an ISA in the SR can therefore further threaten the already challenging personal-professional balance supervisors are expected to maintain. As such, the current study aimed to acquire a deeper understanding of clinical supervisors’ experiences navigating and overcoming ISA in their supervisees, while still appropriately balancing their personal and professional roles. Methodology: Three clinical supervisors practicing in Alberta were interviewed. All participants had experiences within the last five years of successfully easing at least two supervisees’ ISAs into a more secure bond during clinical supervision. Interpretative Phenomenological Analysis was then employed to analyze each interview separately and later collectively to extract similarities and differences in themes among participants. Results: Five group experiential themes (GETs) and 15 sub-themes emerged from the interviews. GETs consisted of: (1) Increased Demands on Supervisors, (2) Supervisors’ Intentional Attunement for Guiding Action, (3) Supervisors’ Encouragement of Vulnerability (Becoming a Safe Haven), (4) Supervisors’ Activation of Exploration (Becoming a Secure Base), and (5) The SR Gaining Equilibrium. Conclusions: The findings from this study reflect many of the findings and recommendations in the attachment theory literature and established best practices for clinical supervisors in the supervision literature. Furthermore, these findings provide further insight into how ISAs can (a) be identified, (b) challenge the supervisor, (c) be successfully and appropriately addressed in the SR, and (d) change when easing into more security. Implications for practicing clinical supervisors and supervision training are presented. Future research may wish to investigate the success of particular methods outlined in this study, gain the perspectives of supervisees, and understand the role of diversity in addressing ISA in SRs.
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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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.005 | 0.006 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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 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".