Telehealth Psychotherapy for Severe Personality Disorder during COVID-19: Experience of Australian Clinicians
Bibliographic record
Abstract
OBJECTIVE: Restrictions on social interaction during the COVID-19 pandemic necessitated a rapid transition to telehealth to continue providing psychotherapy to people diagnosed with personality disorder. This naturalistic cross-sectional study evaluated the experiences of clinicians using telehealth for the first time to treat clients diagnosed with a severe personality disorder (complex and/or high risk presentation). METHODS: Thirty clinicians working at a specialist clinic for personality disorders completed an online survey during May-June 2020 in Melbourne, Australia. RESULTS: Despite having some initial technical issues, most participants rapidly and successfully connected with clients via phone and/or video-conference, recommencing individual and group evidence-based psychotherapies. Appointments were kept more reliably than when in-person treatment was offered. Issues around privacy, confidentiality, risk, quality of interaction, and treatment boundaries were raised, highlighting the need for specific guidelines and formal processes. However, clinicians’ awareness of some of the benefits of telehealth was evident, with most looking forward to using telehealth for some aspects of their work with clients and more generally into the future. CONCLUSIONS: This experience with delivering psychotherapy using telehealth during COVID restrictions suggests that it is an acceptable platform that can be managed safely for treating patients with severe mental illness in the short term at least. This outcome encourages the pursuit of efficacy studies to evaluate telehealth as a more equitable and accessible treatment modality.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".