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Record W4283118478 · doi:10.2519/jospt.2022.11152

Looking at Both Sides of the Coin: Addressing Rupture of the Therapeutic Relationship in Musculoskeletal Physical Therapy/Physiotherapy

2022· article· en· W4283118478 on OpenAlexaff
Maxi Miciak, Giacomo Rossettini

Bibliographic record

VenueJournal of Orthopaedic and Sports Physical Therapy · 2022
Typearticle
Languageen
FieldNeuroscience
TopicPain Management and Placebo Effect
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsPhysical therapyMedicinePhysical medicine and rehabilitationPsychology

Abstract

fetched live from OpenAlex

Synopsis As physical therapists, we may have all experienced tense moments in our therapeutic relationships with patients. Whether small or large, implicit or explicit, relational breakdowns are a normal part of human interactions. Within the clinical encounter, these tensions are called “ruptures.” In psychotherapy, ruptures have been associated with increased dropout rates and poor clinical outcomes. To increase the likelihood that physical therapists establish, maintain, and strengthen therapeutic relationships with their patients, recognizing and repairing ruptures would seem logical. However, we contend that relational tensions, although inevitable, are most often avoided by physical therapists, potentially to the peril of the therapeutic relationship. A responsive approach that involves adjusting our mind-set, being aware, and taking appropriate action could facilitate rupture repair. We provide clinical examples of rupture and repair and discuss the opportunities that “the other side of the coin” presents for professional and personal growth. J Orthop Sports Phys Ther 2022;52(8):500–504. Epub: 19 June 2022. doi:10.2519/jospt.2022.11152

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.509
Threshold uncertainty score0.520

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.030
GPT teacher head0.304
Teacher spread0.273 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations12
Published2022
Admission routes1
Has abstractyes

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