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Record W2194753935 · doi:10.1177/0308022614562784

Communication during goal-setting in brain injury rehabilitation: What helps and what hinders?

2015· article· en· W2194753935 on OpenAlexaff
Anne Hunt, Guylaine Le Dorze, Helene J. Polatajko, Carolina Bottari, Deirdre Dawson

Bibliographic record

VenueBritish Journal of Occupational Therapy · 2015
Typearticle
Languageen
FieldMedicine
TopicTraumatic Brain Injury Research
Canadian institutionsUniversity of TorontoBaycrest HospitalUniversité de MontréalCentre for Interdisciplinary Research in RehabilitationHolland Bloorview Kids Rehabilitation Hospital
Fundersnot available
KeywordsIdentification (biology)ConversationActive listeningPsychologyRehabilitationAcquired brain injuryGoal settingProcess (computing)Cognitive psychologyTraumatic brain injuryCognitionApplied psychologyPsychotherapistSocial psychologyComputer scienceCommunicationNeuroscience

Abstract

fetched live from OpenAlex

Introduction Setting goals with individuals with acquired brain injury may be challenging due to impairments in cognition and communication. The purpose of this study was to explore how occupational therapists' communication behaviours during goal-setting with individuals with traumatic brain injury facilitated and hindered this process. Method This exploratory study used a conversation analysis inspired approach and frequency calculations to analyse and interpret videotaped goal-setting sessions. Sequences of dialogue leading to, and distracting from, problem identification, a key step in goal-setting, were identified and analysed. Specific therapist behaviours that facilitated or hindered problem identification were subsequently distinguished. Results Acknowledgements and affirmations, open-ended questions about specific tasks and reflective listening, were found to lead to problem identification by the client (facilitators). Instances of disconnections were characterized by a single theme, ‘lack of uptake.' Examples of these hindrances to goal-setting included, abrupt topic shifts, lack of acknowlegement and failure to explore what the client said. Conclusion Clinicians should consider their language use during goal-setting interviews and aim to utilize conversational behaviours that are facilitative whilst minimizing those that distract to optimize their client's engagement during the problem identification phase of goal-setting.

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)0.003
metaresearch head score (Gemma)0.001
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 score0.832
Threshold uncertainty score0.504

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.003
Open science0.0000.000
Research integrity0.0000.000
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 head0.094
GPT teacher head0.398
Teacher spread0.304 · 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

Citations14
Published2015
Admission routes1
Has abstractyes

Explore more

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