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Record W2098473809 · doi:10.1080/01612840701748847

Use of Animal-Assisted Therapy in the Rehabilitation of an Assault Victim with a Concurrent Mood Disorder

2008· review· en· W2098473809 on OpenAlexaff
Sanjeev Sockalingam, Madeline Li, Upasana Krishnadev, K.G. Hanson, Kayli Balaban, Laura Pacione, Shree Bhalerao

Bibliographic record

VenueIssues in Mental Health Nursing · 2008
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicHuman-Animal Interaction Studies
Canadian institutionsUniversity of TorontoSt. Michael's Hospital
Fundersnot available
KeywordsRehabilitationMedicineMoodPsychotherapistMultidisciplinary approachPsychiatryPsychologyPhysical therapy

Abstract

fetched live from OpenAlex

Multidisciplinary mental health rehabilitation settings often encounter patients with complex comorbid medical and psychiatric issues that require integrative, multifaceted treatment strategies. Although medication and psychotherapy are typical treatment mainstays, a broader variety of therapeutic options are available, including animal-assisted therapy. Here we describe a patient who received animal-assisted therapy as a psychiatric rehabilitation tool to ameliorate his atypical depression following an assault and subsequent head injury. A review of the relevant literature highlights the therapeutic potential of animal-assisted therapy to restore and maintain patient independence and level of functioning, both of which are key treatment goals.

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)0.000
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: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.980
Threshold uncertainty score0.666

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.075
GPT teacher head0.483
Teacher spread0.408 · 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 designOther design
Domainnot available
GenreReview

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

Citations27
Published2008
Admission routes1
Has abstractyes

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