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Record W3035717317 · doi:10.1080/10550887.2020.1773730

Cognitive state, substance use patterns and outcome after discharge from Kfar Izun, a unique rehabilitation facility

2020· article· en· W3035717317 on OpenAlexaboutno aff
Alon Richter, Anat Sason, Miriam Adelson, Omri Frish, Einat Peles

Bibliographic record

VenueJournal of Addictive Diseases · 2020
Typearticle
Languageen
FieldMedicine
TopicCannabis and Cannabinoid Research
Canadian institutionsnot available
Fundersnot available
KeywordsAnxietyVerbal fluency testCognitionCannabisRehabilitationMontreal Cognitive AssessmentPsychologyClinical psychologyMedicinePsychiatryPhysical therapyNeuropsychologyCognitive impairment

Abstract

fetched live from OpenAlex

We studied cognitive performance following discharge from a novel rehabilitation facility, treating individuals with psychosis that developed during trips abroad following mandatory military service. Montreal Cognitive Assessment (MoCA), phonetic and semantic fluency, State-Trait Anxiety, and self-Efficiency were administered before discharge, and 3 and 6 months after discharge. Of the 43 participants (30.2% females), 23(54.8%) had cognitive impairment (MoCA <27), and 15(35.7%) had poor phonetic fluency. Anxiety trait and state were high and inversely correlated with self-efficacy (R=-0.48, p = 0.001) and phonetic fluency (R=-0.43, p = 0.004) and was higher among those who experienced physical exposure, females, and those who served in non-combat army units. Six months after discharge, of 32 participants, 28 were working/studying with a 58.1% reduction in smoking and alcohol consumption, and 16 participants stopped substance use. Phonetic fluency improved among the high anxiety state group with no change among the others. High anxiety levels lowered among those who were still using drugs after six months. The anxiety level lowered and 87.1% of the participants were conducting a productive lifestyle at 6 months after discharge, but half still abused cannabis. Bigger sample and longer follow up would be needed to learn more about the impact of rehabilitation.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.507

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.023
GPT teacher head0.301
Teacher spread0.277 · 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

Citations1
Published2020
Admission routes1
Has abstractyes

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