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Record W4368360828 · doi:10.1097/jan.0000000000000489

Effective Nursing Recovery-Oriented Interventions for Individuals With Substance Use Disorder

2022· review· en· W4368360828 on OpenAlexaff
Niall Tamayo, Annette Lane

Bibliographic record

VenueJournal of Addictions Nursing · 2022
Typereview
Languageen
FieldHealth Professions
TopicMental Health and Patient Involvement
Canadian institutionsAthabasca UniversityCentre for Addiction and Mental Health
Fundersnot available
KeywordsPsychological interventionNursingNursing Interventions ClassificationHealth careEmpowermentMedicineSubstance usePsychologyPsychiatry

Abstract

fetched live from OpenAlex

ABSTRACT: Nurses support the recovery of individuals with substance use disorder. How they support individuals, however, may impact the effectiveness of their work. For example, there are various paradigms of recovery that alter interventions. In addition, negative attitudes adopted by clinicians discourage individuals who use substances from accessing healthcare services, experiencing further health deterioration. Alternatively, nurses can enact interventions that promote positive experiences, further supporting the recovery of individuals. Hence, it is beneficial to increase nurses' awareness of effective interventions that promote recovery. The purpose of this literature review is to examine effective nursing interventions that promoted recovery of those with substance use disorders from the perspective of nurses and individuals who received nursing care. The review identified that effective interventions were based on three major themes: person-centered care, empowerment, and maintaining supports and capability enhancement. In addition, literature revealed that some interventions were perceived to be more effective; this depended on whose viewpoint was examined-nurses or individuals with substance use disorders. Finally, there are interventions based on spirituality, culture, advocacy, and self-disclosure that are often disregarded but may be effective. Nurses should utilize the more prominent interventions as they offer the most benefit and integrate interventions that are often overlooked.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.967
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0030.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0010.000

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 head0.282
GPT teacher head0.503
Teacher spread0.221 · 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.

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

Citations6
Published2022
Admission routes1
Has abstractyes

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