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Record W4403304080 · doi:10.1177/13591053241270410

Psychological, psychosocial and physical barriers preventing nature-based intervention participation in adults with mental health disorders: A scoping review

2024· review· en· W4403304080 on OpenAlexfundno aff
Mark W Burrell, Jo Barton, Gina Yannitell Reinhardt, Carly Wood

Bibliographic record

VenueJournal of Health Psychology · 2024
Typereview
Languageen
FieldHealth Professions
TopicHealth, psychology, and well-being
Canadian institutionsnot available
FundersOntario Trillium FoundationMcMaster University
KeywordsPsychosocialMental healthPsychological interventionReferralInclusion (mineral)Intervention (counseling)PsychologyMedicineClinical psychologyPsychiatryNursingSocial psychology

Abstract

fetched live from OpenAlex

Nature-based interventions (NBIs) are becoming a common mental health care referral option; however, little is known about the barriers to participation. Research reveals a concentration of evidence on the practical barriers with a paucity of guidance on the personal barriers as experienced by service users. This review explores what is known on the psychological, psychosocial and physical barriers as disclosed by adult mental health service users and the various stakeholders involved in NBI. Nine of the 104 articles screened met the inclusion criteria. The review identified a total of 47 barriers in which the majority were standalone barriers unique to the individual article or participant that generated them. However, other barriers suggest a level of universality with the greatest array of barriers identified in the psychosocial category. The review highlights an urgent need for further research on the psychological, psychosocial and physical barriers to NBI participation.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.024
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.007
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.024
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.004
Bibliometrics0.0050.004
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0010.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.084
GPT teacher head0.600
Teacher spread0.517 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
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

Citations4
Published2024
Admission routes1
Has abstractyes

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