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Record W3195551331 · doi:10.3389/frsc.2021.688473

Contact With Nature as a Mental Health Buffer for Lower Income Communities During the COVID-19 Pandemic

2021· article· en· W3195551331 on OpenAlexaff
Amber L. Pearson, Teresa H. Horton, Karin A. Pfeiffer, Rachel T. Buxton, Joseph C. Gardiner, Wei Liu, Ruth F. Hunter, Mathew P. White

Bibliographic record

VenueFrontiers in Sustainable Cities · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicUrban Green Space and Health
Canadian institutionsCarleton University
FundersNational Cancer InstituteNational Institutes of HealthCollege of Engineering, Michigan State UniversityNegaunee FoundationMichigan State University
KeywordsCoronavirus disease 2019 (COVID-19)PandemicMental health2019-20 coronavirus outbreakSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)PsychologyPsychiatryMedicineVirologyInfectious disease (medical specialty)

Abstract

fetched live from OpenAlex

Despite a growing number of research outputs on the importance of nature contact during the COVID-19 pandemic, we know of no longitudinal research conducted prior to and during the pandemic among low-income and minority ethnicity populations, i.e. those that might be most affected. Furthermore, we have scant information about how and to what degree contact with nature might protect mental health or mitigate worsening of mental health during the pandemic. We filled these gaps using a subset of a longitudinal study of n = 86 individuals in low-income, predominantly African American, neighborhoods in Detroit, MI, USA. The study addressed the following research questions: 1) did self-reported use and perceived value of nature change during, versus prior to, the pandemic; 2) did perceived access to outdoor spaces buffer people against mental health issues such as stress, anxiety and depression symptoms; or 3) did objectively measured quality of nature views from home buffer people against mental health issues, taking into account relevant covariates and pandemic experiences (e.g., loss of employment, death of a friend/relative)? While attitudes to nature improved slightly from pre- to during the pandemic, we also observed significant decreases in most types of outdoor physical activity and passive enjoyment of nature (e.g., smelling plants/rain). We found a positive association between visibility of greenspace and perceived stress and anxiety, which not only contradicts previous research findings, but was especially surprising given that overall there was a decrease in perceived stress from 2019-2020. We did not detect associations between perceived access/use of nature and mental health. However, higher depressive symptoms were associated with exposure to more COVID-19-related stressors (lost employment, death of friends from COVID-19, etc.). Taken together, our results indicate that COVID-19 may serve to prolong or exacerbate mental health issues, rather than create them, in this population and that low quality greenspace may perhaps limit the ability for nature view to buffer mental health during the pandemic.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.038
Threshold uncertainty score0.075

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.010
GPT teacher head0.262
Teacher spread0.252 · 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 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
Published2021
Admission routes1
Has abstractyes

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