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Record W4414227237 · doi:10.18438/eblip30777

Public Libraries Have a Key Role to Play in Planetary Health Programs and Initiatives

2025· article· en· W4414227237 on OpenAlexvenueno aff
Maria King

Bibliographic record

VenueEvidence Based Library and Information Practice · 2025
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicGlobal Public Health Policies and Epidemiology
Canadian institutionsnot available
Fundersnot available
KeywordsFocus groupThematic analysisHealth promotionPublic healthPromotion (chess)Qualitative propertyQualitative researchComputer-assisted web interviewing

Abstract

fetched live from OpenAlex

A Review of: Patrick, R., Bruges, N., Gunasiri, H., Wang, Y., & Henderson‐Wilson, C. (2025). Healthy me, healthy planet: Evaluation of a pilot planetary health library program. Health Promotion Journal of Australia, 36(1), Article e882. https://doi.org/10.1002/hpja.882 Objective – To evaluate the impact of the Healthy Me, Healthy Planet (HMHP) pilot health promotion program, running from December 2021 to August 2022. The program was designed to promote the health benefits of action on climate change to build a climate ready community. Design – Mixed methods design of online quantitative surveys and online qualitative focus groups via Zoom. Setting – Public libraries in Victoria, Australia during the Covid lockdown. Subjects – 136 adults aged 18+ who were members of the public who were program participants, as well as library staff and HMHP delivery partners. Methods – Researchers conducted pre- and post-surveys in English and simplified Chinese using the quantitative Personal Wellbeing Index (PWI) and Environmental Attitudes Inventory (EAI). The pre-surveys were undertaken from December 2021-February 2022 and the post-surveys between the 26th of July and 7th August 2022. A focus group was conducted in July 2022 for program participants, and a second focus group for library staff and HMHO delivery partners. Focus group transcripts were analysed in NViVO using inductive and deductive thematic analysis approaches. Survey and focus group data was triangulated using thematic content analysis. Main Results – The impact evaluation found four main themes: personal health and social-wellbeing, individual capacity building, pro-environmental knowledge, and organisational/community capacity. The authors found that libraries promote meaningful social connections and can use programs like this to create shared community social connections, including intergenerational, on the topics of climate change, sustainability, and healthy environments to alleviate loneliness and isolation and take collective action to adopt pro-environmental behaviours. Public libraries are well placed to deliver these types of programs as trusted community knowledge hubs as they know their communities and can reach populations at every age. As well, libraries are stakeholders for partnership development, empowering communities to take ownership of their health and environmental well-being and engage in pro-environmental behaviour. Conclusion – The HMHP program offers a tested framework for others to adopt to align to health and well-being strategies, particularly around climate change. It highlights the potential benefits of linking health and well-being and planetary health into a joint health promotion, and the value of the use of public libraries as a setting for these types of promotions and programs. It recommends that future programs should prioritise community engagement in the decision-making process, integrate intergenerational aspects more explicitly, and take a systems thinking approach to collaborate with stakeholders across sectors on programs addressing planetary health.

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)0.022
metaresearch head score (Gemma)0.031
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.972
Threshold uncertainty score0.218

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0220.031
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.005
Science and technology studies0.0170.007
Scholarly communication0.0280.024
Open science0.0030.030
Research integrity0.0070.007
Insufficient payload (model declined to judge)0.0650.023

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 head0.036
GPT teacher head0.294
Teacher spread0.258 · 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.

Study designNot applicable
Domainnot available
GenreCommentary

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".

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Citations0
Published2025
Admission routes1
Has abstractyes

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