Positive mental states and their relation to psychosocial resources: protocol of a systematic review focusing on cultural moderators
Bibliographic record
Abstract
INTRODUCTION: Fostering well-being and positive mental states are major aims of many strategies for the promotion of public mental health. Such strategies become increasingly important since many people worldwide suffer from psychological distress and mental disorders, resulting in substantial individual and societal costs. Within the last years, there is a shift from strategies solely focusing on the reduction of mental distress to those also aiming at the promotion of positive mental states. Correlates, that is, psychosocial resources, of positive mental states may represent a starting point for those interventions. To date, a comprehensive systematic review on those correlates is still missing as well as knowledge on culture-related differences. METHODS AND ANALYSIS: A systematic review and meta-analysis on the longitudinal link between psychosocial resources (eg, income, optimism, social support and community coherence) and hedonic and eudaimonic positive mental states (eg, life satisfaction, happiness and forward-looking attitude) will be conducted. Using Hofstede's dimensions of culture and global metrics of Education, Industrialisation, Richness and Democratic values (EIRDness), we will examine culture-related moderators of these associations. The systematic review will be conducted following standards of the Cochrane Collaboration and will be reported in accordance with the Preferred Reporting Items for Systematic reviews and Meta-Analyse guidelines. Literature searches for primary studies will be carried out across four databases (APA PsycNet, Embase, Scopus and the Web of Science Core Collection), including all publications up to 27 January 2025. Screening at the level of titles and abstracts will be performed with the help of artificial intelligence software (ASReview). Study quality will be assessed using an adapted version of the Newcastle Ottawa Scale. We will employ multilevel meta-analyses of correlation coefficients, with cultural variables being examined as moderators. ETHICS AND DISSEMINATION: This systematic review does not require ethics approval, as it solely uses previously published data. Materials and data used for this review will be shared via open repositories (https://osf.io/2xkhs/). Results will be published in an international, peer-reviewed journal and presented at conferences including plain language summaries. OSF REGISTRATION DOI : https://doi.org/10.17605/OSF.IO/K7X52.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.107 | 0.110 |
| Meta-epidemiology (narrow) | 0.007 | 0.006 |
| Meta-epidemiology (broad) | 0.024 | 0.022 |
| Bibliometrics | 0.014 | 0.012 |
| Science and technology studies | 0.005 | 0.006 |
| Scholarly communication | 0.007 | 0.009 |
| Open science | 0.005 | 0.006 |
| Research integrity | 0.010 | 0.008 |
| Insufficient payload (model declined to judge) | 0.061 | 0.009 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".