Questionable prospective associations between mindfulness and mental health problems: A simulated multiverse reanalysis and comment on
Kimmo Sorjonen1, Bo Melin1, Marika Melin1
1Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden.
Abstract:
Based on findings in cross-lagged panel network (CLPN) models, Ma et al. concluded prospective effects between indicators of mindfulness and mental health problems. Here, we used multiverse methodology and found discrepant increasing, decreasing, and null effects depending on the used model, and meta-analytic aggregations of these discrepant effects did not differ significantly from zero. Hence, the conclusions by Ma et al. can be challenged. It is important for researchers to bear in mind that correlations, including cross-lagged effects in CLPN models, do not prove causality in order not to overinterpret findings, something that may have happened to Ma et al. For increased analytic rigor, we recommend researchers to fit, as we did here, alternative models to data and to juxtapose findings.
Insights
Mindfulness and mental health effects are questionable. Multiverse analysis revealed inconsistent results, suggesting no significant prospective relationship, challenging prior conclusions and emphasizing caution with correlational data.
Area of Science:
- Psychology
- Mental Health Research
- Statistical Modeling
Background:
- Previous research by Ma et al. suggested prospective effects between mindfulness and mental health problems using cross-lagged panel network (CLPN) models.
- The interpretation of these findings highlighted potential causal links, necessitating further investigation into the robustness of these conclusions.
Purpose of the Study:
- To re-evaluate the prospective effects between mindfulness indicators and mental health problems.
- To assess the impact of analytical choices on the observed cross-lagged effects using a multiverse methodology.
- To challenge the conclusions drawn by Ma et al. regarding the causal relationship between mindfulness and mental health.
Main Methods:
- Employed multiverse methodology to analyze the data, fitting a range of alternative statistical models.
- Utilized cross-lagged panel network (CLPN) models as a basis for comparison and analysis.
- Conducted meta-analytic aggregations of the discrepant effects obtained from the various models.
Main Results:
- Observed discrepant effects (increasing, decreasing, and null) between mindfulness and mental health problems depending on the specific model used.
- Meta-analytic aggregation of these varied effects showed no significant deviation from zero.
- The findings indicate that the prospective effects previously reported are not consistently supported across different analytical approaches.
Conclusions:
- The conclusions by Ma et al. regarding prospective effects between mindfulness and mental health problems are challenged by the current findings.
- Correlations and cross-lagged effects in CLPN models do not definitively prove causality, urging researchers to avoid overinterpretation.
- Recommends increased analytic rigor through fitting and juxtaposing findings from alternative models to ensure more robust scientific conclusions.
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