Mindfulness and time perception: A systematic integrative review
Bibliographic record
Abstract
Several recent studies have explored the relationships between mindfulness and time perception, an area of research that has become increasingly popular in the last 10-15 years. In this article, we present a systematic integrative review of the evidence on this subject. We also integrate the field's findings into a conceptual framework which considers the multifaceted nature of both mindfulness, and time perception research. To identify the relevant literature, we searched the following databases using relevant keywords: PsycINFO; Medline; EBSCO Host Psychology and Behavioral Sciences Collection; and Web of Science. These searches were last performed on the 4th of May 2022, and additional hand searches were also conducted. To be included, articles had to be in English and contain original data about the potential relationship(s) between mindfulness and time perception. Articles which did not present usable data about the relationship(s) between the variables of interest were excluded. In total, 47 research articles were included in the review (combined sample size of ∼5800 participants). Risks of bias in the selected studies were evaluated using two separate assessment tools designed for this purpose. Through an integrative narrative synthesis, this article reviews how mindfulness may relate to time perception for various reference frames, and for various time perception measures and methods. It also provides new insights by exploring how a wide range of findings can be integrated into a coherent whole, in light of some relevant time perception models and mindfulness theories. Altogether, the reviewed data suggest the existence of complex and multifaceted relationships between mindfulness and time perception, highlighting the importance of considering many factors when planning research or interpreting data in this field. Limitations of the current review include the scarceness of data for certain categories of findings, and the relatively low prevalence of studies with a randomized controlled design in the source literature. This research was partly funded by a grant from the Natural Science and Engineering Research Council of Canada.
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 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 | 0.010 | 0.043 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.006 |
| Bibliometrics | 0.019 | 0.014 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
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".