Evidence map›Paper›PMID 28848466›Full record

ReviewFrontiers in psychology2017

Mental Toughness and Individual Differences in Learning, Educational and Work Performance, Psychological Well-being, and Personality: A Systematic Review.

Ying Lin, Julian Mutz, Peter J Clough, Kostas A Papageorgiou

Abstract readReview
In one paragraph

Review in Frontiers in psychology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 56 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
56citing papers in PubMed, 3 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

56 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Review
  5. Article
  6. Review
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors.

Ying LinDepartment of Psychology, University of Southern California, Los AngelesCA, United States.
Julian MutzDepartment of Epidemiology and Biostatistics, School of Public Health, Faculty of Medicine, Imperial College LondonLondon, United Kingdom.
Peter J CloughManchester Metropolitan UniversityManchester, United Kingdom.
Kostas A PapageorgiouQueen's University BelfastBelfast, United Kingdom.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Mental toughness (MT) is an umbrella term that entails positive psychological resources, which are crucial across a wide range of achievement contexts and in the domain of mental health. We systematically review empirical studies that explored the associations between the concept of MT and individual differences in learning, educational and work performance, psychological well-being, personality, and other psychological attributes. Studies that explored the genetic and environmental contributions to individual differences in MT are also reviewed. The findings suggest that MT is associated with various positive psychological traits, more efficient coping strategies and positive outcomes in education and mental health. Approximately 50% of the variation in MT can be accounted for by genetic factors. Furthermore, the associations between MT and psychological traits can be explained mainly by either common genetic or non-shared environmental factors. Taken together, our findings suggest a 'mental toughness advantage' with possible implications for developing interventions to facilitate achievement in a variety of settings.

Indexed as

educational performancegenetics of mental toughnessmental toughnesspersonalitypsychological well-being

Identifiers

PMID28848466
PMCPMC5554528

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.