Skip to main content
SpringerLink
Log in

Network analysis of the structure and change in the mini-mental state examination: a nationally representative sample

  • Original Paper
  • Published:
Social Psychiatry and Psychiatric Epidemiology Aims and scope Submit manuscript

Abstract

Purpose

The structure of the mini-mental state examination (MMSE) is inconsistent across factor analytic studies, and yet to be examined based on network analysis. The current study aims to identify the (I) cross-sectional network structure and (II) longitudinal network changes of the MMSE.

Methods

The MMSE was administered to a nationally representative sample of older adults (age 50 and over) in Ireland twice over 4 years (2012–2013: N = 7207; 2016: N = 5715). Psychometric network analysis was computed at each time point to identify structure, strength and magnitude of the network associations. Item clustering was examined, and modularity scores were computed to measure the overall strength of clustering. Centrality indices were used to identify the main aspects of the MMSE. Longitudinal differences between the networks were examined.

Results

Cross-sectionally, the MMSE network structure clustered into a single community (modularity score = 0) with orientation items identified as most central. Longitudinally, the MMSE was time invariant regarding structure, centrality and magnitude of the positive associations between the items. The average magnitude of the negative associations increased over time[(t(65.15) = 3.78, p < 0.001; time 1: M = − 0.59, SD = 0.58 time 2: M = − 1.65, SD = 1.97] as did their percentage.

Conclusion

Network analysis of the MMSE showed that the measure consisted of a single entity of cognitive functioning irrespective of time. Orientation items were repeatedly identified as most central. Longitudinal changes of the network were evident in increased negative associations between selected cognitive components after 4 years of follow-up. These changes may be explained by neuro-cognitive compensation processes.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1

Similar content being viewed by others

Availability of data and material

Based on data collected through the Irish Longitudinal study on Ageing (TILDA) available at the Irish Social Science Data Archive (www.ucd.ie/issda).

References

  1. Abraham IL, Manning CA, Boyd MR, Neese JB, Newman MC, Plowfield LA, Reel SJ (1993) Cognitive screening of nursing home residents: factor structure of the modified mini-mental state (3MS) examination. Int J Geriatr Psychiatry 8:133–138

    Google Scholar 

  2. Beaman SRD, Beaman PE, Garcia-Peña C, Villa MA, Heres J, Córdova A, Jagger C (2004) Validation of a modified version of the Mini-Mental State Examination (MMSE) in Spanish. Aging Neuropsychol Cogn 11:1–11

    Google Scholar 

  3. Borsboom D (2017) A network theory of mental disorders. World Psychiatry 16:5–13

    PubMed  PubMed Central  Google Scholar 

  4. Bowie P, Branton T, Holmes J (1999) Should the Mini Mental State Examination be used to monitor dementia treatments? Lancet 354:1527–1528

    CAS  PubMed  Google Scholar 

  5. Braekhus A, Laake K, Engedal K (1992) The Mini-Mental State Examination: identifying the most efficient variables for detecting cognitive impairment in the elderly. J Am Geriatr Soc 40:1139–1145

    CAS  PubMed  Google Scholar 

  6. Cabeza R, Anderson ND, Locantore JK, McIntosh AR (2002) Aging gracefully: compensatory brain activity in high-performing older adults. Neuroimage 17:1394–1402

    PubMed  Google Scholar 

  7. Castro-Costa E, Fuzikawa C, Ferri C, Uchoa E, Firmo J, Lima-Costa MF, Dewey ME, Stewart R (2009) Dimensions underlying the Mini-Mental State Examination in a sample with low-education levels: the Bambui Health and Aging Study. Am J Geriatr Psychiatry 17:863–872

    PubMed  Google Scholar 

  8. Dubois J, Galdi P, Paul LK, Adolphs R (2018) A distributed brain network predicts general intelligence from resting-state human neuroimaging data. Philos Trans R Soc B Biol Sci 373:20170284

    Google Scholar 

  9. Epskamp S, Cramer AOJ, Waldorp LJ, Schmittmann VD, Borsboom D (2012) qgraph: network visualizations of relationships in psychometric data. J Stat Softw 48:1–18

    Google Scholar 

  10. Fillenbaum GG, Wilkinson WE, Welsh KA, Mohs RC (1994) Discrimination between stages of Alzheimer’s disease with subsets of mini-mental state examination items: an analysis of consortium to establish a registry for Alzheimer’s disease data. Arch Neurol 51:916–921

    CAS  PubMed  Google Scholar 

  11. Folstein MF, Folstein SE, McHugh PR (1975) “Mini-mental state”: a practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res 12:189–198

    CAS  PubMed  Google Scholar 

  12. Folstein MF, Robins LN, Helzer JE (1983) The mini-mental state examination. Arch Gen Psychiatry 40:812

    CAS  PubMed  Google Scholar 

  13. Fruchterman TMJ, Reingold EM (1991) Graph drawing by force-directed placement. Softw Pract Exp 21:1129–1164

    Google Scholar 

  14. Galasko D, Klauber MR, Hofstetter CR, Salmon DP, Lasker B, Thal LJ (1990) The Mini-Mental State Examination in the early diagnosis of Alzheimer’s disease. Arch Neurol 47:49–52

    CAS  PubMed  Google Scholar 

  15. Giannakopoulos P, Gold G, Duc M, Michel J-P, Hof PR, Bouras C (2000) Neural substrates of spatial and temporal disorientation in Alzheimer’s disease. Acta Neuropathol 100:189–195

    CAS  PubMed  Google Scholar 

  16. Guerrero-Berroa E, Luo X, Schmeidler J, Rapp MA, Dahlman K, Grossman HT, Haroutunian V, Beeri MS (2009) The MMSE orientation for time domain is a strong predictor of subsequent cognitive decline in the elderly. Int J Geriatr Psychiatry 24:1429–1437

    PubMed  PubMed Central  Google Scholar 

  17. Humphries MD, Gurney K (2008) Network ‘small-world-ness’: a quantitative method for determining canonical network equivalence. PLoS ONE 3:e0002051

    PubMed  Google Scholar 

  18. Jacqmin-Gadda H, Fabrigoule C, Commenges D, Dartigues J-F (1997) A 5-year longitudinal study of the Mini-Mental State Examination in normal aging. Am J Epidemiol 145:498–506

    CAS  PubMed  Google Scholar 

  19. Jones RN, Gallo JJ (2000) Dimensions of the Mini-Mental State Examination among community dwelling older adults. Psychol Med 30:605–618

    CAS  PubMed  Google Scholar 

  20. Kan K-J, van der Maas HLJ, Levine SZ (2019) Extending psychometric network analysis: empirical evidence against g in favor of mutualism? Intelligence 73:52–62

    Google Scholar 

  21. Kenny RA (2018) The Irish Longitudinal Study on Ageing (TILDA), 2012–2013. https://doi.org/10.3886/ICPSR37105.v1

  22. Levine SZ, Leucht S (2016) Identifying a system of predominant negative symptoms: network analysis of three randomized clinical trials. Schizophr Res 178:17–22

    PubMed  Google Scholar 

  23. Lopez MN, Charter RA, Mostafavi B, Nibut LP, Smith WE (2005) Psychometric properties of the folstein mini-mental state examination. Assessment 12:137–144

    PubMed  Google Scholar 

  24. Marsman M, Borsboom D, Kruis J, Epskamp S, van Bork R, Waldorp LJ, Maas HVD, Maris G (2018) An introduction to network psychometrics: relating Ising network models to item response theory models. Multivar Behav Res 53:15–35

    CAS  Google Scholar 

  25. Monsch AU, Foldi NS, Ermini-Fünfschillin DE, Berres M, Taylor KI, Seifritz E, Stähelin HB, Spiegel R (1995) Improving the diagnostic accuracy of the Mini-Mental State Examination. Acta Neurol Scand 92:145–150

    CAS  PubMed  Google Scholar 

  26. Morris JC, Edland S, Clark C, Galasko D, Koss E, Mohs R, Van Belle G, Fillenbaum G, Heyman A (1993) The Consortium to Establish a Registry for Alzheimer’s Disease (CERAD): part IV. Rates of cognitive change in the longitudinal assessment of probable Alzheimer’s disease. Neurology 43:2457

    CAS  PubMed  Google Scholar 

  27. Newman M (2010) Networks: an introduction. Oxford University Press, Oxford

    Google Scholar 

  28. Newman M, Girvan M (2004) Finding and evaluating community structure in networks. Phys Rev E 69:26113

    CAS  Google Scholar 

  29. Nieuwenhuis-Mark RE (2010) The death knoll for the MMSE: has it outlived its purpose? J Geriatr Psychiatry Neurol 23:151–157

    PubMed  Google Scholar 

  30. Noale M, Limongi F, Minicuci N (2006) Identification of factorial structure of MMSE based on elderly cognitive destiny: the Italian Longitudinal Study on Aging. Dement Geriatr Cogn Disord 21:233

    CAS  PubMed  Google Scholar 

  31. Pons P, Latapy M (2006) Computing communities in large networks using random walks. J Graph Algorithms Appl 10:191–218

    Google Scholar 

  32. Rotstein A, Roe D, Gelkopf M, Shadmi E, Levine SZ (2018) Quality of life disparities between persons with schizophrenia and their professional caregivers: network analysis in a National Cohort. Schizophr Res 197:109–115

    PubMed  Google Scholar 

  33. Schultz-Larsen K, Kreiner S, Lomholt RK (2007) Mini-Mental Status Examination: mixed Rasch model item analysis derived two different cognitive dimensions of the MMSE. J Clin Epidemiol 60:268–279

    PubMed  Google Scholar 

  34. Schweren L, van Borkulo CD, Fried E, Goodyer IM (2018) Assessment of symptom network density as a prognostic marker of treatment response in adolescent depression. JAMA Psychiatry 75:98–100

    PubMed  Google Scholar 

  35. Shigemori K, Ohgi S, Okuyama E, Shimura T, Schneider E (2010) The factorial structure of the Mini Mental State Examination (MMSE) in Japanese dementia patients. BMC Geriatr 10:36

    PubMed  PubMed Central  Google Scholar 

  36. Small BJ, Viitanen M, Backman L (1997) Mini-Mental State Examination item scores as predictors of Alzheimer’s disease: incidence data from the Kungsholmen Project, Stockholm. J Gerontol Ser A Biol Sci Med Sci 52:M299–M304

    CAS  Google Scholar 

  37. Small BJ, Fratiglioni L, Viitanen M, Winblad B, Bäckman L (2000) The course of cognitive impairment in preclinical Alzheimer disease: three-and 6-year follow-up of a population-based sample. Arch Neurol 57:839–844

    CAS  PubMed  Google Scholar 

  38. Steis MR, Schrauf RW (2009) A review of translations and adaptations of the Mini-Mental State Examination in languages other than English and Spanish. Res Gerontol Nurs 2:214–224

    PubMed  Google Scholar 

  39. Su YS, Gelman AE, Hill J, Yajima M (2011) Multiple imputation with diagnostics (mi) in R: opening windows into the black box. J Stat Softw 45(2):1–31

    Google Scholar 

  40. Team RC (2000) R language definition. Stat. Comput, Vienna

    Google Scholar 

  41. Tinklenberg J, Brooks JO, Tanke ED, Khalid K, Poulsen SL, Kraemer HC, Gallagher D, Thornton JE, Yesavage JA (1990) Factor analysis and preliminary validation of the mini-mental state examination from a longitudinal perspective. Int Psychogeriatr 2:123–134

    CAS  PubMed  Google Scholar 

  42. Tombaugh TN, McIntyre NJ (1992) The mini-mental state examination: a comprehensive review. J Am Geriatr Soc 40:922–935

    CAS  PubMed  Google Scholar 

  43. Van Borkulo CD, Borsboom D, Epskamp S, Blanken TF, Boschloo L, Schoevers RA, Waldorp LJ (2014) A new method for constructing networks from binary data. Sci Rep 4:5918

    PubMed  PubMed Central  Google Scholar 

  44. van Borkulo C, Epskamp S, van Borkulo MC (2016) Package ‘IsingFit’. (http://cran.r-project.org/web/packages/IsingFit/IsingFit.pdf)

  45. van Borkulo CD, Borsboom D, Epskamp S, Blanken TF, Boschloo L, Schoevers RA, Waldorp LJ (2014) A new method for constructing networks from binary data. Sci Rep 4:5918

    PubMed  PubMed Central  Google Scholar 

  46. Van Borkulo CD, Boschloo L, Kossakowski J, Tio P, Schoevers RA, Borsboom D, Waldorp LJ (2017) Comparing network structures on three aspects: a permutation test. (https://www.researchgate.net/profile/Claudia_Van_Borkulo/publication/314750838_Comparing_network_structures_on_three_aspects_A_permutation_test/links/58c55ef145851538eb8af8a9/Comparing-network-structures-on-three-aspects-A-permutation-test.pdf)

  47. Whelan BJ, Savva GM (2013) Design and methodology of the Irish Longitudinal Study on Ageing. J Am Geriatr Soc 61:S265–S268

    PubMed  Google Scholar 

Download references

Funding

None.

Author information

Authors and Affiliations

  1. Department of Community Mental Health, Faculty of Social Welfare and Health Sciences, University of Haifa, 3498838, Haifa, Israel

    Anat Rotstein

Authors
  1. Anat Rotstein
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Anat Rotstein.

Ethics declarations

Conflict of interest

The author declares no conflict of interest.

Ethical standards

The study was approved by the Faculty of Health Sciences Research Ethics Committee in Trinity College Dublin.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Rotstein, A. Network analysis of the structure and change in the mini-mental state examination: a nationally representative sample. Soc Psychiatry Psychiatr Epidemiol 55, 1363–1371 (2020). https://doi.org/10.1007/s00127-020-01863-3

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00127-020-01863-3

Keywords

Search

Navigation