Understanding complex dynamics of cognitive constructs and the interplay between cognition and daily life activities is possible through network analysis. The objectives of this study are to characterize the cognition network and identify central cognitive constructs, and identify the cognitive constructs bridging cognition and daily life activities. In 210 community-dwelling stroke survivors, we employed network analysis to characterize the cognition network, identify the central cognitive constructs, and examine the bridge pathway connecting cognition and daily life activities. Cognitive constructs were positively correlated within the network, forming clusters of fluid (e.g., components of active problem-solving), crystallized (e.g., world knowledge), and functional cognition. Central constructs included inhibition, organization, and cognitive flexibility, whereas bridge constructs included organization, sequencing, and inhibition. Central and bridge constructs identified by this study are potential targets for future research and intervention. The emergence of functional cognition as central and bridge constructs may support its inclusion in occupational therapy practice.
AkshoomoffN.BeaumontJ. L.BauerP. J.DikmenS. S.GershonR. C.MungasD.. . .HeatonR. K. (2013). VIII. NIH Toolbox Cognition Battery (CB): Composite scores of crystallized, fluid, and overall cognition. Monographs of the Society for Research in Child Development, 78(4), 119–132.
2.
BarbayM.DioufM.RousselM.GodefroyO. (2018). Systematic review and meta-analysis of prevalence in post-stroke neurocognitive disorders in hospital-based studies. Dementia and Geriatric Cognitive Disorders, 46(5–6), 322–334.
3.
BaumC. M.ConnorL. T.MorrisonT.HahnM.DromerickA. W.EdwardsD. F. (2008). Reliability, validity, and clinical utility of the Executive Function Performance Test: A measure of executive function in a sample of people with stroke. American Journal of Occupational Therapy, 62(4), 446–455.
4.
BaumC. M.LauS. C. L.HeinemannA. W.ConnorL. T. (in press). Functional cognition is distinct from fluid and crystallized cognition. American Journal of Occupational Therapy, 77(3).
5.
BaumC. M.WolfT. J.WongA. W. K.ChenC. H.WalkerK.YoungA. C.. . .HeinemannA. W. (2017). Validation and clinical utility of the executive function performance test in persons with traumatic brain injury. Neuropsychological Rehabilitation, 27(5), 603–617.
6.
BeardC.MillnerA. J.ForgeardM. J.FriedE. I.HsuK. J.TreadwayM. T.. . .BjörgvinssonT. (2016). Network analysis of depression and anxiety symptom relationships in a psychiatric sample. Psychological Medicine, 46(16), 3359–3369.
7.
BorsboomD. (2017). A network theory of mental disorders. World Psychiatry, 16(1), 5–13.
8.
BorsboomD.CramerA. O. (2013). Network analysis: An integrative approach to the structure of psychopathology. Annual Review of Clinical Psychology, 9, 91–121.
9.
BoyleP. A.PaulR. H.MoserD. J.CohenR. A. (2004). Executive impairments predict functional declines in vascular dementia. The Clinical Neuropsychologist, 18(1), 75–82.
10.
CahnD. A.SullivanE. V.ShearP. K.PfefferbaumA.HeitG.SilverbergG. (1998). Differential contributions of cognitive and motor component processes to physical and instrumental activities of daily living in Parkinson’s disease. Archives of Clinical Neuropsychology, 13(7), 575–583.
11.
CaraV. M.EsperN. B.de AzeredoL. A.IochpeV.DalfovoN. P.SantosR. C.. . .BuchweitzA. (2019). An fMRI study of inhibitory control and the effects of exposure to violence in Latin-American early adolescents: Alterations in frontoparietal activation and performance. Social Cognitive and Affective Neuroscience, 14(10), 1097–1107.
12.
CarlozziN. E.GoodnightS.CasalettoK. B.GoldsmithA.HeatonR. K.WongA. W. K.. . .TulskyD. S. (2017). Validation of the NIH toolbox in individuals with neurologic disorders. Archives of Clinical Neuropsychology, 32(5), 555–573.
13.
CatroppaC.AndersonV. (2006). Planning, problem-solving and organizational abilities in children following traumatic brain injury: Intervention techniques. Pediatric Rehabilitation, 9(2), 89–97.
14.
CattellR. B. (1963). Theory of fluid and crystallized intelligence: A critical experiment. Journal of Educational Psychology, 54(1), 1–22.
15.
Centers for Disease Control Prevention. (2006). National Health and Nutrition Examination Survey Questionnaire (or examination protocol, or laboratory protocol). U.S. Department of Health and Human Services, Centers for Disease Control and Prevention.
16.
ContrerasA.NietoI.ValienteC.EspinosaR.VazquezC. (2019). The study of psychopathology from the network analysis perspective: A systematic review. Psychotherapy and Psychosomatics, 88(2), 71–83.
17.
CramerA. O.WaldorpL. J.van der MaasH. L.BorsboomD. (2010). Comorbidity: A network perspective. Behavioral and Brain Sciences, 33(2–3), 137–150.
18.
DouiriA.RuddA. G.WolfeC. D. (2013). Prevalence of poststroke cognitive impairment: South London Stroke Register 1995-2010. Stroke, 44(1), 138–145.
19.
EdwardsD. F.WolfT. J.MarksT.AlterS.LarkinV.PadeskyB. L.. . .GilesG. M. (2019). Reliability and validity of a functional cognition screening tool to identify the need for occupational therapy. American Journal of Occupational Therapy, 73(2), 7302205050p1–7302205050p10.
20.
ElliottH.JonesP. J.SchmidtU. (2020). Central symptoms predict posttreatment outcomes and clinical impairment in anorexia nervosa: A network analysis. Clinical Psychological Science, 8(1), 139–154.
21.
EnderbyP. M.WoodV. A.WadeD. T.HewerR. L. (1987). The Frenchay Aphasia Screening Test: A short, simple test for aphasia appropriate for non-specialists. International Rehabilitation Medicine, 8(4), 166–170.
22.
EpskampS.BorsboomD.FriedE. I. (2018). Estimating psychological networks and their accuracy: A tutorial paper. Behavior Research Methods, 50(1), 195–212.
23.
FoygelR.DrtonM. (2010). Extended Bayesian information criteria for Gaussian graphical models. Advances in Neural Information Processing Systems, 604–612.
24.
FriedE. I.EidhofM. B.PalicS.CostantiniG.Huisman-van DijkH. M.BocktingC. L. H.. . .KarstoftK.-I. (2018). Replicability and generalizability of posttraumatic stress disorder (PTSD) networks: A cross-cultural multisite study of PTSD symptoms in four trauma patient samples. Clinical Psychological Science, 6(3), 335–351.
25.
FriedmanN. P.MiyakeA. (2017). Unity and diversity of executive functions: Individual differences as a window on cognitive structure. Cortex, 86, 186–204.
26.
FruchtermanT. M. J.ReingoldE. M. (1991). Graph drawing by force-directed placement. Software: Practice and Experience, 21(11), 1129–1164.
27.
GilesG. M.EdwardsD. F.BaumC.FurnissJ.SkidmoreE.WolfT.LelandN. E. (2020). Making functional cognition a professional priority. The American Journal of Occupational Therapy, 74(1), 7401090010p1–p7401090010p6.
28.
GoveroverY.KalmarJ.Gaudino-GoeringE.ShawarynM.MooreN. B.HalperJ.DeLucaJ. (2005). The relation between subjective and objective measures of everyday life activities in persons with multiple sclerosis. Archives of Physical Medicine and Rehabilitation, 86(12), 2303–2308.
29.
HartfordD.HooperS. R. (2013). Organizational skills. In VolkmarF. R. (Ed.), Encyclopedia of Autism Spectrum Disorders (pp. 2092–2099). Springer.
30.
HeveyD. (2018). Network analysis: A brief overview and tutorial. Health Psychology and Behavioral Medicine, 6(1), 301–328.
31.
HolmM. B.RogersJ. C. (1999). Functional assessment: The Performance Assessment of Self-care Skills (PASS). In HemphillB. J. (Ed.), Assessments in occupational therapy mental health: An integrative approach (pp. 117–124). SLACK.
32.
HornJ. L.CattellR. B. (1967). Age differences in fluid and crystallized intelligence. Acta Psychologica, 26(2), 107–129.
33.
IversonG. L. (2019). Network analysis and precision rehabilitation for the post-concussion syndrome. Frontiers in Neurology, 10, Article 489.
34.
JeffersonA. L.PaulR. H.OzonoffA.CohenR. A. (2006). Evaluating elements of executive functioning as predictors of instrumental activities of daily living (IADLs). Archives of Clinical Neuropsychology, 21(4), 311–320.
35.
LawL. L. F.MokV. C. T.YauM. M. K. (2019). Effects of functional tasks exercise on cognitive functions of older adults with mild cognitive impairment: A randomized controlled pilot trial. Alzheimer’s Research & Therapy, 11(1), Article 98.
36.
LoJ. W.CrawfordJ. D.DesmondD. W.GodefroyO.JokinenH.MahinradS.. . .SachdevP. S. (2019). Profile of and risk factors for poststroke cognitive impairment in diverse ethnoregional groups. Neurology, 93(24), e2257–e2271.
37.
MellonL.BrewerL.HallP.HorganF.WilliamsD.HickeyA. (2015). Cognitive impairment six months after ischaemic stroke: A profile from the ASPIRE-S study. BMC Neurology, 15, Article 31.
38.
MiyakeA.FriedmanN. P.EmersonM. J.WitzkiA. H.HowerterA.WagerT. D. (2000). The unity and diversity of executive functions and their contributions to complex “frontal lobe” tasks: A latent variable analysis. Cognitive Psychology, 41(1), 49–100.
39.
NowrangiM. A.LyketsosC.RaoV.MunroC. A. (2014). Systematic review of neuroimaging correlates of executive functioning: Converging evidence from different clinical populations. Journal of Neuropsychiatry and Clinical Neurosciences, 26(2), 114–125.
40.
ParkJ. H.KimB. J.BaeH.-J.LeeJ.LeeJ.HanM.-K.. . .LeeB.-C. (2013). Impact of post-stroke cognitive impairment with no dementia on health-related quality of life. Journal of Stroke, 15(1), 49–56.
41.
PearlJ. (2000). Causality: Models, reasoning, and inference. Cambridge University Press.
42.
PinoM. C.VagnettiR.MaseduF.AttanasioM.TibertiS.ValentiM.MazzaM. (2020). Mapping the network of social cognition domains in children with autism spectrum disorder through graph analysis. Frontiers in Psychiatry, 11, Article 579339.
43.
PovroznikJ. M.OzgaJ. E.Vonder HaarC.Engler-ChiurazziE. B. (2018). Executive (dys)function after stroke: Special considerations for behavioral pharmacology. Behavioural Pharmacology, 29(7), 638–653.
44.
RobinaughD. J.MillnerA. J.McNallyR. J. (2016). Identifying highly influential nodes in the complicated grief network. Journal of Abnormal Psychology, 125(6), 747–757.
45.
SavaliaT.ShuklaA.BapiR. S. (2016). A unified theoretical framework for cognitive sequencing. Frontiers in Psychology, 7, Article 1821.
46.
SextonE.McLoughlinA.WilliamsD. J.MerrimanN. A.DonnellyN.RohdeD.. . .BennettK. (2019). Systematic review and meta-analysis of the prevalence of cognitive impairment no dementia in the first year post-stroke. European Stroke Journal, 4(2), 160–171.
47.
Simpson-KentI. L.FriedE. I.AkarcaD.MarevaS.BullmoreE. T.Team tC.KievitR. A. (2021). Bridging brain and cognition: A multilayer network analysis of brain structural covariance and general intelligence in a developmental sample of struggling learners. Journal of Intelligence, 9(2), Article 32.
48.
SkidmoreE. R.DawsonD. R.ButtersM. A.GrattanE. S.JuengstS. B.WhyteE. M.. . .BeckerJ. T. (2015). Strategy training shows promise for addressing disability in the first 6 months after stroke. Neurorehabilitation and Neural Repair, 29(7), 668–676.
49.
StawskiR. S.MogleJ. A.SliwinskiM. J. (2013). Associations among fluid and crystallized cognition and daily stress processes in older adults. Psychology and Aging, 28(1), 57–63.
50.
StolwykR. J.MihaljcicT.WongD. K.ChapmanJ. E.RogersJ. M. (2021). Poststroke cognitive impairment negatively impacts activity and participation outcomes. Stroke, 52(2), 748–760.
51.
VagnettiR.PinoM. C.MaseduF.PerettiS.Le DonneI.RossiR.. . .MazzaM. (2020). Exploring the social cognition network in young adults with autism spectrum disorder using graph analysis. Brain and Behavior, 10(3), Article e01524.
52.
van BorkuloC.BoschlooL.BorsboomD.PenninxB. W. J. H.WaldorpL. J.SchoeversR. A. (2015). Association of symptom network structure with the course of depression. JAMA Psychiatry, 72(12), 1219–1226.
53.
van der MaasH. L.DolanC. V.GrasmanR. P.WichertsJ. M.HuizengaH. M.RaijmakersM. E. (2006). A dynamical model of general intelligence: The positive manifold of intelligence by mutualism. Psychological Review, 113(4), 842–861.
54.
WeintraubS.DikmenS. S.HeatonR. K.TulskyD. S.ZelazoP. D.BauerP. J.. . .GershonR. C. (2013). Cognition assessment using the NIH toolbox. Neurology, 80(11 Suppl. 3), S54–S64.
55.
YangY.ShiY.-Z.ZhangN.WangS.UngvariG. S.NgC. H.. . .XiangY.-T. (2016). The disability rate of 5-year post-stroke and its correlation factors: A national survey in China. PLOS ONE, 11(11), Article e0165341.
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