Elevated Anxious and Depressed Mood Relates to Future Executive Dysfunction in Older Adults: A Longitudinal Network Analysis of Psychopathology and Cognitive Functioning

Abstract

Vulnerability models posit that executive-functioning (EF) problems centrally affect future common (vs. rare) psychopathology symptoms. Conversely, scar theory postulates that depression/anxiety (vs. other psychopathology) symptoms centrally influence reduced EF. However, most studies so far have been cross-sectional. We used cross-lagged panel network analysis to determine temporal and component-to-component relations on this topic. Community older adults participated across four time points. Cognitive tests and the caregiver-rated Neuropsychiatric Inventory assessed nine psychopathology and eight cognitive-functioning nodes. Nodes with the highest bridge expected influence cross-sectionally were agitation and episodic memory. Episodic memory had the strongest inverse relation with age. Agitation had the strongest negative association with global cognition. EF nodes tended to be centrally affected by prior depressed and anxious moods rather than influential on any future nodes. Heightened anxious and depressed mood (vs. other nodes) centrally predicted future decreased EF-related (vs. non-EF-related) nodes in older adults, supporting scar (vs. vulnerability) theory.

Keywords

network analysis cross-lagged panel network anxiety executive function psychopathology

Get full access to this article

View all access options for this article.

References

Abramovitch

Short

Schweiger

(2021). The C Factor: Cognitive dysfunction as a transdiagnostic dimension in psychopathology. Clinical Psychology Review, 86, Article 102007. https://doi.org/10.1016/j.cpr.2021.102007

Aichele

Ghisletta

(2019). Memory deficits precede increases in depressive symptoms in later adulthood. Journals of Gerontology, Series B: Psychological Sciences, 74, 943–953. https://doi.org/10.1093/geronb/gbx183

Alexopoulos

G. S.

(2003). Role of executive function in late-life depression. Journal of Clinical Psychiatry, 64(Suppl. 14), 18–23.

Alloy

L. B.

Wagner

C. A.

Black

S. K.

Gerstein

R. K.

Abramson

L. Y.

(2011). The breakdown of self-enhancing and self-protecting cognitive biases in depression. In Alicke

M. D.

Sedikides

(Eds.), Handbook of self-enhancement and self-protection (pp. 358–379). The Guilford Press.

Andreas

Schulz

Volkert

Dehoust

Sehner

Suling

Ausín

Canuto

Crawford

Da Ronch

Grassi

Hershkovitz

Muñoz

Quirk

Rotenstein

Santos-Olmo

A. B.

Shalev

Strehle

Weber

Wegscheider

. . . Harter

(2017). Prevalence of mental disorders in elderly people: The European MentDis_ICF65+ study. British Journal of Psychiatry, 210, 125–131. https://doi.org/10.1192/bjp.bp.115.180463

Ardila

(2007). Normal aging increases cognitive heterogeneity: Analysis of dispersion in WAIS-III scores across age. Archives of Clinical Neuropsychology, 22, 1003–1011. https://doi.org/10.1016/j.acn.2007.08.004

Ardila

Ostrosky-Solís

Bernal

(2006). Cognitive testing toward the future: The example of Semantic Verbal Fluency (ANIMALS). International Journal of Psychology, 41, 324–332. https://doi.org/10.1080/00207590500345542

Badcock

J. C.

Dehon

Laroi

(2017). Hallucinations in healthy older adults: An overview of the literature and perspectives for future research. Frontiers in Psychology, 8, Article 1134. https://doi.org/10.3389/fpsyg.2017.01134

Balsis

Benge

J. F.

Lowe

D. A.

Geraci

Doody

R. S.

(2015). How do scores on the ADAS-Cog, MMSE, and CDR-SOB correspond? The Clinical Neuropsychologist, 29, 1002–1009. https://doi.org/10.1080/13854046.2015.1119312

10.

Bazo-Alvarez

J. C.

Morris

T. P.

Pham

T. M.

Carpenter

J. R.

Petersen

(2020). Handling missing values in interrupted time series analysis of longitudinal individual-level data. Clinical Epidemiology, 12, 1045–1057. https://doi.org/10.2147/clep.s266428

11.

Beaudreau

S. A.

MacKay-Brandt

Reynolds

(2013). Application of a cognitive neuroscience perspective of cognitive control to late-life anxiety. Journal of Anxiety Disorders, 27, 559–566. https://doi.org/10.1016/j.janxdis.2013.03.006

12.

Beaudreau

S. A.

O’Hara

(2008). Late-life anxiety and cognitive impairment: A review. The American Journal of Geriatric Psychiatry, 16, 790–803. https://doi.org/10.1097/JGP.0b013e31817945c3

13.

Beeri

M. S.

Schmeidler

Sano

Wang

Lally

Grossman

Silverman

J. M.

(2006). Age, gender, and education norms on the CERAD neuropsychological battery in the oldest old. Neurology, 67, Article 1006. https://doi.org/10.1212/01.wnl.0000237548.15734.cd

14.

Bernstein

E. E.

Heeren

McNally

R. J.

(2017). Unpacking rumination and executive control: A network perspective. Clinical Psychological Science, 5, 816–826. https://doi.org/10.1177/2167702617702717

15.

Bernstein

E. E.

Kleiman

E. M.

van Bork

Moriarity

D. P.

Mac Giollabhui

McNally

R. J.

Abramson

L. Y.

Alloy

L. B.

(2019). Unique and predictive relationships between components of cognitive vulnerability and symptoms of depression. Depression and Anxiety, 36, 950–959. https://doi.org/10.1002/da.22935

16.

Bessette

K. L.

Jenkins

L. M.

Skerrett

K. A.

Gowins

J. R.

DelDonno

S. R.

Zubieta

J. K.

McInnis

M. G.

Jacobs

R. H.

Ajilore

Langenecker

S. A.

(2018). Reliability, convergent validity and time invariance of default mode network deviations in early adult major depressive disorder. Frontiers in Psychiatry, 9, Article 244. https://doi.org/10.3389/fpsyt.2018.00244

17.

Bessette

K. L.

Karstens

A. J.

Crane

N. A.

Peters

A. T.

Stange

J. P.

Elverman

K. H.

Morimoto

S. S.

Weisenbach

S. L.

Langenecker

S. A.

(2020). A lifespan model of interference resolution and inhibitory control: Risk for depression and changes with illness progression. Neuropsychology Review, 30, 477–498. https://doi.org/10.1007/s11065-019-09424-5

18.

Blanchflower

D. G.

Oswald

A. J.

(2008). Is well-being U-shaped over the life cycle? Social Science & Medicine, 66, 1733–1749. https://doi.org/10.1016/j.socscimed.2008.01.030

19.

Borkowski

J. G.

Benton

A. L.

Spreen

(1967). Word fluency and brain damage. Neuropsychologia, 5, 135–140. https://doi.org/10.1016/0028-3932(67)90015-2

20.

Borsboom

Cramer

A. O. J.

Kalis

(2018). Brain disorders? Not really: Why network structures block reductionism in psychopathology research. Behavioral and Brain Sciences, 42, Article e2. https://doi.org/10.1017/S0140525X17002266

21.

Bringmann

L. F.

Eronen

M. I.

(2018). Don’t blame the model: Reconsidering the network approach to psychopathology. Psychological Review, 125, 606–615. https://doi.org/10.1037/rev0000108

22.

Byers

A. L.

Yaffe

Covinsky

K. E.

Friedman

M. B.

Bruce

M. L.

(2010). High occurrence of mood and anxiety disorders among older adults: The National Comorbidity Survey Replication. Archives of General Psychiatry, 67, 489–496. https://doi.org/10.1001/archgenpsychiatry.2010.35

23.

Byrne

M. E.

Tanofsky-Kraff

Lavender

J. M.

Parker

M. N.

Shank

L. M.

Swanson

T. N.

Ramirez

LeMay-Russell

Yang

S. B.

Brady

S. M.

Zenno

Chivukula

K. K.

Kelly

N. R.

Yanovski

J. A.

(2021). Bridging executive function and disinhibited eating among youth: A network analysis. International Journal of Eating Disorders, 54, 721–732. https://doi.org/10.1002/eat.23476

24.

Cano-Lopez

Alino

Duque

Martinez

Almela

Garcia-Rubio

M. J.

Puig-Perez

(2021). Educational level as a protective factor against the influence of depressive symptoms on cognition in older adults: Implications for functional independence during a 10-year follow-up. International Psychogeriatrics, 33, 813–825. https://doi.org/10.1017/S1041610221000272

25.

Cao

Tan

C.-C.

Cao

X.-P.

Dong

Tan

J.-T.

(2020). The prevalence of dementia: A systematic review and meta-analysis. Journal of Alzheimer’s Disease, 73, 1157–1166. https://doi.org/10.3233/JAD-191092

26.

Cervin

Miguel

E. C.

Guler

A. S.

Ferrao

Y. A.

Erdogdu

A. B.

Lazaro

Gökçe

Geller

D. A.

Yulaf

Başgül

Ş. S.

Özcan

Ö.

Karabekiroğlu

Fontenelle

L. F.

Yazgan

Storch

E. A.

Leckman

J. F.

do Rosário

M. C.

Mataix-Cols

(2021). Towards a definitive symptom structure of obsessive-compulsive disorder: A factor and network analysis of 87 distinct symptoms in 1366 individuals. Psychological Medicine. Advance online publication. https://doi.org/10.1017/S0033291720005437

27.

Chan

J. Y. C.

Yiu

K. K. L.

Kwok

T. C. Y.

Wong

S. Y. S.

Tsoi

K. K. F.

(2019). Depression and antidepressants as potential risk factors in dementia: A systematic review and meta-analysis of 18 longitudinal studies. Journal of the American Medical Directors Association, 20, 279–286.e271. https://doi.org/10.1016/j.jamda.2018.12.004

28.

Chang

W. C.

Wong

C. S. M.

P. C. F.

Chu

A. O. K.

Hui

C. L. M.

Chan

S. K. W.

Lee

Suen

Y. N.

Chen

E. Y. H.

(2020). Inter-relationships among psychopathology, premorbid adjustment, cognition and psychosocial functioning in first-episode psychosis: A network analysis approach. Psychological Medicine, 50, 2019–2027. https://doi.org/10.1017/S0033291719002113

29.

Chen

(2008). Extended Bayesian information criteria for model selection with large model spaces. Biometrika, 95, 759–771. https://doi.org/10.1093/biomet/asn034

30.

Chen

Shi

Zhou

(2017). The impact of neuroticism on symptoms of anxiety and depression in elderly adults: The mediating role of rumination. Current Psychology, 39, 42–50. https://doi.org/10.1007/s12144-017-9740-3

31.

Cuesta

M. J.

Lecumberri

Moreno-Izco

Lopez-Ilundain

J. M.

Ribeiro

Cabada

Lorente-Omeñaca

de Erausquin

García-Martí

Sanjuan

Sánchez-Torres

A. M.

Gómez

Peralta

(2021). Motor abnormalities and basal ganglia in first-episode psychosis (FEP). Psychological Medicine, 51, 1625–1636. https://doi.org/10.1017/S0033291720000343

32.

Cullum

C. M.

Larrabee

G. J.

(2010). Chapter 6 – WAIS-IV use in neuropsychological assessment. In Weiss

L. G.

Saklofske

D. H.

Coalson

D. L.

Raiford

S. E.

(Eds.), WAIS-IV clinical use and interpretation (pp. 167–187). Academic Press. https://doi.org/10.1016/B978-0-12-375035-8.10006-0

33.

Cummings

J. L.

(1997). The Neuropsychiatric Inventory: Assessing psychopathology in dementia patients. Neurology, 48, S10–S16. https://doi.org/10.1212/wnl.48.5_suppl_6.10s

34.

de Sousa

R. D.

Rodrigues

A. M.

Gregorio

M. J.

Branco

J. D. C.

Gouveia

M. J.

Canhao

Dias

S. S.

(2017). Anxiety and depression in the Portuguese older adults: Prevalence and associated factors. Frontiers in Medicine, 4, Article 196. https://doi.org/10.3389/fmed.2017.00196

35.

GBD 2017 Mortality Collaborators. (2018). Global, regional, and national age-sex-specific mortality and life expectancy, 1950–2017: A systematic analysis for the Global Burden of Disease Study 2017. The Lancet, 392, 1684–1735. https://doi.org/10.1016/s0140-6736(18)31891-9

36.

Diniz

B. S.

Reynolds

C. F.

3rd Sibille

Lin

C. W.

Tseng

Lotrich

Aizenstein

H. J.

Butters

M. A.

(2017). Enhanced molecular aging in late-life depression: The senescent-associated secretory phenotype. American Journal of Geriatric Psychiatry, 25, 64–72. https://doi.org/10.1016/j.jagp.2016.08.018

37.

Dolsen

M. R.

Asarnow

L. D.

Harvey

A. G.

(2014). Insomnia as a transdiagnostic process in psychiatric disorders. Current Psychiatry Reports, 16, Article 471. https://doi.org/10.1007/s11920-014-0471-y

38.

Eadeh

H. M.

Markon

K. E.

Nigg

J. T.

Nikolas

M. A.

(2021). Evaluating the viability of neurocognition as a transdiagnostic construct using both latent variable models and network analysis. Research on Child and Adolescent Psychopathology, 49, 697–710. https://doi.org/10.1007/s10802-021-00770-8

39.

East-Richard

R.-Mercier

Nadeau

Cellard

(2020). Transdiagnostic neurocognitive deficits in psychiatry: A review of meta-analyses. Canadian Psychology / Psychologie Canadienne, 61, 190–214. https://doi.org/10.1037/cap0000196

40.

Ekkers

Korrelboom

Huijbrechts

Smits

Cuijpers

van der Gaag

(2011). Competitive Memory Training for treating depression and rumination in depressed older adults: A randomized controlled trial. Behaviour Research and Therapy, 49, 588–596. https://doi.org/10.1016/j.brat.2011.05.010

41.

Elliott

Jones

P. J.

Schmidt

(2019). Central symptoms predict posttreatment outcomes and clinical impairment in anorexia nervosa: A network analysis. Clinical Psychological Science, 8, 139–154. https://doi.org/10.1177/2167702619865958

42.

Epskamp

(2020). Psychometric network models from time-series and panel data. Psychometrika, 85, 206–231. https://doi.org/10.1007/s11336-020-09697-3

43.

Epskamp

Borsboom

Fried

E. I.

(2018). Estimating psychological networks and their accuracy: A tutorial paper. Behavior Research Methods, 50, 195–212. https://doi.org/10.3758/s13428-017-0862-1

44.

Epskamp

Cramer

A. O.

Waldorp

L. J.

Schmittmann

V. D.

Borsboom

(2012). qgraph: Network visualizations of relationships in psychometric data. Journal of Statistical Software, 48, 1–18. https://doi.org/10.18637/jss.v048.i04

45.

Erickson

K. I.

Donofry

S. D.

Sewell

K. R.

Brown

B. M.

Stillman

C. M.

(2022). Cognitive aging and the promise of physical activity. Annual Review of Clinical Psychology, 18, 417–442. https://doi.org/10.1146/annurev-clinpsy-072720-014213

46.

Eysenck

M. W.

Derakshan

Santos

Calvo

M. G.

(2007). Anxiety and cognitive performance: Attentional control theory. Emotion, 7, 336–353. https://doi.org/10.1037/1528-3542.7.2.336

47.

Fastenau

P. S.

Denburg

N. L.

Mauer

B. A.

(1998). Parallel short forms for the Boston Naming Test: Psychometric properties and norms for older adults. Journal of Clinical and Experimental Neuropsychology, 20, 828–834. https://doi.org/10.1076/jcen.20.6.828.1105

48.

Folstein

M. F.

Folstein

S. E.

McHugh

P. R.

(1975). “Mini-mental state”: A practical method for grading the cognitive state of patients for the clinician. Journal of Psychiatric Research, 12, 189–198. https://doi.org/10.1016/0022-3956(75)90026-6

49.

Fong

T. G.

Fearing

M. A.

Jones

R. N.

Shi

Marcantonio

E. R.

Rudolph

J. L.

Yang

F. M.

Kiely

D. K.

Inouye

S. K.

(2009). Telephone interview for cognitive status: Creating a crosswalk with the Mini-Mental State Examination. Alzheimer’s & Dementia, 5, 492–497. https://doi.org/10.1016/j.jalz.2009.02.007

50.

Fried

E. I.

van Borkulo

C. D.

Cramer

A. O. J.

Boschloo

Schoevers

R. A.

Borsboom

(2017). Mental disorders as networks of problems: A review of recent insights. Social Psychiatry and Psychiatric Epidemiology, 52, 1–10. https://doi.org/10.1007/s00127-016-1319-z

51.

Friedman

Hastie

Tibshirani

(2008). Sparse inverse covariance estimation with the graphical lasso. Biostatistics, 9, 432–441. https://doi.org/10.1093/biostatistics/kxm045

52.

Friedman

Hastie

Tibshirani

(2010). Regularization paths for generalized linear models via coordinate descent. Journal of Statistical Software, 33, 1–22. https://www.jstatsoft.org/v33/i01/

53.

Funkhouser

C. J.

Chacko

A. A.

Correa

K. A.

Kaiser

A. J. E.

Shankman

S. A.

(2021). Unique longitudinal relationships between symptoms of psychopathology in youth: A cross-lagged panel network analysis in the ABCD study. Journal of Child Psychology and Psychiatry, 62, 184–194. https://doi.org/10.1111/jcpp.13256

54.

Fusar-Poli

Deste

Smieskova

Barlati

Yung

A. R.

Howes

Stieglitz

R. D.

Vita

McGuire

Borgwardt

(2012). Cognitive functioning in prodromal psychosis: A meta-analysis. Archives of General Psychiatry, 69, 562–571. https://doi.org/10.1001/archgenpsychiatry.2011.1592

55.

Galderisi

Rucci

Kirkpatrick

Mucci

Gibertoni

Rocca

Rossi

Bertolino

Strauss

G. P.

Aguglia

Bellomo

Murri

M. B.

Bucci

Carpiniello

Comparelli

Cuomo

De Berardis

Dell’Osso

Di Fabio

, . . . Italian Network for Research on Psychoses. (2018). Interplay among psychopathologic variables, personal resources, context-related factors, and real-life functioning in individuals with schizophrenia: A network analysis. JAMA Psychiatry, 75, 396–404. https://doi.org/10.1001/jamapsychiatry.2017.4607

56.

Galimberti

Bosi

M. F.

Caricasole

Zanello

Dell’Osso

Vigano

C. A.

(2020). Using network analysis to explore cognitive domains in patients with unipolar versus bipolar depression: A prospective naturalistic study. CNS Spectrums, 25, 380–391. https://doi.org/10.1017/S1092852919000968

57.

Gallagher

Kiss

Lanctot

Herrmann

(2016). Depressive symptoms and cognitive decline: A longitudinal analysis of potentially modifiable risk factors in community dwelling older adults. Journal of Affective Disorders, 190, 235–240. https://doi.org/10.1016/j.jad.2015.09.046

58.

Zhu

McConnell

E. S.

(2018). Technology-based cognitive training and rehabilitation interventions for individuals with mild cognitive impairment: A systematic review. BMC Geriatrics, 18, Article 213. https://doi.org/10.1186/s12877-018-0893-1

59.

Geda

Y. E.

Roberts

R. O.

Mielke

M. M.

Knopman

D. S.

Christianson

T. J. H.

Pankratz

V. S.

Boeve

B. F.

Sochor

Tangalos

E. G.

Petersen

R. C.

Rocca

W. A.

(2014). Baseline neuropsychiatric symptoms and the risk of incident mild cognitive impairment: A population-based study. American Journal of Psychiatry, 171, 572–581. https://doi.org/10.1176/appi.ajp.2014.13060821

60.

Global Burden of Disease Study 2013 Collaborators. (2015). Global, regional, and national incidence, prevalence, and years lived with disability for 301 acute and chronic diseases and injuries in 188 countries, 1990–2013: A systematic analysis for the Global Burden of Disease Study 2013. The Lancet, 386, 743–800. https://doi.org/10.1016/s0140-6736(15)60692-4

61.

Goh

P. K.

Smith

T. E.

Lee

C. A.

Bansal

P. S.

Eng

A. G.

Martel

M. M.

(2021). Etiological networks of attention-deficit/hyperactivity disorder during childhood and adolescence. Journal of Clinical Child & Adolescent Psychology. Advance online publication. https://doi.org/10.1080/15374416.2021.1946820

62.

Golino

Christensen

A. P.

(2022). EGAnet: Exploratory graph analysis – A framework for estimating the number of dimensions in multivariate data using network psychometrics (R package version 1.1.1).

63.

Gotlib

I. H.

Joormann

(2010). Cognition and depression: Current status and future directions. Annual Review of Clinical Psychology, 6, 285–312. https://doi.org/10.1146/annurev.clinpsy.121208.131305

64.

Granger

C. W. J.

(1969). Investigating causal relations by econometric models and cross-spectral methods. Econometrica, 37, 424–438. https://doi.org/10.2307/1912791

65.

Grund

Lüdtke

Robitzsch

(2018). Multiple imputation of missing data for multilevel models: Simulations and recommendations. Organizational Research Methods, 21, 111–149. https://doi.org/10.1177/1094428117703686

66.

Gulpers

Ramakers

Hamel

Köhler

Oude Voshaar

Verhey

(2016). Anxiety as a predictor for cognitive decline and dementia: A systematic review and meta-analysis. American Journal of Geriatric Psychiatry, 24, 823–842. https://doi.org/10.1016/j.jagp.2016.05.015

67.

Hale

J. B.

Hoeppner

J.-A. B.

Fiorello

C. A.

(2002). Analyzing digit span components for assessment of attention processes. Journal of Psychoeducational Assessment, 20, 128–143. https://doi.org/10.1177/073428290202000202

68.

Harry

Crowe

S. F.

(2014). Is the Boston Naming Test still fit for purpose? The Clinical Neuropsychologist, 28, 486–504. https://doi.org/10.1080/13854046.2014.892155

69.

Haslbeck

J. M. B.

Waldorp

L. J.

(2018). How well do network models predict observations? On the importance of predictability in network models. Behavior Research Methods, 50, 853–861. https://doi.org/10.3758/s13428-017-0910-x

70.

Hill

N. T.

Mowszowski

Naismith

S. L.

Chadwick

V. L.

Valenzuela

Lampit

(2017). Computerized cognitive training in older adults with mild cognitive impairment or dementia: A systematic review and meta-analysis. American Journal of Psychiatry, 174, 329–340. https://doi.org/10.1176/appi.ajp.2016.16030360

71.

Hirsch

C. R.

Mathews

(2012). A cognitive model of pathological worry. Behaviour Research and Therapy, 50, 636–646. https://doi.org/10.1016/j.brat.2012.06.007

72.

Hori

(2015). Current pharmacotherapy strategies and considerations for the cognitive dysfunction associated with schizophrenia: A mini review. International Journal of Neurology and Neurotherapy, 2, Article 024. https://doi.org/10.23937/2378-3001/2/1/1024

73.

Jeste

D. V.

Savla

G. N.

Thompson

W. K.

Vahia

I. V.

Glorioso

D. K.

Martin

A. S.

Palmer

B. W.

Rock

Golshan

Kraemer

H. C.

Depp

C. A.

(2013). Association between older age and more successful aging: Critical role of resilience and depression. American Journal of Psychiatry, 170, 188–196. https://doi.org/10.1176/appi.ajp.2012.12030386

74.

Jiang

S. Y.

Shan

H. D.

Zhang

R. T.

Lui

S. S. Y.

Yang

H. X.

Cheung

E. F. C.

Chan

R. C. K.

(2021). Network analysis of executive function, emotion, and social anhedonia. PsyCh Journal, 11, 232–234. https://doi.org/10.1002/pchj.444

75.

John

Patel

Rusted

Richards

Gaysina

(2019). Affective problems and decline in cognitive state in older adults: A systematic review and meta-analysis. Psychological Medicine, 49, 353–365. https://doi.org/10.1017/S0033291718001137

76.

John

Rusted

Richards

Gaysina

(2021). Bidirectional relation between affective symptoms and cognitive function from middle to late adulthood: A population-based birth cohort study. Aging and Mental Health, 25, 1642–1648. https://doi.org/10.1080/13607863.2020.1758916

77.

Jones

(2020). networktools: Tools for identifying important nodes in networks (R package version 1.2.3). https://CRAN.R-project.org/package=networktools

78.

Jones

P. J.

Heeren

McNally

R. J.

(2017). Commentary: A network theory of mental disorders. Frontiers in Psychology, 8, Article 1305. https://doi.org/10.3389/fpsyg.2017.01305

79.

Kaplan

Goodglass

Weintraub

(1983). Boston Naming Test. Lea & Febiger.

80.

Karim

H. T.

Krafty

Tudorascu

D. L.

Aizenstein

H. J.

Andreescu

(2021). Aging faster: Worry and rumination in late life are associated with greater brain age. Neurobiology of Aging, 101, 13–21. https://doi.org/10.1016/j.neurobiolaging.2021.01.009

81.

Karyakina

Shmukler

(2021). Network analysis of cognitive deficit in patients with schizophrenia spectrum disorders. Schizophrenia Research: Cognition, 26, Article 100213. https://doi.org/10.1016/j.scog.2021.100213

82.

Keller

A. S.

Leikauf

J. E.

Holt-Gosselin

Staveland

B. R.

Williams

L. M.

(2019). Paying attention to attention in depression. Translational Psychiatry, 9, Article 279. https://doi.org/10.1038/s41398-019-0616-1

83.

Knuff

Leung

R. H.

Seitz

D. P.

Pallaveshi

Burhan

A. M.

(2019). Use of actigraphy to measure symptoms of agitation in dementia. American Journal of Geriatric Psychiatry, 27, 865–869. https://doi.org/10.1016/j.jagp.2019.02.013

84.

Koo

Y. W.

Kolves

De Leo

(2017). Suicide in older adults: Differences between the young-old, middle-old, and oldest old. International Psychogeriatrics, 29, 1297–1306. https://doi.org/10.1017/S1041610217000618

85.

Krell-Roesch

Syrjanen

J. A.

Machulda

M. M.

Christianson

T. J.

Kremers

W. K.

Mielke

M. M.

Knopman

D. S.

Petersen

R. C.

Vassilaki

Geda

Y. E.

(2021). Neuropsychiatric symptoms and the outcome of cognitive trajectories in older adults free of dementia: The Mayo Clinic Study of Aging. International Journal of Geriatric Psychiatry, 36, 1362–1369. https://doi.org/10.1002/gps.5528

86.

Kuring

J. K.

Mathias

J. L.

Ward

(2020). Risk of dementia in persons who have previously experienced clinically-significant depression, anxiety, or PTSD: A systematic review and meta-Analysis. Journal of Affective Disorders, 274, 247–261. https://doi.org/10.1016/j.jad.2020.05.020

87.

Kwak

Park

S. M.

Jeon

Y. J.

D. J.

Lee

J. Y.

(2022). Multiple cognitive and behavioral factors link association between brain structure and functional impairment of daily instrumental activities in older adults. Journal of the International Neuropsychological Society, 28(7), 673–686. https://doi.org/10.1017/S1355617721000916

88.

Langa

K. M.

Plassman

B. L.

Wallace

R. B.

Herzog

A. R.

Heeringa

S. G.

Ofstedal

M. B.

Burke

J. R.

Fisher

G. G.

Fultz

N. H.

Hurd

M. D.

Potter

G. G.

Rodgers

W. L.

Steffens

D. C.

Weir

D. R.

Willis

R. J.

(2005). The aging, demographics, and memory study (ADAMS): Study design and methods. Neuroepidemiology, 25, 181–191. https://doi.org/10.1159/000087448

89.

Laukka

E. J.

Dykiert

Allerhand

Starr

J. M.

Deary

I. J.

(2018). Effects of between-person differences and within-person changes in symptoms of anxiety and depression on older age cognitive performance. Psychological Medicine, 48, 1350–1358. https://doi.org/10.1017/S0033291717002896

90.

Lezak

Howieson

Bigler

Tranel

(2012). Neuropsychological assessment. Oxford University Press.

91.

Lindert

Paul

K. C.

Lachman

M. E.

Ritz

Seeman

T. E.

(2021). Depression-, anxiety-, and anger and cognitive functions: Findings from a longitudinal prospective study. Frontiers in Psychiatry, 12, Article 665742. https://doi.org/10.3389/fpsyt.2021.665742

92.

Lloyd

W. K.

Morriss

Macdonald

Joanknecht

Nihouarn

van Reekum

C. M.

(2021). Longitudinal change in executive function is associated with impaired top-down frontolimbic regulation during reappraisal in older adults. NeuroImage, 225, Article 117488. https://doi.org/10.1016/j.neuroimage.2020.117488

93.

Karim

H. T.

Becker

J. T.

Lopez

O. L.

Anderson

S. J.

Aizenstein

H. J.

Reynolds

C. F.

Zmuda

M. D.

Butters

M. A.

(2021). Late-life depression and increased risk of dementia: A longitudinal cohort study. Translational Psychiatry, 11, Article 147. https://doi.org/10.1038/s41398-021-01269-y

94.

McAlister

Schmitter-Edgecombe

(2016). Executive function subcomponents and their relations to everyday functioning in healthy older adults. Journal of Clinical and Experimental Neuropsychology, 38, 925–940. https://doi.org/10.1080/13803395.2016.1177490

95.

McNally

R. J.

(2021). Network analysis of psychopathology: Controversies and challenges. Annual Review of Clinical Psychology, 17, 31–53. https://doi.org/10.1146/annurev-clinpsy-081219-092850

96.

Messinis

Bakirtzis

Kosmidis

M. H.

Economou

Nasios

Anyfantis

Konitsiotis

Ntoskou

Peristeri

Dardiotis

Grigoriadis

Gourzis

Papathanasopoulos

(2021). Symbol Digit Modalities Test: Greek normative data for the oral and written version and discriminative validity in patients with multiple sclerosis. Archives of Clinical Neuropsychology, 36, 117–125. https://doi.org/10.1093/arclin/acaa028

97.

Moheb

Charuworn

Ashla

M. M.

Desarzant

Chavez

Mendez

M. F.

(2019). Repetitive behaviors in frontotemporal dementia: Compulsions or impulsions? Journal of Neuropsychiatry and Clinical Neurosciences, 31, 132–136. https://doi.org/10.1176/appi.neuropsych.18060148

98.

Morris

J. C.

Heyman

Mohs

R. C.

Hughes

J. P.

van Belle

Fillenbaum

Mellits

E. D.

Clark

(1989). The Consortium to Establish a Registry for Alzheimer’s Disease (CERAD). Part I. Clinical and neuropsychological assessment of Alzheimer’s disease. Neurology, 39, 1159–1165. https://doi.org/10.1212/wnl.39.9.1159

99.

Nassiri

Molenberghs

Verbeke

Barbosa-Breda

(2019). Iterative multiple imputation: A framework to determine the number of imputed datasets. The American Statistician, 74, 125–136. https://doi.org/10.1080/00031305.2018.1543615

100.

Nieto

Romero

Ros

Zabala

Martinez

Ricarte

J. J.

Serrano

J. P.

Latorre

J. M.

(2020). Differences in coping strategies between young and older adults: The role of executive functions. International Journal of Aging and Human Development, 90, 28–49. https://doi.org/10.1177/0091415018822040

101.

Orzechowska

Filip

Galecki

(2015). Influence of pharmacotherapy on cognitive functions in depression: A review of the literature. Medical Science Monitor, 21, 3643–3651. https://doi.org/10.12659/msm.895156

102.

Pahlen

Hamdi

N. R.

Dahl Aslan

A. K.

Horwitz

B. N.

Panizzon

M. S.

Petersen

Zavala

Christensen

Finkel

Franz

C. E.

Gatz

Johnson

Kremen

W. S.

Krueger

R. F.

Neiderhiser

J. M.

Reynolds

C. A.

Pedersen

N. L.

McGue

(2018). Age-moderation of genetic and environmental contributions to cognitive functioning in mid- and late-life for specific cognitive abilities. Intelligence, 68, 70–81. https://doi.org/10.1016/j.intell.2017.12.004

103.

Peterson

R. A.

(2021). A simple aggregation rule for penalized regression coefficients after multiple imputation. Journal of Data Science, 19(1), 1–14. https://doi.org/10.6339/21-jds995

104.

Pietrzak

R. H.

Maruff

Woodward

Fredrickson

Krystal

J. H.

Southwick

S. M.

Darby

(2012). Mild worry symptoms predict decline in learning and memory in healthy older adults: A 2-year prospective cohort study. American Journal of Geriatric Psychiatry, 20, 266–275. https://doi.org/10.1097/JGP.0b013e3182107e24

105.

Pietrzak

R. H.

Scott

J. C.

Neumeister

Lim

Y. Y.

Ames

Ellis

K. A.

Harrington

Lautenschlager

N. T.

Szoeke

Martins

R. N.

Masters

C. L.

Villemagne

V. L.

Rowe

C. C.

Maruff

, & Australian Imaging, Biomarkers and Lifestyle (AIBL) Research Group. (2014). Anxiety symptoms, cerebral amyloid burden and memory decline in healthy older adults without dementia: 3-year prospective cohort study. British Journal of Psychiatry, 204, 400–401. https://doi.org/10.1192/bjp.bp.113.134239

106.

Pons

Latapy

(2005). Computing communities in large networks using random walks. In Yolum

Güngör

Gürgen

Özturan

(Eds.), Computer and information sciences: ISCIS 2005 (pp. 284–293). Springer. https://doi.org/10.1007/11569596_31

107.

R Core Team. (2021). R: A language and environment for statistical computing. R Foundation for Statistical Computing. https://www.R-project.org/

108.

Ramos

A. A.

Machado

(2021). A comprehensive meta-analysis on short-term and working memory dysfunction in Parkinson’s Disease. Neuropsychology Review, 31, 288–311. https://doi.org/10.1007/s11065-021-09480-w

109.

Reeves

S. J.

Gould

R. L.

Powell

J. F.

Howard

R. J.

(2012). Origins of delusions in Alzheimer’s disease. Neuroscience & Biobehavioral Reviews, 36, 2274–2287. https://doi.org/10.1016/j.neubiorev.2012.08.001

110.

Rodriguez-Aranda

Sundet

(2006). The frontal hypothesis of cognitive aging: Factor structure and age effects on four frontal tests among healthy individuals. Journal of Genetic Psychology, 167, 269–287. https://doi.org/10.3200/GNTP.167.3.269-287

111.

Rubin

D. B.

(1986). Statistical matching using file concatenation with adjusted weights and multiple imputations. Journal of Business & Economic Statistics, 4, 87–94. https://doi.org/10.2307/1391390

112.

Sabey

A. K.

Jensen

Major

Zinbarg

Pinsof

(2020). Are older adults unique? Examining presenting issues and changes in therapy across the life span. Journal of Applied Gerontology, 39, 250–258. https://doi.org/10.1177/0733464818818048

113.

Sanislow

C. A.

Ferrante

Pacheco

Rudorfer

M. V.

Morris

S. E.

(2019). Advancing translational research using NIMH Research Domain Criteria and computational methods. Neuron, 101, 779–782. https://doi.org/10.1016/j.neuron.2019.02.024

114.

Savva

G. M.

Arthur

(2015). Who has undiagnosed dementia? A cross-sectional analysis of participants of the Aging, Demographics and Memory Study. Age and Ageing, 44, 642–647. https://doi.org/10.1093/ageing/afv020

115.

Shao

Janse

Visser

Meyer

A. S.

(2014). What do verbal fluency tasks measure? Predictors of verbal fluency performance in older adults. Frontiers in Psychology, 5, Article 772. https://doi.org/10.3389/fpsyg.2014.00772

116.

Steinberg

B. A.

Bieliauskas

L. A.

Smith

G. E.

Langellotti

Ivnik

R. J.

(2005). Mayo’s older Americans normative studies: Age- and IQ-adjusted norms for the Boston naming test, the MAE token test, and the judgment of line orientation test. The Clinical Neuropsychologist, 19, 280–328. https://doi.org/10.1080/13854040590945229

117.

Sutin

A. R.

Terracciano

Milaneschi

Ferrucci

Zonderman

A. B.

(2013). The trajectory of depressive symptoms across the adult life span. JAMA Psychiatry, 70, 803–811. https://doi.org/10.1001/jamapsychiatry.2013.193

118.

Tombaugh

T. N.

McIntyre

N. J.

(1992). The mini-mental state examination: A comprehensive review. Journal of the American Geriatrics Society, 40, 922–935. https://doi.org/10.1111/j.1532-5415.1992.tb01992.x

119.

Tsang

R. S.

Mather

K. A.

Sachdev

P. S.

Reppermund

(2017). Systematic review and meta-analysis of genetic studies of late-life depression. Neuroscience & Biobehavioral Reviews, 75, 129–139. https://doi.org/10.1016/j.neubiorev.2017.01.028

120.

van Buuren

Groothuis-Oudshoorn

(2011). Mice: Multivariate imputation by chained equations in R. Journal of Statistical Software, 45, 1548–7660.

121.

van der Linde

Stephan

B. C. M.

Matthews

F. E.

Brayne

Savva

G. M.

, & the Medical Research Council Cognitive Function and Ageing Study. (2010). Behavioural and psychological symptoms in the older population without dementia – Relationship with socio-demographics, health and cognition. BMC Geriatrics, 10, Article 87. https://doi.org/10.1186/1471-2318-10-87

122.

van der Linde

R. M.

Dening

Stephan

B. C.

Prina

A. M.

Evans

Brayne

(2016). Longitudinal course of behavioural and psychological symptoms of dementia: Systematic review. British Journal of Psychiatry, 209, 366–377. https://doi.org/10.1192/bjp.bp.114.148403

123.

van Ginkel

J. R.

Linting

Rippe

R. C. A.

van der Voort

(2020). Rebutting existing misconceptions about multiple imputation as a method for handling missing data. Journal of Personality Assessment, 102, 297–308. https://doi.org/10.1080/00223891.2018.1530680

124.

van Wanrooij

L. L.

Borsboom

Moll van Charante

E. P.

Richard

van Gool

W. A.

(2019). A network approach on the relation between apathy and depression symptoms with dementia and functional disability. International Psychogeriatrics, 31, 1655–1663. https://doi.org/10.1017/S1041610218002387

125.

von Hippel

Vasey

M. W.

Gonda

Stern

(2006). Executive function deficits, rumination and late-onset depressive symptoms in older adults. Cognitive Therapy and Research, 32, 474–487. https://doi.org/10.1007/s10608-006-9034-9

126.

Walhovd

K. B.

Fjell

A. M.

Espeseth

(2014). Cognitive decline and brain pathology in aging - Need for a dimensional, lifespan and systems vulnerability view. Scandinavian Journal of Psychology, 55, 244–254. https://doi.org/10.1111/sjop.12120

127.

Wang

Blazer

D. G.

(2015). Depression and cognition in the elderly. Annual Review of Clinical Psychology, 11, 331–360. https://doi.org/10.1146/annurev-clinpsy-032814-112828

128.

Wechsler

(2008). Wechsler Adult Intelligence Scale-Fourth edition: Technical and interpretative manual. Pearson Assessment.

129.

White

I. R.

Royston

Wood

A. M.

(2011). Multiple imputation using chained equations: Issues and guidance for practice. Statistics in Medicine, 30, 377–399. https://doi.org/10.1002/sim.4067

130.

Wrosch

Jobin

Scheier

M. F.

(2017). Do the emotional benefits of optimism vary across older adulthood? A life span perspective. Journal of Personality, 85, 388–397. https://doi.org/10.1111/jopy.12247

131.

Wysocki

A. C.

Rhemtulla

(2021). On penalty parameter selection for estimating network models. Multivariate Behavioral Research, 56, 288–302. https://doi.org/10.1080/00273171.2019.1672516

132.

Zahodne

L. B.

Ornstein

Cosentino

Devanand

D. P.

Stern

(2015). Longitudinal relationships between Alzheimer disease progression and psychosis, depressed mood, and agitation/aggression. American Journal of Geriatric Psychiatry, 23, 130–140. https://doi.org/10.1016/j.jagp.2013.03.014

133.

Zainal

N. H.

Newman

M. G.

(2018). Executive function and other cognitive deficits are distal risk factors of generalized anxiety disorder 9 years later. Psychological Medicine, 48, 2045–2053. https://doi.org/10.1017/S0033291717003579

134.

Zainal

N. H.

Newman

M. G.

(2021a). Depression and executive functioning bidirectionally impair one another across 9 years: Evidence from within-person latent change and cross-lagged models. European Psychiatry, 64, Article e43. https://doi.org/10.1192/j.eurpsy.2021.2217

135.

Zainal

N. H.

Newman

M. G.

(2021b). Depression and worry symptoms predict future executive functioning impairment via inflammation. Psychological Medicine. Advance online publication. https://doi.org/10.1017/S0033291721000398

136.

Zainal

N. H.

Newman

M. G.

(2022). Inflammation mediates depression and generalized anxiety symptoms predicting executive function impairment after 18 years. Journal of Affective Disorders, 296, 465–475. https://doi.org/10.1016/j.jad.2021.08.077

137.

Zetsche

Burkner

P. C.

Renneberg

(2019). Future expectations in clinical depression: Biased or realistic? Journal of Abnormal Psychology, 128, 678–688. https://doi.org/10.1037/abn0000452

Supplementary Material

Please find the following supplemental material available below.

For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.

For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.

0.00 MB

1.02 MB