Evidence map›Paper›PMID 29303475›Full record

Trial reportExperimental aging research

The ACTIVE conceptual framework as a structural equation model.

Alden L Gross, Brennan R Payne, Ramon Casanova, Pega Davoudzadeh, Joseph M Dzierzewski, Sarah Farias, Tania Giovannetti, Edward H Ip, Michael Marsiske, George W Rebok and 4 more

Abstract readMulticenter StudyRandomized Controlled Trial
PubMed Full text at PMC Publisher
In one paragraph

Trial report in Experimental aging research. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–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

5 citing papers in PubMed.

  1. Comparing Web-Based and Classroom-Based Memory Training for Older Adults: The ACTIVE Memory Works™ Study.The journals of gerontology. Series B, Psychological sciences and social sciences · 2020
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

14 authors.

Alden L Grossa Departments of Epidemiology , Johns Hopkins Center on Aging and Health, Johns Hopkins Bloomberg School of Public Health , Baltimore , Maryland , USA.
Brennan R Paynec Department of Psychology and The Beckman Institute for Advanced Science and Technology , University of Illinois, Urbana-Champaign , Illinois , USA.
Ramon Casanovad Departments of Biostatistical Sciences , Wake Forest School of Medicine , Winston Salem , North Carolina , USA.
Pega Davoudzadehf Department of Psychology , University of California , Davis , California , USA.
Joseph M Dzierzewskig Department of Psychology , Virginia Commonwealth University , Richmond , Virginia , USA.
Sarah Fariash Department of Neurology , University of California, Davis Medical Center , Sacramento , California , USA.
Tania Giovannettii Department of Psychology , Temple University , Philadelphia , Pennsylvania , USA.
Edward H Ipd Departments of Biostatistical Sciences , Wake Forest School of Medicine , Winston Salem , North Carolina , USA.
Michael Marsiskej Department of Clinical and Health Psychology , University of Florida , Gainesville , Florida , USA.
George W Rebokb Departments of Mental Health , Johns Hopkins Center on Aging and Health, Johns Hopkins Bloomberg School of Public Health , Baltimore , Maryland , USA.
K Warner Schaiek Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle, WA; Department of Radiology , Integrated Brain Imaging Center (IBIC), University of Washington , Seattle , WA.
Kelsey Thomasj Department of Clinical and Health Psychology , University of Florida , Gainesville , Florida , USA.ORCID 0000-0003-4277-8876
Sherry Willisk Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle, WA; Department of Radiology , Integrated Brain Imaging Center (IBIC), University of Washington , Seattle , WA.
Richard N Jonesl Departments of Psychiatry and Human Behavior , Warren Alpert Medical School, Brown University , Providence , Rhode Island , USA.

Funding

UCLA Clinical and Translational Science InstituteUL1TR000124 · NCATS · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI DUBINETT, STEVEN M. · 2012 to 2015
$57.0M
'T V ASSESSMENT - MEMORY DISORDERED PATIENTS'P50AG005146 · NIA · JOHNS HOPKINS UNIVERSITY · PI HUGANIR, RICHARD L · 1985 to 2019
$37.6M
UCLA OLDER AMERICANS INDEPENDENCE CENTERP30AG028748 · NIA · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI KARLAMANGLA, ARUN S · 2006 to 2017
$9.8M
Cognitive and inflammatory consequences of sleep disorders in older adultsK23AG049955 · NIA · VIRGINIA COMMONWEALTH UNIVERSITY · PI DZIERZEWSKI, JOSEPH MICHAEL · 2016 to 2020
$794k
Intersection of Physiologic Frailty and Cognitive Performance in Older Adults: An Integrative Data AnalysisK01AG050699 · NIA · JOHNS HOPKINS UNIVERSITY · PI GROSS, ALDEN L. · 2016 to 2020
$648k
Conference on Advanced Psychometric Methods in Cognitive Aging ResearchR13AG030995 · NIA · UNIVERSITY OF CALIFORNIA AT DAVIS · PI MUNGAS, DAN M. · 2008 to 2022
$620k
NCATS NIH HHS UL1 TR000124NIA NIH HHS K01 AG050699NIA NIH HHS K23 AG049955NIA NIH HHS P30 AG028748NIA NIH HHS P50 AG005146NIA NIH HHS R13 AG030995
6 · The paper itself

Abstract

Background/Study Context: Conceptual frameworks are analytic models at a high level of abstraction. Their operationalization can inform randomized trial design and sample size considerations.

methodsThe Advanced Cognitive Training for Independent and Vital Elderly (ACTIVE) conceptual framework was empirically tested using structural equation modeling (N=2,802). ACTIVE was guided by a conceptual framework for cognitive training in which proximal cognitive abilities (memory, inductive reasoning, speed of processing) mediate treatment-related improvement in primary outcomes (everyday problem-solving, difficulty with activities of daily living, everyday speed, driving difficulty), which in turn lead to improved secondary outcomes (health-related quality of life, health service utilization, mobility). Measurement models for each proximal, primary, and secondary outcome were developed and tested using baseline data. Each construct was then combined in one model to evaluate fit (RMSEA, CFI, normalized residuals of each indicator). To expand the conceptual model and potentially inform future trials, evidence of modification of structural model parameters was evaluated by age, years of education, sex, race, and self-rated health status.

resultsPreconceived measurement models for memory, reasoning, speed of processing, everyday problem-solving, instrumental activities of daily living (IADL) difficulty, everyday speed, driving difficulty, and health-related quality of life each fit well to the data (all RMSEA < .05; all CFI > .95). Fit of the full model was excellent (RMSEA = .038; CFI = .924). In contrast with previous findings from ACTIVE regarding who benefits from training, interaction testing revealed associations between proximal abilities and primary outcomes are stronger on average by nonwhite race, worse health, older age, and less education (p < .005).

conclusionsEmpirical data confirm the hypothesized ACTIVE conceptual model. Findings suggest that the types of people who show intervention effects on cognitive performance potentially may be different from those with the greatest chance of transfer to real-world activities.

Indexed as

Models, PsychologicalActivities of Daily LivingAgedAged, 80 and overAgingCognition DisordersFemaleGeriatric AssessmentHealth EducationHealth StatusHumansMaleMemory DisordersProblem SolvingQuality of LifeResearch Design

Identifiers

PMID29303475
PMCPMC5793899

What OpenQuestion holds

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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.