CogniFit Research · Journals of Gerontology: Medical Sciences · 2020

Study: 8 Weeks of Home Cognitive Training Improved Cognition in Older Adults With Diabetes at Higher Dementia Risk

Study citation
Bahar-Fuchs A, Barendse MEA, Bloom R, Ravona-Springer R, Heymann A, Dabush H, Bar L, Slater-Barkan S, Rassovsky Y, Schnaider Beeri M (2020)
Computerized Cognitive Training for Older Adults at Higher Dementia Risk due to Diabetes: Findings From a Randomized Controlled Trial. The Journals of Gerontology: Series A, Medical Sciences, 75(4), 747–754. DOI: 10.1093/gerona/glz073 · Registration: NCT02709629 · Funding: Maccabi Health Services (grant 25860). The training platform was donated by CogniFit, which had no role in trial design, analysis, or reporting.
Key points
  • 84 older adults with type 2 diabetes (mean age 71.45) were randomized to tailored-adaptive or generic training, both at home on the CogniFit platform, 48 sessions over 8 weeks.
  • Global cognition improved post-training (Cohen's d = 0.495, p < .001) and gained further at 6 months (d = 0.207); self-reported diabetes self-management also improved (d = 0.249) and held.[1]
  • Lower-cognition participants gained about 3× more (d = 1.072 vs 0.367); the tailored arm kept 100% of participants through post-testing versus 80% (p = .002).[1]
  • What it does not show: with no untreated control group, practice effects cannot be fully excluded, although d = 0.495 far exceeds the d = 0.12–0.18 retest effects meta-analyses report for control groups.[1]

Why diabetes raises the stakes for brain health

According to an increasingly dominant view in dementia research, better management of common modifiable risk factors could prevent more than a third of all dementia cases.[2] Type 2 diabetes sits near the top of that risk list: population studies repeatedly link it to cognitive decline and to dementia-spectrum disorders.

There is a second, practical problem. Diabetes demands a daily self-management regimen, and subtle cognitive dysfunction in older adults with diabetes is common and tied to worse self-management. Cognition and disease control can drag each other down. This trial, run in the metropolitan Tel-Aviv area, was the first to test whether multidomain computerized cognitive training (CCT) could improve both cognition and diabetes self-management in this population.[1]

What the study tested

Eighty-five community-dwelling older adults with diabetes (mean age 71.45, SD 4.85; 51 men; 16 years of education on average) enrolled; 84 were randomized in this single-blind trial. All had diabetes but no dementia or Alzheimer's diagnosis. Randomization (1:1) assigned them to one of two home-based programs, both on the commercially available multidomain CogniFit platform:[1]

Tailored and adaptive CCT (TA-CCT, n = 44): tasks matched to each participant's cognitive profile, difficulty adapting to performance, feedback after every session. Generic CCT (G-CCT, n = 40): same tasks for everyone, fixed difficulty, scores shown only at baseline and end of training.[1]

Both arms had the same prescribed dose: three training days per week for 8 weeks, two 10–15-minute sessions per day, 48 sessions, plus an optional 3-session booster at month 3. Each arm was further randomized to a global, cognition-specific, or no self-efficacy intervention (fortnightly phone calls plus two short videos).

The primary outcome was a global cognition composite across a named battery: Mini-Addenbrooke's Cognitive Evaluation, L'Hermitte Board, Logical Memory test, Rey Auditory Verbal Learning Test, Rey figure copy, Verbal Fluency, Digit Span, Digit-Symbol Coding, Boston Naming Test, and Trail-Making Task. The main secondary outcome was the Diabetes Self-Management Questionnaire (DSMQ). Psychologists blind to allocation assessed at baseline, post-intervention, and 6 months.

What it found

Cognition improved, and kept improving. Across both arms, global cognition rose from baseline to post-intervention (β = 0.23, Cohen's d = 0.495, p < .001) and again from post-intervention to 6-month follow-up (β = 0.10, d = 0.207, p = .007). Delayed memory (d = 0.540) and memory-and-learning (d = 0.494) showed the largest post-training gains; the non-memory composite improved more modestly (d = 0.189).[1]

Diabetes self-management improved too. Self-reported diabetes self-management improved after training (β = 0.40, d = 0.249) and held at 6 months, the first reported evidence that, in this trial's participants, multidomain CCT was associated with improvement on a self-reported diabetes self-management outcome, though the change appeared only in self-report.[1]

Effect of time on key outcomes (both training arms pooled; Cohen's d)
Outcome compositeBaseline → post-trainingPost-training → 6-month follow-up
Global cognitiond = 0.495[1]d = 0.207[1]
Delayed memoryd = 0.540[1]d = 0.271[1]
Memory and learningd = 0.494[1]d = 0.404[1]
Non-memoryd = 0.189[1]d = 0.071[1]
Diabetes self-management (self-report)d = 0.249[1]d = −0.098 (maintained)[1]

Who benefited most? The 15 participants with lower baseline cognition (z ≤ −0.5) improved far more than the 68 with average-to-high baselines: d = 1.072 versus 0.367. Of 75 completers, 13 showed a "clinically meaningful" cognitive improvement (≥0.5 SD) and 16 a clinically meaningful (≥1 SD) self-management improvement.[1]

Adherence and retention were strong, strongest in the tailored arm. Overall, 89% (76/85) completed post-intervention assessment and 82% (70) the 6-month follow-up; 68% and 71% of the two arms completed at least 80% of the 48 prescribed sessions. TA-CCT participants were more likely to finish post-testing (100% vs 80%, p = .002) and follow-up (93% vs 72%, p = .01), and trained longer (553 vs 412 minutes, p = .009). Yet objective cognitive gains were similar in both arms, tailoring drove engagement, not extra test-score benefit. Dose still mattered: more training time meant higher global cognition at every assessment (p = .0005).[1]

The study's own verdict
"Our findings suggest that older adults at higher dementia risk due to diabetes can show improvements in both cognition and disease self-management following home-based multidomain computerized cognitive training."
, Bahar-Fuchs et al., 2020[1]

Limitations, what it does not show

No untreated control group. Both arms received active training, so practice and retest effects cannot be fully ruled out. The authors counter with three observations: the global effect (d = 0.495) was significantly larger than meta-analytic effects for passive (d = 0.12, CI 0.08–0.16) or active (d = 0.18, CI 0.12–0.24) controls; CCT has already beaten both control types in prior studies; and the 4 participants who completed under 20% of the training improved much less (d = 0.17) than the rest (d = 0.49).[1]

A self-selected, high-functioning sample. Participants were predominantly well-educated (16 years on average) and motivated, limiting generalizability to the wider diabetic population.

Self-report gap. The self-management improvement appeared in self-reports but not informant reports, cognitive and self-management changes were not clearly related (r = −.09, ns), and biological outcomes such as hemoglobin A1c were not measured.[1]

Tailoring was not the active ingredient. Tailored, adaptive training showed no extra objective cognitive benefit over generic training, in the authors' words, "adaptive difficulty and individual task tailoring may not be critical components of such interventions", even though it clearly improved retention and training time.

Where this fits in the broader evidence

The result extends a substantial prior literature. A 2017 meta-analysis by Hill and colleagues found CCT effective in older adults with mild cognitive impairment,[4] and a 2018 double-blind RCT by Whitelock and colleagues showed adults with type 2 diabetes improved visuospatial attention after working-memory training.[5] This trial is the first to test multidomain CCT on both cognition and disease self-management in this population. Its null tailoring result contrasts with a 2017 trial in which tailored, adaptive training beat generic training,[6] a discrepancy flagged for head-to-head replication. The paper concludes that "CCT represents an intervention that is relatively easy to implement in a range of community and clinical settings at relatively low cost." Browse all peer-reviewed CogniFit research in the research studies index.

References

  1. Bahar-Fuchs A, Barendse MEA, Bloom R, Ravona-Springer R, Heymann A, Dabush H, Bar L, Slater-Barkan S, Rassovsky Y, Schnaider Beeri M. Computerized Cognitive Training for Older Adults at Higher Dementia Risk due to Diabetes: Findings From a Randomized Controlled Trial. J Gerontol A Biol Sci Med Sci. 2020;75(4):747–754. doi:10.1093/gerona/glz073
  2. Livingston G, Sommerlad A, Orgeta V, et al. Dementia prevention, intervention, and care. Lancet. 2017;390:2673–2734. doi:10.1016/S0140-6736(17)31363-6
  3. Bloom R, Schnaider-Beeri M, Ravona-Springer R, et al. Computerized cognitive training for older diabetic adults at risk of dementia: study protocol. Alzheimers Dement (N Y). 2017;3:636–650. doi:10.1016/j.trci.2017.10.003
  4. Hill NT, Mowszowski L, Naismith SL, Chadwick VL, Valenzuela M, Lampit A. Computerized cognitive training in older adults with mild cognitive impairment or dementia: a systematic review and meta-analysis. Am J Psychiatry. 2017;174:329–340. doi:10.1176/appi.ajp.2016.16030360
  5. Whitelock V, Nouwen A, Houben K, van den Akker O, Rosenthal M, Higgs S. Does working memory training improve dietary self-care in type 2 diabetes mellitus? Results of a double blind randomised controlled trial. Diabetes Res Clin Pract. 2018;143:204–214. doi:10.1016/j.diabres.2018.07.005
  6. Bahar-Fuchs A, Webb S, Bartsch L, et al. Tailored and adaptive computerized cognitive training in older adults at risk for dementia: a randomized controlled trial. J Alzheimers Dis. 2017;60:889–911. doi:10.3233/JAD-170404
Published by CogniFit, a cognitive training provider. This page is educational and is not medical advice. CogniFit training is a general wellness program, not a disease treatment. Some cited evidence may come from studies that did not use CogniFit; links are provided so readers can review scope and limitations.