Long COVID brain fog treatment: An early-phase randomized controlled trial of constraint-induced cognitive therapy signals go.
Bibliographic record
Abstract
ABSTRACT Purpose Long COVID brain fog is often disabling. Yet, no empirically-supported treatments exist. This study’s objectives were to evaluate feasibility and efficacy, provisionally, of a new rehabilitation approach, Constraint-Induced Cognitive Therapy (CICT), for post-COVID-19 cognitive sequelae. Design Sixteen community-residents ≥ 3-months post-COVID-19 infection with mild cognitive impairment and dysfunction in instrumental activities of daily living (IADL) were enrolled. Participants were randomized to Immediate-CICT or treatment-as-usual (TAU) with crossover to CICT. CICT combined behavior change techniques modified from Constraint-Induced Movement Therapy with Speed of Processing Training, a computerized cognitive-training program. CICT was deemed feasible if (a) ≥80% of participants completed treatment, (b) the same found treatment highly satisfying and at most moderately difficult, and (c) <2 study-related, serious adverse-events occurred. The primary outcome was IADL performance in daily life (Canadian Occupational Performance Measure). Employment status and brain fog (Mental Clutter Scale) were also assessed. Results Fourteen completed Immediate-CICT ( n =7) or TAU ( n =7); two withdrew from TAU before their second testing session. Completers were [ M (S D )]: 10 (7) months post-COVID; 51 (13) years old; 10 females, 4 males; 1 African American, 13 European American. All the feasibility benchmarks were met. Immediate-CICT, relative to TAU, produced very large improvements in IADL performance ( M =3.7 points, p<.001, d =2.6) and brain fog ( M =−4 points, p<.001, d =−2.9). Four of five non-retired Immediate-CICT participants returned-to-work post-treatment; no TAU participants did, p =.048. Conclusions CICT has promise for reducing brain fog, improving IADL, and promoting returning-to-work in adults with Long COVID. Findings warrant a large-scale RCT with an active-comparison group. IMPACT Brain fog in adults with Long COVID is often associated with dysfunction in everyday activities and unemployment. Yet, there are no empirically supported treatments targeting cognition in this population. Findings from this small-scale, pilot randomized controlled trial (RCT) suggest that a novel intervention, i.e., Constraint-Induced Cognitive Therapy, is a feasible cognitive rehabilitation method in adults with Long COVID cognitive sequelae with promise of (a) improving performance of cognition-based tasks in daily life and (b) promoting return-to-work. Further studies with larger sample sizes are warranted. Speed of Processing Training (SOPT) has been shown to increase processing speed in older adults without neurological disorders but has not been applied to adults with brain fog due to Long COVID, in whom slowing of cognitive processing speed is common. The results of this pilot RCT suggest that SOPT, in conjunction with behavior change techniques, may increase cognitive processing speed in this brain-injured population.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".