ArticleBrain and behavior2026
Feasibility and Effectiveness of Personalized Home-Based Neurostimulation for Teachers Experiencing Work-Related Rumination.
Article in Brain and behavior, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
introductionWork-related rumination is associated with poor mental and physical health. This study aimed to develop and evaluate a personalized Bayesian optimization (pBO) algorithm, designed to tailor transcranial alternating current stimulation (tACS) parameters for UK schoolteachers experiencing elevated work-related rumination.
methodsThe algorithm adjusted tACS parameters based on individual head circumference and rumination levels. During the development phase, 80 burn-in and 319 personalized home-based sessions were conducted with 67 schoolteachers to model parameter-outcome relationships. In a preregistered, double-blind, within-participant follow-up study, 38 schoolteachers received both personalized and sham stimulation sessions in a counterbalanced order. Measures included work-related rumination, daytime sleepiness, actigraphy-based sleep fragmentation and efficiency, and side-effect ratings.
resultsIn the algorithm development phase, higher-amplitude stimulation was associated with reduced sleep fragmentation. In the follow-up study, both personalized and sham stimulation reduced rumination, but no significant differences were observed between conditions. Higher amplitudes were associated with greater reductions in daytime sleepiness. Post-stimulation changes in sleepiness and ruminations were associated only at higher amplitudes in the personalized condition and were not observed following sham stimulation. Side-effect severity did not differ significantly between conditions.
conclusionsHome-based neurostimulation interventions are feasible and well tolerated. While personalized stimulation did not outperform sham, the findings identify current amplitude as a key factor influencing daytime sleepiness and highlight the need to further refine personalization algorithms and stimulation strategies to optimize effectiveness.
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