{"schema_version":1,"experiment_id":"eoa_inverse_innovation_exp04_retrieval_first_paired20_20260802","cell_id":"invariant_mode_decomposition_design__psychology","hypothesis_id":"H1","search_queries":["personalized CBT idiographic dynamic network treatment module selection EMA intervention eigenvalues","psychotherapy symptom network control theory personalized intervention selection clinical time series","within-person symptom dynamics eigenvalue stability psychotherapy treatment selection","ecological momentary assessment control theoretic intervention mental health personalized treatment","\"modal controllability\" psychological networks intervention targets eigenvectors","personalized modular CBT dynamic factor analysis EMA module selection randomized trial","\"Open trial of a personalized modular treatment for mood and anxiety\"","\"Network Control Theory in Personalized Intervention Selection\" intervention effects clinical time-series"],"sources":[{"source_id":"C1","title":"On the Control of Psychological Networks","publisher":"Psychometrika / Springer Nature","url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC9205512/","source_class":"PRIMARY_RESEARCH","claims_supported":["Introduces average and modal controllability for selecting intervention targets in psychological networks.","Computes modal controllability from the transition matrix's eigenvalues and eigenvectors.","Uses clinical EMA data and simulations to evaluate single-target, multi-target, and empirical interventions."]},{"source_id":"C2","title":"Network Control Theory in Personalized Intervention Selection: A Proof-of-Concept Approach to Simulating Therapeutic Intervention Effects in Clinical Time-Series Data","publisher":"Psychotherapy Research / Taylor & Francis","url":"https://doi.org/10.1080/10503307.2026.2666624","source_class":"PRIMARY_RESEARCH","claims_supported":["Fits person-specific linear dynamical systems to pretreatment EMA from patients with depression or anxiety.","Represents 31 therapeutic interventions as system inputs and ranks their theoretical effects using average controllability and cumulative impulse response.","Already performs the nominated workflow's core treatment-selection function, although it does not report restricting selection to locally unstable eigenmodes."]},{"source_id":"C3","title":"A Control Theoretic Approach to Evaluate and Inform Ecological Momentary Interventions","publisher":"Psychophysiology / Wiley","url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC11495417/","source_class":"PRIMARY_RESEARCH","claims_supported":["Models multivariate psychological EMA as individualized linear dynamical systems and interventions as perturbations.","Evaluates personalized intervention-delivery rules using network control theory, including maximum-average-controllability and optimal-control strategies.","Shows that control-theoretic selection of mental-health interventions predates the nominated trial design."]},{"source_id":"C4","title":"Open Trial of a Personalized Modular Treatment for Mood and Anxiety","publisher":"Behaviour Research and Therapy / Elsevier","url":"https://pubmed.ncbi.nlm.nih.gov/30831478/","source_class":"PRIMARY_RESEARCH","claims_supported":["Uses intensive repeated measurements, person-specific factor analysis, and dynamic factor modeling to generate individualized modular CBT plans.","Demonstrates that converting idiographic temporal models into patient-specific CBT module selection was already tested clinically."]},{"source_id":"C5","title":"Clinical Trial Protocol NCT06517589: Process-Based Therapy Versus Routine CBT","publisher":"ClinicalTrials.gov / U.S. National Library of Medicine","url":"https://cdn.clinicaltrials.gov/large-docs/89/NCT06517589/Prot_001.pdf","source_class":"GOVERNMENT_OR_REGULATOR","claims_supported":["Specifies a randomized comparison of process-based therapy and routine CBT using individualized EMA and dynamic network analysis.","Directs therapists to select interventions by matching mechanisms of change to central nodes, feedback loops, and self-loops in each patient's network.","Identifies control-theory-based personalized treatment decisions as the next development beyond node-centrality selection."]},{"source_id":"C6","title":"A SMART Approach to Personalized Care: Preliminary Data on How to Select and Sequence Skills in Transdiagnostic CBT","publisher":"Journal of Consulting and Clinical Psychology / American Psychological Association","url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC9749849/","source_class":"PRIMARY_RESEARCH","claims_supported":["Randomizes adults to personalized or standard sequencing of modular transdiagnostic CBT skills.","Documents established alternatives based on relative strengths, relative deficits, and standard module order.","Finds no advantage in improvement trajectories from the tested personalized sequencing rules, supporting the need to test rather than assume benefits from a new selection rule."]}],"proximity":"SUBSTANTIAL_COLLISION","closest_analogues":[{"name":"Network Control Theory in Personalized Intervention Selection","similarity":"Very high: it estimates person-specific EMA transition systems, encodes therapeutic interventions as inputs, simulates their effects, and produces individualized intervention recommendations.","remaining_difference":"It uses average controllability and cumulative impulse response rather than first isolating locally unstable eigenmodes and ranking those modes by sensitivity of functioning.","source_ids":["C2"]},{"name":"On the Control of Psychological Networks","similarity":"High: it explicitly uses eigenvalues, eigenvectors, and modal controllability to identify psychological-network intervention targets from clinical EMA.","remaining_difference":"It targets controllable symptoms or sets of symptoms, not CBT modules assigned specifically to the most outcome-sensitive unstable mode.","source_ids":["C1"]},{"name":"Personalized modular CBT using dynamic factor models","similarity":"High at the clinical-workflow level: idiographic intensive longitudinal models already determine individualized CBT modules and their sequence.","remaining_difference":"The module rule follows predominant dimensions and temporal precedence rather than an unstable-eigenmode partition and functioning-sensitivity calculation.","source_ids":["C4","C6"]},{"name":"Process-Based Therapy randomized protocol","similarity":"High: weekly CBT decisions are informed by individualized EMA dynamic networks and matched change-process interventions.","remaining_difference":"Its operative rule emphasizes central nodes and feedback structures; the protocol describes control-theoretic selection as future development rather than using the nominated unstable-mode rule.","source_ids":["C5"]},{"name":"Control-theoretic ecological momentary intervention selection","similarity":"Moderate to high: individualized psychological state-transition models and control algorithms already select among mental-health interventions.","remaining_difference":"It concerns ecological momentary interventions and control-energy/controllability rules, not weekly CBT modules selected through unstable-mode outcome sensitivity.","source_ids":["C3"]}],"overlapping_components":["Within-patient ecological momentary assessment state vectors","Person-specific lagged linear transition operators","Eigenvalue-and-eigenvector analysis of psychological dynamics","Modal controllability of psychological-network intervention targets","Simulation of therapeutic interventions as multivariable control inputs","Personalized ranking or sequencing of CBT interventions and skill modules","Dynamic-network alternatives to targeting a single prominent or central symptom","Outcome-trajectory estimation after modeled interventions","Randomized comparison of personalized and conventional CBT decision rules"],"remaining_contrastive_claim":"Unlike the located systems, the nominated rule explicitly partitions a patient's transition eigenmodes by local stability and assigns the next CBT module to the unstable mode with greatest functioning sensitivity, claiming at least a 0.3-standardized-unit advantage over largest-symptom targeting.","claim_falsifier":"The contrast would be falsified by a pre-2026 publication, patent, protocol, or product that already selects psychotherapy modules by the combined unstable-eigenmode and functional-outcome-sensitivity rule; its clinical-effect portion would be rejected if the specified randomized pilot fails to show the prespecified 0.3-standardized-unit advantage.","problem_support":"MODERATE","recommendation":"RESEARCH","world_novelty_boundary":"This eight-query, six-source review found substantial prior art for every major element except the precise conjunction of unstable-mode partitioning, functioning-sensitivity ranking, and weekly CBT-module assignment. It expressly does not conclude that the hypothesis is novel worldwide: ordinary web search may miss patents, unpublished systems, non-English literature, paywalled details, and differently named implementations, so the remaining distinction is only a bounded-search finding."}