Un elenco di letture per chi desidera approfondire: i libri e gli articoli a cui noi stessi torniamo di continuo, dai classici sull'auto-organizzazione alle ricerche recenti sui processi di cambiamento in psicoterapia. L'elenco non è completo e cresce insieme alla piattaforma.
Haken, H., & Schiepek, G. (2010). Synergetik in der Psychologie: Selbstorganisation verstehen und gestalten (2. Aufl.). Hogrefe.
Tschacher, W., Schiepek, G., & Brunner, E. J. (Eds.) (1992). Self-Organization and Clinical Psychology: Empirical Approaches to Synergetics in Psychology. Springer.
Guastello, S. J., Koopmans, M., & Pincus, D. (Eds.) (2009). Chaos and Complexity in Psychology: The Theory of Nonlinear Dynamical Systems. Cambridge University Press.
Kelso, J. A. S. (1995). Dynamic Patterns: The Self-Organization of Brain and Behavior. MIT Press.
Thelen, E., & Smith, L. B. (1994). A Dynamic Systems Approach to the Development of Cognition and Action. MIT Press.
Scheffer, M. (2009). Critical Transitions in Nature and Society. Princeton University Press.
Strogatz, S. H. (2015). Nonlinear Dynamics and Chaos: With Applications to Physics, Biology, Chemistry, and Engineering (2nd ed.). Westview Press.
Schiepek, G., Eckert, H., Aas, B., Wallot, S., & Wallot, A. (2015). Integrative Psychotherapy: A Feedback-Driven Dynamic Systems Approach. Hogrefe.
Hayes, S. C., & Hofmann, S. G. (Eds.) (2018). Process-Based CBT: The Science and Core Clinical Competencies of Cognitive Behavioral Therapy. New Harbinger.
Sturmberg, J. P., & Martin, C. M. (Eds.) (2013). Handbook of Systems and Complexity in Health. Springer.
Kunnen, E. S., de Ruiter, N. M. P., Jeronimus, B. F., & van der Gaag, M. A. E. (Eds.) (2019). Psychosocial Development in Adolescence: Insights from the Dynamic Systems Approach. Routledge.
van Geert, P. (2026). Mensen zijn complex: Een inleiding in de theorie van complexe dynamische systemen voor de psychologische en pedagogische praktijk. University of Groningen Press. Open access
van Geert, P. (1994). Dynamic Systems of Development: Change between Complexity and Chaos. Harvester Wheatsheaf.
Guastello, S. J., & Gregson, R. A. M. (Eds.) (2011). Nonlinear Dynamical Systems Analysis for the Behavioral Sciences Using Real Data. CRC Press.
Riley, M. A., & Van Orden, G. C. (Eds.) (2005). Tutorials in Contemporary Nonlinear Methods for the Behavioral Sciences. National Science Foundation (online).
van Steen, M. (2010). Graph Theory and Complex Networks: An Introduction. Maarten van Steen (download gratuito).
Sprott, J. C. (2003). Chaos and Time-Series Analysis. Oxford University Press. Sito di supporto
Sprott, J. C. (2010). Elegant Chaos: Algebraically Simple Chaotic Flows. World Scientific.
Schiepek, G. (2009). Complexity and nonlinear dynamics in psychotherapy. European Review, 17(2), 331-356. doi:10.1017/S1062798709000763
Hayes, A. M., Laurenceau, J.-P., Feldman, G., Strauss, J. L., & Cardaciotto, L. (2007). Change is not always linear: The study of nonlinear and discontinuous patterns of change in psychotherapy. Clinical Psychology Review, 27(6), 715-723.
Borsboom, D. (2017). A network theory of mental disorders. World Psychiatry, 16(1), 5-13.
Schiepek, G., & Pincus, D. (2023). Complexity science: A framework for psychotherapy integration. Counselling & Psychotherapy Research, 23(4), 941-955. doi:10.1002/capr.12641
Schiepek, G. (2020). Contributions of systemic research to the development of psychotherapy. In M. Ochs, M. Borcsa & J. Schweitzer (Eds.), Systemic Research in Individual, Couple, and Family Therapy and Counseling (pp. 11-38). Springer Nature.
Olthof, M., Hasselman, F., Aas, B., Lamoth, D., Scholz, S., Daniels-Wredenhagen, N., Goldbeck, F., Weinans, E., Strunk, G., Schiepek, G., Bosman, A. M. T., & Lichtwarck-Aschoff, A. (2023). The best of both worlds? General principles of psychopathology in personalized assessment. Journal of Psychopathology and Clinical Science, 132(7), 808-819. doi:10.1037/abn0000858
Schiepek, G., & Strunk, G. (2010). The identification of critical fluctuations and phase transitions in short term and coarse-grained time series: A method for the real-time monitoring of human change processes. Biological Cybernetics, 102(3), 197-207. doi:10.1007/s00422-009-0362-1
Schiepek, G., Tominschek, I., & Heinzel, S. (2014). Self-organization in psychotherapy: Testing the synergetic model of change processes. Frontiers in Psychology, 5, 1089. doi:10.3389/fpsyg.2014.01089
Olthof, M., Hasselman, F., Strunk, G., van Rooij, M., Aas, B., Helmich, M. A., Schiepek, G., & Lichtwarck-Aschoff, A. (2020). Critical fluctuations as an early-warning signal for sudden gains and losses in patients receiving psychotherapy for mood disorders. Clinical Psychological Science, 8(1), 25-35. doi:10.1177/2167702619865969
Olthof, M., Hasselman, F., Strunk, G., Aas, B., Schiepek, G., & Lichtwarck-Aschoff, A. (2020). Destabilization in self-ratings of the psychotherapeutic process is associated with better treatment outcome in patients with mood disorders. Psychotherapy Research, 30(4), 520-531. doi:10.1080/10503307.2019.1633484
Helmich, M. A., Wichers, M., Olthof, M., Strunk, G., Aas, B., Aichhorn, W., Schiepek, G., & Snippe, E. (2020). Sudden gains in day-to-day change: Revealing nonlinear patterns of individual improvement in depression. Journal of Consulting and Clinical Psychology, 88(2), 119-127. doi:10.1037/ccp0000469
Schiepek, G., Schöller, H., de Felice, G., Steffensen, S. V., Skaalum Bloch, M., Fartacek, C., Aichhorn, W., & Viol, K. (2020). Convergent validation of methods for the identification of phase transitions in time series of empirical and model systems. Frontiers in Psychology, 11, 1970. doi:10.3389/fpsyg.2020.01970
Viol, K., Schöller, H., Kaiser, A., Fartacek, C., Aichhorn, W., & Schiepek, G. (2022). Detecting pattern transitions in psychological time series: A validation study on the Pattern Transition Detection Algorithm (PTDA). PLoS ONE, 17(3), e0265335. doi:10.1371/journal.pone.0265335
Scheffer, M., Bascompte, J., Brock, W. A., Brovkin, V., Carpenter, S. R., Dakos, V., Held, H., van Nes, E. H., Rietkerk, M., & Sugihara, G. (2009). Early-warning signals for critical transitions. Nature, 461, 53-59.
van de Leemput, I. A., Wichers, M., Cramer, A. O. J., Borsboom, D., Tuerlinckx, F., Kuppens, P., van Nes, E. H., Viechtbauer, W., Giltay, E. J., Aggen, S. H., Derom, C., Jacobs, N., Kendler, K. S., van der Maas, H. L. J., Neale, M. C., Peeters, F., Thiery, E., Zachar, P., & Scheffer, M. (2014). Critical slowing down as early warning for the onset and termination of depression. PNAS, 111(1), 87-92.
Wichers, M., Smit, A. C., & Snippe, E. (2020). Early warning signals based on momentary affect dynamics can expose nearby transitions in depression: A confirmatory single-subject time-series study. Journal for Person-Oriented Research, 6(1), 1-15. doi:10.17505/jpor.2020.22042
Helmich, M. A., et al. (2024). Slow down and be critical before using early warning signals in psychopathology. Nature Reviews Psychology, 3, 767-780. doi:10.1038/s44159-024-00369-y
Smit, A. C., Helmich, M. A., Bringmann, L. F., Oldehinkel, A. J., Wichers, M., & Snippe, E. (2025). Critical slowing down in momentary affect as early warning signal of impending transitions in depression. Clinical Psychological Science. doi:10.1177/21677026241305136
Schiepek, G., Eckert, H., Kolenik, T., Aichhorn, W., & Schöller, H. (2026). The Synergetic Navigation System (SNS): A generic process and outcome monitoring system on human change dynamics. Zeitschrift für Klinische Psychologie und Psychotherapie, 55(3), 172-184. doi:10.1026/1616-3443/a000887
Schiepek, G., Aichhorn, W., Gruber, M., Strunk, G., Bachler, E., & Aas, B. (2016). Real-time monitoring of psychotherapeutic processes: Concept and compliance. Frontiers in Psychology, 7, 604. doi:10.3389/fpsyg.2016.00604
Schiepek, G., Stöger-Schmidinger, B., Kronberger, H., Aichhorn, W., Kratzer, L., Heinz, P., Viol, K., Lichtwarck-Aschoff, A., & Schöller, H. (2019). The Therapy Process Questionnaire: Factor analysis and psychometric properties of a multidimensional self-rating scale for high-frequency monitoring of psychotherapeutic processes. Clinical Psychology & Psychotherapy, 26, 586-602. doi:10.1002/cpp.2384
de Jong, K., Douglas, S., Wolpert, M., Delgadillo, J., Aas, B., Bovendeerd, B., Carlier, I., Compare, A., Edbrooke-Childs, J., Janse, P., Lutz, W., Moltu, C., Nordberg, S., Poulsen, S., Rubel, J. A., Schiepek, G., Schilling, V. N. L. S., van Sonsbeek, M., & Barkham, M. (2024). Using progress feedback to enhance treatment outcomes: A narrative review. Administration and Policy in Mental Health and Mental Health Services Research. doi:10.1007/s10488-024-01381-3
Seizer, L., Schiepek, G., Cornelissen, G., & Löchner, J. (2024). A primer on sampling rates of ambulatory assessments. Psychological Methods. doi:10.1037/met0000656
Schiepek, G., Gelo, O., Viol, K., Kratzer, L., Orsucci, F., de Felice, G., Stöger-Schmidinger, B., Sammet, I., Aichhorn, W., & Schöller, H. (2020). Complex individual pathways or standard tracks? A data-based discussion on the trajectories of change in psychotherapy. Counselling & Psychotherapy Research, 20(4), 689-702. doi:10.1002/capr.12300
Schiepek, G., de Felice, G., Desmet, M., Aichhorn, W., & Sammet, I. (2022). How to measure outcome: A perspective from the complex dynamic systems approach. Counselling & Psychotherapy Research, 22(4), 937-945. doi:10.1002/capr.12521
de Felice, G., Giuliani, A., Pincus, D., Scozzari, A., Berardi, V., Kratzer, L., Aichhorn, W., Schöller, H., Viol, K., & Schiepek, G. (2022). Stability and flexibility in psychotherapy process predict outcome. Acta Psychologica, 227, 103604. doi:10.1016/j.actpsy.2022.103604
Seizer, L., Kratzer, L., Löchner, J., Schöller, H., Aichhorn, W., & Schiepek, G. (2026). Psychotherapy process dynamics and their relation to treatment success do not differ across diagnoses. Clinical Psychology & Psychotherapy. doi:10.1002/cpp.70222
Høgenhaug, S. S., Kongerslev, M. T., Orsucci, F., Zimatore, G., Steffensen, S. V., Ekberg, A., Campanella, M., Schiepek, G., & Kjaersdam Telléus, G. (2025). Pattern formation, ruptures, and repairs in treatments of personality disorders: An idiographic case series study. Frontiers in Human Neuroscience, 19, 1552895. doi:10.3389/fnhum.2025.1552895
Schiepek, G., Aas, B., & Viol, K. (2016). The mathematics of psychotherapy: A nonlinear model of change dynamics. Nonlinear Dynamics, Psychology, and Life Sciences, 20(3), 369-399.
Schöller, H., Viol, K., Aichhorn, W., Hütt, M. T., & Schiepek, G. (2018). Personality development in psychotherapy: A synergetic model of state-trait dynamics. Cognitive Neurodynamics, 12(5), 441-459. doi:10.1007/s11571-018-9488-y
Guastello, S. J. (2001). Nonlinear dynamics in psychology. Discrete Dynamics in Nature and Society, 6, 11-29.
Sprott, J. C. (2004). Dynamical models of love. Nonlinear Dynamics, Psychology, and Life Sciences, 8(3), 303-314.
Sprott, J. C. (2005). Dynamical models of happiness. Nonlinear Dynamics, Psychology, and Life Sciences, 9(1), 23-36.
Nonlinear Dynamics, Psychology, and Life Sciences · Rivista della Society for Chaos Theory in Psychology & Life Sciences, dal 1997.
Society for Chaos Theory in Psychology & Life Sciences · Società internazionale, con un'ampia pagina di risorse e spiegazioni.
Complexity Science in Psychotherapy (SPR) · Gruppo di interesse speciale della Society for Psychotherapy Research.
Complexity Explorer (Santa Fe Institute) · Corsi online gratuiti sui sistemi complessi.
Synergetic Navigation System (SNS) · Il sistema di monitoraggio sviluppato da Günter Schiepek e dal Center for Complex Systems.
TISEAN · Software gratuito per l'analisi non lineare delle serie temporali (Kantz & Schreiber).
Lezioni, video e dimostrazioni per chi desidera vedere i concetti anche in movimento. Gran parte di questo materiale proviene dal fisico Clint Sprott (University of Wisconsin), che da decenni insegna il caos e la complessità in modo accessibile.
Self-Organization: Nature's Intelligent Design · video lezione; anche in diapositive
The New Science of Chaos · video lezione
The Science of Complexity · lezione (diapositive)
Strange Attractors: From Art to Science · lezione (diapositive)
A Fractal View of the World · lezione (PowerPoint)
Ergodicity · lezione (PowerPoint)
Mathematical Models of Love and Happiness · lezione (diapositive): come relazioni e umore si comportano come sistemi dinamici
Popular Lectures by J. C. Sprott · la panoramica completa delle sue lezioni
Chaos Demonstrations · software per mettere personalmente in moto sistemi caotici
Chaos Data Analyzer · software per l'analisi non lineare delle proprie serie temporali
Sprott's Fractal Gallery · frattali e attrattori strani da guardare
Sprott's Gateway · il punto di partenza per tutto il suo materiale
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