TY - THES U1 - Dissertation / Habilitation A1 - Groß, Daniel T1 - In the Maze of Self-Control and Self-Regulation: Taking into Account Self-Ratings, Executive Functions, Heart Rate Variability, and Action-State Orientation N2 - Abstract Abstract Deutsch Diese Dissertation konzentriert sich zunächst in Studie 1 auf den geringen Zusammenhang zwischen der Messung kognitiver Funktionen, die eine erfolgreiche Selbstregulation unterstützen, den sogenannten Exekutiven Funktionen (EFs), und der vagal vermittelten Ruhe-Herzratenvariabilität (HRV), der Veränderung der Zeitintervalle zwischen zwei aufeinanderfolgenden Herzschlägen (RR/NN-Intervalle oder Interbeat-Intervalle genannt), die aus der parasympathischen Aktivität des autonomen Nervensystems, insbesondere des Vagus Nervs resultiert. Die vagal vermittelte HRV sollte aufgrund des neuroviszeralen Integrationsmodells (Thayer et al., 2009; Thayer & Lane 2000, 2009), das darauf hinweist, dass der präfrontale Kortex eine wichtige Kortexregion sowohl für die vagal vermittelte HRV als auch für die EFs ist, mit den EFs assoziiert sein, was jedoch durch zwei Metaanalysen in Frage gestellt wird (Holzman & Bridgett, 2017; Zahn et al., 2016). In der vorliegenden Thesis wird erwartet, dass dieser Zusammenhang deshalb gering ist, da in den bisherigen Studien die individuelle implizite Affekt- und Aufmerksamkeitsregulationskapazität, die durch die individuelle Handlungs-Lageorientierung gemessen werden kann, oft nicht berücksichtigt wurde (vgl. Fischer et al., 2015; Koole & Jostmann, 2004; Kuhl, 1994a, 1994b; Wolff et al., 2016). Generell können handlungsorientierte Individuen in anspruchsvollen Situationen positive Affekte leichter hochregulieren und sich selbst Anreize setzen (anforderungsbezogene Subskala der Handlungs-Lageorientierung; Kuhl, 1994a, 1994b), negative Affekte herunterregulieren (fehlerbezogene Subskala der Handlungs-Lageorientierung; Kuhl, 1994a, 1994b), auf eine Aufgabe fokussiert bleiben, bis sie abgeschlossen ist (leistungsbezogene Subskala der Handlungs-Lageorientierung; Kuhl, 1994a, 1994b), und so ihre EFs effizienter mobilisieren. Lageorientierte Personen haben jedoch Probleme damit, sich selbst zu motivieren, bis zum Abschluss der Aufgabe konzentriert zu bleiben, den positiven und negativen Affekt zu regulieren und so ihre EFs effektiv zu Abstract mobilisieren (z.B., Gröpel et al., 2014; Jostmann & Koole, 2006, 2007; Koole et al., 2012; Kuhl, 2000; Wolff et al., 2016). Studie 1 zeigte, dass der Zusammmenhang zwischen der Leistung in EF-Aufgaben (in einer Verschiebeaufgabe, einer Inhibitionsaufgabe und einer Aktualisierungsaufgabe) und der vagal vermittelten Ruhe-HRV durch die fehlerbezogene (Verschiebe- und Inhibitionsaufgabe) oder die leistungsbezogene (Aktualisierungsaufgabe) Handlungs-Lageorientierung Subskalen (Kuhl, 1994a, 1994b) moderiert wurde, wenn Anforderungen und Fehlerrückmeldungen der EF-Aufgaben ebenfalls berücksichtigt wurden. Jedoch zeigten die Johnson-Neyman-Tests nur für lageorientierte Individuen eine signifikante Beziehung an1, die sich auch in der Richtung zwischen anspruchsvollen (Verschiebe- und Aktualisierungsaufgabe) und wenig anspruchsvollen (Inhibitionsaufgabe) EF-Aufgaben unterschied, was darauf hindeutet, dass bei wenig anspruchsvollen EF-Aufgaben lageorientierte Individuen sogar handlungsorientierte Individuen übertreffen können (vgl. Koole et al., 2012; Koole et al., 2005). Aufgrund der nicht-signifikanten Beziehung für handlungsorientierte Individuen kann Studie 1 das neuroviszerale Integrationsmodell nicht vollständig bestätigen (Thayer et al., 2009; Thayer & Lane 2000, 2009). In Studie 2 wurden mögliche Indikatoren für die aktuelle (Zustands-) Selbstkontrollkapazität (gemessen anhand einer Simon-Aufgabe) nach anspruchsvollen EF-Aufgaben sowie für die generelle (Eingenschafts-) Selbstkontrolle (gemessen anhand eines Fragebogens) analysiert, wobei der Schwerpunkt auf dem Zusammenspiel zwischen Kontrollkapazität und Selbstmotivation lag (angezeigt durch die anforderungsbezogene Subskala der Handlungs-Lageorientierung; Kuhl, 1994a, 1994b). Als mögliche Kontrollkapazitätsvariablen konzentrierte sich Studie 2 auf die Arbeitsgedächtniskapazität (WMC), basierend auf der integrativen Theorie der Selbstkontrolle (Kotabe & Hofmann, 2015), 1 Dies mag daran liegen, dass die anspruchsvolle EF-Aufgaben so anstrengend waren, dass sie sogar die tiefgreifende Affekt- und Aufmerksamkeitsregulationsfähigkeit handlungsorientierter Individuen überstiegen (vgl. Koole et al., 2005) oder daran, dass die Angabe handlungsorientiert zu sein auch mit sozial erwünschtem Antwortverhalten zusammenhängt (Diefendorff et al., 2000). Abstract und auf die Vaguskontrolle des Herzens (angezeigt durch die vagal vermittelte Ruhe-HRV), ein möglicher physiologischen Index der Kontrollkapazität (nicht eine Ressource selbst), basierend auf der Theorie des vagalen Tanks (Laborde et al., 2018b). Da die Theorie des vagalen Tanks (Laborde et al., 2018b) auch intraindividuelle Veränderungen der Vaguskontrolle des Herzens als möglichen Indikator der aktuellen (Zustands-) Selbstkontrollkapazität sieht, wurden auch Veränderungen der Vaguskontrolle des Herzens von einer Baselinemessung bis nach dem Event analysiert. Mit Fokus auf die integrative Theorie der Selbstkontrolle (Kotabe & Hofmann, 2015) deuteten die Ergebnisse darauf hin, dass sowohl die aktuelle (Zustands-) als auch die generelle (Eingenschafts-) Selbstkontrolle durch ein Zusammenspiel von WMC und anforderungsbezogener Handlungs-Lageorientierung vorhergesagt wird. Blickt man auf die Theorie des vagalen Tanks (Laborde et al., 2018b) deuten die Ergebnisse darauf hin, dass die aktuelle (Zustands-) Selbstkontrollkapazität am besten durch die intraindividuelle Veränderung der Vaguskontrolle des Herzens vorhergesagt werden kann (lageorientierte Individuen mit einer niedrigen WMC [wie von der integrativen Theorie der Selbstkontrolle erwartet; Kotabe & Hofmann, 2015] zeigten die grösste Reduktion der Vaguskontrolle des Herzens nach den anspruchsvollen EF-Aufgaben). Vergleicht man jedoch die Unterschiede in der Vaguskontrolle des Herzens zwischen Probanden scheinen diese mehrdeutig und weniger klar für die Vorhersage der Selbstkontrollfähigkeit zu sein, da diese nur schwach mit der generellen (Eingenschafts-) Selbstkontrolle zusammenhängen, wenn die Vaguskontrolle des Herzens unabhängig von der Handlungs-Lageorientierung betrachtet wird (d.h. nur die Korrelation wird berücksichtigt). Die Unterschiede zwischen aktueller (Zustands-) und genereller (Eingenschafts-) Selbstkontrolle könnten darauf zurückzuführen sein, dass die variablen und stabilen Komponenten der HRV von unterschiedlichem Anteil sind (Bertsch et al., 2012). Da eine höhere vagal vermittelte HRV häufig mit Gesundheit, besserer Selbstregulierung und Selbstkontrollfähigkeit, erhöhter EF, Anpassungsfähigkeit (mehr Flexibilität zur Reaktion auf verschiedene Situationen) und Resilienz assoziiert wird (z.B., Abstract bei gesunden Personen. Hier erweist sich die PMR als effektiv, während der Abstract down self-regulatory mechanisms: A meta-analytic review. Neuroscience & Biobehavioral Reviews, 74, 233–255. https://doi.org/10.1016/j.neubiorev.2016.12.032 Jostmann, N. B., & Koole, S. L. (2006). On the waxing and waning of working memory: Action orientation moderates the impact of demanding relationship primes on working memory capacity. Personality and Social Psychology Bulletin, 32, 1716–1728. https://doi.org/10.1177/0146167206292595 Jostmann, N. B., & Koole, S. L. (2007). On the regulation of cognitive control: Action orientation moderates the impact of high demands in Stroop interference tasks. Journal of Experimental Psychology: General, 136, 593–609. https://doi.org/10.1037/0096-3445.136.4.593 Koole, S. L., & Jostmann, N. B. (2004). Getting a grip on your feelings: Effects of action orientation and external demands on intuitive affect regulation. Journal of Personality and Social Psychology, 87, 974–990. https://doi.org/10.1037/0022-3514.87.6.974 Koole, S. L., Jostmann, N. B., & Baumann, N. (2012). Do demanding conditions help or hurt self-regulation?. Social and Personality Psychology Compass, 6, 328–346. https://doi.org/10.1111/j.1751-9004.2012.00425.x Koole, S. L., Kuhl, J., Jostmann, N. B., & Vohs, K. D. (2005). On the hidden benefits of state orientation: Can people prosper without efficient affect regulation skills?. In A. Tesser, J. Wood, & D. A. Stapel (Eds.), On building, defending, and regulating the self: A psychological perspective (pp. 217–243). London, UK: Taylor & Francis. Kotabe, H. P., & Hofmann, W. (2015). On integrating the components of self-control. Perspectives on Psychological Science, 10, 618–638. https://doi.org/10.1177/1745691615593382 Kuhl, J. (1994a). A theory of action and state orientations. In J. Kuhl & J. Beckmann (Eds.), Abstract Volition and personality: Action versus state orientation (pp. 9–46). Göttingen, Germany: Hogrefe & Huber Publishers. Kuhl, J. (1994b). Action versus state orientation: Psychometric properties of the Action Control Scale (ACS-90). In J. Kuhl & J. Beckmann (Eds.), Volition and personality: Action versus state orientation (pp. 47–59). Göttingen, Germany: Hogrefe & Huber Publishers. Kuhl, J. (2000). A functional-design approach to motivation and self-regulation: The dynamics of personality systems interactions. In M. Boekaerts, P. R. Pintrich, & M. Zeidner (Eds.), Handbook of self-regulation (pp. 111–169). Burlington, MA: Elsevier/Academic Press. https://doi.org/10.1016/B978-012109890-2/50034-2 Laborde, S., Mosley, E., & Mertgen, A. (2018a). A unifying conceptual framework of factors associated to cardiac vagal control. Heliyon, 4, e01002. https://doi.org/10.1016/j.heliyon.2018.e01002 Laborde, S., Mosley, E., & Mertgen, A. (2018b). Vagal tank theory: The three Rs of cardiac vagal control functioning–resting, reactivity, and recovery. Frontiers in Neuroscience, 12. https://doi.org/10.3389/fnins.2018.00458 Quintana, D. S., & Heathers, J. A. J. (2014). Considerations in the assessment of heart rate variability in biobehavioral research. Frontiers in Psychology, 5. https://doi.org/10.3389/fpsyg.2014.00805 Schumann, A., Köhler, S., Brotte, L., & Bär, K.-J. (2019). Effect of an eight-week smartphone-guided HRV-biofeedback intervention on autonomic function and impulsivity in healthy controls. Physiological Measurement, 40, 064001. https://doi.org/10.1088/1361-6579/ab2065 Segerstrom, S. C., & Nes, L. S. (2007). Heart rate variability reflects self-regulatory strength, effort, and fatigue. Psychological Science, 18, 275–281. https://doi.org/10.1111/j.1467- Abstract 9280.2007.01888.x Shaffer, F., & Ginsberg, J. P. (2017). An overview of heart rate variability metrics and norms. Frontiers in Public Health, 5. https://doi.org/10.3389/fpubh.2017.00258 Thayer, J. F., Åhs, F., Fredrikson, M., Sollers, J. J., & Wager, T. D. (2012). A meta-analysis of heart rate variability and neuroimaging studies: Implications for heart rate variability as a marker of stress and health. Neuroscience & Biobehavioral Reviews, 36, 747–756. https://doi.org/10.1016/j.neubiorev.2011.11.009 Thayer, J. F., Hansen, A. L., Saus-Rose, E., & Johnsen, B. H. (2009). Heart rate variability, prefrontal neural function, and cognitive performance: The neurovisceral integration perspective on self-regulation, adaptation, and health. Annals of Behavioral Medicine, 37, 141–153. https://doi.org/10.1007/s12160-009-9101-z Thayer, J. F., & Lane, R. D. (2000). A model of neurovisceral integration in emotion regulation and dysregulation. Journal of Affective Disorders, 61, 201–216. https://doi.org/10.1016/s0165-0327(00)00338-4 Thayer, J. F., & Lane, R. D. (2009). Claude Bernard and the heart–brain connection: Further elaboration of a model of neurovisceral integration. Neuroscience & Biobehavioral Reviews, 33, 81–88. https://doi.org/10.1016/j.neubiorev.2008.08.004 Wolff, M., Krönke, K.-M., Venz, J., Kräplin, A., Bühringer, G., Smolka, M. N., & Goschke, T. (2016). Action versus state orientation moderates the impact of executive functioning on real-life self-control. Journal of Experimental Psychology: General, 145, 1635–1653. https://doi.org/10.1037/xge0000229 Zahn, D., Adams, J., Krohn, J., Wenzel, M., Mann, C. G., Gomille, L. K., Jacobi-Scherbening, V., & Kubiak, T. (2016). Heart rate variability and self-control–a meta-analysis. Biological Psychology, 115, 9–26. https://doi.org/10.1016/j.biopsycho.2015.12.007 Abstract Abstract Englisch This dissertation firstly focuses in Study 1 on the low relationship between the measurement of cognitive functions that support successful self-regulation, called executive functions (EFs), and vagally mediated resting heart rate variability (HRV), the change in the time intervals between two consecutive heartbeats (called RR/NN intervals or interbeat intervals), which results from the parasympathetic activity of the autonomic nervous system, in particular of the vagus nerve. Vagally mediated HRV should be associated with EFs due to the neurovisceral integration model (Thayer et al., 2009; Thayer & Lane 2000, 2009) which indicates that the prefrontal cortex is an important cortex region for both vagally mediated HRV and EFs but is questioned by two meta-analyses (Holzman & Bridgett, 2017; Zahn et al., 2016). In this thesis, it is expected that this relationship is low because past studies often did not consider individual implicit affect and attention regulation capacity which can be measured by action-state orientation (cf. Fischer et al., 2015; Koole & Jostmann, 2004; Kuhl, 1994a, 1994b; Wolff et al., 2016). In general, in demanding situations, action-oriented individuals can more easily up-regulate positive affect and self-generate rewarding incentives (demand-related action-state orientation subscale; Kuhl, 1994a, 1994b), down-regulate negative affect (failure-related action-state orientation subscale; Kuhl, 1994a, 1994b), stay focused on a task until it is finished (performance-related action-state orientation subscale; Kuhl, 1994a, 1994b), and thus mobilize their EFs more efficiently. State-oriented individuals, however, have problems with motivating themselves, staying focused on the task until it is finished, regulating the positive and negative affect, and thus with effectively mobilizing EFs (e.g., Gröpel et al., 2014; Jostmann & Koole, 2006, 2007; Koole et al., 2012; Kuhl, 2000; Wolff et al., 2016). Study 1 identified that the relationship between EF task performance (in a shifting task, an inhibition task, and an updating task) and vagally mediated resting HRV was moderated by failure-related (shifting and inhibition task) or performance-related (updating task) action-state orientation subscales (Kuhl, 1994a, 1994b) if demands and error feedback of the EF tasks were also being Abstract considered. However, the Johnson-Neyman tests only indicated a significant relationship for state-oriented individuals2, which also differed in the direction between demanding (shifting and updating task) and low-demanding (inhibition task) EF tasks, indicating that in low-demanding EF tasks state-oriented individuals can even outperform action-oriented individuals (cf. Koole et al., 2012; Koole et al., 2005). Because of the non-significant relationship for action-oriented individuals, Study 1 cannot fully confirm the neurovisceral integration model (Thayer et al., 2009; Thayer & Lane 2000, 2009). In Study 2 possible indicators for state self-control capacity (measured by a Simon task) after demanding EF tasks, as well as for trait self-control (measured by a questionnaire) were analyzed by focusing on the interplay between control capacity and self-motivation (indicated by the demand-related action-state orientation subscale; Kuhl, 1994a, 1994b). As possible control capacity variables, Study 2 focused on working memory capacity (WMC), based on the integrative theory of self-control (Kotabe & Hofmann, 2015), and on cardiac vagal control (index by vagally mediated resting HRV), a possible physiological index of control capacity (not a resource itself), based on the vagal tank theory (Laborde et al., 2018b). Since the vagal tank theory (Laborde et al., 2018b) also focuses on within-subject changes in cardiac vagal control as a possible index of state self-control capacity, baseline to post-event cardiac vagal control changes were also analyzed. Following the integrative theory of self-control (Kotabe & Hofmann, 2015), the results indicated that state, as well as trait self-control, is predicted by an interplay of WMC, and demand-related action-state orientation. Focusing on the vagal tank theory (Laborde et al., 2018b), the results indicated that state self-control capacity can best be detected by the within-subject changes in cardiac vagal control (state-oriented individuals with a low WMC [as expected by the integrative theory of self-control; Kotabe & Hofmann, 2015] 2 This may be because demanding EF tasks where so stressful, that they exceeded even the profound affect and attention regulation capacity of action-oriented individuals (cf. Koole et al., 2005) or on the fact that being action-oriented is significantly associated with socially desirable responding (Diefendorff et al., 2000). Abstract indicated the greatest reduction in cardiac vagal control after the demanding EF tasks). However, between-subject differences of cardiac vagal control seem to be ambiguous and less clear for predicting self-control capacity since they are only weakly related to trait self-control if cardiac vagal control is considered without action-state orientation (i.e., only the correlation is considered). These differences here between state and trait self-control might be because the variable and stable components of HRV are of different sizes (Bertsch et al., 2012). Since higher vagally mediated HRV is often associated with health, better self-regulation and self-control capacity, increased EFs, adaptability (more flexibility to reaction on different situations), and resilience (e.g., Segerstrom & Nes, 2007; Shaffer & Grinsberg, 2017; Thayer et al., 2009, 2012), Study 3 examined whether it is possible to increase vagally mediated HRV in healthy subjects with average resonant frequency training (RFT; i.e., 6 breaths/minute) and progressive muscle relaxation (PMR) within 77 days. The effects were tested against an active control group, which did a dual-task consisting of a balance task with parallel cognitive tasks. Every morning, participants measured resting vagally mediated HRV with a mobile device by themselves. A linear mixed-effect model, using random slopes (daily HRV measurement), and random intercepts (participants) indicated that only the PMR group significantly increased their vagally mediated HRV compared to the active control group. However, the non-significant effect of the average RFT group can be caused by the fact that they had a significantly higher HRV compared to the active control group, which could not be further increased (cf. Schumann et al., 2019), or by the fact that the average RFT (daily for 5 minutes respectively) and PMR (three times a week for approximately 18 minutes respectively) intervention differed in frequency and duration, and the duration of a single average RFT session was too short. Altogether Study 1 and Study 2 indicated that personality traits (here, action-state orientation) are an important factor and moderator when analyzing the association between Abstract different self-control variables or when analyzing possible indicators for state as well as trait self-control. Furthermore, Study 2 indicated that due to the multiple influences on HRV (cf. Fatisson et al, 2016; Laborde et al., 2018a), which can serve as an indicator of self-control capacity, it should best be studied in within-subject designs rather than in between-subject designs (cf. Quintana & Heathers, 2014). Finally, Study 3 deals with the possibility of increasing HRV by average RFT and PMR in healthy individuals. Here, PMR is shown to be effective, whereas the non-effectiveness of average RFT might be because the average RFT group generally had a significantly higher HRV (cf. Schumann et al., 2019) or that specific personality traits should also be taken into account in intervention studies. To sum it up, the three studies (for an overview of all studies) extend the self-control and self-regulation research and shed some light on the maze of self-control and self-regulation. References Bertsch, K., Hagemann, D., Naumann, E., Schachinger, H., & Schulz, A. (2012). Stability of heart rate variability indices reflecting parasympathetic activity. Psychophysiology 49, 672–682. https://doi.org/10.1111/j.1469-8986.2011.01341.x Diefendorff, J. M., Hall, R. J., Lord, R. G., & Strean, M. L. (2000). Action–state orientation: Construct validity of a revised measure and its relationship to work-related variables. Journal of Applied Psychology, 85, 250–263. https://doi.org/10.1037/0021-9010.85.2.250 Fatisson, J., Oswald, V., & Lalonde, F. (2016). Influence diagram of physiological and environmental factors affecting heart rate variability: An extended literature overview. Heart International, 11, e32–e40. https://doi.org/10.5301/heartint.5000232 Fischer, R., Plessow, F., Dreisbach, G., & Goschke, T. (2015). Individual differences in the context-dependent recruitment of cognitive control: Evidence from action versus state orientation. Journal of Personality, 83, 575–583. https://doi.org/10.1111/jopy.12140 Abstract Gröpel, P., Baumeister, R. F., & Beckmann, J. (2014). Action versus state orientation and self-control performance after depletion. Personality and Social Psychology Bulletin, 40, 476–487. https://doi.org/10.1177/0146167213516636 Holzman, J. B., & Bridgett, D. J. (2017). Heart rate variability indices as bio-markers of top-down self-regulatory mechanisms: A meta-analytic review. Neuroscience & Biobehavioral Reviews, 74, 233–255. https://doi.org/10.1016/j.neubiorev.2016.12.032 Jostmann, N. B., & Koole, S. L. (2006). On the waxing and waning of working memory: Action orientation moderates the impact of demanding relationship primes on working memory capacity. Personality and Social Psychology Bulletin, 32, 1716–1728. https://doi.org/10.1177/0146167206292595 Jostmann, N. B., & Koole, S. L. (2007). On the regulation of cognitive control: Action orientation moderates the impact of high demands in Stroop interference tasks. Journal of Experimental Psychology: General, 136, 593–609. https://doi.org/10.1037/0096-3445.136.4.593 Koole, S. L., & Jostmann, N. B. (2004). Getting a grip on your feelings: Effects of action orientation and external demands on intuitive affect regulation. Journal of Personality and Social Psychology, 87, 974–990. https://doi.org/10.1037/0022-3514.87.6.974 Koole, S. L., Jostmann, N. B., & Baumann, N. (2012). Do demanding conditions help or hurt self-regulation?. Social and Personality Psychology Compass, 6, 328–346. https://doi.org/10.1111/j.1751-9004.2012.00425.x Koole, S. L., Kuhl, J., Jostmann, N. B., & Vohs, K. D. (2005). On the hidden benefits of state orientation: Can people prosper without efficient affect regulation skills?. In A. Tesser, J. Wood, & D. A. Stapel (Eds.), On building, defending, and regulating the self: A psychological perspective (pp. 217–243). London, UK: Taylor & Francis. Abstract Kotabe, H. P., & Hofmann, W. (2015). On integrating the components of self-control. Perspectives on Psychological Science, 10, 618–638. https://doi.org/10.1177/1745691615593382 Kuhl, J. (1994a). A theory of action and state orientations. In J. Kuhl & J. Beckmann (Eds.), Volition and personality: Action versus state orientation (pp. 9–46). Göttingen, Germany: Hogrefe & Huber Publishers. Kuhl, J. (1994b). Action versus state orientation: Psychometric properties of the Action Control Scale (ACS-90). In J. Kuhl & J. Beckmann (Eds.), Volition and personality: Action versus state orientation (pp. 47–59). Göttingen, Germany: Hogrefe & Huber Publishers. Kuhl, J. (2000). A functional-design approach to motivation and self-regulation: The dynamics of personality systems interactions. In M. Boekaerts, P. R. Pintrich, & M. Zeidner (Eds.), Handbook of self-regulation (pp. 111–169). Burlington, MA: Elsevier/Academic Press. https://doi.org/10.1016/B978-012109890-2/50034-2 Laborde, S., Mosley, E., & Mertgen, A. (2018a). A unifying conceptual framework of factors associated to cardiac vagal control. Heliyon, 4, e01002. https://doi.org/10.1016/j.heliyon.2018.e01002 Laborde, S., Mosley, E., & Mertgen, A. (2018b). Vagal tank theory: The three Rs of cardiac vagal control functioning–resting, reactivity, and recovery. Frontiers in Neuroscience, 12. https://doi.org/10.3389/fnins.2018.00458 Quintana, D. S., & Heathers, J. A. J. (2014). Considerations in the assessment of heart rate variability in biobehavioral research. Frontiers in Psychology, 5. https://doi.org/10.3389/fpsyg.2014.00805 Schumann, A., Köhler, S., Brotte, L., & Bär, K.-J. (2019). Effect of an eight-week smartphone-guided HRV-biofeedback intervention on autonomic function and impulsivity in healthy Abstract controls. Physiological Measurement, 40, 064001. https://doi.org/10.1088/1361-6579/ab2065 Segerstrom, S. C., & Nes, L. S. (2007). Heart rate variability reflects self-regulatory strength, effort, and fatigue. Psychological Science, 18, 275–281. https://doi.org/10.1111/j.1467-9280.2007.01888.x Shaffer, F., & Ginsberg, J. P. (2017). An overview of heart rate variability metrics and norms. Frontiers in Public Health, 5. https://doi.org/10.3389/fpubh.2017.00258 Thayer, J. F., Åhs, F., Fredrikson, M., Sollers, J. J., & Wager, T. D. (2012). A meta-analysis of heart rate variability and neuroimaging studies: Implications for heart rate variability as a marker of stress and health. Neuroscience & Biobehavioral Reviews, 36, 747–756. https://doi.org/10.1016/j.neubiorev.2011.11.009 Thayer, J. F., Hansen, A. L., Saus-Rose, E., & Johnsen, B. H. (2009). Heart rate variability, prefrontal neural function, and cognitive performance: The neurovisceral integration perspective on self-regulation, adaptation, and health. Annals of Behavioral Medicine, 37, 141–153. https://doi.org/10.1007/s12160-009-9101-z Thayer, J. F., & Lane, R. D. (2000). A model of neurovisceral integration in emotion regulation and dysregulation. Journal of Affective Disorders, 61, 201–216. https://doi.org/10.1016/s0165-0327(00)00338-4 Thayer, J. F., & Lane, R. D. (2009). Claude Bernard and the heart–brain connection: Further elaboration of a model of neurovisceral integration. Neuroscience & Biobehavioral Reviews, 33, 81–88. https://doi.org/10.1016/j.neubiorev.2008.08.004 Wolff, M., Krönke, K.-M., Venz, J., Kräplin, A., Bühringer, G., Smolka, M. N., & Goschke, T. (2016). Action versus state orientation moderates the impact of executive functioning on real-life self-control. Journal of Experimental Psychology: General, 145, 1635–1653. Abstract https://doi.org/10.1037/xge0000229 Zahn, D., Adams, J., Krohn, J., Wenzel, M., Mann, C. G., Gomille, L. K., Jacobi-Scherbening, V., & Kubiak, T. (2016). Heart rate variability and self-control–a meta-analysis. Biological Psychology, 115, 9–26. https://doi.org/10.1016/j.biopsycho.2015.12.007 KW - Self-Control KW - Self-Regulation Y2 - 2020 U6 - https://nbn-resolving.org/urn:nbn:de:bsz:752-opus4-1252 UN - https://nbn-resolving.org/urn:nbn:de:bsz:752-opus4-1252 SP - 119 S1 - 119 ER -