Feasibility and utility of idiographic models in the clinic: A pilot study

References

• American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders: DSM-5 (5th ed.).
   Google Scholar
• Asparouhov, T., Hamaker, E. L., & Muthén, B. (2018). Dynamic structural equation models. Structural Equation Modeling, 25(3), 359–388. https://doi.org/10.1080/10705511.2017.1406803
   Web of Science ®Google Scholar
• Beck, E. D., & Jackson, J. J. (2020). Consistency and change in idiographic personality: A longitudinal ESM network study. Journal of Personality and Social Psychology, 118(5), 1080–1100. https://doi.org/10.1037/pspp0000249.
   PubMed Web of Science ®Google Scholar
• Beck, A. T., Steer, R. A., & Brown, G. K. (1996). Manual for the beck depression inventory – II. Psychological Corporation.
   Google Scholar
• Beltz, A. M., Wright, A. G. C., Sprague, B. N., & Molenaar, P. C. M. (2016). Bridging the nomothetic and idiographic approaches to the analysis of cinical data. Assessment, 23(4), 447–458. https://doi.org/10.1177/1073191116648209
   PubMed Web of Science ®Google Scholar
• Bos, F. M., Snippe, E., Bruggeman, R., Wichers, M., & van der Krieke, L. (2019). Insights of patients and clinicians on the promise of the experience sampling method for psychiatric care. Psychiatric Services, 70(11), 983–991. https://doi.org/10.1176/appi.ps.201900050
   PubMed Web of Science ®Google Scholar
• Bringmann, L. F., Ferrer, E., Hamaker, E. L., Borsboom, D., & Tuerlinckx, F. (2018). Modeling nonstationary emotion dynamics in dyads using a time-varying vector-autoregressive model. Multivariate Behavioral Research, 53(3), 293–314. https://doi.org/10.1080/00273171.2018.1439722.
   PubMed Web of Science ®Google Scholar
• Bringmann, L. F., Hamaker, E. L., Vigo, D. E., Aubert, A., Borsboom, D., & Tuerlinckx, F. (2017). Changing dynamics: Time-varying autoregressive models using generalized additive modeling. Psychological Methods, 22(3), 409–425. https://doi.org/10.1037/met0000085
   PubMed Web of Science ®Google Scholar
• Brown, T. A., Antony, M. M., & Barlow, D. H. (1992). Psychometric properties of the Penn state worry questionnaire in a clinical anxiety disorders sample. Behavior Research and Therapy, 30(1), 33–37. https://doi.org/10.1016/0005-7967(92)90093-v
   PubMed Web of Science ®Google Scholar
• Chambless, D. L., Caputo, G. C., Bright, P., & Gallagher, R. (1984). Assessment of fear of fear in agoraphobics: The body sensations questionnaire and the agoraphobic cognitions questionnaire. Journal of Consulting and Clinical Psychology, 52(6), 1090–1097. https://doi.org/10.1037/0022-006X.52.6.1090
   PubMed Web of Science ®Google Scholar
• Cox, B. J., Ross, L., Swinson, R. P., & Direnfeld, D. M. (1998). A comparison of social phobia outcome measures in cognitive-behavioral group therapy. Behavior Modification, 22(3), 285–297. https://doi.org/10.1177/01454455980223004
   PubMed Web of Science ®Google Scholar
• Epskamp, S. (2016). Brief report on estimating regularized gaussian networks from continuous and ordinal data. 1606.05771.
   Google Scholar
• Epskamp, S. (2018). GraphicalVAR: Graphical VAR for experience sampling data. https://cran.r-project.org/web/packages/graphicalVAR/graphicalVAR.pdf.
   Google Scholar
• Epskamp, S., Cramer, A. O. J., Waldorp, L. J., Schmittmann, V. D., & Borsboom, D. (2012). Qgraph: Network visualizations of relationships in psychometric data. Journal of Statistical Software, 48(4), 1–18. https://doi.org/10.18637/jss.v048.i04
   Web of Science ®Google Scholar
• Epskamp, S., & Fried, E. I. (2018). A tutorial on regularized partial correlation networks. Psychological Methods, 23(4), 617–634. https://doi.org/10.1037/met0000167
   PubMed Web of Science ®Google Scholar
• Finn, S. E., Fischer, C. T., & Handler, L. (2012). Collaborative/therapeutic assessment: Basic concepts, history, and research. In S. E. Finn, C. T. Fischer, & L. Handler (Eds.), Collaborative/therapeutic assessment: A casebook and guide (pp. 1–24). John Wiley & Sons.
   Google Scholar
• Fisher, A. J., Bosley, H. G., Fernandez, K. C., Reeves, J. W., Soyster, P. D., Diamond, A. E., & Barkin, J. (2019). Open trial of a personalized modular treatment for mood and anxiety. Behaviour Research and Therapy, 116, 69–79. https://doi.org/10.1016/j.brat.2019.01.010
   PubMed Web of Science ®Google Scholar
• Fisher, A. J., Medaglia, J. D., & Jeronimus, B. F. (2018). Lack of group-to-individual generalizability is a threat to human subjects research. Proceedings of the National Academy of Sciences, 115(27), E6106–E6115. https://doi.org/10.1073/pnas.1711978115
   PubMed Web of Science ®Google Scholar
• Fresco, D. M., Coles, M. E., Heimberg, R. G., Liebowitz, M. R., Hami, S., Stein, M. B., & Goetz, D. (2001). The Liebowitz social anxiety scale: A comparison of the psychometric properties of self-report and clinician-administered formats. Psychological Medicine, 31(6), 1025–1035. https://doi.org/10.1017/S0033291701004056
   PubMed Web of Science ®Google Scholar
• Fried, E. I., & Nesse, R. M. (2015). Depression is not a consistent syndrome: An investigation of unique symptom patterns in the STAR*D study. Journal of Affective Disorders, 172, 96–102. https://doi.org/10.1016/j.jad.2014.10.010
   PubMed Web of Science ®Google Scholar
• Fried, E. I., van Borkulo, C. D., Cramer, A. O. J., Boschloo, L., Schoevers, R. A., & Borsboom, D. (2017). Mental disorders as networks of problems: A review of recent insights. Social Psychiatry and Psychiatric Epidemiology, 52(1), 1–10. https://doi.org/10.1007/s00127-016-1319-z
   PubMed Web of Science ®Google Scholar
• Fruchterman, T. M. J., & Reingold, E. M. (1991). Graph drawing by force-directed placement. Software: Practice and Experience, 21(11), 1129–1164. https://doi.org/10.1002/spe.4380211102
   Web of Science ®Google Scholar
• Haslbeck, J., & Ryan, O. (2019). Recovering bistable systems from psychological time series. PsyArXiv. https://doi.org/10.31234/OSF.IO/KCV3S.
   Google Scholar
• Haslbeck, J., & Waldorp, L. (2015). MGM: Estimating time-varying mixed graphical models in high-dimensional data. http://cran.r-project.org/
   Google Scholar
• Hofmann, S. G., Curtiss, J., & McNally, R. J. (2016). A complex network perspective on clinical science. Perspectives on Psychological Science, 11(5), 597–605. https://doi.org/10.1177/1745691616639283
   Web of Science ®Google Scholar
• Howard, K. I., Kopta, S. M., Krause, M. S., & Orlinsky, D. E. (1986). The dose-effect relationship in psychotherapy. American Psychologist, 41(2), 159–164. https://doi.org/10.1037/0003-066X.41.2.159
   PubMed Web of Science ®Google Scholar
• Jacobson, N. C., Chow, S. M., & Newman, M. G. (2019). The differential time-varying effect model (DTVEM): A tool for diagnosing and modeling time lags in intensive longitudinal data. Behavior Research Methods, 51(1), 295–315. https://doi.org/10.3758/s13428-018-1101-0
   PubMed Web of Science ®Google Scholar
• Jobes, D. (2016). Managing suicidal risk: A collaborative approach. Guilford Press.
   Google Scholar
• Kaiser, T., & Laireiter, A. R. (2017). DynAMo: A modular platform for monitoring process, outcome, and algorithm-based treatment planning in psychotherapy. JMIR Medical Informatics, 5(3), e20. https://doi.org/10.2196/medinform.6808
   PubMedGoogle Scholar
• Kessler, R. C., Berglund, P., Demler, O., Jin, R., Merikangas, K. R., & Walters, E. E. (2005). Lifetime prevalence and age-of-onset distributions of DSM-IV disorders in the national comorbidity survey replication. Archives of General Psychiatry, 62(6), 593–602. https://doi.org/10.1001/archpsyc.62.6.593
   PubMed Web of Science ®Google Scholar
• Levine, F., Sandeen, E., & Murphy, C. (1992). The therapist’s dilemma: Using nomothetic information to answer idiographic questions. Psychotherapy: Theory, Research, Practice, Training, 29(3), 410–415. https://doi.org/10.1037/h0088544
   Web of Science ®Google Scholar
• Meyer, T. J., Miller, M. L., Metzger, R. L., & Borkovec, T. D. (1990). Development and validation of the Penn state worry questionnaire. Behavior Research and Therapy, 28(6), 487–495. https://doi.org/10.1016/0005-7967(90)90135-6
   PubMed Web of Science ®Google Scholar
• Molenaar, P. C. M. (2004). A manifesto on psychology as idiographic science: Bringing the person back into scientific psychology, this time forever. Measurement: Interdisciplinary Research & Perspective, 2(4), 201–218. https://doi.org/10.1207/s15366359mea0204_1
   Google Scholar
• Pe, M. L., Kircanski, K., Thompson, R. J., Bringmann, L. F., Tuerlinckx, F., Mestdagh, M., Mata, J., Jaeggi, S. M., Buschkuehl, M., Jonides, J., Kuppens, P., & Gotlib, I. H. (2015). Emotion-network density in major depressive disorder. Clinical Psychological Science, 3(2), 292–300. https://doi.org/10.1177/2167702614540645
   PubMed Web of Science ®Google Scholar
• Persons, J. B. (2006). Case formulation-driven psychotherapy. Clinical Psychology: Science and Practice, 13(2), 167–170. https://doi.org/10.1111/j.1468-2850.2006.00019.x
   Web of Science ®Google Scholar
• Piccirillo, M. L., Beck, E. D., & Rodebaugh, T. L. (2019). A clinician’s primer for idiographic research: Considerations and recommendations. Behavior Therapy, 50(5), 938–951. https://doi.org/10.1016/j.beth.2019.02.002
   PubMed Web of Science ®Google Scholar
• Piccirillo, M. L., & Rodebaugh, T. L. (2019). Foundations of idiographic methods in psychology and applications for psychotherapy. Clinical Psychology Review, 71, 90–100. https://doi.org/10.1016/J.CPR.2019.01.002.
   PubMed Web of Science ®Google Scholar
• Rytwinski, N. K., Fresco, D. M., Heimberg, R. G., Coles, M. E., Liebowitz, M. R., Cissell, S., Stein, M. B., & Hofmann, S. G. (2009). Screening for social anxiety disorder with the self-report version of the Liebowitz social anxiety scale. Depression and Anxiety, 26(1), 34–38. https://doi.org/10.1002/da.20503
   PubMed Web of Science ®Google Scholar
• Schiepek, G. K., Stöger-Schmidinger, B., Aichhorn, W., Schöller, H., & Aas, B. (2016). Systemic case formulation, individualized process monitoring, and state dynamics in a case of dissociative identity disorder. Frontiers in Psychology, 7, 1545. https://doi.org/10.3389/fpsyg.2016.01545.
   PubMed Web of Science ®Google Scholar
• van der Krieke, L., Emerencia, A. C., Bos, E. H., Rosmalen, J. G., Riese, H., Aiello, M., Sytema, S., & de Jonge, P. (2015). Ecological momentary assessments and automated time series analysis to promote tailored health care: A proof-of-principle study. JMIR Research Protocols, 4(3), e100. https://doi.org/10.2196/resprot.4000
   PubMed Web of Science ®Google Scholar
• Wild, B., Eichler, M., Friederich, H.-C., Hartmann, M., Zipfel, S., & Herzog, W. (2010). A graphical vector autoregressive modelling approach to the analysis of electronic diary data. BMC Medical Research Methodology, 10(1), 28. https://doi.org/10.1186/1471-2288-10-28
   PubMed Web of Science ®Google Scholar
• Wright, A. G. C., & Woods, W. C. (2020). Personalized models of psychopathology. Annual Review of Clinical Psychology, 16(1), 49–74. https://doi.org/10.1146/annurev-clinpsy-102419-125032
   PubMedGoogle Scholar
• Zimmermann, J., Woods, W. C., Ritter, S., Happel, M., Masuhr, O., Jaeger, U., Spitzer, C., & Wright, A. G. C. (2019). Integrating structure and dynamics in personality assessment: First steps toward the development and validation of a personality dynamics diary. Psychological Assessment, 31(4), 516–531. https://doi.org/10.1037/pas0000625
   PubMed Web of Science ®Google Scholar