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Research on Child and Adolescent Psychopathology

Gepubliceerd in:

25-01-2020

Modeling Treatment-Related Decision-Making Using Applied Behavioral Economics: Caregiver Perspectives in Temporally-Extended Behavioral Treatments

Auteurs: Shawn P. Gilroy, Brent A. Kaplan

Gepubliceerd in: Research on Child and Adolescent Psychopathology | Uitgave 5/2020

Abstract

Evidence-based behavioral therapies for children with disruptive and challenging behavior rarely yield immediate improvements in behavior. For caregivers participating in behavioral therapies, the benefits from these efforts are seldom visible until after substantial time commitments. Delays associated with relief from challenging behavior (i.e., improved behavior) can influence how caregivers decide to respond to instances of problem behavior, and in turn, their continued commitment (i.e., integrity, adherence) to treatments that require long-term implementation to produce improvements in child behavior. This study applied delay discounting methods to evaluate how delays affected caregiver preferences related to options for managing their child’s behavior. Specifically, methods were designed to evaluate the degree to which caregiver preferences for a more efficacious, recommended approach was affected by delays (i.e., numbers of weeks in treatment). That is, methods evaluated at which point caregivers opted to disregard the optimal, delayed strategy and instead elected to pursue suboptimal, immediate strategies. Results indicated that caregivers regularly discounted the value of the more efficacious treatment, electing to pursue suboptimal approaches when delays associated with the optimal approach grew larger. Caregivers demonstrated similar patterns of suboptimal choice across both clinical (i.e., intervention) and non-clinical (i.e., monetary) types of decisions. These findings are consistent with research that has highlighted temporal preferences as an individual factor that may be relevant to caregiver adherence to long-term evidence-based treatments and encourage the incorporation of behavioral economic methods to better understand caregiver decision-making.

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We make note that behavioral economics draws from various areas of behavioral science, e.g. neuroscience, cognitive science, behavior analysis. While we discuss behavioral economics broadly here, the methodology used here most directly relates to operant behavioral economics and the experimental delay discounting framework.

All elements of this study (e.g., data) and materials necessary to recreate these findings (e.g., statistical scripts, figure rendering) are included as supplemental materials as well as archived on the corresponding author’s GitHub account under the repository “Caregiver-Delay-Discounting” at https://github.com/miyamot0/Caregiver-Delay-Discounting.

We note here that HITs were published to the MTurk framework until the recommended number of caregivers meeting all criteria for use in the statistical analysis was reached (n = 61).

The demographics, data, and results for both the screened and total example are available as supplemental materials.

Ainslie, G. W. (1974). Impulse control in pigeons. Journal of the Experimental Analysis of Behavior, 21(3), 485–489. https://doi.org/10.1901/jeab.1974.21-485.CrossRefPubMedPubMedCentral

Ainslie, G. W. (1975). Specious reward: A behavioral theory of impulsiveness and impulse control. Psychological Bulletin, 82(4), 463–496. https://doi.org/10.1037/h0076860.CrossRefPubMed

Ainslie, G. W. (1992). Picoeconomics: The strategic interaction of successive motivational states within the person: Cambridge University Press.

Akaike, H. (1974). A new look at the statistical model identification. IEEE Transactions on Automatic Control, 19(6), 716–723. https://doi.org/10.1109/tac.1974.1100705.CrossRef

Armbruster, P., & Kazdin, A. E. (1994). Attrition in child-psychotherapy. Advances in Clinical Child Psychology, 16(16), 81–108. https://doi.org/10.1007/978-1-4757-9041-2_3.CrossRef

Bennett, D. S., Power, T. J., Rostain, A. L., & Carr, D. E. (1996). Parent acceptability and feasibility of ADHD interventions: Assessment, correlates, and predictive validity. Journal of Pediatric Psychology, 21(5), 643–657. https://doi.org/10.1093/jpepsy/21.5.643.CrossRefPubMed

Borges, A. M., Kuang, J., Milhorn, H., & Yi, R. (2016). An alternative approach to calculating area-under-the-curve (AUC) in delay discounting research. Journal of the Experimental Analysis of Behavior, 106(2), 145–155. https://doi.org/10.1002/jeab.219.CrossRefPubMed

Bromberg, U., Lobatcheva, M., & Peters, J. (2017). Episodic future thinking reduces temporal discounting in healthy adolescents. PLoS One, 12(11), e0188079. https://doi.org/10.1371/journal.pone.0188079.CrossRefPubMedPubMedCentral

Call, N. A., Delfs, C. H., Reavis, A. R., & Mevers, J. L. (2015a). Factors influencing treatment decisions by parents for their children with autism spectrum disorder. Research in Autism Spectrum Disorders, 15-16, 10–20. https://doi.org/10.1016/j.rasd.2015.04.001.CrossRef

Call, N. A., Reavis, A. R., McCracken, C. E., Gillespie, S. E., & Scheithauer, M. C. (2015b). The impact of delays on parents' perceptions of treatments for problem behavior. Journal of Autism and Developmental Disorders, 45(4), 1013–1025. https://doi.org/10.1007/s10803-014-2257-9.CrossRefPubMed

Camerer, C. F., & Loewenstein, G. (2004). Behavioral economics: Past, present, future. In In Advances in Behavioral Economics. Princeton: Princeton University Press.CrossRef

Carr, T., Shih, W., Lawton, K., Lord, C., King, B., & Kasari, C. (2016). The relationship between treatment attendance, adherence, and outcome in a caregiver-mediated intervention for low-resourced families of young children with autism spectrum disorder. Autism, 20(6), 643–652. https://doi.org/10.1177/1362361315598634.CrossRefPubMed

Chacko, A., Wymbs, B. T., Chimiklis, A., Wymbs, F. A., & Pelham, W. E. (2012). Evaluating a comprehensive strategy to improve engagement to group-based behavioral parent training for high-risk families of children with ADHD. Journal of Abnormal Child Psychology, 40(8), 1351–1362. https://doi.org/10.1007/s10802-012-9666-z.CrossRefPubMed

Chacko, A., Jensen, S. A., Lowry, L. S., Cornwell, M., Chimklis, A., Chan, E., Lee, D., & Pulgarin, B. (2016a). Engagement in behavioral parent training: Review of the literature and implications for practice. Clinical Child and Family Psychology Review, 19(3), 204–215. https://doi.org/10.1007/s10567-016-0205-2.CrossRefPubMed

Chacko, A., Wymbs, B. T., Rajwan, E., Wymbs, F., & Feirsen, N. (2016b). Characteristics of parents of children with ADHD who never attend, drop out, and complete behavioral parent training. Journal of Child and Family Studies, 26(3), 950–960. https://doi.org/10.1007/s10826-016-0618-z.CrossRef

Chandler, J., & Shapiro, D. (2016). Conducting clinical research using Crowdsourced convenience samples. Annual Review of Clinical Psychology, 12(1), 53–81. https://doi.org/10.1146/annurev-clinpsy-021815-093623.CrossRefPubMed

Chapman, G. B. (1996). Temporal discounting and utility for health and money. Journal of Experimental Psychology: Learning, Memory, and Cognition, 22(3), 771–791. https://doi.org/10.1037/0278-7393.22.3.771.CrossRefPubMed

Chapman, G. B. (2002). Your money or your health: Time preferences and trading money for health. Medical Decision Making, 22(5), 410–416. https://doi.org/10.1177/027298902236929.CrossRefPubMed

Chapman, G. B., & Coups, E. J. (1999). Time preferences and preventive health behavior: Acceptance of the influenza vaccine. Medical Decision Making, 19(3), 307–314. https://doi.org/10.1177/0272989X9901900309.CrossRefPubMed

Chapman, G. B., Li, M., Colby, H., & Yoon, H. (2010). Opting in vs opting out of influenza vaccination. JAMA, 304(1), 43–44. https://doi.org/10.1001/jama.2010.892.CrossRefPubMed

Christophersen, E. R., & Mortweet, S. L. (2013). Treatments that work with children: Empirically supported strategies for managing childhood problems (2nd ed.). Washington, DC: American Psychological Association.

Chung, S. H., & Herrnstein, R. J. (1967). Choice and delay of reinforcement. Journal of the Experimental Analysis of Behavior, 10(1), 67–74. https://doi.org/10.1901/jeab.1967.10-67.CrossRefPubMedPubMedCentral

Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Hillsdale: Erlbaum.

Cunningham, C. E., Chen, Y., Deal, K., Rimas, H., McGrath, P., Reid, G., Lipman, E., & Corkum, P. (2013). The interim service preferences of parents waiting for children's mental health treatment: A discrete choice conjoint experiment. Journal of Abnormal Child Psychology, 41(6), 865–877. https://doi.org/10.1007/s10802-013-9728-x.CrossRefPubMed

Cunningham, C. E., Rimas, H., Chen, Y., Deal, K., McGrath, P., Lingley-Pottie, P., Reid, G. J., Lipman, E., & Corkum, P. (2015). Modeling parenting programs as an interim Service for Families Waiting for Children's mental health treatment. Journal of Clinical Child and Adolescent Psychology, 44(4), 616–629. https://doi.org/10.1080/15374416.2014.888666.CrossRefPubMed

Dadds, M. R., Sicouri, G., Piotrowska, P. J., Collins, D. A. J., Hawes, D. J., Moul, C., ... Tully, L. A. (2018). Keeping parents involved: Predicting attrition in a self-directed, Online Program for Childhood Conduct Problems. Journal of Clinical Child & Adolescent Psychology, 1–13. https://doi.org/10.1080/15374416.2018.1485109.

Dallery, J., & Raiff, B. R. (2007). Delay discounting predicts cigarette smoking in a laboratory model of abstinence reinforcement. Psychopharmacology, 190(4), 485–496. https://doi.org/10.1007/s00213-006-0627-5.CrossRefPubMed

Daniel, T. O., Stanton, C. M., & Epstein, L. H. (2013). The future is now: Comparing the effect of episodic future thinking on impulsivity in lean and obese individuals. Appetite, 71, 120–125. https://doi.org/10.1016/j.appet.2013.07.010.CrossRefPubMedPubMedCentral

DebRoy, S., Bates, D., & Pinheiro, J. (1999). R Core team (2015) nls: Nonlinear least squares.

DeHart, W. B., & Odum, A. L. (2015). The effects of the framing of time on delay discounting. Journal of the Experimental Analysis of Behavior, 103(1), 10–21. https://doi.org/10.1002/jeab.125.CrossRefPubMed

dosReis, S., Park, A., Ng, X., Frosch, E., Reeves, G., Cunningham, C., Janssen, E. M., & Bridges, J. F. P. (2017). Caregiver treatment preferences for children with a new versus existing attention-deficit/hyperactivity disorder diagnosis. Journal of Child and Adolescent Psychopharmacology, 27(3), 234–242. https://doi.org/10.1089/cap.2016.0157.CrossRefPubMedPubMedCentral

Doyle, J. R. (2013). Survey of time preference, delay discounting models. Judgment and Decision making, 8(2), 116–135. https://doi.org/10.2139/ssrn.1685861.CrossRef

Dreyer, A. S., O'Laughlin, L., Moore, J., & Milam, Z. (2010). Parental adherence to clinical recommendations in an ADHD evaluation clinic. Journal of Clinical Psychology, 66(10), 1101–1120. https://doi.org/10.1002/jclp.20718.CrossRefPubMed

Du, W., Green, L., & Myerson, J. (2002). Cross-cultural comparisons of discounting delayed and probabilistic rewards. The Psychological Record, 52(4), 479–492.CrossRef

Ebert, J. E. J., & Prelec, D. (2007). The fragility of time: Time-insensitivity and valuation of the near and far future. Management Science, 53(9), 1423–1438. https://doi.org/10.1287/mnsc.1060.0671.CrossRef

Faul, F., Erdfelder, E., Lang, A.-G., & Buchner, A. (2007). G*Power 3: A flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behavior Research Methods, 39(2), 175–191. https://doi.org/10.3758/bf03193146.CrossRef

Fishburn, P. C., & Rubinstein, A. (1982). Time preference. International Economic Review, 677-694.

Franck, C. T., Koffarnus, M. N., House, L. L., & Bickel, W. K. (2015). Accurate characterization of delay discounting: A multiple model approach using approximate Bayesian model selection and a unified discounting measure. Journal of the Experimental Analysis of Behavior, 103(1), 218–233. https://doi.org/10.1002/jeab.128.CrossRefPubMed

Frye, C. C., Galizio, A., Friedel, J. E., DeHart, W. B., & Odum, A. L. (2016). Measuring delay discounting in humans using an adjusting amount task. Journal of Visualized Experiments, 107. https://doi.org/10.3791/53584.

Gaudiano, B. A., Weinstock, L. M., & Miller, I. W. (2008). Improving treatment adherence in bipolar disorder: A review of current psychosocial treatment efficacy and recommendations for future treatment development. Behavior Modification, 32(3), 267–301. https://doi.org/10.1177/0145445507309023.CrossRefPubMedPubMedCentral

Gearing, R. E., Schwalbe, C. S., Dweck, P., & Berkowitz, J. (2012). Investigating adherence promoters in evidence-based mental health interventions with children and adolescents. Community Mental Health Journal, 48(1), 63–70. https://doi.org/10.1007/s10597-011-9394-9.CrossRefPubMed

Gilroy, S. P., & Hantula, D. A. (2018). Discounting model selection with area-based measures: A case for numerical integration. Journal of the Experimental Analysis of Behavior, 109(2), 433–449. https://doi.org/10.1002/jeab.318.CrossRefPubMed

Gilroy, S. P., Kaplan, B. A., & Leader, G. (2018). A systematic review of applied behavioral economics in assessments and treatments for individuals with developmental disabilities. Review Journal of Autism and Developmental Disorders, 5(3), 247–259. https://doi.org/10.1007/s40489-018-0136-6.CrossRef

Goin-Kochel, R. P., Myers, B. J., & Mackintosh, V. H. (2007). Parental reports on the use of treatments and therapies for children with autism spectrum disorders. Research in Autism Spectrum Disorders, 1(3), 195–209. https://doi.org/10.1016/j.rasd.2006.08.006.CrossRef

Green, L., & Myerson, J. (2004). A discounting framework for choice with delayed and probabilistic rewards. Psychological Bulletin, 130(5), 769–792. https://doi.org/10.1037/0033-2909.130.5.769.CrossRefPubMedPubMedCentral

Henley, A. J., DiGennaro Reed, F. D., Reed, D. D., & Kaplan, B. A. (2016). A crowdsourced nickel-and-dime approach to analog OBM research: A behavioral economic framework for understanding workforce attrition. Journal of the Experimental Analysis of Behavior, 106(2), 134–144. https://doi.org/10.1002/jeab.220.CrossRefPubMed

Hogue, A., Henderson, C. E., Dauber, S., Barajas, P. C., Fried, A., & Liddle, H. A. (2008). Treatment adherence, competence, and outcome in individual and family therapy for adolescent behavior problems. Journal of Consulting and Clinical Psychology, 76(4), 544–555. https://doi.org/10.1037/0022-006X.76.4.544.CrossRefPubMedPubMedCentral

Jit, M., & Mibei, W. (2015). Discounting in the evaluation of the cost-effectiveness of a vaccination programme: A critical review. Vaccine, 33(32), 3788–3794. https://doi.org/10.1016/j.vaccine.2015.06.084.CrossRefPubMed

Johnson, M. W., & Bickel, W. K. (2002). Within-subject comparison of real and hypothetical money rewards in delay discounting. Journal of the Experimental Analysis of Behavior, 77(2), 129–146. https://doi.org/10.1901/jeab.2002.77-129.CrossRefPubMedPubMedCentral

Johnson, M. W., & Bickel, W. K. (2008). An algorithm for identifying nonsystematic delay-discounting data. Experimental and Clinical Psychopharmacology, 16(3), 264–274. https://doi.org/10.1037/1064-1297.16.3.264.CrossRefPubMedPubMedCentral

Kazdin, A. E., & Mazurick, J. L. (1994). Dropping out of child psychotherapy: Distinguishing early and late dropouts over the course of treatment. Journal of Consulting and Clinical Psychology, 62(5), 1069–1074. https://doi.org/10.1037/0022-006X.62.5.1069.CrossRefPubMed

Kazdin, A. E., & Wassell, G. (1999). Barriers to treatment participation and therapeutic change among children referred for conduct disorder. Journal of Clinical Child Psychology, 28(2), 160–172. https://doi.org/10.1207/s15374424jccp2802_4.CrossRefPubMed

Kendall, P. C., & Sugarman, A. (1997). Attrition in the treatment of childhood anxiety disorders. Journal of Consulting and Clinical Psychology, 65(5).

Krishnan-Sarin, S., Reynolds, B., Duhig, A. M., Smith, A., Liss, T., McFetridge, A., ... Potenza, M. N. (2007). Behavioral impulsivity predicts treatment outcome in a smoking cessation program for adolescent smokers. Drug and Alcohol Dependence, 88(1), 79–82. doi:https://doi.org/10.1016/j.drugalcdep.2006.09.006.

Lavigne, J. V., Lebailly, S. A., Gouze, K. R., Binns, H. J., Keller, J., & Pate, L. (2010). Predictors and correlates of completing behavioral parent training for the treatment of oppositional defiant disorder in pediatric primary care. Behavior Therapy, 41(2), 198–211. https://doi.org/10.1016/j.beth.2009.02.006.CrossRefPubMed

Lebeau, G., Consoli, S. M., Le Bouc, R., Sola-Gazagnes, A., Hartemann, A., Simon, D., ... Lemogne, C. (2016). Delay discounting of gains and losses, glycemic control and therapeutic adherence in type 2 diabetes. Behavioural Processes, 132, 42–48. doi:https://doi.org/10.1016/j.beproc.2016.09.006.

Ludwig, V. U., Nusser, C., Goschke, T., Wittfoth-Schardt, D., Wiers, C. E., Erk, S., ... Walter, H. (2015). Delay discounting without decision-making: Medial prefrontal cortex and amygdala activations reflect immediacy processing and correlate with impulsivity and anxious-depressive traits. Frontiers in Behavioral Neuroscience, 9, 280. https://doi.org/10.3389/fnbeh.2015.00280.

MacNaughton, K. L., & Rodrigue, J. R. (2001). Predicting adherence to recommendations by parents of clinic-referred children. Journal of Consulting and Clinical Psychology, 69(2), 262.CrossRef

Madden, G. J., Begotka, A. M., Raiff, B. R., & Kastern, L. L. (2003). Delay discounting of real and hypothetical rewards. Experimental and Clinical Psychopharmacology, 11(2), 139–145 Retrieved from https://www.ncbi.nlm.nih.gov/pubmed/12755458.CrossRef

Mazur, J. E. (1987). An adjusting procedure for studying delayed reinforcement. In Quantitative analysis of behavior: Vol. 5. The effect of delay and intervening events on reinforcement value (pp. 55-73). Hillsdale, NJ: Erlbaum.

Miller, L. M., Southam-Gerow, M. A., & Allin, R. B. (2008). Who stays in treatment? Child and family predictors of youth client retention in a public mental health agency. Child & Youth Care Forum, 37(4), 153–170. https://doi.org/10.1007/s10566-008-9058-2.CrossRef

Miller, V. A., Schreck, K. A., Mulick, J. A., & Butter, E. (2012). Factors related to parents’ choices of treatments for their children with autism spectrum disorders. Research in Autism Spectrum Disorders, 6(1), 87–95. https://doi.org/10.1016/j.rasd.2011.03.008.CrossRef

Moore, T. R., & Symons, F. J. (2009). Adherence to behavioral and medical treatment recommendations by parents of children with autism spectrum disorders. Journal of Autism and Developmental Disorders, 39(8), 1173–1184. https://doi.org/10.1007/s10803-009-0729-0.CrossRefPubMed

Morrison, K. L., Madden, G. J., Odum, A. L., Friedel, J. E., & Twohig, M. P. (2014). Altering impulsive decision making with an acceptance-based procedure. Behavior Therapy, 45(5), 630–639. https://doi.org/10.1016/j.beth.2014.01.001.CrossRefPubMedPubMedCentral

Myerson, J., Green, L., & Warusawitharana, M. (2001). Area under the curve as a measure of discounting. Journal of the Experimental Analysis of Behavior, 76(2), 235–243. https://doi.org/10.1901/jeab.2001.76-235.CrossRefPubMedPubMedCentral

Nock, M. K., & Ferriter, C. (2005). Parent Management of Attendance and Adherence in child and adolescent therapy: A conceptual and empirical review. Clinical Child and Family Psychology Review, 8(2), 149–166. https://doi.org/10.1007/s10567-005-4753-0.CrossRefPubMed

Odum, A. L. (2011). Delay discounting: Trait variable? Behavioural Processes, 87(1), 1–9. https://doi.org/10.1016/j.beproc.2011.02.007.CrossRefPubMedPubMedCentral

Paolacci, G., & Chandler, J. (2014). Inside the Turk. Current Directions in Psychological Science, 23(3), 184–188. https://doi.org/10.1177/0963721414531598.CrossRef

Peters, J., & Buchel, C. (2010). Episodic future thinking reduces reward delay discounting through an enhancement of prefrontal-mediotemporal interactions. Neuron, 66(1), 138–148. https://doi.org/10.1016/j.neuron.2010.03.026.CrossRefPubMed

Piessens, R., Doncker-Kapenga, E., Überhuber, C. W., & Kahaner, D. K. (1983). Quadpack: A subroutine package for automatic integration: Springer-Verlag.

Pinheiro, J., Bates, D., DebRoy, S., & Sarkar, D. (2014). R Core team (2014) nlme: Linear and nonlinear mixed effects models. R package version 3.1–117. Available at http://CRAN.R-project.org/package=nlme.

R Core Team. (2017). R: A language and environment for statistical computing (Version 3.4.1): R Foundation for Statistical Computing.

Rachlin, H. (2006). Notes on discounting. Journal of the Experimental Analysis of Behavior, 85(3), 425–435. https://doi.org/10.1901/jeab.2006.85-05.CrossRefPubMedPubMedCentral

Roma, P. G., Hursh, S. R., & Hudja, S. (2016). Hypothetical purchase task questionnaires for behavioral economic assessments of value and motivation. Managerial and Decision Economics, 37(4–5), 306–323. https://doi.org/10.1002/mde.2718.CrossRef

Sanetti, L. M. H., & Kratochwill, T. R. (2009). Toward developing a science of treatment integrity: Introduction to the special series. School Psychology Review, 38(4).

Santana, L., & Fontenelle, L. F. (2011). A review of studies concerning treatment adherence of patients with anxiety disorders. Patient Preference and Adherence, 5, 427–439. https://doi.org/10.2147/PPA.S23439.CrossRefPubMedPubMedCentral

Schoenwald, S. K., Letourneau, E. J., & Halliday-Boykins, C. (2005). Predicting therapist adherence to a transported family-based treatment for youth. Journal of Clinical Child and Adolescent Psychology, 34(4), 658–670. https://doi.org/10.1207/s15374424jccp3404_8.CrossRefPubMed

Schoenwald, S. K., Garland, A. F., Southam-Gerow, M. A., Chorpita, B. F., & Chapman, J. E. (2011). Adherence measurement in treatments for disruptive behavior disorders: Pursuing clear vision through varied lenses. Clinical Psychology (New York), 18(4), 331–341. https://doi.org/10.1111/j.1468-2850.2011.01264.x.CrossRef

Snider, S. E., LaConte, S. M., & Bickel, W. K. (2016). Episodic future thinking: Expansion of the temporal window in individuals with alcohol dependence. Alcoholism: Clinical and Experimental Research, 40(7), 1558–1566. https://doi.org/10.1111/acer.13112.CrossRef

Springer, C., & Reddy, L. A. (2010). Measuring parental treatment adherence in a multimodal treatment program for children with ADHD: A preliminary investigation. Child and Family Behavior Therapy, 32(4), 272–290. https://doi.org/10.1080/07317107.2010.515522.CrossRef

Stoianova, M., Tampke, E. C., Lansing, A. H., & Stanger, C. (2018). Delay discounting associated with challenges to treatment adherence and glycemic control in young adults with type 1 diabetes. Behavioural Processes, 157, 474–477. https://doi.org/10.1016/j.beproc.2018.06.013.CrossRefPubMedPubMedCentral

Strickland, J. C., & Stoops, W. W. (2019). The use of crowdsourcing in addiction science research: Amazon mechanical Turk. Experimental and Clinical Psychopharmacology, 27(1), 1.CrossRef

Swift, J. K., & Callahan, J. L. (2008). A delay discounting measure of great expectations and the effectiveness of psychotherapy. Professional Psychology: Research and Practice, 39(6), 581–588. https://doi.org/10.1037/0735-7028.39.6.581.CrossRef

Swift, J. K., & Callahan, J. L. (2010). A delay discounting model of psychotherapy termination. International Journal of Behavioral Consultation and Therapy, 5(3–4), 278–293. https://doi.org/10.1037/h0100889.CrossRef

Thompson, L., & McCabe, R. (2012). The effect of clinician-patient alliance and communication on treatment adherence in mental health care: A systematic review. BMC Psychiatry, 12, 87. https://doi.org/10.1186/1471-244X-12-87.CrossRefPubMedPubMedCentral

Watson, T. S., & Gresham, F. M. (2013). Handbook of child behavior therapy: Springer Science & Business Media.

Weisz, J. R., Weiss, B., & Langmeyer, D. B. (1987). Giving Up on Child Psychotherapy: Who Drops Out? Journal of Consulting and Clinical Psychology, 55(6), 916–918 Retrieved from https://www.ncbi.nlm.nih.gov/pubmed/3693659.CrossRef

Yoon, J. H., & Higgins, S. T. (2008). Turning k on its head: Comments on use of an ED50 in delay discounting research. Drug and Alcohol Dependence, 95(1–2), 169–172. https://doi.org/10.1016/j.drugalcdep.2007.12.011.CrossRefPubMedPubMedCentral

Yoon, J. H., Higgins, S. T., Heil, S. H., Sugarbaker, R. J., Thomas, C. S., & Badger, G. J. (2007). Delay discounting predicts postpartum relapse to cigarette smoking among pregnant women. Experimental and Clinical Psychopharmacology, 15(2), 176–186. https://doi.org/10.1037/1064-1297.15.2.186.CrossRefPubMed

Young, M. E. (2017). Discounting: A practical guide to multilevel analysis of indifference data. Journal of the Experimental Analysis of Behavior, 108(1), 97–112. https://doi.org/10.1002/jeab.265.CrossRefPubMed

Titel: Modeling Treatment-Related Decision-Making Using Applied Behavioral Economics: Caregiver Perspectives in Temporally-Extended Behavioral Treatments
Auteurs: Shawn P. Gilroy
Brent A. Kaplan
Publicatiedatum: 25-01-2020
Uitgeverij: Springer US
Gepubliceerd in: Research on Child and Adolescent Psychopathology / Uitgave 5/2020
Print ISSN: 2730-7166
Elektronisch ISSN: 2730-7174
DOI: https://doi.org/10.1007/s10802-020-00619-6

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