Personalizing cognitive behavioral therapy for cancer-related fatigue using ecological momentary assessments followed by automated individual time series analyses: A case report series
Introduction: A common approach to personalizing psychological interventions is the allocation of treatment modules to individual patients based on cut-off scores on questionnaires, which are mostly based on group studies. However, this way, intraindividual variation and temporal dynamics are not ta...
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doaj-962dc3744ffe4ee08da35ef08db23a312021-08-02T04:41:04ZengElsevierInternet Interventions2214-78292021-09-0125100430Personalizing cognitive behavioral therapy for cancer-related fatigue using ecological momentary assessments followed by automated individual time series analyses: A case report seriesSusan J. Harnas0Hans Knoop1Sanne H. Booij2Annemarie M.J. Braamse3Amsterdam University Medical Centers, University of Amsterdam, Department of Medical Psychology, Cancer Center Amsterdam, Amsterdam Public Health Research Institute, Amsterdam, the Netherlands; Corresponding author at: Amsterdam University Medical Centers, Department of Medical Psychology, Meibergdreef 9, 1105 AZ Amsterdam, the Netherlands.Amsterdam University Medical Centers, University of Amsterdam, Department of Medical Psychology, Cancer Center Amsterdam, Amsterdam Public Health Research Institute, Amsterdam, the NetherlandsUniversity of Groningen, Faculty of Behavioural and Social Sciences, Department of Developmental Psychology, Groningen, the Netherlands; Center for Integrative Psychiatry, Lentis, Groningen, the NetherlandsAmsterdam University Medical Centers, University of Amsterdam, Department of Medical Psychology, Cancer Center Amsterdam, Amsterdam Public Health Research Institute, Amsterdam, the NetherlandsIntroduction: A common approach to personalizing psychological interventions is the allocation of treatment modules to individual patients based on cut-off scores on questionnaires, which are mostly based on group studies. However, this way, intraindividual variation and temporal dynamics are not taken into account. Automated individual time series analyses are a possible solution, since these can identify the factors influencing the targeted symptom in a specific individual, and associated modules can be allocated accordingly. The aim of this study was to illustrate how automated individual time series analyses can be applied to personalize cognitive behavioral therapy for cancer-related fatigue in cancer survivors and how this procedure differs from allocating modules based on questionnaires. Methods: This study was a case report series (n = 3). Patients completed ecological momentary assessments at the start of therapy, and after three treatment modules (approximately 14 weeks). Assessments were analyzed with AutoVAR, an R package that automates the process of finding optimal vector autoregressive models. The results informed the treatment plan. Results: Three cases were described. From the ecological momentary assessments and automated time series analyses three individual treatment plans were constructed, in which the most important predictor for cancer-related fatigue was treated first. For two patients, this led to the treatment ending after the follow-up ecological momentary assessments. One patient continued treatment until six months, the standard treatment time in regular treatment. All three treatment plans differed from the treatment plans informed by questionnaire scores. Discussion: This study is one of the first to apply time series analyses in systematically personalizing psychological treatment. An important strength of this approach is that it can be used for every modular cognitive behavioral intervention where each treatment module addresses specific maintaining factors. Whether or not personalized CBT is more efficacious than standard, non-personalized CBT remains to be determined in controlled studies comparing it to usual care.http://www.sciencedirect.com/science/article/pii/S2214782921000701Individual time series analysesEcological momentary assessmentsPersonalizationCognitive behavioral therapyCancer-related fatigueCancer survivors |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Susan J. Harnas Hans Knoop Sanne H. Booij Annemarie M.J. Braamse |
spellingShingle |
Susan J. Harnas Hans Knoop Sanne H. Booij Annemarie M.J. Braamse Personalizing cognitive behavioral therapy for cancer-related fatigue using ecological momentary assessments followed by automated individual time series analyses: A case report series Internet Interventions Individual time series analyses Ecological momentary assessments Personalization Cognitive behavioral therapy Cancer-related fatigue Cancer survivors |
author_facet |
Susan J. Harnas Hans Knoop Sanne H. Booij Annemarie M.J. Braamse |
author_sort |
Susan J. Harnas |
title |
Personalizing cognitive behavioral therapy for cancer-related fatigue using ecological momentary assessments followed by automated individual time series analyses: A case report series |
title_short |
Personalizing cognitive behavioral therapy for cancer-related fatigue using ecological momentary assessments followed by automated individual time series analyses: A case report series |
title_full |
Personalizing cognitive behavioral therapy for cancer-related fatigue using ecological momentary assessments followed by automated individual time series analyses: A case report series |
title_fullStr |
Personalizing cognitive behavioral therapy for cancer-related fatigue using ecological momentary assessments followed by automated individual time series analyses: A case report series |
title_full_unstemmed |
Personalizing cognitive behavioral therapy for cancer-related fatigue using ecological momentary assessments followed by automated individual time series analyses: A case report series |
title_sort |
personalizing cognitive behavioral therapy for cancer-related fatigue using ecological momentary assessments followed by automated individual time series analyses: a case report series |
publisher |
Elsevier |
series |
Internet Interventions |
issn |
2214-7829 |
publishDate |
2021-09-01 |
description |
Introduction: A common approach to personalizing psychological interventions is the allocation of treatment modules to individual patients based on cut-off scores on questionnaires, which are mostly based on group studies. However, this way, intraindividual variation and temporal dynamics are not taken into account. Automated individual time series analyses are a possible solution, since these can identify the factors influencing the targeted symptom in a specific individual, and associated modules can be allocated accordingly. The aim of this study was to illustrate how automated individual time series analyses can be applied to personalize cognitive behavioral therapy for cancer-related fatigue in cancer survivors and how this procedure differs from allocating modules based on questionnaires. Methods: This study was a case report series (n = 3). Patients completed ecological momentary assessments at the start of therapy, and after three treatment modules (approximately 14 weeks). Assessments were analyzed with AutoVAR, an R package that automates the process of finding optimal vector autoregressive models. The results informed the treatment plan. Results: Three cases were described. From the ecological momentary assessments and automated time series analyses three individual treatment plans were constructed, in which the most important predictor for cancer-related fatigue was treated first. For two patients, this led to the treatment ending after the follow-up ecological momentary assessments. One patient continued treatment until six months, the standard treatment time in regular treatment. All three treatment plans differed from the treatment plans informed by questionnaire scores. Discussion: This study is one of the first to apply time series analyses in systematically personalizing psychological treatment. An important strength of this approach is that it can be used for every modular cognitive behavioral intervention where each treatment module addresses specific maintaining factors. Whether or not personalized CBT is more efficacious than standard, non-personalized CBT remains to be determined in controlled studies comparing it to usual care. |
topic |
Individual time series analyses Ecological momentary assessments Personalization Cognitive behavioral therapy Cancer-related fatigue Cancer survivors |
url |
http://www.sciencedirect.com/science/article/pii/S2214782921000701 |
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