Using smartphone-based ecological momentary assessment and personalized feedback for patients with chronic cancer-related fatigue: A proof-of-concept study

Bootsma, Tom I.; Schellekens, Melanie P. J.; Woezik, Rosalie van; Slatman, Jenny; Lee, Marije van der

doi:10.1016/j.invent.2022.100568

Cited by 6 publications

(8 citation statements)

References 31 publications

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“…These individual networks have been used as part of psycho-education for fatigued cancer patients, with positive responses from patients. 37 These applications would be of great interest in glioma patients to improve our understanding of causal mechanisms behind the emergence of symptoms, and to guide psycho-education and symptom management in individual patients.…”

Section: Discussionmentioning

confidence: 99%

Symptom networks in glioma patients: understanding the multidimensionality of symptoms and quality of life

Röttgering¹,

Varkevisser²,

Gorter³

et al. 2022

Preprint

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Objectives: To comprehend the complex relationship between symptoms such as fatigue and depression, and health-related quality of life (HRQoL) in patients with diffuse glioma, we estimated symptom networks to identify patterns of associations amongst a set of patient-reported outcome measures (PROMs). Additionally, we aimed to compare symptom networks of subgroups based on disease characteristics and fatigue status.Methods: We analyzed PROMs on fatigue, depression, cognitive functioning, brain tumor-related symptoms, and HRQoL from 256 patients. We stratified the sample based on disease status (preoperative vs. postoperative), tumor grade (grade II vs. III/IV), and fatigue status (non-fatigued vs. fatigued). We constructed group-level symptom networks with 21 nodes, wherein a node represented a subscale or item of a questionnaire, and an edge between two nodes signified a partial correlation between the two. We statistically compared global strength (GS, i.e., how strongly all nodes in a network are connected) between networks.Results: Across the networks, fatigue severity, depression, and social functioning were the most connected nodes. We found no differences in GS between the networks based on disease characteristics. However, GS was lower in the non-fatigued network compared to the fatigued network (GS=5.51 vs. GS=7.49, p<0.001).Conclusions: Symptom network analysis is a novel approach to understand and quantify the interrelatedness of symptoms in glioma. Interestingly, global network strength did not differ between networks based on disease-specific characteristics, but PROMs were more tightly intercorrelated in fatigued patients compared to non-fatigued patients. This underlines the need for integrative symptom management targeting fatigue.

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Section: Discussionmentioning

confidence: 99%

Symptom networks in glioma patients: understanding the multidimensionality of symptoms and quality of life

Röttgering¹,

Varkevisser²,

Gorter³

et al. 2022

Preprint

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“…The Energy Insight app includes items on fatigue symptoms, positive and negative affect, social context, physical activity, and coping strategies of fatigue. After a proof‐of‐concept study, in which the suitability and usability of the EMA items, app and procedure were extensively assessed, these items were further finetuned, resulting in the present set of 20 items 24 …”

Section: Methodsmentioning

confidence: 99%

“…The primary study aim of REFINE 2.0 was to examine the feasibility and effectiveness of implementing person-specific fatigue networks in the routine clinical practice of a mental health institute to help personalize treatment for CRF. 24 Ethical approval was obtained from the Ethical Review Board of Tilburg University (TSB_RP461). For the present study, we combined the EMA data of the participants to estimate dynamic group-level networks.…”

Section: Designmentioning

confidence: 99%

“…During the 21-day EMA period, participants filled out the experience sampling app EnergyInSight five times a day, with each questionnaire taking approximately two minutes to fill out. 24 The questionnaires were sent at five quasi-random time intervals within three-hour time windows. To prevent dropout, notification timing was personalised to each participant's sleep-wake schedule.…”

Section: Ecological Momentary Assessmentmentioning

confidence: 99%

“…After a proof-of-concept study, in which the suitability and usability of the EMA items, app and procedure were extensively assessed, these items were further finetuned, resulting in the present set of 20 items. 24 To be included in the present analyses, participants needed to fill out a minimum of 75 EMA questionnaires, as a recent simulation study showed that with 75-100 assessments per person the network can include approximately 6 nodes for it to be reliable. 27 When participants missed too many EMA questionnaires, the assessment period was extended with the number of days necessary for reaching 75 observations.…”

Section: Ecological Momentary Assessmentmentioning

confidence: 99%

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Exploring the dynamic interconnectedness of protective and perpetuating factors of cancer‐related fatigue

van Roozendaal,

Schellekens,

van Woezik

et al. 2023

Psycho-Oncology

Self Cite

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ObjectiveApproximately 25% of cancer patients suffer from cancer‐related fatigue (CRF) after cancer treatment. CRF is a multi‐factorial condition affected by several interrelated protective and perpetuating factors. As most studies merely assessed bivariate associations, more insight into the complex relationships among these constructs is needed. We applied the multivariate network approach to gain a better understanding of how patients' fatigue, perpetuating and protective factors are dynamically interconnected.MethodBetween February and August 2022, 30 cancer patients filled out a carefully developed ecological momentary assessment questionnaire (EnergyInSight) five times a day for at least 21 days while being on the waitlist for psychological care for CRF. We performed a multi‐level vector autoregression analysis to examine the interconnectedness among fatigue, protective factors (allowing rest, acceptance, and self‐efficacy) and perpetuating factors (worrying, catastrophizing, and feeling guilty).ResultsIn the contemporaneous network (concurrent associations), higher acceptance and self‐efficacy were associated with lower fatigue, whereas all other factors were associated with higher fatigue. The strongest relationships were between worrying and feeling guilty and between acceptance and allowing rest. In the temporal network (lagged associations), fatigue was related to two factors: higher self‐efficacy preceded lower fatigue, and higher fatigue preceded increased allowing rest.ConclusionsTaking all included factors into account, the networks identified self‐efficacy and allowing rest as key protective factors of CRF. Patients may benefit from psychological interventions that cultivate self‐efficacy, as it seems to pave the way to reduced fatigue.

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Symptom networks in glioma patients: understanding the multidimensionality of symptoms and quality of life

et al. 2023

View full text Add to dashboard Cite

Purpose To comprehend the complex relationship between symptoms and health-related quality of life (HRQoL) in patients with diffuse glioma, we applied symptom network analysis to identify patterns of associations between depression, cognition, brain tumor-related symptoms, and HRQoL. Additionally, we aimed to compare global strength between symptom networks to understand if symptoms are more tightly connected in different subgroups of patients. Methods We included 256 patients and stratified the sample based on disease status (preoperative vs. postoperative), tumor grade (grade II vs. III/IV), and fatigue status (non-fatigued vs. fatigued). For each subgroup of patients, we constructed a symptom network. In these six networks, each node represented a validated subscale of a questionnaire and an edge represented a partial correlation between two nodes. We statistically compared global strength between networks. Results Across the six networks, nodes were highly correlated: fatigue severity, depression, and social functioning in particular. We found no differences in GS between the networks based on disease characteristics. However, global strength was lower in the non-fatigued network compared to the fatigued network (5.51 vs. 7.49, p < 0.001). Conclusions Symptoms and HRQoL are highly interrelated in patients with glioma. Interestingly, nodes in the network of fatigued patients were more tightly connected compared to non-fatigued patients. Implications for Cancer Survivors We introduce symptom networks as a method to understand the multidimensionality of symptoms in glioma. We find a clear association between multiple symptoms and HRQoL, which underlines the need for integrative symptom management targeting fatigue in particular.

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Using smartphone-based ecological momentary assessment and personalized feedback for patients with chronic cancer-related fatigue: A proof-of-concept study

Cited by 6 publications

References 31 publications

Symptom networks in glioma patients: understanding the multidimensionality of symptoms and quality of life

Symptom networks in glioma patients: understanding the multidimensionality of symptoms and quality of life

Exploring the dynamic interconnectedness of protective and perpetuating factors of cancer‐related fatigue

Symptom networks in glioma patients: understanding the multidimensionality of symptoms and quality of life

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