A Digital Phenotypic Assessment in Neuro-Oncology (DANO): A Pilot Study on Sociability Changes in Patients Undergoing Treatment for Brain Malignancies

Overview

Journal Cancers (Basel)

Publisher MDPI

Date 2025 Jan 11

PMID 39796767

Authors

Francesca Siddi

Patrick Emedom-Nnamdi

Michael P Catalino

Aakanksha Rana

Alessandro Boaro

Hassan Y Dawood

Francesco Sala

Jukka-Pekka Onnela

Timothy R Smith

Affiliations

Soon will be listed here.

Abstract

Background: The digital phenotyping tool has great potential for the deep characterization of neurological and quality-of-life assessments in brain tumor patients. Phone communication activities (details on call and text use) can provide insight into the patients' sociability.

Methods: We prospectively collected digital-phenotyping data from six brain tumor patients. The data were collected using the Beiwe application installed on their personal smartphones. We constructed several daily sociability features from phone communication logs, including the number of incoming and outgoing text messages and calls, the length of messages and duration of calls, message reciprocity, the number of communication partners, and number of missed calls. We compared variability in these sociability features against those obtained from a control group, matched for age and sex, selected among patients with a herniated disc.

Results: In brain tumor patients, phone-based communication appears to deteriorate with time, as evident in the trend for total outgoing minutes, total outgoing calls, and call out-degree.

Conclusions: These measures indicate a possible decrease in sociability over time in brain tumor patients that may correlate with survival. This exploratory analysis suggests that a quantifiable digital sociability phenotype exists and is comparable for patients with different survival outcomes. Overall, assessing neurocognitive function using digital phenotyping appears promising.

References

Akeret K, Vasella F, Geisseler O, Dannecker N, Ghosh A, Brugger P . Time to be "smart"-Opportunities Arising From Smartphone-Based Behavioral Analysis in Daily Patient Care. Front Behav Neurosci. 2018; 12:303. PMC: 6290758. DOI: 10.3389/fnbeh.2018.00303. View

Panda N, Solsky I, Huang E, Lipsitz S, Pradarelli J, Delisle M . Using Smartphones to Capture Novel Recovery Metrics After Cancer Surgery. JAMA Surg. 2019; 155(2):123-129. PMC: 6820047. DOI: 10.1001/jamasurg.2019.4702. View

Mugge L, Mansour T, Crippen M, Alam Y, Schroeder J . Depression and glioblastoma, complicated concomitant diseases: a systemic review of published literature. Neurosurg Rev. 2018; 43(2):497-511. DOI: 10.1007/s10143-018-1017-2. View

Jayakumar P, Lin E, Galea V, Mathew A, Panda N, Vetter I . Digital Phenotyping and Patient-Generated Health Data for Outcome Measurement in Surgical Care: A Scoping Review. J Pers Med. 2020; 10(4). PMC: 7765378. DOI: 10.3390/jpm10040282. View

Mastoras R, Iakovakis D, Hadjidimitriou S, Charisis V, Kassie S, Alsaadi T . Touchscreen typing pattern analysis for remote detection of the depressive tendency. Sci Rep. 2019; 9(1):13414. PMC: 6746713. DOI: 10.1038/s41598-019-50002-9. View

Fusaroli R, Perlman M, Mislove A, Paxton A, Matlock T, Dale R . Timescales of massive human entrainment. PLoS One. 2015; 10(4):e0122742. PMC: 4400172. DOI: 10.1371/journal.pone.0122742. View

Siddi F, Amedume A, Boaro A, Shah A, Abunimer A, Bain P . Mobile health and neurocognitive domains evaluation through smartphones: A meta-analysis. Comput Methods Programs Biomed. 2021; 212:106484. DOI: 10.1016/j.cmpb.2021.106484. View

Domenech-Abella J, Lara E, Rubio-Valera M, Olaya B, Moneta M, Rico-Uribe L . Loneliness and depression in the elderly: the role of social network. Soc Psychiatry Psychiatr Epidemiol. 2017; 52(4):381-390. DOI: 10.1007/s00127-017-1339-3. View

Straczkiewicz M, Wisniewski H, Carlson K, Heidary Z, Knights J, Keshavan M . Combining digital pill and smartphone data to quantify medication adherence in an observational psychiatric pilot study. Psychiatry Res. 2022; 315:114707. DOI: 10.1016/j.psychres.2022.114707. View

10.

Moser A, Stuck A, Silliman R, Ganz P, Clough-Gorr K . The eight-item modified Medical Outcomes Study Social Support Survey: psychometric evaluation showed excellent performance. J Clin Epidemiol. 2012; 65(10):1107-16. PMC: 4119888. DOI: 10.1016/j.jclinepi.2012.04.007. View

11.

Duey A, Rana A, Siddi F, Hussein H, Onnela J, Smith T . Daily Pain Prediction Using Smartphone Speech Recordings of Patients With Spine Disease. Neurosurgery. 2023; 93(3):670-677. DOI: 10.1227/neu.0000000000002474. View

12.

Abdullah S, Matthews M, Frank E, Doherty G, Gay G, Choudhury T . Automatic detection of social rhythms in bipolar disorder. J Am Med Inform Assoc. 2016; 23(3):538-43. PMC: 11740758. DOI: 10.1093/jamia/ocv200. View

13.

Kohler M, Steinmann E, Mehdorn H, Pedersen A, Goebel S . The importance of social relationships for brain tumor patients' quality of life: A case for the inclusion of the concept of disclosure in psycho-oncological care. J Psychosoc Oncol. 2019; 38(3):310-327. DOI: 10.1080/07347332.2019.1642283. View

14.

Toivonen R, Castello X, Eguiluz V, Saramaki J, Kaski K, San Miguel M . Broad lifetime distributions for ordering dynamics in complex networks. Phys Rev E Stat Nonlin Soft Matter Phys. 2009; 79(1 Pt 2):016109. DOI: 10.1103/PhysRevE.79.016109. View

15.

Matthews M, Abdullah S, Murnane E, Voida S, Choudhury T, Gay G . Development and Evaluation of a Smartphone-Based Measure of Social Rhythms for Bipolar Disorder. Assessment. 2016; 23(4):472-483. PMC: 6155452. DOI: 10.1177/1073191116656794. View

16.

DeMasi O, Feygin S, Dembo A, Aguilera A, Recht B . Well-Being Tracking via Smartphone-Measured Activity and Sleep: Cohort Study. JMIR Mhealth Uhealth. 2017; 5(10):e137. PMC: 5649042. DOI: 10.2196/mhealth.7820. View

17.

Faurholt-Jepsen M, Vinberg M, Frost M, Christensen E, Bardram J, Kessing L . Smartphone data as an electronic biomarker of illness activity in bipolar disorder. Bipolar Disord. 2015; 17(7):715-28. DOI: 10.1111/bdi.12332. View

18.

Ben-Zeev D, Brenner C, Begale M, Duffecy J, Mohr D, Mueser K . Feasibility, acceptability, and preliminary efficacy of a smartphone intervention for schizophrenia. Schizophr Bull. 2014; 40(6):1244-53. PMC: 4193714. DOI: 10.1093/schbul/sbu033. View

19.

Toivonen R, Kivela M, Saramaki J, Viinikainen M, Vanhatalo M, Sams M . Networks of emotion concepts. PLoS One. 2012; 7(1):e28883. PMC: 3262789. DOI: 10.1371/journal.pone.0028883. View

20.

Anjum K, Shagufta B, Abbas S, Patel S, Khan I, Ali Shah S . Current status and future therapeutic perspectives of glioblastoma multiforme (GBM) therapy: A review. Biomed Pharmacother. 2017; 92:681-689. DOI: 10.1016/j.biopha.2017.05.125. View