Time Toxicity of Cancer: the Time Demands of Cancer-related Activities and Their Impact on Well-being and Quality of Life
Conditions: Metastatic Breast Cancer, Ovarian Cancer
Sponsor: Masonic Cancer Center, University of Minnesota

SOCIAL PROTOCOL (HRP-580) 
PROTOCOL TITLE: Time toxicity of cancer: the time demands of cancer-related activities and 
their impact on well-being and quality of life 
VERSION DATE: 02/27/2024 
 
 
  
 
Page 1 of 39 
Template Revised On: 06/302022 
 
 
ANCILLARY REVIEWS 
DO NOT DELETE. Submit the completed checklist below with your protocol. 
Which ancillary reviews do I need and when do I need them? 
Refer to HRP-309 for more information about these ancillary reviews. 
Select yes or 
no 
Does your study… 
If yes… 
Impact on 
IRB Review 
☐ Yes 
X No 
 
Include Gillette resources, staff 
or locations 
Gillette Scientific review and Gillette 
Research Administration approval is 
required. Contact: 
research@gillettechildrens.com  
Required 
prior to IRB 
submission 
X Yes 
☐ No 
Involve Epic, or Fairview 
patients, staff, locations, or 
resources? 
The Fairview ancillary review will be 
assigned to your study by IRB staff 
Contact: ancillaryreview@Fairview.org 
Approval 
must be 
received 
prior to IRB 
committee/ 
designated 
review.  
 
Consider 
seeking 
approval 
prior to IRB 
submission. 
☐ Yes 
X No 
Include evaluation of drugs, 
devices, biologics, tobacco, or 
dietary supplements or data 
subject to FDA inspection? 
STOP – Complete the Medical Template 
Protocol (HRP-590) 
 
The regulatory ancillary review will be 
assigned to your study by IRB staff 
Contact: medreg@umn.edu  
See 
https://policy.umn.edu/research/indide  
      
Require Scientific Review? Not 
sure? See guidance in the 
Investigator Manual (HRP-
103).      
 
ONLY REQUIRED BIOMEDICAL 
RESEARCH REVIEWED BY FULL 
COMMITTEE 
  
X Yes 
☐ No 
Relate to cancer patients, 
cancer treatments, cancer 
screening/prevention, or 
tobacco? 
 
 
Complete the CPRC application process.  
Contact: ccprc@umn.edu  

SOCIAL PROTOCOL (HRP-580) 
PROTOCOL TITLE: Time toxicity of cancer: the time demands of cancer-related activities and 
their impact on well-being and quality of life 
VERSION DATE: 02/27/2024 
 
 
  
 
Page 2 of 39 
Template Revised On: 06/302022 
 
☐ Yes 
X No 
Include the use of radiation? 
(x-ray imaging, 
radiopharmaceuticals, external 
beam or brachytherapy) 
 
Complete the AURPC Human Use 
Application and follow instructions on 
the form for submission to the AURPC 
committee. 
Contact: barmstro@umn.edu  
Approval 
from these 
committees 
must be 
received 
prior to IRB 
approval;  
 
These 
groups 
each have 
their own 
application 
process.  
☐ Yes 
X No 
Use the Center for Magnetic 
Resonance Research (CMRR) 
or MR at Masonic Institute for 
the Developing Brain (MIDB) 
as a study location? 
Complete the CMRR pre-IRB ancillary 
review  
Contact: ande2445@umn.edu  
☐ Yes 
X No 
Include the use of 
recombinant or synthetic 
nucleic acids, toxins, or 
infectious agents? 
STOP – Complete the Medical Template 
Protocol (HRP-590) 
☐ Yes 
X No 
Include the use of human fetal 
tissue, human embryos, or 
embryonic stem cells? 
STOP – Complete the Medical Template 
Protocol (HRP-590) 
X Yes 
☐ No 
Include PHI or are you 
requesting a HIPAA waiver? 
If yes, HIPCO will conduct a review of this 
protocol. 
Contact: privacy@umn.edu  
☐ Yes 
X No 
Plan to use CTSI Monitoring 
services, and/or have an IND, IDE, 
or designated NSR-IDE by the 
UMN IRB? 
The CTSI monitoring ancillary review 
will be assigned to your study by IRB 
staff. 
Please note eligibility criteria here. 
Contact: fencl003@umn.edu 
Approval 
must be 
received 
prior to IRB 
approval. 
 
These 
groups do 
not have a 
separate 
application 
process but 
additional 
information 
from the 
☐ Yes 
X No 
Use data from CTSI Best 
Practices Integrated 
Informatics Core (BPIC) 
Formerly the AHC Information 
Exchange (AHC-IE)? 
The Information Exchange ancillary 
review will be assigned to your study by 
IRB staff 
Contact: bpic@umn.edu  
☐ Yes 
X No 
Use the Biorepository and 
Laboratory Services to collect 
tissue for research? 
STOP – Complete the Medical Template 
Protocol (HRP-590)  
 
The BLS ancillary review will be 
assigned to your study by IRB staff. 

SOCIAL PROTOCOL (HRP-580) 
PROTOCOL TITLE: Time toxicity of cancer: the time demands of cancer-related activities and 
their impact on well-being and quality of life 
VERSION DATE: 02/27/2024 
 
 
  
 
Page 3 of 39 
Template Revised On: 06/302022 
 
Contact: Jenny Pham 
Pham0435@umn.edu 
study team 
may be 
required. 
 
X    Yes 
☐ No 
Have a PI or study team 
member with a conflict of 
interest? 
The CoI ancillary review will be 
assigned to your study by IRB staff 
Contact: becca002@umn.edu  
X Yes 
☐ No 
Need to be registered on 
clinicaltrials.gov? 
If you select “No” in ETHOS, the 
clinicaltrials.gov ancillary review will be 
assigned to your study by IRB staff 
Contact: fencl003@umn.edu  
X Yes 
☐ No 
Require registration in 
OnCore? 
If you select “No” or “I Don’t Know” in 
ETHOS, the OnCore ancillary review will 
be assigned to your study by IRB staff 
Contact: oncore@umn.edu  
Does not 
affect IRB 
approval. 
 
 
 
 

SOCIAL PROTOCOL (HRP-580) 
PROTOCOL TITLE: Time toxicity of cancer: the time demands of cancer-related activities and 
their impact on well-being and quality of life 
VERSION DATE: 02/27/2024 
 
 
  
 
Page 4 of 39 
Template Revised On: 06/302022 
 
 
PROTOCOL COVER PAGE 
Protocol Title 
Time toxicity of cancer: the time demands of cancer-related 
activities and their impact on well-being and quality of life 
Principal 
Investigator/Faculty 
Advisor 
Name: Rachel I. Vogel, PhD 
Department: Obstetrics, Gynecology, and Women’s Health 
Telephone Number: 612-624-6928 
Email Address: isak0023@umn.edu 
Student Investigator 
Name: 
Current Academic Status (Student, Fellow, Resident): 
  
Department: 
Telephone Number: 
Institutional Email Address: 
Scientific Assessment 
Nationally-based, federal funding organizations 
Version 
Number/Date: 
4.0, 02/27/2024 
 
 
 

SOCIAL PROTOCOL (HRP-580) 
PROTOCOL TITLE: Time toxicity of cancer: the time demands of cancer-related activities and 
their impact on well-being and quality of life 
VERSION DATE: 02/27/2024 
 
 
  
 
Page 5 of 39 
Template Revised On: 06/302022 
 
REVISION HISTORY 
 
Revision # 
Version Date 
Summary of Changes 
Consent Change? 
1 
05/05/2023 
Named mobile app for use in the 
protocol as Daynamica and provide 
details for data security 
No 
2 
09/14/2023 
Added option to interact with 
participants via email regarding data 
collection, clarify consent procedure 
options (both electronic and paper, 
in-person or remote) 
Yes 
3 
02/27/2024 
Increase total number to be 
consented to account for drop out 
before mobile app data collection 
(replace individuals who consent but 
do not download/utilize the mobile 
app) 
No 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

SOCIAL PROTOCOL (HRP-580) 
PROTOCOL TITLE: Time toxicity of cancer: the time demands of cancer-related activities and 
their impact on well-being and quality of life 
VERSION DATE: 02/27/2024 
 
 
  
 
Page 6 of 39 
Template Revised On: 06/302022 
 
Table of Contents 
1.0 
Objectives ......................................................................................................................................... 8 
2.0 
Background ....................................................................................................................................... 8 
3.0 
Study Endpoints/Events/Outcomes .......................................................................................... 10 
4.0 
Study Intervention(s)/Interaction(s) ......................................................................................... 10 
5.0 
Procedures Involved ..................................................................................................................... 10 
6.0 
Storing Data for Future Use ........................................................................................................ 14 
7.0 
Sharing of Results with Participants ......................................................................................... 17 
8.0 
Study Duration .............................................................................................................................. 17 
9.0 
Study Population .......................................................................................................................... 17 
10.0 
Vulnerable Populations ............................................................................................................... 17 
11.0 
Number of Participants ............................................................................................................... 19 
12.0 
Recruitment Methods .................................................................................................................. 20 
13.0 
Withdrawal of Participants ........................................................................................................ 21 
14.0 
Risks to Participants ..................................................................................................................... 21 
15.0 
Incomplete Disclosure or Deception .......................................................................................... 22 
16.0 
Potential Benefits to Participants .............................................................................................. 22 
17.0 
Statistical Considerations ............................................................................................................ 22 
18.0 
Health Information and Privacy Compliance ........................................................................... 29 
19.0 
Confidentiality ............................................................................................................................... 32 
20.0 
Provisions to Monitor the Data to Ensure the Safety of Participants ................................. 33 
21.0 
Compensation for Research-Related Injury ............................................................................. 33 
22.0 
Consent Process ............................................................................................................................ 34 
23.0 
Setting ............................................................................................................................................ 35 
24.0 
Multi-Site Research ...................................................................................................................... 35 
25.0 
Coordinating Center Research.................................................................................................... 35 
26.0 
Resources Available ..................................................................................................................... 35 
27.0 
References ..................................................................................................................................... 36 
 
 

SOCIAL PROTOCOL (HRP-580) 
PROTOCOL TITLE: Time toxicity of cancer: the time demands of cancer-related activities and 
their impact on well-being and quality of life 
VERSION DATE: 02/27/2024 
 
 
  
 
Page 7 of 39 
Template Revised On: 06/302022 
 
ABBREVIATIONS/DEFINITIONS 
AUC 
Area under the curve 
EHR 
Electronic Health Record 
CAB 
Community Advisory Board 
MARS Mobility App Rating Scale 
PETS 
Patient Experience with Treatment and Self-Management 
POI 
Point of interest 
QOL 
Quality of Life 
TBQ 
Treatment Burden Questionnaire 
 
 

SOCIAL PROTOCOL (HRP-580) 
PROTOCOL TITLE: Time toxicity of cancer: the time demands of cancer-related activities and 
their impact on well-being and quality of life 
VERSION DATE: 02/27/2024 
 
 
  
 
Page 8 of 39 
Template Revised On: 06/302022 
 
1.0 
Objectives 
1.0 Purpose: Our overall objectives are to 1) measure, describe, and quantify sources of 
cancer-related time toxicity among individuals treated for cancer, and their effect on 
QOL; and 2) create time toxicity scores which can be used in future studies to 
identify opportunities to minimize time toxicity. Our specific aims are: 
Aim 1: Measure and describe components of objective time use associated with 
cancer-related healthcare interactions via a mobile health application. 
Aim 2: Characterize associations between measures of cancer-related time use and 
self-reported well-being, and explore the role of context in modifying these 
associations. 
Aim 3: Create a time toxicity summary score based on measures of cancer-related 
time use and assess its association with psychosocial outcomes. 
2.0 
Background 
2.1 Significance of Research Question/Purpose: Cancer-related demands on patients’ 
time and stress have multiple sources: time spent on care itself (appointments, 
taking medication), travel and wait times, and other activities such as scheduling, 
paperwork, dealing with bills and insurance, and organizing one’s schedule in order 
to accommodate time for these activities. The time spent on these activities 
competes with time patients would otherwise dedicate to loved ones, work, 
childcare, preventive care, caregiving, household activities, or leisure time. Leisure 
time serves as a buffer to cope with negative life events through distraction, 
adaptation, self-restoration, and stress compensation, enabling better coping with 
cancer.[1, 2] The burdens of care can only be fully understood in the context of and 
in interaction with other time and labor demands. Accurately defining and 
measuring time toxicity as both the direct and indirect time burdens of cancer and 
related treatments is a necessary first step for identifying effective interventions to 
address them. 
Whether cancer-related tasks and time use become a toxic burden depends on 
unique patient situations. Disadvantaged patient populations and those with 
multiple other responsibilities are likely to be most affected, and some of these 
populations bear a disproportionate cancer burden.[3, 4] For example, low-income 
patients and some ethno-racial minority groups experience more pain and symptom 
burden, more financial distress, lower survival rates, and poorer QOL.[5-7] Other 
vulnerable groups include: women who, despite shifts in traditional family roles, 
often still carry significant household and family responsibilities in addition to 
contributing to family incomes; populations with limited geographic access to cancer 
care [8] such as rural populations with long travel distances to clinics; and those with 

SOCIAL PROTOCOL (HRP-580) 
PROTOCOL TITLE: Time toxicity of cancer: the time demands of cancer-related activities and 
their impact on well-being and quality of life 
VERSION DATE: 02/27/2024 
 
 
  
 
Page 9 of 39 
Template Revised On: 06/302022 
 
reduced transportation access who need to rely on public transit and other means of 
travel.[9, 10] 
2.2 Preliminary Data: The concept of time toxicity in cancer care expands the concept of 
treatment burden in chronic disease management. Theories such as the Burden of 
Treatment Theory [11] and Cumulative Complexity Model [12] have highlighted the 
complexity of treatment burden. Instruments such as the Treatment Burden 
Questionnaire (TBQ) [13] and the Patient Experience with Treatment and Self-
management survey (PETS) [14] collect recall-based data on various aspects of 
treatment burden including patient workload and its impact on patient well-being. 
Our proposal will add to the field by creating measures that capture time spent on 
specific cancer-related tasks (e.g. time in clinics, traveling time), and by exploring 
how sources of treatment burden interact with specific individual (clinical, 
demographic, life stage) situations that may or may not make the same cancer-
related task burdensome.  
In work by our group, we have estimated cancer-related time uses among patients 
with metastatic breast cancer during initial treatment [15] and among patients with 
cancer receiving chemotherapy [16]. We have also examined self-reported cancer-
related workload among patients with breast cancer and found those with stage III 
and IV cancer reported disproportionate cancer-related time and workload burdens 
and found these burdens were associated with worse psychosocial outcomes and 
lower QOL (in preparation). In a study of adolescents and young adults with cancer, 
we found that those with the most intensive cancer treatments more often believed 
that cancer would negatively impact their plans for work and/or school.[17] In that 
study, we also found that only a fraction of patients’ time is spent interacting with 
healthcare providers, with substantial time spent traveling to and waiting for care 
services. The work proposed here will help identify areas to improve time efficiency 
of care.[15, 16] One of our conclusions was that total time spent on care should not 
only be reduced, but also distributed more efficiently to allow for more health-care 
free days.[18] For example, splitting 10 hours of cancer care over two instead of five 
days gives patients three days that are uninterrupted by care. 
We will build on our prior work and comprehensively measure cancer-related time 
burdens. For this, we will use a customized version of the Daynamica mobile 
application, created by Co-PI Wolfson and Co-I Fan, which is an established, easy-to-
use sensor-based tool to collect data automatically on daily activities and time use 
requiring minimal user input. More details on the app are provided below. Between 
2016 and 2020, the Daynamica app has been deployed in multiple research studies 
[19-23], collecting information from over 2,000 individuals with >20,000 days of time 
use and well-being data.  

SOCIAL PROTOCOL (HRP-580) 
PROTOCOL TITLE: Time toxicity of cancer: the time demands of cancer-related activities and 
their impact on well-being and quality of life 
VERSION DATE: 02/27/2024 
 
 
  
 
Page 10 of 39 
Template Revised On: 06/302022 
 
2.3 Existing Literature: The relevant literature is cited in sections 2.1 and 2.2 above. 
There is an urgent need for a tool that generates accurate, comprehensive, and 
timely measures of logistic toxicity.  
3.0 
Study Endpoints/Events/Outcomes 
3.1 Primary Endpoint/Event/Outcome:  
Aim 1: Summary measures of time use by activity and trip type; for each 
activity/trip type, the number of minutes per day spent on that activity, the number 
of separate episodes, and the number of days per week on which that activity 
occurs 
Aim 2: Daily well-being, as measured by the American Time Use Survey 
Aim 3: Time toxicity score 
3.2 Secondary Endpoint(s)/Event(s)/Outcome(s): overall quality of life, emotional 
health, symptoms, financial toxicity 
4.0 
Study Intervention(s)/Interaction(s) 
4.0 Description: A total of 80 individuals receiving treatment for metastatic breast or 
advanced stage ovarian cancer will be asked to 1) complete a baseline survey and 
install the Daynamica mobile app on their smartphone; 2) carry the smartphone for 
28 consecutive days while outside the home; 3) keep smartphone location and 
motion services active; 4) confirm and correct (if needed) smartphone-detected 
activities and trips; 5) use the app interface to provide additional information on 
activities and trips related to cancer treatment tasks; 6) complete daily surveys 
regarding well-being; and 7) at the end of the 28 day period, complete an online 
survey. Individuals who do not install and use the Daynamica mobile app after 
completing the consent process and baseline survey will be replaced and not count 
toward the goal sample size of 80 participants.  
5.0 
Procedures Involved 
5.1 Study Design: Observational cohort study 
5.2 Study Procedures: All participant interactions fall under Aim 1. Aims 2 and 3 involve 
analysis of data collected under Aim 1.  
A total of up to 100 individuals currently undergoing treatment for metastatic breast 
or advanced stage ovarian cancer (frontline, maintenance or for recurrence) will be 
invited to participate in the study. Participation in the study will not affect clinical 
treatment decisions. Enrolled participants will be asked to:  
1) Complete a baseline survey (paper or online per personal preference). 
2) Install the Daynamica app from the Google Play or Apple App Store on their 
smartphone (we will provide a smartphone with the app pre-installed to 
participants who do not own one). 

SOCIAL PROTOCOL (HRP-580) 
PROTOCOL TITLE: Time toxicity of cancer: the time demands of cancer-related activities and 
their impact on well-being and quality of life 
VERSION DATE: 02/27/2024 
 
 
  
 
Page 12 of 39 
Template Revised On: 06/302022 
 
Figure 1. Smartphone app measurements and aims. 
For this study, participants will install an app on their personal smartphones for a 
28-day period. The app, currently designed to capture common activities, e.g. home, 
work, shopping, education, eating out, leisure/recreation, car, bike, bus, will be 
modified to allow users to indicate and annotate cancer care-related activities. 
When a cancer care-related activity is reported, participants will be prompted to 
provide additional information on three items: wait time, time with the provider, 
and time spent receiving treatment or imaging. If participants repeatedly visit the 
same care location, these episodes will be automatically recognized such that 
participants need only provide the additional information. At the end of each day, 
participants will be asked to complete a short (<5 minute) 8-item survey, including 
questions regarding any phone calls or other activities that day related to cancer 
that were not otherwise reported, and time spent on those activities. The survey will 
also include questions on well-being based on the American Time Use Survey: two 
positive emotion questions (happy and meaningful) and four negative emotion 
questions (sad, painful, stressful, and tired). These questions will generate episode-
level well-being measures, and will be used to generate outcome variables of daily 
emotional well-being: (1) U-Index at the person-day level: the proportion of time an 
individual spends in an unpleasant state during the 24-hour period, with an 
unpleasant state defined as the individual having a negative emotion more intense 
than any positive emotions; (2) Duration-weighted sum of average happiness, 

SOCIAL PROTOCOL (HRP-580) 
PROTOCOL TITLE: Time toxicity of cancer: the time demands of cancer-related activities and 
their impact on well-being and quality of life 
VERSION DATE: 02/27/2024 
 
 
  
 
Page 13 of 39 
Template Revised On: 06/302022 
 
meaningfulness, sadness, pain, stress, and tiredness scores during a 24-hour period 
at the person-day level. 
Survey data. Additional patient-reported outcomes will be collected at baseline and 
28 days (following completion of mobile app data). Measures will be collected on 
paper or via online surveys in REDCap per participant preference. Study outcomes 
include reliable and validated measures used previously by the study team and will 
be scored following standard procedures.  
Demographics: Demographic characteristics collected will include age, sex, 
race/ethnicity, household income, education, insurance status, relationship status, 
parenting and caregiver status, employment status, and zip code to assess rurality 
and distance from clinic.  
General Quality of Life: QOL is a multi-dimensional concept including domains of 
physical, psychological, social health, and overall life satisfaction.[27] We will 
measure QOL using the Functional Assessment of Cancer Therapy - General (FACT-G) 
questionnaire (39 items).[31]  
Depression and Anxiety: Symptoms of anxiety and depression will be measured using 
the Hospital Anxiety-Depression Scale (HADS). This measure consists of 14 items 
rated on a 4-point scale and provides separate scores for anxiety and depression, 
including cut-offs for potentially clinically relevant anxiety and depression.  
Distress: We will measure cancer-related distress using the National Comprehensive 
Cancer Network Distress Thermometer, a single-item tool measuring distress on a 
scale from 0-10 with an accompanying problem list of potential contributing issues, 
including practical, physical, family, emotional, and spiritual concerns.[33, 34] 
Symptom Management: Breast and ovarian cancers and their treatments can result 
in significant side effects and symptom burden for patients and these symptoms can 
increase healthcare utilization while decreasing QOL. The MD Anderson Symptom 
Inventory (MDASI) is a multi-symptom patient-reported measure of 13 core 
symptoms that are common and often severe, with impacts on functioning, in 
patients with cancer.[35]  
Opportunity Costs: The Oncology Opportunity Cost Assessment Tool (OOCAT) 
evaluates opportunity costs - including time spent seeking care, lost wages, lost 
leisure time, and other indirect costs associated with seeking cancer care.[36] The 
18–item instrument includes six domains: travel, appointments, work and school, 
home, health system, and caregiver burden.  
Work, Insurance and Financials: We will measure financial toxicity using the 
Comprehensive Score for Financial Toxicity (COST) instrument, an 11-item 
questionnaire validated in individuals with cancer.[37] We will also measure current 
employment status, days missed due to illness, and health insurance coverage using 

SOCIAL PROTOCOL (HRP-580) 
PROTOCOL TITLE: Time toxicity of cancer: the time demands of cancer-related activities and 
their impact on well-being and quality of life 
VERSION DATE: 02/27/2024 
 
 
  
 
Page 14 of 39 
Template Revised On: 06/302022 
 
validated measures derived from the American Cancer Society Study of Cancer 
Survivors II [38] and National Health Interview [39] surveys. 
Patient-reported time burden: We will ask respondents to add free-text comments, 
for example to describe circumstances in their life that may have amplified or 
reduced the cancer-related time burdens.  
Medical record data. Participant medical data, including diagnosis, treatments 
received and dosage, adverse events, comorbidities and healthcare encounters, will 
be abstracted from the medical records at each site and entered into REDCap.  
5.3 Follow-Up: Survey data will be collected before the study and immediately after 
participants finish using the app for 28 days. 
Individually Identifiable Health Information: We will obtain written HIPAA 
agreement from participants. Daynamica uses GPS location data to infer activity 
type and trip mode; such detailed location data constitute Protected Health 
Information (PHI). 
 
6.0 
Storing Data for Future Use 
6.1 Storage and Access:  
Daynamica user data on the device is saved only on internal smartphone storage, 
which is encrypted, inaccessible to other applications on the device and is deleted 
when the Daynamica app is uninstalled. Study participants are instructed to use a 
passcode to secure their device while engaged in data collection. In the case of 
unauthorized device access, the location data visible in the Daynamica app is the 
same as would be readily available by viewing an individual's Google or Apple Maps 
location history. When notified that a device has been lost or stolen, the Daynamica 
team will terminate data collection, which prevents device users from viewing 
participant location data from within the app.  
The Daynamica app transfers data to a server for additional processing and secure 
storage. For this project, the upload and processing server will be operated entirely 
by UMN Health Sciences Technology (HST). Daynamica will coordinate with HST to 
install necessary software on secure, HIPAA-compliant HST servers. Prior to the start 
of data collection, Daynamica will be provided with access to an HST server to install 
the software needed to receive uploads from the Daynamica smartphone app. Once 
data collection begins, Daynamica staff will no longer have access to HST servers. 
The HST server will be configured to receive uploads and transfer the PHI location 
data to a separate server that does not accept external connections. Non-PHI data 
will be made available via a secure API so that study managers can access 
information about data completeness. The setup of the UMN HST server will be 

SOCIAL PROTOCOL (HRP-580) 
PROTOCOL TITLE: Time toxicity of cancer: the time demands of cancer-related activities and 
their impact on well-being and quality of life 
VERSION DATE: 02/27/2024 
 
 
  
 
Page 15 of 39 
Template Revised On: 06/302022 
 
similar to that used for previous projects, specifically DashPAD (UMN IRB Study 
#00006570), in collaboration with Chris Dinger and HST.  
The details of the data processing and storage plan are: 
• All data collected by the Daynamica app will be linked to a randomly-
generated, non-identifiable participant ID code. Only the principal 
investigator(s) and approved study managers will have access to the data file 
linking participant ID codes to participant contact information (e.g., phone 
number, email address), and this data file will be stored in a separate 
secured location (e.g., UMN Box). 
• The identifiable (i.e., PHI) data collected by Daynamica consists of detailed 
location information in the form of the GPS coordinates of daily trips and 
activities. These data are stored in a separate table in the encrypted internal 
app database and are linked to (non-identifiable) time and type information 
about daily trips and activities via a numeric "calendar item" code. Only the 
principal investigator(s) will have permission to download the PHI data and 
link it to other participant information via the calendar item codes. 
• Upon request, HST staff will be provided with access to relevant 
documentation and source code of both the Daynamica app and the server 
software to verify that the uploads are happening as described in this plan 
for the purpose of security review. Daynamica source code is proprietary, 
and hence access to source code by HST staff, if needed, will be subject to a 
Non-Disclosure Agreement between Daynamica, Inc. and the University of 
Minnesota.  
• Study investigators and managers will access a dashboard to assist in study 
management. This dashboard will be based entirely on non-PHI data 
provided via a secure API managed by HST; the dashboard will not have any 
access to the PHI location data stored on HST servers. 
De-identified data collected as part of the project will be available for sharing in raw or 
aggregate form. A long-term data sharing and preservation plan will be used to store 
and make publicly accessible the data beyond the life of the project. The data will be 
deposited into the Data Repository for the University of Minnesota (DRUM). This 
University Libraries’ hosted institutional data repository is an open access platform 
for dissemination and archiving of university research data. Date files in DRUM are 
written to an Isilon storage system with two copies, one local to each of the two 
geographically separated University of Minnesota Data Centers. The local Isilon 
cluster stores the data in a way that the data can survive the loss of any two disks or 
any one node of the cluster. Within two hours of the initial write, data replication to 
the 2nd Isilon cluster commences. The 2nd cluster employs the same protections as 
the local cluster, and both verify with a checksum procedure that data has not 
altered on write. In addition, DRUM provides long-term preservation of digital data 

SOCIAL PROTOCOL (HRP-580) 
PROTOCOL TITLE: Time toxicity of cancer: the time demands of cancer-related activities and 
their impact on well-being and quality of life 
VERSION DATE: 02/27/2024 
 
 
  
 
Page 16 of 39 
Template Revised On: 06/302022 
 
files for at least 10 years using services such as migration (limited format types), 
secure backup, bit-level checksums, and maintains a persistent DOIs for data sets, 
facilitating data citations. In accordance to DRUM policies, the de-identified data will 
be accompanied by the appropriate documentation, metadata, and code to facilitate 
reuse and provide the potential for interoperability with similar data sets. The 
DRUM has data access policies and procedures consistent with NIH data sharing 
policies. 
All identifiable data, including app data and data entered in REDCap along with 
paper documents, will be destroyed within 10 years of study completion.  
6.2 Data: Survey data (baseline, day 28) and mobile application activity and well-being 
summary data will be stored and available for future use. 
6.3 Release/Sharing: Survey data will be available as a .csv file that can be exported into 
MS Excel, SAS, SPSS, or ASCII files. 
The final data file to be shared will include (a) raw item-level data (where applicable 
to recreate analyses; will not include location data) with appropriate variable and 
value labels and (b) computed variables created during analysis. These data will be 
the de-identified and individual- or aggregate-level data used for the final and 
published analyses. 
Dataset documentation will consist of electronic codebooks documenting the 
following information: (a) a description of the research questions, methodology, and 
sample, (b) a description of each specific data source, and (c) a description of the 
raw data and derived variables, including variable lists and definitions (project 
codebook). To aid in final dataset documentation, throughout the project, we will 
maintain a log of when, where, and how data were collected, decisions related to 
methods, coding, and analysis, statistical analyses, software and instruments used, 
where data and corresponding documentation are stored, and future research ideas 
and plans. 
The Principal Investigators will be the data stewards while the data are “active” (i.e., 
during data collection, coding, analysis, and publication phases of the project), and 
will be responsible for documenting and managing the data throughout this time. 
Additional project personnel (project coordinators and graduate research assistants) 
will also be responsible for adhering to the data management plan. 
The PIs will develop study-specific protocols and will train all project staff who 
handle data to follow these protocols. Protocols will include guidelines for managing 
confidentiality of data, as well as protocols for naming, organizing, and sharing files 
and entering and downloading data.  
At the end of the project, the data will be archived and shared and the University of 
Minnesota Libraries will serve as the steward of the de-identified, archived dataset 

SOCIAL PROTOCOL (HRP-580) 
PROTOCOL TITLE: Time toxicity of cancer: the time demands of cancer-related activities and 
their impact on well-being and quality of life 
VERSION DATE: 02/27/2024 
 
 
  
 
Page 17 of 39 
Template Revised On: 06/302022 
 
from that point forward. These de-identified data will be available to all interested 
parties. No specific data sharing agreement will be needed for DRUM; however, 
DRUM does have a general end-user access policy available online. 
 
7.0 
Sharing of Results with Participants 
7.1 Participants will be able to view their own data on the mobile app, however, we will 
not otherwise share results with participants.  
8.0 
Study Duration 
8.1 The duration an individual participant will be involved in the study is approximately 
30 days. We plan to enroll all participants within 24 months and anticipate all study 
procedures and data analysis will be completed within 60 months.  
9.0 
Study Population 
9.1 Inclusion Criteria:  
• 18 years of age or older 
• Diagnosed with advanced stage (III, IV) ovarian (ovarian, fallopian tube or 
prmary peritoneal) or metastatic breast cancer [do not need to be newly 
diagnosed] 
• Currently receiving any type of therapy for their cancer [can be front-line, 
maintenance therapy, or treatment for recurrence] 
• Able to complete study tasks in English  
• Able to provide voluntary informed consent 
• Own an Android or iOS smartphone on which the operating system is version 
9.0 or higher for Android or 10.0 higher for iOS; or willing to use a 
researcher-provided smartphone  
9.2 Exclusion Criteria:  
• Those who are currently incarcerated 
• Have opted out of research contact 
9.3 Screening: Potentially eligible participants will be identified by a study coordinator. 
Those identified as potentially eligible will be called ahead of an upcoming clinical 
appointment or approached at the time of a scheduled visit by the clinic’s research 
coordinator or study staff. 
10.0 Vulnerable Populations 
10.1 Vulnerable Populations:  

SOCIAL PROTOCOL (HRP-580) 
PROTOCOL TITLE: Time toxicity of cancer: the time demands of cancer-related activities and 
their impact on well-being and quality of life 
VERSION DATE: 02/27/2024 
 
 
  
 
Page 18 of 39 
Template Revised On: 06/302022 
 
Population / Group 
Identify whether any of the 
following populations will be 
primary focus of the research 
(targeted), included but not the 
focus of the research or excluded 
from participation in the study.  
Children 
Excluded 
Pregnant women/fetuses/neonates 
included but not the focus 
Prisoners 
Excluded 
Adults lacking capacity to consent 
and/or adults with diminished 
capacity to consent, including, but 
not limited to, those with acute 
medical conditions, psychiatric 
disorders, neurologic disorders, 
developmental disorders, and 
behavioral disorders 
Excluded 
Non-English speakers 
Excluded 
Those unable to read (illiterate) 
Excluded 
Employees of the researcher 
Excluded 
Students of the researcher 
Excluded 
Undervalued or disenfranchised 
social group 
included but not the focus 
Active members of the military 
(service members), DoD personnel 
(including civilian employees) 
included but not the focus 

SOCIAL PROTOCOL (HRP-580) 
PROTOCOL TITLE: Time toxicity of cancer: the time demands of cancer-related activities and 
their impact on well-being and quality of life 
VERSION DATE: 02/27/2024 
 
 
  
 
Page 19 of 39 
Template Revised On: 06/302022 
 
Individual or group that is 
approached for participation in 
research during a stressful situation 
such as emergency room setting, 
childbirth (labor), etc. 
Excluded 
Individual or group that is 
disadvantaged in the distribution of 
social goods and services such as 
income, housing, or healthcare. 
included but not the focus 
Individual or group with a serious 
health condition for which there are 
no satisfactory standard treatments. 
included but not the focus 
Individual or group with a fear of 
negative consequences for not 
participating in the research (e.g. 
institutionalization, deportation, 
disclosure of stigmatizing behavior). 
included but not the focus 
Any other circumstance/dynamic 
that could increase vulnerability to 
coercion or exploitation that might 
influence consent to research or 
decision to continue in research. 
Excluded 
10.2 Additional Safeguards:  
All participants will have a cancer diagnosis, which is a serious health condition. 
This study specifically aims to understand the time burdens of cancer care. Our 
study carries minimal risk for participants. 
The proposed research will not specifically seek military members or DOD 
personnel, disadvantaged individuals or members of undervalued or 
disenfranchised social groups, however, if volunteers meets the inclusion criteria 
and also happen to be from one of the groups checked above, they will be eligible 
to participate in the study.  
11.0  Number of Participants 
11.1 Number of Participants to be Consented: Up to 100 

SOCIAL PROTOCOL (HRP-580) 
PROTOCOL TITLE: Time toxicity of cancer: the time demands of cancer-related activities and 
their impact on well-being and quality of life 
VERSION DATE: 02/27/2024 
 
 
  
 
Page 20 of 39 
Template Revised On: 06/302022 
 
12.0 Recruitment Methods 
12.1 Recruitment Process:  
Recruitment and initial patient contact will be made by the patient’s healthcare 
team and/or clinic study coordinator. Potentially eligible patients will be approached 
at or near the time of any scheduled visit by the clinic’s research coordinator or 
study staff.  
The study coordinator will review medical records and upcoming provider and 
chemotherapy schedules for individuals who may be eligible for this study. They may 
contact the provider prior to the visit to confirm their eligibility if questions arise.  
Individuals may be recruited in the following ways depending on visit type:  
Standard of Care visit with oncologist/provider: 
Video visits: For appointments that are conducted via virtual video, the provider will 
briefly describe the study at the end of the virtual visit and ask if the participant is 
interested in learning more about the study and how to participate. If they are 
interested and have time to meet with the study coordinator at that time, the study 
coordinator will then join the in-progress virtual visit to describe the study. If the 
participant is interested in participating, the study coordinator will provide them 
with the consent materials via mail or a link to the electronic consent in REDCap via 
email.  
Phone visits: The provider will describe the study and if interested, give the patient 
contact information for the study coordinator. The patient will be instructed to 
contact the study coordinator for more information and to proceed with the consent 
process.  
In clinic: The provider may introduce the study and the study coordinator will 
describe the study in detail. The coordinator can conduct in-person consent or 
provide information for the patient to complete the consent online in REDCap at a 
later time.  
Chemotherapy administration or other in-person healthcare visit:  
The study coordinator will describe the study. If the patient is interested in 
participating, the study coordinator will conduct in-person consent.  
Eligible and interested patients will be asked to complete the consent form and 
HIPAA forms. Registration will occur after the subject consent is signed and eligibility 
is confirmed, but before any study data are collected.  
Upon completion of the screening evaluation, eligibility confirmation and obtaining 
consent, the study staff will enroll the subject into REDCap.  
12.2 Source of Participants: Patients receiving care at a participating clinic site. 

SOCIAL PROTOCOL (HRP-580) 
PROTOCOL TITLE: Time toxicity of cancer: the time demands of cancer-related activities and 
their impact on well-being and quality of life 
VERSION DATE: 02/27/2024 
 
 
  
 
Page 21 of 39 
Template Revised On: 06/302022 
 
12.3 Identification of Potential Participants: Potentially eligible participants will be 
identified by a clinic study coordinator by reviewing the clinic schedule and medical 
records. The study coordinators will confirm that the patient has not declined 
research (we will not approach patients with "Research Opt-out" status indicated 
their medical record, in order to comply with Minnesota Statute 144.651, 
subdivision 13).  
12.4 Recruitment Materials: A study summary sheet is included.  
12.5 Payment: Participants will receive $25 for completing the baseline survey and 
mobile app installation. Participants will receive an additional $125 for completing 
the 28-day mobile application data collection, and $25 following completion of the 
final survey for a total of up to $175. 
13.0 Withdrawal of Participants 
13.1 Withdrawal Circumstances: No participant will be withdrawn from the study against 
their will. Participants will only be withdrawn from the study if they ask to withdraw, 
become too ill or die prior to completing the study. If participants become too ill, 
they will not be withdrawn from the study until they have given their voluntary 
consent for study withdrawal. 
13.2 Withdrawal Procedures: If a participant chooses to withdraw at any point, their 
decisions will be respected without repercussions. Data collected until the point of 
withdrawal will be used unless the participant specifies otherwise. 
13.3 Termination Procedures: Participants will not be terminated from the study for any 
reason. 
14.0 Risks to Participants 
14.1 Foreseeable Risks: This study has few risks. We identified the following 2 possible 
risks to subjects:  
Risk to confidentiality: Inadvertent breaches of confidentiality by investigators or 
their staff are unlikely but may occur. Identifying information will be kept private 
and all identifiers will be removed prior to any data being given to researchers. The 
records will be identified only with a unique ID number on an encrypted database. 
Data transfer will only occur with de-identified data with encrypted transfer of all 
information containing protected health information between participants and 
study databases.  
The Daynamica app records information about daily activities, including relevant 
locations such as home and work. These data are potentially highly sensitive, and 
hence there is a non-trivial risk of loss of confidentiality and privacy if the data are 
accessed inappropriately. We have put multiple safeguards in place to ensure data 
security, including strict guidelines about which study team members have access to 

SOCIAL PROTOCOL (HRP-580) 
PROTOCOL TITLE: Time toxicity of cancer: the time demands of cancer-related activities and 
their impact on well-being and quality of life 
VERSION DATE: 02/27/2024 
 
 
  
 
Page 22 of 39 
Template Revised On: 06/302022 
 
which data, and how the data are to be used. In addition, the Daynamica app 
empowers users by providing an interface to review and edit all data collected (e.g., 
change start/end times, modify activity types and trip modes, etc.). Further, users 
are always free to turn off the app during time periods where they would prefer not 
to be tracked. 
Discomfort while interacting with the app or answering survey questions: There is a 
possibility that some participants may feel uncomfortable interacting with the app 
or when answering survey questions which may remind them of their cancer 
diagnosis. They will be reminded that they can skip any questions or discontinue at 
any time.  
The data from these studies will not be used to direct patient care. Therefore, 
participation in this study will have no influence on the care the patient receives nor 
will it influence treatment decisions.  
Adverse event reporting: This study carries minimal risk and will comply with the 
University of Minnesota IRB reporting requirements. Events requiring prompt 
reporting include any adverse event that requires a change to the protocol or 
consent form, any unauthorized disclosure of confidential information, any 
unresolved subject complaint or any protocol deviation that resulting in harm or the 
unanticipated death of an enrolled subject. Deaths are not considered an adverse 
event for this protocol as this is not a treatment study, however, participants may 
die as a result of unexpected progression of the disease before completing research 
activities.  
Refer to http://www.research.umn.edu/irb/guidance/ae.html#.VC7xraI0-sh for 
additional guidance.  
Any event requiring prompt reporting to the IRB must also be reported to the 
Masonic Cancer Center’s SAE Coordinator (email - mcc-saes@umn.edu). 
14.2 Reproduction Risks: N/A 
14.3 Risks to Others: N/A 
15.0 Incomplete Disclosure or Deception 
15.1 Incomplete Disclosure or Deception: N/A 
16.0 Potential Benefits to Participants 
16.1 Potential Benefits: We expect no immediate benefits for study participants. Some 
participants may appreciate contributing to a study that might benefit others 
diagnosed with cancer in the future.  
17.0 Statistical Considerations 
17.1 Data Analysis Plan:  

SOCIAL PROTOCOL (HRP-580) 
PROTOCOL TITLE: Time toxicity of cancer: the time demands of cancer-related activities and 
their impact on well-being and quality of life 
VERSION DATE: 02/27/2024 
 
 
  
 
Page 23 of 39 
Template Revised On: 06/302022 
 
Aim 1: For the time use component, we will focus on characterizing the distributions 
of summary measures of time use by activity and trip type. Similar to our previous 
work,[19] we will compute, for each activity/trip type, the number of minutes per 
day spent on that activity, the number of separate episodes, and the number of days 
per week on which that activity occurs. For common activities and trip types (home, 
work, driving), means and variances of these measures generally provide useful 
summaries of how individuals engage in these activities. For less common activities 
such as cancer care-related activities, total number of episodes, total time spent, 
and the mean/variance of episode duration may be more meaningful summary 
measures. 
Aim 2: Qualitative analysis component. Some individual circumstances (for example, 
competing time demands, level of support, flexibility of employers) that either 
buffer against or aggravate the burden cannot be easily ascertained from our app- 
and survey-based measurements. Therefore, we will examine free-text responses to 
open-ended survey questions. All entries will be transcribed. We will examine 
themes and consistencies. Two coders will read the entries and apply the constant 
comparative method to analyze and code data. As themes are identified, coders will 
return to the transcripts to reread and recode excerpts, thus ensuring that themes 
are grounded in data. A computer-assisted qualitative data analysis system (NVivo) 
will be used to enhance these analyses.  
Aim 3: Generating a time toxicity score. Using the Daynamica app-based 
spatiotemporal data collected in Aim 1, we will calculate time-based measures for 
each individual that characterize the degree of burden and disruption to daily life 
associated with receiving treatments for cancer. We propose to quantify four 
subtypes of time toxicity: episodic toxicity, travel toxicity, opportunity toxicity, and 
scheduling toxicity. Each of these subtypes is described by a different set of time-
based measures. Table 2 lists the four subtypes and describes the time-based 
measures that we will calculate to characterize each subtype.  
We will compute an individual's score for each time toxicity subtype by calculating 
an average of z-scores for each of the time-based measures associated with that 
subtype. This z-score averaging approach is commonly applied in a wide variety of 
domains to generate a single summary metric from observations taken on different 
subscales.[40-43] For example, if there are five time-based measures associated 
with a subtype (for example, those associated with Episodic Toxicity listed in Table 
2), then we will first compute a z-score for each measure by subtracting its average 
and dividing by its standard deviation across all individuals. All features will be 
transformed so that higher values correspond to higher time burdens. The summary 
score for the subtype will be computed by averaging the five z-scores, then 
converting the resulting average into a population percentile from a standard 
Normal random variable expressed as a number out of 100. For example, if the 

SOCIAL PROTOCOL (HRP-580) 
PROTOCOL TITLE: Time toxicity of cancer: the time demands of cancer-related activities and 
their impact on well-being and quality of life 
VERSION DATE: 02/27/2024 
 
 
  
 
Page 24 of 39 
Template Revised On: 06/302022 
 
average of the summary feature z-scores associated with travel toxicity is 1.05, then 
the travel toxicity score will be P(Z<1.05) x 100 = 85, while a z-score average of -0.42 
would lead to a travel toxicity score of P(Z<-0.42) x 100 = 34. 
Table 2. Time use subtypes and measures 
Toxicity Subtype 
Spatiotemporal Measures 
1. Episodic Toxicity 
Toxicity associated with 
activities directly related to 
care. 
• Number of days with a medical appointment per 
week 
• Number of days receiving treatment per week 
• Hours per week spent in medical appointments 
• Hours per week spent receiving treatment  
2. Travel / Wait Time Toxicity 
Toxicity associated with 
traveling to/from and waiting 
for medical appointments 
• Number of trips to/from appointments per week 
• Hours per week spent traveling to/from 
appointments 
• Hours per week spent waiting for appointments 
• Average distance traveled to/from medical 
appointments 
3. Opportunity Toxicity 
Toxicity associated with the 
opportunity cost of time spent 
on cancer treatment-related 
medical activities 
• Time spent on medical appointments as a 
fraction of time spent at home, on work, leisure, 
education, childcare, caregiving, and household 
• Proximity of medical appointment/treatment 
locations to individual points of interest (home, 
work, etc.) 
• Variation of schedule between days with and 
without a medical appointment 
4. Scheduling / Administrative 
Toxicity 
Toxicity associated with 
paperwork, scheduling 
appointments, dealing with bills 
and insurance, arrangement to 
accommodate cancer-related 
activities 
• Number of different locations associated with 
cancer care 
• Number of appointments per week 
• Hours per week spent on scheduling and 
administrative cancer work 
• Weekly variation in the duration of medical 
appointments and calls 
• Variation in time between medical activities 
The overall time toxicity score will be a weighted average of the four subtype 
scores 𝑆1, 𝑆2, 𝑆3, 𝑆4:𝑇 =  𝑤1𝑆1 + 𝑤2𝑆2 + 𝑤3𝑆3 + 𝑤4𝑆4 where the weights are 
constrained to sum to one. We will consider several versions of the time toxicity 
score defined by the relative weights of the various subtypes. The simplest time 
toxicity score is one where each subtype is assigned equal weight, and therefore the 
overall score is a simple average of the population percentiles across the four 
subtypes. For example, if an individual has subtype scores of 55, 75, 60, and 90, then 
their time toxicity score will be (55 + 75 + 60 + 90)/4 = 70, which suggests that their 
time toxicity burden is higher than approximately 70% of the population. In some 
scenarios, it may be appropriate to pre-specify non-equal weights for the different 

SOCIAL PROTOCOL (HRP-580) 
PROTOCOL TITLE: Time toxicity of cancer: the time demands of cancer-related activities and 
their impact on well-being and quality of life 
VERSION DATE: 02/27/2024 
 
 
  
 
Page 25 of 39 
Template Revised On: 06/302022 
 
subtypes; for example, personalized time toxicity scores could be generated based 
on individuals' prior weightings of each subtype, which, for example, might give 
opportunity toxicity more weight than travel toxicity. 
In addition to pre-specified (equal or unequal) weights, we will also use our daily 
burden and well-being measures to derive data-driven versions of the time toxicity 
score. Let 𝑀𝑖𝑗 denote the daily well-being measure of person i on day j. We will fit 
the model Mij = 𝛽0 + 𝛽2𝑋𝑖𝑗 + 𝜃1𝑆1𝑖𝑗+ 𝜃2𝑆2𝑖𝑗 + 𝜃3𝑆3𝑖𝑗+ 𝜃4𝑆4𝑖𝑗+ ϵij where 𝑋𝑖𝑗 
represents a set of individual, and day-level covariates, and 𝑆1𝑖𝑗, 𝑆2𝑖𝑗, 𝑆3𝑖𝑗, 𝑆4𝑖𝑗 are 
the subtype scores computed for person i on day j. The coefficients 
𝜃1, 𝜃2, 𝜃3, 𝜃4represent the relative weightings of the subtypes that best predict the 
mean of 𝑀 after adjusting for covariates. These coefficients will be standardized to 
yield weights using the formula 𝑤𝑘= 𝜃𝑘/∑𝜃𝑘. 
Our proposed approach to deriving time toxicity scores was developed with a view 
towards how this score may be used in clinical practice going forward. First, 
computation of the score relies only on time use summary metrics, which could be 
collected in a variety of ways. While the collection of these metrics is made 
substantially easier by the app, the time toxicity score could also be applied to time 
use summary metrics obtained via traditional diary-based recall methods. Second, 
the four component scores provide easy to understand insights into which types of 
time use are driving the overall score, and may allow clinicians and patients to 
better identify interventions (e.g., increased use of telehealth) that could reduce 
time toxicity. Lastly, the score can be easily adapted to different populations (by re-
weighting subtype scores), applied with incomplete data (by using either imputed or 
complete-case data to compute subtype scores), and computed across a range of 
time periods.  
17.2 Power Analysis:  
Aim 1: Our planned sample size of 80 participants strikes a balance between 
feasibility and statistical precision and power to estimate the quantities of interest. 
We will recruit 40 participants with breast and ovarian cancer undergoing treatment 
at each of the two sites over a two-year period. We do not anticipate any difficulties 
obtaining this sample size. The UMN and UAB sites combined treat approximately 80 
patients with newly diagnosed ovarian cancer, 100 with recurrent ovarian cancer, 
and 300 patients with metastatic breast cancer annually; therefore we will need to 
recruit <10% of eligible patients into this study over two years.  
For descriptive statistics of individual-level measures (e.g., mean number of minutes 
per week spent on cancer care related activities) on the entire sample, we will be 
able to estimate means of continuous measures with a margin of error of ±0.22 
standard deviations. For example, if the average number of minutes per week spent 
on cancer care in the sample was 250 with a standard deviation of 80, then the 95% 

SOCIAL PROTOCOL (HRP-580) 
PROTOCOL TITLE: Time toxicity of cancer: the time demands of cancer-related activities and 
their impact on well-being and quality of life 
VERSION DATE: 02/27/2024 
 
 
  
 
Page 26 of 39 
Template Revised On: 06/302022 
 
confidence interval for the mean number of minutes would be (232, 268). For 
comparing means of individual-level measures between two equal-sized subgroups 
(e.g., those with breast and ovarian cancer), our sample size yields 80% power to 
detect a difference of 0.64 standard deviations, equivalent to approximately 50 
minutes using the same standard deviation as above. Our power to detect 
associations and differences for day-level measures will be higher since we will have 
~20-28 (correlated) observations per person. 
Aim 2: Though we have a limited number of individuals in our study, we will have 
sufficient power to detect associations between daily time use and self-reported 
well-being as we will have 28 days of observations for each participant. To estimate 
power, we conducted a simulation study to estimate the effect size of a binary daily 
time use measure (e.g., whether or not a medical appointment occurred on a given 
day) and continuous well-being. We generated probabilities of having a medical 
appointment from a Beta(2,4) distribution and well-being measures from a linear 
mixed model calibrated to have a mean of 3, a (Normal) residual standard deviation 
of 1.5 units, and within-person correlation of approximately 0.4. With 28 days of 
observations on N=80 participants, we estimate that we will have approximately 
90% power to detect a difference of 0.25 units between days within different 
characteristics. An effect of this magnitude (approximately 5% of the range of the 1-
6 well-being scale) seems plausible and is at or below a threshold likely to be 
clinically meaningful. Power to detect associations between continuous time use 
measures (e.g., number of hours spent on medical appointments) and well-being 
will be higher than for the binary measures. 
Aim 3: The main target of inference in this aim is the association between the time 
toxicity score and survey measures at 28 days. With our planned sample size of 
n=80, we will have >80% power to detect a 0.4 standard deviation effect on survey 
measures associated with a 1 SD difference in the time toxicity score. Previous 
studies from our team among this target population identified a standard deviation 
of 17 points for the FACT-G QOL instrument,[44] hence a 0.4 SD effect would 
correspond to a difference of 6.8 points. This effect size corresponds to a "medium" 
effect on the FACT-G as suggested by a meta-analysis of studies using FACT-G as an 
outcome [45] and is in line with the effects demonstrated by supportive activities for 
cancer treatment such as muscle relaxation [46] and associations with co-occurring 
conditions such as skeletal morbidities.[47] Further, it has been previously shown 
that effect sizes of 0.35-0.5 are expected to be clinically relevant for QOL 
measures.[48] 
17.3 Statistical Analysis:  
Aim 1: These per-activity summary measures will be used as outcomes in 
generalized linear regression models to quantify differences between relevant 
subgroups (e.g., those caring for dependents vs. not, those experiencing higher vs. 

SOCIAL PROTOCOL (HRP-580) 
PROTOCOL TITLE: Time toxicity of cancer: the time demands of cancer-related activities and 
their impact on well-being and quality of life 
VERSION DATE: 02/27/2024 
 
 
  
 
Page 27 of 39 
Template Revised On: 06/302022 
 
lower treatment burden) adjusting for individual demographic and clinical 
characteristics. For example, we will be able to compute covariate-adjusted 
differences in the total number of episodes and minutes spent on various cancer 
care-related activities between patients with and without dependents, which will 
provide insight into how family structure affects the time burden of care. Random 
effects models will be used to quantify associations between factors that vary day to 
day within individuals and time use outcomes, e.g., to understand whether 
completing a cancer care-related task on a given day affects the number of hours 
spent working or engaged in leisure activities. In addition, we will apply techniques 
developed by Dr. Wolfson and colleagues [49] to describe day-level activity patterns 
via sequence alignment (see Figure 1). These techniques will allow us to identify 
clusters of days with similar activity sequences, and quantify how individual 
participants' characteristics determine their likelihood of experiencing these 
different day archetypes. 
Aim 2: Relating cancer-related time use measures to self-reported well-being. 
Associations between time use and daily well-being measures will be quantified via 
longitudinal regression modeling. We will use generalized linear mixed models to 
describe the longitudinal relationship between daily time use summary measures 
(calculated in Aim 1) and self-reported daily well-being. Separate models will be 
fitted for each of the six daily well-being measures along with an overall well-being 
score, the U-index.[50, 51] Models will be of the form 𝑔([𝐸(𝑊𝑖𝑗
(𝑟))])
= 𝛽0 +
 𝛽1𝑇𝑖𝑗+ 𝛽2𝑋𝑖𝑗+ 𝑏𝑖+ 𝜖𝑖𝑗where 𝑊𝑖𝑗
(𝑟) is the rth well-being measure (e.g., Happy, 
Sad, Stress) reported by person i on day j; g is a function depending on the 
regression model type; 𝑏𝑖 is a person-specific random effect, and 𝜖𝑖𝑗is the residual. 
The predictors of interest 𝑇𝑖𝑗 are a vector of daily time use measures (time spent on 
medical appointments, number of medical-related phone calls, etc.). 𝑋𝑖𝑗is a vector 
of covariates for adjustment including both individual-level (age, race, cancer type, 
etc.) and day-level (day of the week, time of year, time since initiation of the current 
round of treatment, etc.) factors. Mixed models are chosen to account for 
correlation of repeated measurements over the course of the 28-day mobile data 
collection period. The main output from these analyses will be inference about the 
coefficients in 𝛽1, which summarize the association between time use measures and 
self-reported well-being. In addition to models of the type presented above, which 
correlate well-being with time use on the same day, we will also fit models using 
time use summary measures that aggregate time use longitudinally. These models 
will allow us, for instance, to assess whether aggregated cancer-related time use 
over the past week is a stronger predictor of daily well-being than time use on the 
current day only.  
Defining and exploring the role of context as an effect modifier. We will use 
quantitative and qualitative approaches to understand the role of context in 

SOCIAL PROTOCOL (HRP-580) 
PROTOCOL TITLE: Time toxicity of cancer: the time demands of cancer-related activities and 
their impact on well-being and quality of life 
VERSION DATE: 02/27/2024 
 
 
  
 
Page 28 of 39 
Template Revised On: 06/302022 
 
modifying the association between cancer-related time use and well-being. Given 
limited sample size, we view the results from this part of the analysis as primarily 
hypothesis generating to guide future work. For the quantitative component of this 
analysis, we will follow two approaches. First, we will identify time use measures 
that appear moderately or strongly associated with self-reported well-being and run 
exploratory analyses to assess whether there is preliminary evidence that these 
associations are modified by well-established individual predictors of time use, in 
particular age, employment status, and family structure, as well as day- and 
individual-level contextual time use. To maximize statistical power, we will consider 
each candidate pair of measures of time use and well-being separately, by fitting 
models with main effects for the time use measure and potential moderator as well 
as an interaction term between them. Given limited sample size, we expect 
confidence intervals for moderation effects to be wide, and hence will focus 
primarily on their estimated magnitude. Second, we will derive covariates that 
define day-level time use patterns. For example, we will apply unsupervised 
clustering methods to identify common day structures (e.g., workday, stay at home, 
multiple errands). We will evaluate these derived day structures as potential 
modifiers of the association between time use and well-being; for example, to 
assess whether medical appointments on a workday lead to higher levels of stress 
than those that occur on a day mostly spent at home. To identify clusters of days 
with similar time use patterns, we will use standard k-means clustering [52] applied 
directly to time use measures as well as a novel sequence alignment-based 
approaches for identifying daily activity patterns recently co-developed by co-PI 
Wolfson.[49] For the k-means clustering, measures will be normalized so that 
distances between all measures are on the same scale. As the number of study 
participants is limited, we will constrain our clustering methods to generate a small 
number of clusters (3-5) so that each cluster contains a sufficient number of days to 
allow us to assess its effect on well-being. 
Aim 3: To assess the association between time toxicity scores and survey-based 
measures (e.g. QOL), we will calculate individual time toxicity scores over the data 
collection period and fit linear regression models of the form 𝑀𝑒 = 𝛾0 + 𝛾1𝑆+
𝛾2𝑀𝑏+ 𝛾3𝑋 +  𝜖 where 𝑀𝑒 and 𝑀𝑏 are survey measures taken at the beginning and 
end of the data collection period, 𝑆 is the time toxicity score, and 𝑋 is a set of 
individual-level covariates for adjustment. Separate models will be fit for each 
survey instrument used (e.g., FACT-G for QOL, HADS for depression and anxiety). 
Initially, we will fit unadjusted versions of these models (with 𝛾3 = 0) to assess 
whether the time toxicity score is associated with the final survey measurement, 
controlling only for the baseline survey measurement. Then, we will fit covariate-
adjusted models to see whether associations between the time toxicity score and 
survey measures remain after controlling for individual characteristics. In 
exploratory analyses, we will investigate whether the associations between the time 

SOCIAL PROTOCOL (HRP-580) 
PROTOCOL TITLE: Time toxicity of cancer: the time demands of cancer-related activities and 
their impact on well-being and quality of life 
VERSION DATE: 02/27/2024 
 
 
  
 
Page 29 of 39 
Template Revised On: 06/302022 
 
toxicity score and survey measures are modified by individual-level covariates by 
including 𝑆× 𝑋 interaction terms in the above regression model. Finally, we will 
investigate whether specific subtype scores are more strongly associated with 
survey measures by replacing the overall time toxicity score in the above model by 
the four subtype scores.  
17.4 Data Integrity: Data integrity and completeness will be monitored on an ongoing 
basis by the study coordinator and statistician, using both the reporting tools 
provided by REDCap and the study/data management dashboard associated with 
the app. 
18.0 Health Information and Privacy Compliance 
18.1 Select which of the following is applicable to your research: 
☐ My research does not require access to individual health information and 
therefore assert HIPAA does not apply. If this option is selected, please skip to 
Section 19. 
X I am requesting that all research participants sign a HIPCO approved HIPAA 
Disclosure Authorization to participate in the research (either the standalone 
form or the combined consent and HIPAA Authorization). 
☐ I am requesting the IRB to approve a Waiver or an alteration of research 
participant authorization to participate in the research. 
Appropriate Use for Research:  
☐ An external IRB (e.g. Advarra) is reviewing and we are requesting use of the 
authorization language embedded in the template consent form in lieu of the U 
of M stand-alone HIPAA Authorization. Note: External IRB must be serving as 
the privacy board for this option. 
18.2 
Identify the source of Private Health Information you will be using for your 
research (Check all that apply)  
☐ I will use the Informatics Consulting Services (ICS) available through CTSI (also 
referred to as the University's Information Exchange (IE) or data shelter) to pull 
records for me 
X I will collect information directly from research participants. 
☐ I will use University services to access and retrieve records from the Bone 
Marrow Transplant (BMPT) database, also known as the HSCT (Hematopoietic 
Stem Cell Transplant) database. 

SOCIAL PROTOCOL (HRP-580) 
PROTOCOL TITLE: Time toxicity of cancer: the time demands of cancer-related activities and 
their impact on well-being and quality of life 
VERSION DATE: 02/27/2024 
 
 
  
 
Page 30 of 39 
Template Revised On: 06/302022 
 
X I will pull records directly from EPIC. 
☐ I will retrieve record directly from axiUm / MiPACS 
☐ I will receive data from the Center for Medicare/Medicaid Services  
X I will receive a limited data set from another institution  
Study coordinators at outside participating sites (e.g. University of Alabama 
Birmingham) will be reviewing the medical records of their participants at their 
site and entering the appropriate data in REDCap. This will include details 
regarding cancer diagnosis, stage, treatments received, hospitalizations and other 
medical encounters related to cancer diagnosis and treatment.  
☐ Other. Describe:  
18.3 
Explain how you will ensure that only records of patients who have agreed to have 
their information used for research will be reviewed. 
The study coordinators will confirm that the patient has not declined research (we 
will not approach patients with "Research Opt-out" status indicated their medical 
record, in order to comply with Minnesota Statute 144.651, subdivision 13). 
18.4 Approximate number of records required for review: N/A 
18.5 
Please describe how you will communicate with research participants during the 
course of this research. Check all applicable boxes 
☐ This research involves record review only. There will be no communication with 
research participants. 
☐ Communication with research participants will take place in the course of 
treatment, through MyChart, or other similar forms of communication used 
with patients receiving treatment.  
X Communication with research participants will take place outside of treatment 
settings. If this box is selected, please describe the type of communication and 
how it will be received by participants.  
Communication with potential and consented participants will occur in-person 
during other scheduled clinic visits and by phone. Individuals interested in 
electronic consent will be emailed those materials directly from REDCap. 
Surveys will be mailed or emailed directly from REDCap. Enrolled and consented 
participants who complete an email authorization form may be contacted about 
the app use and data collection via email during the study period. 
 

SOCIAL PROTOCOL (HRP-580) 
PROTOCOL TITLE: Time toxicity of cancer: the time demands of cancer-related activities and 
their impact on well-being and quality of life 
VERSION DATE: 02/27/2024 
 
 
  
 
Page 31 of 39 
Template Revised On: 06/302022 
 
18.6 Access to participants 
Participants will complete consent and HIPAA forms prior to any data collection. 
After they agree to participate, all data will be provided by the participants and 
from review of their medical records.  
18.7  Location(s) of storage, sharing and analysis of research data, including any links to 
research data (check all that apply).  
☐ In the data shelter of the Information Exchange (IE)  
 ☐ Store  ☐ Analyze 
☐ Share 
☐ In the Bone Marrow Transplant (BMT) database, also known as the HSCT 
(Hematopoietic Stem Cell Transplant) Database  
 ☐ Store 
☐ Analyze 
☐ Share 
X In REDCap (recap.ahc.umn.edu)  
 X Store 
X Analyze 
X Share 
☐ In Qualtrics (qualtrics.umn.edu) 
 ☐ Store 
☐ Analyze 
☐ Share 
☐ In OnCore (oncore.umn.edu)  
 ☐ Store 
☐ Analyze 
☐ Share 
X In the University’s Box Secure Storage (box.umn.edu) 
 X Store 
X Analyze 
X Share 
X In an AHC-IS supported server. Provide folder path, location of server and IT 
Support Contact: 
IT Support Contact: 
IT Contact: Mike Doherty        
\\cancer.ahc.umn.edu\cancer\CancerCenter\CCSG\Vogel, RI\time_toxicity 
 X Store  
X Analyze 
☐ Share 
☐ In an AHC-IS supported desktop or laptop.  
Provide UMN device numbers of all devices: 

SOCIAL PROTOCOL (HRP-580) 
PROTOCOL TITLE: Time toxicity of cancer: the time demands of cancer-related activities and 
their impact on well-being and quality of life 
VERSION DATE: 02/27/2024 
 
 
  
 
Page 32 of 39 
Template Revised On: 06/302022 
 
 ☐ Store 
☐ Analyze 
☐ Share 
☐ Other.  
Indicate if data will be collected, downloaded, accessed, shared or stored using a 
server, desktop, laptop, external drive or mobile device (including a tablet computer 
such as an iPad or a smartform (iPhone or Android devices) that you have not 
already identified in the preceding questions 
☐I will use a server not previously listed to collect/download research data 
☐I will use a desktop or laptop not previously listed 
☐I will use an external hard drive or USB drive (“flash” or “thumb” drives) not 
previously listed  
☐I will use a mobile device such as an tablet or smartphone not previously listed 
18.8 Consultants. Vendors. Third Parties.  
Participants will use a modified version of a mobile application provided by 
Daynamica, Inc. to collect data on their daily activities. Details of the application and 
storage process are provided in detail in Section 6.1 and will be controlled by UMN 
HST.   
18.9 Links to identifiable data: When patients agreed to participate, they will be given a 
study ID which will be used for the remainder of the study. The identifying 
information will be stored in REDCap (survey data collection) with the study ID and 
all other data will be stored using this ID alone.   
18.10 Sharing of Data with Research Team Members. Data will be shared using Box and 
REDCap. 
18.11 Storage of Documents: All consent, HIPAA, email authorization, and survey paper 
forms will be stored in locked cabinets within locked offices/spaces. Electronic 
copies will be stored within REDCap, Box and on the AHC server space described 
above.  
18.12 Disposal of Documents: Following publication and dissemination (up to 10 years 
post study initiation), all paper documents will be shredded and all identifying 
information in REDCap will be removed. 
19.0 Confidentiality 
19.1 Data Security: All study investigators and staff will be fully trained on data safety and 
participant confidentiality. An electronic copy of the signed consent form will be 
stored on an AHC-IS supported server. Participants’ research data will not be placed 
in the participants’ medical record. 

SOCIAL PROTOCOL (HRP-580) 
PROTOCOL TITLE: Time toxicity of cancer: the time demands of cancer-related activities and 
their impact on well-being and quality of life 
VERSION DATE: 02/27/2024 
 
 
  
 
Page 33 of 39 
Template Revised On: 06/302022 
 
Medical record data will be entered by the study coordinator and will be stored on 
the secure REDCap database. Study data will be de-identified before data analysis. 
Only the researchers directly involved with the study will have access to the data. 
Identifying data will be stored until completion of the study and manuscript 
submission.  
Data collected by the Daynamica app will be uploaded to and stored on a secure HST 
server on a daily basis. As noted previously, all data will be referenced with study 
code numbers; the master file linking these codes to participant contact information 
will be stored separately.  
Study staff involved in data collection will only have access to Daynamica data via 
the data quality dashboard described in the previous section.  The dashboard 
provides data quality summary statistics such as the number of trips and activities 
that have been recorded by the app for each individual. It does not provide any 
access to individual-level demographic or location information. Only the study 
investigators will have access to both the full suite of uploaded data and the master 
file linking participant identifiers to contact information. After completion of the 
study, the master link file will be destroyed, so that all remaining data will not be 
connected to individual participant contact information. 
19.2 Data Sharing: See Section 6.1. The University of Minnesota Libraries / DRUM will 
work with the investigative team to ensure the data are de-identified before they 
are made available to others.  
20.0 Provisions to Monitor the Data to Ensure the Safety of Participants 
20.1 Data Integrity Monitoring. The PI will review all signed consent forms for 
completeness at the time of participant entry into the study. The integrity of the 
data collected via the mobile app will be monitored by the PI and study staff using a 
password-protected, web-based study manager application. 
20.2  Data Safety Monitoring. This study carries minimal risk and therefore the PI will 
assume responsibility for monitoring and reporting safety concerns/events to the 
University of Minnesota IRB. Events requiring prompt reporting include any adverse 
event that requires a change to the protocol or consent form, any unauthorized 
disclosure of confidential information, any unresolved subject complaint or any 
protocol deviation that resulting in harm or the unanticipated death of an enrolled 
subject.  Compensation for Research-Related Injury 
21.0 Compensation for Research-Related Injury 
21.0 Compensation for Research-Related Injury: N/A 
21.1 Contract Language: N/A 
 

SOCIAL PROTOCOL (HRP-580) 
PROTOCOL TITLE: Time toxicity of cancer: the time demands of cancer-related activities and 
their impact on well-being and quality of life 
VERSION DATE: 02/27/2024 
 
 
  
 
Page 34 of 39 
Template Revised On: 06/302022 
 
22.0 Consent Process 
22.0 Consent Process (when consent will be obtained): All potential study participants 
will be provided a paper or electronic copy of the IRB-approved consent to review at 
a scheduled clinic visit at the oncology clinic or from home. Regardless of method, 
potential participants will be encouraged to ask for more information before 
deciding whether or not they would like to participate in the study. 
In-person consent: In an area of the clinic where the conversation cannot be 
overheard, the PI or study coordinator will explain all aspects of the study in lay 
language and answer all questions regarding the study. If the participant decides to 
participate in the study, they will be asked to sign and date the consent and HIPAA 
documents (paper or electronic using the e-consent functionality in REDCap). The 
study coordinator/person obtaining written consent will also sign and date the 
consent document (paper or electronically). Participants will also receive a signed 
and dated copy of the consent and HIPAA forms (paper copy or emailed PDFs).  
Remote consent: Individuals approached in the clinic may review the documents 
and consent at a later time online. Online consents and HIPAA forms will obtain 
signatures captured electronically via the e-consent functionality in REDCap. 
Individuals interested in this option will be emailed a link specifically for them to 
invite them to review and complete the documents. The recruiting coordinator will 
electronically sign and date the documents following completion by the participant.  
Electronic signatures will be stored within REDCap as well as a copy on the Academic 
Health Center (AHC) secure servers. Access to these records will be limited to the 
study team as needed or required. 
Patients who refuse to participate or who withdraw from the study will be treated 
without prejudice.   
22.1 Waiver or Alteration of Consent Process (when consent will not be obtained, 
required information will not be disclosed, or the research involves deception): N/A 
22.2 Waiver of Written/Signed Documentation of Consent (when written/signed consent 
will not be obtained): N/A 
22.3 Non-English Speaking Participants: N/A 
22.4 Participants Who Are Not Yet Adults (infants, children, teenagers under 18 years of 
age): N/A 
22.5 Cognitively Impaired Adults, or adults with fluctuating or diminished capacity to 
consent: N/A 
22.6 Adults Unable to Consent: N/A 
 

SOCIAL PROTOCOL (HRP-580) 
PROTOCOL TITLE: Time toxicity of cancer: the time demands of cancer-related activities and 
their impact on well-being and quality of life 
VERSION DATE: 02/27/2024 
 
 
  
 
Page 35 of 39 
Template Revised On: 06/302022 
 
23.0 Setting 
23.0 Research Sites: Participants will be recruited through the University of 
Minnesota/MHealth Fairview network and through the University of Alabama 
Birmingham. All study procedures will be conducted at cancer clinics within these 
networks or remotely.  
23.1 International Research: N/A 
23.2 Community Based Participatory Research: N/A 
 
24.0 Multi-Site Research 
24.0 Study-Wide Number of Participants: Up to 100  
24.1 Study-Wide Recruitment Methods: Participants will be recruited by site-specific staff 
following the procedures described in section 12.0 (Local Recruitment methods).  
24.2 Study-Wide Recruitment Materials: Example study summary sheets and mail 
recruitment letter are included. 
24.3 Communication Among Sites: Communication between sites be managed by the PI 
and UMN project manager. Both sites will have the most current version of the 
protocol, consent documents, and, HIPAA authorization. All modifications will be 
communicated to sites, and approved by the University of Minnesota IRB before the 
modification is implemented. All non-compliance with the study protocol or 
applicable requirements will be reported in accordance with university or local 
policy. 
24.4 Communication to Sites: Regular teleconferences to facilitate communication 
between participating sites regarding the study’s progress, patient updates, data 
completion, and other issues for discussion. The PI and University of Minnesota 
project manager will communicate more frequently as the study nears closure to 
ensure we do not over-enroll.  
25.0 Coordinating Center Research N/A 
26.0 Resources Available 
26.1 Resources Available:  
All investigators are committed to this project and will provide appropriate effort as 
needed. This study will be supported by an NIH R01 to Drs. Vogel and Wolfson with a 
subaward to Dr. Roque at UAB. Drs. Vogel and Wolfson will have appropriate 
dedicated time to oversee and conduct the research described.  
All members of the study team have reviewed and approved the protocol and study 
procedures. They have understood their duties and study roles, and provide the 

SOCIAL PROTOCOL (HRP-580) 
PROTOCOL TITLE: Time toxicity of cancer: the time demands of cancer-related activities and 
their impact on well-being and quality of life 
VERSION DATE: 02/27/2024 
 
 
  
 
Page 36 of 39 
Template Revised On: 06/302022 
 
skills needed to conduct the study and study analyses. All members of the research 
team have relevant publication records. They have also completed appropriate 
trainings and these trainings will be revisited as appropriate, particularly for those 
involved directly with participants in the consent process and/or data collection. 
27.0 References 
1. 
Caldwell, L.L., Leisure and health: why is leisure therapeutic? British Journal of 
Guidance & Counselling, 2005. 33(1): p. 7-26. 
2. 
Kleiber, D.A., S.L. Hutchinson, and R. Williams, Leisure as a Resource in Transcending 
Negative Life Events: Self-Protection, Self-Restoration, and Personal Transformation. 
Leisure Sciences, 2002. 24(2): p. 219-235. 
3. 
Smith, J.L. and I.J. Hall, Advancing health equity in cancer survivorship: opportunities 
for public health. American journal of preventive medicine, 2015. 49(6): p. S477-
S482. 
4. 
Alcaraz, K.I., et al., Understanding and addressing social determinants to advance 
cancer health equity in the United States: a blueprint for practice, research, and 
policy. CA: a cancer journal for clinicians, 2020. 70(1): p. 31-46. 
5. 
Blinder, V.S. and J.J. Griggs, Health disparities and the cancer survivor. Semin Oncol, 
2013. 40(6): p. 796-803. 
6. 
Hoffman, K.M., et al., Racial bias in pain assessment and treatment 
recommendations, and false beliefs about biological differences between blacks and 
whites. Proc Natl Acad Sci U S A, 2016. 113(16): p. 4296-301. 
7. 
Zafar, S.Y. and A.P. Abernethy, Financial toxicity, Part I: a new name for a growing 
problem. Oncology (Williston Park), 2013. 27(2): p. 80-1, 149. 
8. 
Lin, C.C., et al., Association Between Geographic Access to Cancer Care, Insurance, 
and Receipt of Chemotherapy: Geographic Distribution of Oncologists and Travel 
Distance. J Clin Oncol, 2015. 33(28): p. 3177-85. 
9. 
Onega, T., et al., The influence of travel time on breast cancer characteristics, receipt 
of primary therapy, and surveillance mammography. Breast Cancer Res Treat, 2011. 
129(1): p. 269-75. 
10. Blumenberg, E., A. Brown, and A. Schouten, Car-deficit households: determinants 
and implications for household travel in the U.S. Transportation, 2020. 47. 
11. May, C.R., et al., Rethinking the patient: using Burden of Treatment Theory to 
understand the changing dynamics of illness. BMC Health Serv Res, 2014. 14: p. 281. 
12. Shippee, N.D., et al., Cumulative complexity: a functional, patient-centered model of 
patient complexity can improve research and practice. J Clin Epidemiol, 2012. 65(10): 
p. 1041-51. 
13. Tran, V.-T., et al., Development and description of measurement properties of an 
instrument to assess treatment burden among patients with multiple chronic 
conditions. BMC medicine, 2012. 10(1): p. 1-10. 

SOCIAL PROTOCOL (HRP-580) 
PROTOCOL TITLE: Time toxicity of cancer: the time demands of cancer-related activities and 
their impact on well-being and quality of life 
VERSION DATE: 02/27/2024 
 
 
  
 
Page 37 of 39 
Template Revised On: 06/302022 
 
14. Eton, D.T., et al., Development and validation of the Patient Experience with 
Treatment and Self-management (PETS): a patient-reported measure of treatment 
burden. Quality of Life Research, 2017. 26(2): p. 489-503. 
15. Rocque, G.B., et al., Health care-related time costs in patients with metastatic breast 
cancer. Cancer Med, 2020. 9(22): p. 8423-8431. 
16. Gupta, A., et al., Reducing Wait Time Between Admission and Chemotherapy 
Initiation. J Oncol Pract, 2018. 14(5): p. e316-e323. 
17. Parsons, H.M., et al., Impact of cancer on work and education among adolescent and 
young adult cancer survivors. J Clin Oncol, 2012. 30(19): p. 2393-400. 
18. Gupta, A., et al., Time-Related Burdens of Cancer Care. JCO Oncol Pract, 2021: p. 
OP2100662. 
19. Fan, Y., et al., Understanding trip happiness using smartphone-based data: the 
effects of trip-and person-level characteristics. Findings, 2019: p. 7124. 
20. Le, H.T., et al., Expanding the positive utility of travel through weeklong tracking: 
Within-person and multi-environment variability of ideal travel time. Journal of 
Transport Geography, 2020. 84: p. 102679. 
21. Glasgow, T.E., et al., How transport modes, the built and natural environments, and 
activities influence mood: A GPS smartphone app study. Journal of Environmental 
Psychology, 2019. 66: p. 101345. 
22. Lal, R.M., et al., Connecting Air Quality with Emotional Well-Being and Neighborhood 
Infrastructure in a US City. Environ Health Insights, 2020. 14: p. 1178630220915488. 
23. Brown, R., et al., Iterated multisource exchangeability models for individualized 
inference with an application to mobile sensor data. Biometrics, 2021. 77(2): p. 401-
412. 
24. Ambrose, G., et al., Is gardening associated with greater happiness of urban 
residents? A multi-activity, dynamic assessment in the Twin-Cities region, USA. 
Landscape and Urban Planning, 2020. 198: p. 103776. 
25. Brown, R., A Statistical Framework for Harnessing Human Activity Data to 
Understand Behavior, Health, and Well-Being, in Biostatistics. 2020, University of 
Minnesota: University of Minnesota Digital Conservancy. 
26. Fan, Y., et al., Smartphone-Based Interventions for Sustainable Travel Behavior: The 
University of Minnesota Parking Contract Holder Study. 2020. 
27. Sprangers, M., Quality of life assessment in Oncology. Acta Oncol, 2002. 41: p. 229-
237. 
28. Butow, P.N., A.S. Coates, and S.M. Dunn, Psychosocial predictors of survival in 
metastatic melanoma. J Clin Oncol, 1999. 17(7): p. 2256-63. 
29. Lehto, U.S., et al., Baseline psychosocial predictors of survival in localized melanoma. 
J Psychosom Res, 2007. 63(1): p. 9-15. 
30. Chiarion-Sileni, V., et al., Quality of life evaluation in a randomised trial of 
chemotherapy versus bio-chemotherapy in advanced melanoma patients. Eur J 
Cancer, 2003. 39(11): p. 1577-85. 

SOCIAL PROTOCOL (HRP-580) 
PROTOCOL TITLE: Time toxicity of cancer: the time demands of cancer-related activities and 
their impact on well-being and quality of life 
VERSION DATE: 02/27/2024 
 
 
  
 
Page 38 of 39 
Template Revised On: 06/302022 
 
31. Cella, D.F., et al., The Functional Assessment of Cancer Therapy scale: development 
and validation of the general measure. Journal of clinical oncology, 1993. 11(3): p. 
570-579. 
32. Basen-Engquist, K., et al., Reliability and validity of the functional assessment of 
cancer therapy-ovarian. J Clin Oncol, 2001. 19(6): p. 1809-17. 
33. Jacobsen, P.B., et al., Screening for psychologic distress in ambulatory cancer 
patients: a multicenter evaluation of the distress thermometer. Cancer, 2005. 103(7): 
p. 1494-1502. 
34. Mitchell, A.J., Short screening tools for cancer-related distress: a review and 
diagnostic validity meta-analysis. Journal of the National Comprehensive Cancer 
Network, 2010. 8(4): p. 487-494. 
35. Cleeland, C.S., et al., Assessing symptom distress in cancer patients: the M.D. 
Anderson Symptom Inventory. Cancer, 2000. 89(7): p. 1634-46. 
36. Handley, N.R., et al., Development of the Oncology Opportunity Cost Assessment 
Tool: Item Generation and Content Validity Testing. JCO Oncol Pract, 2021: p. 
OP2100288. 
37. Souza, J.A., et al., The development of a financial toxicity patient‐reported outcome 
in cancer: the COST measure. Cancer, 2014. 120(20): p. 3245-3253. 
38. Blanchard, C., K. Courneya, and K. Stein, Cancer survivors' adherence to lifestyle 
behavior recommendations and associations with health-related quality of life: 
Results from the American Cancer Society's SCS-II. Journal of Clinical Oncology, 2008. 
26(13): p. 2198-2204. 
39. National Center for Health Statistics, National Health Interview Surveys. 2000-2010, 
Centers for Disease Control: Hyattsville, Maryland. 
40. Kalmijn, S., et al., Metabolic cardiovascular syndrome and risk of dementia in 
Japanese-American elderly men. The Honolulu-Asia aging study. Arterioscler Thromb 
Vasc Biol, 2000. 20(10): p. 2255-60. 
41. Gottman, J.M. and L.J. Krokoff, Marital interaction and satisfaction: a longitudinal 
view. J Consult Clin Psychol, 1989. 57(1): p. 47-52. 
42. Rodrigue, J.R., G.R. Geffken, and S.B. Morgan, Perceived competence and behavioral 
adjustment of siblings of children with autism. J Autism Dev Disord, 1993. 23(4): p. 
665-74. 
43. BenAri, O., et al., A double-blind placebo-controlled clinical trial testing the effect of 
hyperbaric oxygen therapy on brain and cognitive outcomes of mildly cognitively 
impaired elderly with type 2 diabetes: Study design. Alzheimers Dement (N Y), 2020. 
6(1): p. e12008. 
44. Jewett PI, T.D., Petzel S, Lee H, Messelt A, Kendall J, Hatuskami D, Everson-Rose SA, 
Blaes AH, Vogel RI, Cancer-Related Distress:  Revisiting The Utility Of The National 
Comprehensive Cancer Network Distress Thermometer Problem List In A Cohort Of 
Individuals With Gynecologic Cancers. Journal of Oncology Practice, 2020. 

SOCIAL PROTOCOL (HRP-580) 
PROTOCOL TITLE: Time toxicity of cancer: the time demands of cancer-related activities and 
their impact on well-being and quality of life 
VERSION DATE: 02/27/2024 
 
 
  
 
Page 39 of 39 
Template Revised On: 06/302022 
 
45. King, M.T., et al., Meta-analysis provides evidence-based effect sizes for a cancer-
specific quality-of-life questionnaire, the FACT-G. J Clin Epidemiol, 2010. 63(3): p. 
270-81. 
46. Paras-Bravo, P., et al., The impact of muscle relaxation techniques on the quality of 
life of cancer patients, as measured by the FACT-G questionnaire. PLoS One, 2017. 
12(10): p. e0184147. 
47. DePuy, V., et al., Effects of skeletal morbidities on longitudinal patient-reported 
outcomes and survival in patients with metastatic prostate cancer. Support Care 
Cancer, 2007. 15(7): p. 869-76. 
48. Norman, G.R., J.A. Sloan, and K.W. Wyrwich, Interpretation of changes in health-
related quality of life: the remarkable universality of half a standard deviation. Med 
Care, 2003. 41(5): p. 582-92. 
49. Song, Y., et al., Visualizing, clustering, and characterizing activity-trip sequences via 
weighted sequence alignment and function data analysis. Transportation Research 
Part C: Emerging Technologies, 2021. 126(103007). 
50. Kahneman, D. and A.B. Krueger, Developments in the Measurement of Subjective 
Well-Being. Journal of Economic Perspectives, 2006. 20(1): p. 3-24. 
51. Krueger, A.B. and D.A. Schkade, The Reliability of Subjective Well-Being Measures. J 
Public Econ, 2008. 92(8-9): p. 1833-1845. 
52. Hartigan, J. and M. Wong, A k-means clustering algorithm. Journal of the Royal 
Statistical Society, 1979. 28(1): p. 100-8.