Symptoms and General Pathology

All Conditions

Neoplasms

Mouth and Tooth Diseases

Digestive System Diseases

Pain

Head and Neck Neoplasms

Stomatitis

Mucositis

Gastroenteritis

Gastrointestinal Diseases

Mouth Diseases

Stomatognathic Diseases

This study examines whether the smartphone OM Pain App is a feasible and valid tool to assess pain from radiation-induced oral mucositis.

Each study participant will be issued an Android smartphone, or he or she may use his/her own compatible device (whether or not it has an active data service) to which the OM Pain App will be downloaded and installed. Subjects will receive a preprogrammed alarm four times a day from their smartphones prompting them to directly enter OM pain levels on the device. Patients may submit as many pain entries as they wish beyond the four minimum levels.

Subjects will receive a preprogrammed alarm four times a day from their smartphones prompting them to directly enter OM pain levels on the device. Patients may submit as many pain entries as they wish beyond the four minimum levels.

OM Pain App

Each patient will be issued an accelerometer and will be encouraged to wear it continuously during the study period (weekly during radiation therapy and four weeks following radiation therapy).

Accelerometer

Stuart J Wong, MD

This research is being done to evaluate whether or not the Oral Mucositis (OM) Pain App (a smartphone application) is a feasible and valid tool to assess pain from radiation sores (also referred to as "mucositis") when treating head and neck cancers with radiation. The mobile app will be designed to help people better understand the pain from the radiation sores.

OVERVIEW: This is a single-arm, observational, supportive care clinical trial for patients with tumors involving the oral cavity, oropharynx, or unknown primary expecting to receive at least a 50 Gy dose of definitive radiation therapy.

OM PAIN APP (DESCRIPTION): The Oral Mucositis (OM) PAIN APP (App) is a smartphone application that was designed to permit patients to key in pain severity, using a visual analog 0-10 scale. The App is programed with an alarm to prompt the patient to record pain severity at prescribed intervals daily and through spontaneous patient input. Data collected on each patient's smartphone can be backed up wirelessly to a central server where the data can be analyzed remotely or data can be viewed on the device. The software is capable of generating a time-weighted measure of pain, total area under the pain cure (AUC), a summary measure that integrates serial assessments of a patient's pain over the duration of the study.

DAILY OBSERVATION: Subjects will receive a preprogrammed alarm four times a day from their smartphones prompting them to directly enter OM pain levels on the device. Patients may submit as many pain entries as they wish beyond the four minimum levels. Data recording will not commence until radiation starts. Because symptoms of mucositis do not commence typically until the third week of radiation therapy, and no sooner than week 2, recordings from week 1 will be used for baseline data. Recording of data will cease four weeks after the end of radiation therapy at which time mucositis symptoms typically start to resolve and pain symptoms substantially abate.

ACCELEROMETER: Each patient will be issued an accelerometer and will be encouraged to wear it continuously during the study period. To help determine whether decline in physical activity is associated with severity of pain, physical activity will be assessed directly with accelerometers (activity monitor). Participants will wear an accelerometer during sleep and waking hours, but not while bathing, starting one week prior to the start radiation therapy. Accelerometer output data will be obtained in 1-minute epochs that will be then summed to provide raw daily average activity units, which will be subsequently divided by 1000 for clarity. Data will by synced weekly by the study coordinator to a computer connected to a central server.

Smartphone Pain App for Assessing Oral Mucositis Pain in Patients

Smartphone Pain App for Assessing Oral Mucositis Pain in Patients Receiving Head and Neck Radiation Therapy

The study coordinator will download data and check the equipment weekly for proper functioning and compliance. Patients will be interviewed weekly to assure the device is functioning correctly and that data is being recorded.

Stuart Wong

Professor, Department of Medicine, Division of Hematology/Oncology

All subjects eligible for inclusion in this study will receive usual care physiotherapy treatment. The number of treatment sessions and content of physiotherapy treatment sessions will depend on the diagnosis and needs of the individual patient. This study will not interfere with the content of the usual care physiotherapy treatment. Usual care physiotherapy sessions wil take approximately 20-30 minutes per session. They receive no additional intervention and will not use Hospital Fit as part of their physiotherapy treatment. The patients in the control group will receive an activity monitor to collect data about their physical activity levels. However, patients and their healthcare professionals will not receive feedback on patients' physical activity levels.

Patients in the intervention group will receive usual care physiotherapy and us Hospital Fit additionally. At the end of the last physiotherapy treatment session before discharge, or after a maximum of nine days of study inclusion (whichever comes first), the physiotherapist will remove the activity monitor and data collection will end.

Hospital Fit consists of a smartphone app combined to the MOX accelerometer. Hospital Fit provides patients and physiotherapists direct feedback on patients' physical activity behavior. Individual goals regarding the number of minutes per day spent walking can be set by the therapist. Hospital Fit also gives patients insight into their own recovery process. During every treament, the physiotherapist will evaluate the extent of functional recovery. In addition, Hospital Fit will give physiotherapists the option of creating a patient-specific exercise program supported by videos. During every treatment session, the patient and physiotherapist will evaluate (and if necessary adapt) the amount of activity performed since the previous treatment, the extent of functional recovery and the exercise program.

Hospital Fit 2.0, HFITAPP0, release 05, Maastricht Instruments B.V., the Netherlands

Antoine F Lenssen, Prof, PhD

The primary objective of this study is to investigate the effectiveness of using Hospital Fit as part of the physiotherapy treatment on average time spent walking per day in patients hospitalised at the Medical Oncology or Cardiology Departments of the Maastricht University Medical Center (MUMC+) and Radboud University Medical Center (Radboudumc) compared to patients who received physiotherapy before implementation of Hospital Fit. Secondary: to investigate the effectiveness of using Hospital Fit as part of the physiotherapy treatment on average time spent standing per day, average time spent lying/sitting per day, average number of transitions per day and the Modified Iowa Level of Assistance scale (mILAS) scores in hospitalised patients. Besides, the reach, efficacy, adoption, and implementation of using Hospital Fit as part of the physiotherapy treatment will be investigated from the perspective of both patients and healthcare professionals.

Rationale: Physical inactivity is a major, underrecognised problem in patients during their hospital stay. Patients spend between 87 and 100% of their time lying or sitting. This physical inactivity has been associated with adverse outcomes such as functional decline, increased length of hospital stay and mortality. Digital health tools could be valuable to prevent negative effects of inactivity. Hospital Fit is a promising app-based intervention to stimulate physical activity by 1) continuous physical activity monitoring, 2) personalised goalsetting, 3) providing patients insight in their functional recovery, 4) providing patients tailored exercise programs, 5) informing patients about benefits of physical activity, and 6) reminding patients to use Hospital Fit 7) linking the data to the electronic medical record, making it available for other healthcare professionals.

Objectives: Primary: to investigate the effectiveness of using Hospital Fit as part of the physiotherapy treatment on average time spent walking per day in patients hospitalised at the Medical Oncology or Cardiology Departments of the Maastricht University Medical Center (MUMC+) and Radboud University Medical Center (Radboudumc) compared to patients who received physiotherapy before implementation of Hospital Fit. Secondary: 1) to investigate the effectiveness of using Hospital Fit as part of the physiotherapy treatment on average time spent standing per day, average time spent lying/sitting per day, average number of transitions per day and the Modified Iowa Level of Assistance scale (mILAS) scores in hospitalised patients; and 2) to investigate the reach, efficacy, adoption, and implementation of using Hospital Fit as part of the physiotherapy treatment from the perspective of both patients and healthcare professionals.

Study design: A prospective, multi-centre, stepped-wedge cluster randomised trial will be performed to investigate the effectiveness of Hospital Fit. Additionally a process evaluation will be performed using questionnaires and semi-structured interviews in patients and focus-group interviews in healthcare professionals.

Study population: In total 180 patients hospitalised at the Medical Oncology Department or Cardiology Departments at the MUMC+ or Radboudumc will be included to study the effectiveness. The process evaluation will be performed in the intervention group using a questionnaire in all 90 patients, semi-structured interviews in 24 purposefully selected patients (or less if data saturation is reached), and focus group interviews in 24 healthcare professionals (i.e., physiotherapists, nurses, and physicians (assistants).

Intervention: Physical activity will be measured in all patients with an accelerometer until discharge with a maximum of nine days. The control group will receive usual care physiotherapy (n=90), while the intervention group will use Hospital Fit additionally (n=90).

Main study parameters/endpoints: Primary outcome parameter: average time spent walking per day (min). Secondary outcome parameters: average time spent standing and lying/sitting per day (min.), average number of transitions from lying/sitting to standing/walking per day, and mILAS score per day. Outcome parameters process evaluation: participation; representation; perceived efficacy; use of app; use of different functionalities; barriers and facilitators to Hospital Fit use; and expected maintenance.

Nature and extent of the burden and risks associated with participation, benefit and group relatedness: The burden and risks on patients are minimal. The control group will receive usual care physiotherapy and will wear an accelerometer. The intervention group will use Hospital Fit additionally. Wearing a small accelerometer and using Hospital Fit should not be a burden to patients. The only burden is the time it takes to prepare subjects (install app, explain study). No invasive interventions will take place. Anticipated benefits of Hospital Fit use include improved physical activity, therewith reducing the negative effects associated with low physical activity.

A prospective, multi-center, stepped-wedge cluster-randomised trial will be performed to investigate the effectiveness of Hospital Fit. Additionally, a process evaluation will be performed using semi-structured interviews and questionnaires in patients and focus-group interviews in healthcare professionals.

Effectiveness of Hospital Fit on Physical Activity of Hospitalised Patients

Effectiveness of Hospital Fit on Physical Activity of Hospitalised Patients: a Stepped-wedge Cluster-randomised Clinical Trial and Process Evaluation

We do not intent to make IPD available to other researchers.

The 'total number of users' (included patients allocated to the intervention group that used Hospital Fit) divided by the 'total number of included subjects' (all included patients allocated to the intervention group). A 'user' is defined included subject who has indicated that she/he used Hospital Fit at least once.

Patient characteristics (i.e., age, gender, clinical diagnosis) of patients in the intervention group shown separate for users and non-users. A 'user' is defined included subject who has indicated that she/he used Hospital Fit at least once. A 'non-user' is an included subject who has indicated in the questionnaire that she/he did not use Hospital Fit.

Data on perceived efficacy will be collected using individual, semi-structured, face-to-face interviews with 24 patients included in the intervention group and 4 focus group interviews with in total 6 healthcare professionals (physiotherapists, nurses, and physician(s) assistant(s)) per focus group. The following topics will be discussed: What is the impact of Hospital Fit use on physical activity of patients during their hospital stay according to patients? How do healthcare professionals determine if Hospital Fit use has been effective for patients? What were perceived positive and negative outcomes? How likely is it that Hospital Fit improved patients' physical activity?

Patients included in the intervention roup will score how many times per day she/he has used Hospital Fit on a daily questionnaire.

Patients included in the intervention group will score how many times per day the different functionalities of Hospital Fit were used on a daily questionnaire.

Barriers and facilitators to Hospital Fit use according to patients allocated to the intervention group and healthcare professionals. This will be explored using individual, semi-structured, face-to-face interviews with 24 patients included in the intervention group and 4 focus group interviews with in total 6 healthcare professionals (physiotherapists, nurses, and physician(s) assistant(s)) per focus group.

Expected maintenance will be explored using individual, semi-structured, face-to-face interviews with 24 patients included in the intervention group and 4 focus group interviews with in total 6 healthcare professionals (physiotherapists, nurses, and physician(s) assistant(s)) per focus group. The following topics will be discussed: What might be the long-lasting effects of Hospital Fit on physical activity of patients? How will Hospital Fit be maintained at the hospital ward?

Total number of minutes walking divided by the total number of valid measurement days in the period between inclusion and discharge, with a maximum of nine days.

Total number of minutes standing divided by the total number of valid measurement days in the period between inclusion and discharge, with a maximum of nine days.

Total number of minutes lying/sitting divided by the total number of valid measurement days in the period between inclusion and discharge, with a maximum of nine days.

Total number of transitions divided by the total number of valid measurement days in the period between inclusion and discharge, with a maximum of nine days.

The 5-item Modified Lowa Level of Assistance Scale (mILAS) assesses the ability of patients to perform 5 activities of daily living and rates the amount of assistance and type of walking aid needed. Each item has a 7-point rating scale (0-6 points), resulting in total scores ranging between 0-30 points. Higher scores indicate that a patient needs more assistance.

Radboud University Medical Center

Maastricht University Medical Center

Bilingual Houston area Latinos surveyed for 7 continuous days with objective and subjective assessments using accelerometer and smart phone.

36 questionnaires at the first visit (a total of 474 questions) and 25 questionnaires at the second visit (a total of 278 questions), taking about 60 to 90 minutes to complete each visit.

Questionnaires

Small device worn on the hip for 7 consecutive days that measures physical activity.

Questions on smart phone up to 5 times a day for 7 days taking about 5-7 minutes to complete each time.

Smart Phone

Larkin L. Strong, PHD

The goal of this research study is to learn how cultural, environmental, and interpersonal experiences, as well as personal thoughts and feelings, influence cancer risk behaviors among Latino residents of Houston, Texas.

Study Participation:

If you are eligible and choose to take part in this study, you can choose to visit the clinic 2 times or have research staff visit you in your home or a community setting (such as a church or community center) 2 times.

At the first visit (this is the same visit where you complete the in-person screening test):

* You will have your height, weight, and waistline measured.
* You will be given a smart phone to take home with you. You will answer questions on the smart phone up to 5 times a day for 7 days. The phone will beep at random times (4 times per day) and set times (in the evening) to prompt you to answer questions about what you are doing and your current thoughts and feelings. These questions should take about 5-7 minutes to complete each time.
* You will be given an accelerometer (a movement meter). The accelerometer is a small device worn on your hip that measures the amount of physical activity you do. You will wear the accelerometer for 7 days in a row.
* You will receive training on how to use the smart phone and the accelerometer.

At the second visit, you will return the smart phone and the accelerometer.

At both study visits, you will be asked to complete questionnaires that ask about your feelings, moods, and behaviors. You will complete 36 questionnaires at the first visit (a total of 474 questions) and 25 questionnaires at the second visit (a total of 278 questions). These questionnaires should take about 60 to 90 minutes to complete.

Throughout the study, you will be contacted by mail, email, or telephone for reminders of visits. You will be reminded before each visit. You will be asked to provide the names and contact information for family and/or friends should the study staff have trouble reaching you.

Confidentiality:

Each time you complete a survey on the smart phone, your answers will be saved on the phone. When you return the phone, all of your answers will be downloaded from the phone to a secure server, where they will be stored. Then, all of your information will be deleted from the phone. Your name or other personal information will not be stored on the phone.

Your name and other identifying information will not be stored together in the same files as other information you provide during your participation in the study. The link between your identifying information and other data will be kept in a separate file and securely protected. The link between you and the study data will be destroyed 5 years after the study ends.

Length of Study:

You will be considered off study when you complete the second visit.

This is an investigational study.

Up to 225 participants will take part in this study. All will be enrolled at MD Anderson.

Determinants of Multiple Health Risk Behaviors Among Latinos

Outcomes assessed through daily diary ecological momentary assessment (EMA) data and coded as yes (engaged in activity) or no (did not engage in activity). EMA assessments done over 7 contiguous days in a questionnaire computer-administered self-interview format.

National Cancer Institute (NCI)

National Institutes of Health (NIH)

M.D. Anderson Cancer Center

Gland and Hormone Related Diseases

Blood and Lymph Conditions

Immune System Diseases

Behaviors and Mental Disorders

Rare Diseases

Fatigue

Pancreatic Neoplasms

Lymphoma

Gastrointestinal Neoplasms

Digestive System Neoplasms

Endocrine Gland Neoplasms

Pancreatic Diseases

Endocrine System Diseases

Quality of Life

Pancreatic Cancer

Lymphosarcoma

Patients with a verified diagnosis of lymphoma, colorectal or pancreatic cancer requiring surgical, chemo or radio therapy.

No intervention - observational study only

Ali A Aghdassi, Professor

Mats L Wiese, MSc

Sebastian Schmidt

Physical activity is an important aspect of cancer therapy but correct measurement of physical activity is difficult. In this study, the physical activity of patients undergoing cancer therapy is assessed by questionnaire and by motion tracker. The results are then compared to answer whether there are differences between the two measurements. Findings of this study will help to improve the assessment of physical activity in cancer patients.

Although physical activity has been identified as a relevant determinant of cancer therapy outcome, its valid assessment remains challenging. In principle, direct and indirect assessment instruments can be employed for assessment of physical activity. While direct instruments, e.g. accelerometers, are considered to provide a more objective measurement, indirect tools such as questionnaires are less expensive and more applicable for use in larger study populations. The validity of both forms of measurements in cancer patients is however not well studied. Therefore, this study aims to elucidate the relative validity of an accelerometer in comparison to a standardized physical questionnaire at different time points of cancer therapy. Findings of this study will allow conclusions regarding the ideal modalities for assessment of physical activity in cancer patients.

Comparison of the Physical Activity in Cancer Patients Assessed by Questionnaire and Motion Tracker

Comparison of the Physical Activity Assessed by an Accelerometer and the International Physical Activity Questionnaire in Oncologic Patients

Difference in physical activity measured by the GeneActiv accelerometer and the short version of the International Physical Activity Questionnaire (IPAQ-sf) in metabolic equivalents of tasks (METs)

Difference in changes of physical activity measured by the GeneActiv accelerometer and the short version of the International Physical Activity Questionnaire (IPAQ-sf) in metabolic equivalents of tasks (METs)

Physical activity measured by the GeneActiv accelerometer in metabolic equivalents of tasks (METs)

Physical activity measured by the short version of the International Physical Activity Questionnaire (IPAQ-sf) in metabolic equivalents of tasks (METs)

Association between ECOG Performance Status and physical activity measured by the GeneActiv accelerometer in metabolic equivalents of tasks (METs)

Association between ECOG Performance Status and physical activity measured by the short version of the International Physical Activity Questionnaire (IPAQ-sf) in metabolic equivalents of tasks (METs)

Association between KPS and physical activity measured by the GeneActiv accelerometer in metabolic equivalents of tasks (METs)

Association between KPS and physical activity measured by the short version of the International Physical Activity Questionnaire (IPAQ-sf) in metabolic equivalents of tasks (METs)

Association between age and physical activity measured by the GeneActiv accelerometer in metabolic equivalents of tasks (METs)

Association between age and physical activity measured by the short version of the International Physical Activity Questionnaire (IPAQ-sf) in metabolic equivalents of tasks (METs)

Association between sex and physical activity measured by the GeneActiv accelerometer in metabolic equivalents of tasks (METs)

Association between sex and physical activity measured by the short version of the International Physical Activity Questionnaire (IPAQ-sf) in metabolic equivalents of tasks (METs)

Association between quality of life assessed by the European Organisation for Research and Treatment of Cancer Core Quality of Life Questionnaire (EORTC QLQ C-30) and physical activity measured by the GeneActiv accelerometer in metabolic equivalents of tasks (METs)

Association between quality of life assessed by the European Organisation for Research and Treatment of Cancer Core Quality of Life Questionnaire (EORTC QLQ C-30) and physical activity measured by the short version of the International Physical Activity Questionnaire (IPAQ-sf) in metabolic equivalents of tasks (METs)

Association between quality of life assessed by the European Organisation for Research and Treatment of Cancer Core Quality of Life Questionnaire (EORTC QLQ C-30) and cancer therapy modality

Association between fatigue assessed by the European Organisation for Research and Treatment of Cancer Quality of Life Fatigue Questionnaire (EORTC QLQFA-12) and physical activity measured by the GeneActiv accelerometer in metabolic equivalents of tasks (METs)

Association between fatigue assessed by the European Organisation for Research and Treatment of Cancer Quality of Life Fatigue Questionnaire (EORTC QLQFA-12) and physical activity measured by the short version of the International Physical Activity Questionnaire (IPAQ-sf) in metabolic equivalents of tasks (METs)

Association between fatigue assessed by the European Organisation for Research and Treatment of Cancer Quality of Life Fatigue Questionnaire (EORTC QLQFA-12) and cancer therapy modality

Association between sleep duration measured by the GeneActiv accelerometer in hours and physical activity measured by the GeneActiv accelerometer in metabolic equivalents of tasks (METs)

Association between sleep duration measured by the GeneActiv accelerometer in hours and physical activity measured by the short version of the International Physical Activity Questionnaire (IPAQ-sf) in metabolic equivalents of tasks (METs)

Association between sleep efficiency, i.e. the ratio of sleep duration to total bed time measured by the GeneActiv accelerometer in hours, and physical activity measured by the GeneActiv accelerometer in metabolic equivalents of tasks (METs)

Association between sleep efficiency, i.e. the ratio of sleep duration to total bed time measured by the GeneActiv accelerometer in hours, and physical activity measured by the short version of the International Physical Activity Questionnaire (IPAQ-sf) in metabolic equivalents of tasks (METs)

Association between sleep duration measured by the GeneActiv accelerometer in hours and cancer therapy modality

Association between sleep efficiency, i.e. the ratio of sleep duration to total bed time measured by the GeneActiv accelerometer in hours, and cancer therapy modality

Differences in fatigue assessed by the European Organisation for Research and Treatment of Cancer Quality of Life Fatigue Questionnaire (EORTC QLQFA-12)

Differences in quality of life assessed by the European Organisation for Research and Treatment of Cancer Core Quality of Life Questionnaire (EORTC QLQ C-30)

Association between tumor entity and changes in physical activity measured by the GeneActiv accelerometer and the short version of the International Physical Activity Questionnaire (IPAQ-sf) in metabolic equivalents of tasks (METs)

Association between cancer therapy modality and changes in physical activity measured by the GeneActiv accelerometer and the short version of the International Physical Activity Questionnaire (IPAQ-sf) in metabolic equivalents of tasks (METs)

University Medicine Greifswald

Patients perform 2 physical activities in an exam room that are recorded using a Microsoft Kinect 2 stationary movement tracking device on days 1 and 21. The first activity is rising from a chair, walking 10 feet, and returning to the chair. The second activity is moving from the chair to the step-up examination table. Patients also wear a movement tracking wristband, Microsoft Band 2, around their wrist, complete a smartphone application based PRO questionnaire, and weigh themselves daily for 60 days.

Laboratory Biomarker Analysis

Perform physical activities recorded by Microsoft Kinect 2

Physical Activity Measurement

Telephone-Based Intervention

Jorge Nieva

This clinical trial studies movement tracking devices in optimizing and monitoring physical activity in patients with solid tumors undergoing chemotherapy in a health care facility during the day without spending the night. Movement tracking devices, such as Microsoft Kinect 2 and Microsoft Band 2, may help doctors learn about the health of cancer patients.

PRIMARY OBJECTIVES:

I. To determine the feasibility of monitoring cancer patients using wrist-worn activity monitors and movement trackers.

SECONDARY OBJECTIVES:

I. To evaluate the association between activity and patient reported fatigue. II. To evaluate the association between movement and incidents of health care interventions (hospitalizations, physical visits, intravenous hydration, etc.)

TERTIARY OBJECTIVES:

I. To compare physician and patient assessed Eastern Cooperative Oncology Group (ECOG) and Karnofsky performance status scores with the data obtained from movement trackers.

OUTLINE:

Patients perform 2 physical activities in an exam room that are recorded using a Microsoft Kinect 2 stationary movement tracking device on days 1 and 21. The first activity is rising from a chair, walking 10 feet, and returning to the chair. The second activity is moving from the chair to the step-up examination table. Patients also wear a movement tracking wristband, Microsoft Band 2, around their wrist, complete a smartphone application based patient reported outcome (PRO) questionnaire, and weigh themselves daily for 60 days.

After completion of study, patients are followed up at 90 days.

Movement Tracking Devices to Monitor Physical Activity in Patients Undergoing Chemotherapy

Accelerometry to Optimize and Monitor Human Performance in Cancer Chemotherapy Outpatients

The association between the "get up and go" time and moving onto the examination table will be explored.

The association between the presence of circulating tumor cells and patient activity will be explored.

The association between patient movement and the sum of inpatient and outpatient hospital encounters up to 90 days after study discontinuation will be explored.

Patients who are unable to comply and have data transmitted, including technical failures, personal decision, hospitalization, or any other reason are counted as "data capture failures". Data from patients who die while on study will not be replaced but will be included prior to their date of death, days between death and day 60 will not be included in the denominator when calculating "data capture success" rates.

The relationship between the change in weight over time and patient activity

University of Southern California

Urinary Tract, Sexual Organs, and Pregnancy Conditions

Prostatic Neoplasms

Genital Neoplasms, Male

Urogenital Neoplasms

Genital Diseases

Genital Diseases, Male

Urogenital Diseases

Prostatic Diseases

Male Urogenital Diseases

Patients and partners complete questionnaires over 60 minutes about demographic information, stress, coping, and lifestyle behaviors at baseline and end of study. Patients and partners also receive an accelerometer and complete EMA questionnaire on stress, coping, physical activity, and eating behaviors over 5-10 minutes QID (7:30 am, 11:30 am, 3:30 pm, and 7:30 pm) via an smartphone app for 14 days. Patients and partners also complete a survey on nutrition BIW for a total of 4 surveys.

Ecological Momentary Assessment

Questionnaire Administration

Survey Administration

Dalnim Cho

This trial studies the day-to-day stress, social support, and health lifestyle behaviors (such as physical activity and nutrition) in African American patients with stage 0-III prostate cancer survivors and their partners. How patients cope with stress may affect their lifestyle behaviors. This study may help understand not only survivors' behaviors but also partners' behaviors and how they interact.

PRIMARY OBJECTIVES:

I. Examine temporal associations between dyadic coping and health behaviors such as physical activity and diet.

II. Identify social and physical contexts in which health behaviors occur/co-occur among survivors and their partners.

EXPLORATORY OBJECTIVE:

I. Investigate potential moderators for the associations between stress and dyadic coping.

OUTLINE:

Patients and partners complete questionnaires over 60 minutes about demographic information, stress, coping, and lifestyle behaviors at baseline and end of study. Patients and partners also receive an accelerometer and complete Ecological Momentary Assessment (EMA) questionnaire on stress, coping, physical activity, and eating behaviors over 5-10 minutes four time daily (QID; 7:30 am, 11:30 am, 3:30 pm, and 7:30 pm) via an smartphone application (app) for 14 days. Patients and partners also complete a survey on nutrition twice weekly (BIW) for a total of 4 surveys.

Lifestyle Behavior Influences Among African American Patients With Stage 0-III Prostate Cancer Survivors and Their Partners

One Plus One Can Be Greater Than Two: Ecological Momentary Assessment for Black Prostate Cancer Survivors and Partners

To assess the association between the common dyadic coping of partner or survivor and physical activity of the survivor or partner, will construct 2 new variables corresponding to each common dyadic coping variable for each individual.

To assess the association between the common dyadic coping of partner or survivor and nutrition of the survivor or partner, will construct 2 new variables corresponding to each common dyadic coping variable for each individual.

Descriptive analysis (e.g., frequency) will be conducted to examine the places (e.g., home, neighborhood) in which the health behaviors occurred and the number of health behaviors engaged alone and with others (especially with partner). Also, contexts (days of a week and times of a day and place) in which survivors and partners engaged in health behaviors together will be investigated. All analyses will be exploratory in nature.

Hypersensitivity

Robert Friedman, MD

The purpose of this study is to develop a tool that can more accurately assess the intensity and kind of physical activity that a person performs. The experimental tool, which will use a mobile computing device as a way of automatically identifying when a certain activity is being performed and at what intensity, will be tested against a self reported paper diary of activities performed on a day to day basis. It is hoped that this study will increase understanding of the health benefits of certain types of physical activity performed in the home.

Engaging in regular physical activity that requires a moderate to vigorous effort is related to good health and a reduced risk of a multitude of diseases. Currently physical activity and health promotion research is limited by self- report data that is confounded by participants' ability to accurately remember and record their physical activity. A potentially new method of accurately assessing moderate-intensity physical activity is called context sensitive- ecological momentary assessment (CS-EMA). Mobile computing devices (personal computing devices, PDAs) that automatically identify when a specific type of physical activity (e.g., moderate-intensity physical activity) is being performed has the potential to provide valuable objective data for naturalistic, experimental, and clinical intervention research purposes, and has the potential for educational, recreational, and clinical applications. The goal of this exploratory study is to assess the accuracy of two methods of collecting data on moderate-intensity physical activity. The study will compare the use of a paper diary to collect self-reported data on moderate-intensity physical activities performed throughout the day to self-reported data collected using ecological momentary assessment methods which are facilitated by a PDA that cues the participant to record when specific intensity levels of physical activity are achieved. This study will also develop algorithms that will automatically identify specific types of physical activities being performed. The data collected from the heart rate monitor, motion sensor, and information requested directly from the participant via the PDA interface will be used to train pattern recognition systems to classify the intensity and type of physical activity being performed by the participant. This study will contribute to research on context- awareness and human activity recognition.

Study title	NCT ID	Conditions	Interventions	Eligibility	Organization
Smartphone Pain App for Assessing Oral Mucositis Pain in Patients	NCT02727062	Oral Mucositis	OM Pain App Accelerometer	18 Years -	Medical College of Wisconsin
Effectiveness of Hospital Fit on Physical Activity of Hospitalised Patients	NCT05378724	Cardiovascular ... Oncology Activation, Pat...	Hospital Fit 2....	18 Years -	Maastricht University Medical Center
Determinants of Multiple Health Risk Behaviors Among Latinos	NCT01479257	Cancer Risk Factors in...	Questionnaires Accelerometer Smart Phone	18 Years - 65 Years	M.D. Anderson Cancer Center
Effectiveness of Hospital Fit on Physical Activity of Hospitalised Patients	NCT05378724	Cardiovascular ... Oncology Activation, Pat...	Hospital Fit 2....	18 Years -	Maastricht University Medical Center
Smartphone Pain App for Assessing Oral Mucositis Pain in Patients	NCT02727062	Oral Mucositis	OM Pain App Accelerometer	18 Years -	Medical College of Wisconsin
Comparison of the Physical Activity in Cancer Patients Assessed by Questionnaire and Motion Tracker	NCT05501379	Lymphoma Pancreas Cancer Colorectal Canc...	No intervention...	18 Years -	University Medicine Greifswald
Movement Tracking Devices to Monitor Physical Activity in Patients Undergoing Chemotherapy	NCT03098277	Solid Neoplasm	Accelerometer Laboratory Biom... Physical Activi... Telephone-Based...	18 Years -	University of Southern California
Lifestyle Behavior Influences Among African American Patients With Stage 0-III Prostate Cancer Survivors and Their Partners	NCT04189770	Cancer Survivor Partner Spouse Stage I Prostat... Stage II Prosta... Stage IIA Prost... Stage IIB Prost... Stage IIC Prost... Stage III Prost... Stage IIIA Pros... Stage IIIB Pros... Stage IIIC Pros...	Accelerometer Ecological Mome... Questionnaire A... Survey Administ...	18 Years -	M.D. Anderson Cancer Center
The Development and Testing of an Electronic Tool to Measure Physical Activity in Domestic Settings	NCT00207181	Cancer		18 Years -	Boston Medical Center
Lifestyle Behavior Influences Among African American Patients With Stage 0-III Prostate Cancer Survivors and Their Partners	NCT04189770	Cancer Survivor Partner Spouse Stage I Prostat... Stage II Prosta... Stage IIA Prost... Stage IIB Prost... Stage IIC Prost... Stage III Prost... Stage IIIA Pros... Stage IIIB Pros... Stage IIIC Pros...	Accelerometer Ecological Mome... Questionnaire A... Survey Administ...	18 Years -	M.D. Anderson Cancer Center

Spots Global Cancer Trial Database for accelerometer