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

Symptoms and General Pathology

All Conditions

Rare Diseases

Chronic Disease

Disease Attributes

Chronic Graft Versus Host Disease

Patients will have a prevention visit with a Prevention Practitioner (a healthcare provider who has received additional training), complete the baseline survey then be invited to receive ongoing support from a trained, volunteer peer health coach, for up to six months. The coach will support the patient as she works towards achieving personalized health goals to reduce her risk of chronic diseases, including cancer. Patients will be administered additional surveys at 3 and 6 months and a final survey at 12 months.

Patients will have a prevention visit with a Prevention Practitioner (a healthcare provider who has received additional training) and complete a baseline survey, after which they will receive usual care from their healthcare providers. Patients will be administered another survey at 3 months and a final survey at 6 months. After study completion (about 6-months after the initial prevention visit), patients will be invited to receive ongoing support from a trained, volunteer peer health coach, for up to six months. The coach will support the patient as she works towards achieving personalized health goals to reduce her risk of chronic diseases, including cancer.

Patients will have a one-on-one, approximately one-hour long visit with a specially trained Prevention Practitioner. During this visit, they will discuss the patient's health history, their risks for developing chronic diseases, including cancer, and possible steps they can take to reduce those risks. The Prevention Practitioner will also assist the patient to develop and articulate specific goals the patient would like to work on to reduce their risk of chronic diseases.

Prevention Visit

Patients will be invited to register with the software platform used to facilitate peer health coaching. Once they have registered, they will be matched to a peer health coach who will connect with the patient to initiate the process. The coach will work collaboratively with the patient to help her follow through on a step-wise, personalized plan to achieve health goals that were developed with their prevention practitioner. The coach's approach will be informed by principles of brief action planning and motivational interviewing. Coaches will also provide social support, help to navigate to relevant information and community resources, and advise about options for self-monitoring. Coaching will occur over 12-16 sessions via phone calls, text messages, video calls and/or in-person meetings as desired/convenient and in accordance with local public health guidelines.

Peer health coaching

Natasha Kithulegoda, MPH

Camille K Williams, PhD

Stu Murdoch, MD

Priya Rajput, MD

Dara Maker, MD

Noah M Ivers, MD, PhD

Aisha Lofters, MD, PhD

The Building on Existing Tools To improvE cancer and chronic disease pRevention and screening in primary care (BETTER) Program allows patients in primary care to have a dedicated visit with a prevention practitioner to discuss chronic disease prevention and cancer screening. A prevention practitioner is a health professional, working in primary care, who has received additional training to discuss chronic disease prevention and screening and develop health goals with patients through shared decision-making. Previous studies have shown that this approach increases the number of prevention and screening actions completed by program participants. However, maintenance of health behaviour changes is difficult without on-going support. There is also some evidence that peer-delivered coaching can improve health outcomes in community settings. As such, the BETTER Women program extends the BETTER program by focusing on 40 to 68-year-old women and providing time-limited support for health behaviour change through peer health coaches. Coaches are volunteers - trained in techniques to support health behaviour change - who support women to achieve their health goals over a 6-month period. In this study, the investigators will explore: (i) whether patients who participate in health coaching after a prevention visit are more likely to increase the number of prevention and screening actions that they complete after six months, compared to women who participate in a prevention visit but do not get health coaching; (ii) whether the intervention effects endure six months after the intervention ends; and (iii) the implementation of the program to learn about factors that affect various aspects of the success and sustainability of the program.

While the BETTER program has been shown to successfully increase the number of preventive care and screening actions completed by patient participants after six months, it is known that it is difficult to maintain new health behaviours in the long-term. Unfortunately, it is not feasible to fund health professionals to offer repeated follow-up visits over the time needed to turn initial behaviour changes into long-term habits. Therefore, the investigators are building upon the existing BETTER program by adding a peer health coaching extension that will provide time-limited coaching for patients who want support as they work towards achieving preventive health goals. This approach takes advantage of growing awareness of the role of lay health coaches in improving and extending the quality and value of primary care.

This is a three-site, pragmatic, wait-list-controlled, randomized, Type 1 hybrid effectiveness-implementation trial with blinded outcome collection after 6 months. One site will be an urban, academic, hospital-based clinic; the second will be a clinic serving a greater proportion of patients from rural areas; and the third site will be a suburban clinic with a large South Asian population. Investigators will invite women who are 40-68 years old to have a single visit with a prevention practitioner and receive behaviour change support for up to six months from a health coach. Coaches will do a 24-hr training course, which includes special techniques to support health behaviour change, before they are matched to a patient. At the suburban site, only South Asian peer health coaches will be recruited and this work is being guided by a South Asian Community Advisory Council made up of members of various community organizations in that region. Patients who enroll in BETTER Women will be randomized to receive health coaching either immediately (intervention group) or after a 6-month delay (wait-list control group).

Effectiveness of the program will be assessed by evaluating for each patient, how many of a set of target chronic disease prevention and screening actions were completed at six months, in comparison to baseline. Investigators will also assess whether patients achieved the health goals that they set with their prevention practitioners, physiological markers of health, as well as habits and behaviours related to diet, physical activity, smoking and alcohol use. These outcomes will be collected via electronic surveys administered at baseline, 3- and 6-months\* post enrollment as well as through extraction of data from the patients' electronic medical records and BETTER program documents. These outcomes will be compared between the two groups of patients in the study. Additionally, investigators will survey intervention group participants and extract relevant data from their electronic medical records at 12-months\* post enrollment.

An embedded process evaluation will be conducted during the trial to examine the implementation of the program. The process evaluation will include collection of program data, electronic surveys administered to patients as well as qualitative interviews with intervention group patients, peer health coaches and prevention practitioners. Investigators will examine how acceptable the program was to patients; whether and why any adaptations were made; how well the program was utilized; how well the coaches delivered the intervention (e.g., what behaviour change techniques were used); how engaged patients and coaches were with the program; and mechanism(s) of action. Ultimately, investigators expect to gain an understanding of the program's sustainability, acceptability, cost-effectiveness, and factors that might impact future attempts at spread and scale.

Investigators expect to see that women in the intervention group (i.e., those who had a health coach) will complete more preventive and screening actions after six months. Investigators also expect to see that women in the intervention group will make more progress on achieving health goals and making lifestyle changes which reduce the risk of chronic diseases and cancers, that the intervention will increase women's access to resources in their primary care clinics and community, as well as improve the women's ability to maintain healthy behaviours.

Note\*: The investigators initially planned to collect surveys and data for the primary outcome (for both groups) at 12 months post enrollment. However, due to pandemic-related recruitment challenges, the data collection timeline was amended as described above to allow more time for recruitment within the project timeline.

Any person who self-identifies as a woman, regardless of sex assigned at birth, and meets all other eligibility criteria will be invited to participate.

Evaluation of the Effectiveness and Implementation of the BETTER Women Peer Health Coaching Program

BETTER Women: Community-Based, Primary Care-Linked Peer Health Coaching to Achieve Evidence-Based Preventive Care Goals - A Pragmatic, Wait-List Controlled Effectiveness-Implementation Trial

Health utility score based on European Quality of Life-5 Dimensions-5 Levels (EQ-5D-5L) health state

An estimation of the combined health utility values derived from responses from EQ-5D-5L and length of life experienced by patient, between measurement time points

Number of times patient accessed publicly funded outpatient healthcare services (e.g., visit to primary care physician, outpatient hospital-based services) while enrolled in the study

Number of times patient accessed publicly funded healthcare services from a hospital emergency room while enrolled in the study

The total cost of publicly funded healthcare utilization (outside of delivery of the intervention) by patient while enrolled in the study

Incremental cost of the intervention (i.e., delivery of peer health coaching only) per patient

This outcome is ordinal and calculated \*only for intervention group patients\*. It represents the nature of the change in the number of completed targeted behaviours from end of intervention (at 6 months) to end of follow-up (at 12 months). The targeted behaviours include the status (meeting evidence-based target or not) of four behavioural determinants for risk of cancer and chronic disease (diet, smoking, alcohol use, physical activity). If a patient meets more targets at 12 months compared to 6 months, the patient will be said to have improved. If the same number of targets are met, the patient will be said to be unchanged. If fewer targets are met, the patient will be said to have worsened.

The primary outcome is binary and defined as whether a patient increased the number of completed targeted behaviours from baseline to end of follow-up at 6 months. The targeted behaviours include the status (up to date or out of date) of three cancer screening tests (cervical, breast, colorectal) and the status (meeting evidence-based target or not) of four behavioural determinants for risk of cancer and chronic disease (diet, smoking, alcohol use, physical activity). If a patient meets at least one more target at 6 months than they met at baseline, their outcome will be considered positive.

Percentage of patient-set health goals that was achieved

Binary assessment of whether the patient is up to date on their breast cancer screening, as per their history and level of risk

Binary assessment of whether the patient is up to date on their cervical cancer screening, as per their history and level of risk

Binary assessment of whether the patient is up to date on their colorectal cancer screening, as per their history and level of risk

Binary assessment of whether the patient's Mediterranean Diet Score is at target (≥9)

Binary assessment of whether there was an evidence-based improvement (change ≥2) in diet between assessment points

Binary assessment of whether patient took at least one meaningful action towards diet management

Binary assessment of whether time (in minutes) spent doing moderate to vigorous physical activity in the last seven days is at the evidence-based target (≥150minutes)

Binary assessment of whether or not there was improvement in the physical activity index (PAI) between assessment points

Binary assessment of whether patient took at least one meaningful action towards physical activity management

Binary assessment of whether smoking status meets the target of abstinent for the last 30 days

Binary assessment of whether the patient's cigarette consumption category, based on consumption of cigarettes per day (cpd), has improved (i.e., cpd decreased) between assessment points

Binary assessment of whether patient took at least one meaningful action towards management of smoking behaviour

Binary assessment of whether alcohol use is at evidence-based target, i.e., number of drinks per day is \<1 and never having ≥1 drink on one occasion

Binary assessment of whether AUDIT risk category has improved (i.e., risk level has decreased) between assessment points

Binary assessment of whether patient took at least one meaningful action towards management of alcohol use

Binary assessment of whether the latest HbA1c measurement is up to date at study end, as per patient's characteristics

Binary assessment of whether the latest measurement, at study end, is up to date and at target (\<7%)

The most recent and up to date HbA1c measurement for patients with diabetes mellitus (DM)

Binary assessment of whether patient with DM (HbA1c not at target) has taken any meaningful actions towards management of blood sugar through initiation of new antihyperglycemic medication, up-titration of existing antihyperglycemic medications, or discussion with healthcare professional regarding behavioural changes needed to improve blood sugar

Binary assessment of whether the latest BP measurement is up to date, as per patient's characteristics

Binary assessment of whether the most recent measurement is up to date and at target as per patient's characteristics

The most recent and up to date systolic BP measurement

The most recent and up to date diastolic BP measurement

Binary assessment of whether patient with BP not at target has taken at least one action towards management of hypertension through initiation of new blood pressure medication, up-titration of existing blood pressure medication, or discussion with healthcare professional regarding behavioural changes needed to improve blood pressure

Binary assessment of whether the latest LDL measurement is up to date, as per patient's characteristics

Binary assessment of whether the most recent LDL measurement is up to date and at target as per patient's characteristics

The most recent and up to date LDL measurement

Binary assessment of whether patient with LDL not at target has taken at least one action towards management of LDL through initiation of new LDL medication, up-titration of existing LDL medication, or discussion with healthcare professional regarding behavioural changes needed to improve cholesterol

Binary assessment of whether body mass index (BMI) calculation or waist circumference (WC) measurement is up to date, as per patient's characteristics

Binary assessment of whether latest, up to date BMI is within target (≤ 30kg/m2)

Binary assessment of whether patient with BMI not at target took any meaningful actions towards management of obesity through use of medication or discussion with healthcare professional regarding behavioural changes needed to manage obesity

Study title	NCT ID	Conditions	Interventions	Eligibility	Organization
Effectiveness of Hospital Fit on Physical Activity of Hospitalised Patients	NCT05378724	Cardiovascular ... Oncology Activation, Pat...	Hospital Fit 2....	18 Years -	Maastricht University Medical 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
Evaluation of the Effectiveness and Implementation of the BETTER Women Peer Health Coaching Program	NCT04746859	Chronic Disease Cancer	Prevention Visi... Peer health coa...	40 Years - 68 Years	Women's College Hospital

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