Steps Ahead: optimising physical activity in adults with cystic fibrosis: Study Protocol&nbsp;for a pilot randomised trial using wearable technology, goal setting and text message feedback.

Maire Curran; Audrey C. Tierney; Louise Collins; Lauren Kennedy; Ciara McDonnell; Andrew J. Jurascheck; Ali Sheikhi; Cathal Walsh; Brenda Button; Rose Galvin; Brian Casserly; Roisin Cahalan

doi:10.12688/hrbopenres.13025.3

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Study Protocol

Clinical trial

Revised

Steps Ahead: optimising physical activity in adults with cystic fibrosis: Study Protocol for a pilot randomised trial using wearable technology, goal setting and text message feedback.

[version 3; peer review: 2 approved]

Previously titled: Steps Ahead: optimising physical activity in adults with cystic fibrosis: Study Protocol for a pilot randomised trial using wearable technology

Maire Curran ^1-3, Audrey C. Tierney^1,3-5, Louise Collins², [...] Lauren Kennedy², Ciara McDonnell², Andrew J. Jurascheck¹, Ali Sheikhi³, Cathal Walsh³, Brenda Button^6,7, Rose Galvin^1,3,8, Brian Casserly², Roisin Cahalan^1,3,9

Maire Curran ^1-3, Audrey C. Tierney^1,3-5, [...] Louise Collins², Lauren Kennedy², Ciara McDonnell², Andrew J. Jurascheck¹, Ali Sheikhi³, Cathal Walsh³, Brenda Button^6,7, Rose Galvin^1,3,8, Brian Casserly², Roisin Cahalan^1,3,9

PUBLISHED 16 Nov 2020

Author details Author details

¹ School of Allied Health, University of Limerick, Limerick, Ireland
² University Hospital Limerick, Limerick, Ireland
³ Health Research Institute, University of Limerick, Limerick, Ireland
⁴ Health Implementation Science and Technology Research Group, Health Research Institute, University of Limerick, Ireland
⁵ Department of Dietetics, Nutrition and Sport, La Trobe University, Melbourne, Australia
⁶ Department of Medicine, Nursing and Health Sciences, Monash University, Melbourne, Australia
⁷ Departments of Respiratory Medicine and Physiotherapy, The Alfred, Melbourne, Australia
⁸ Ageing Research Centre, Health Research Institute, University of Limerick, Ireland
⁹ Physical Activity for Health Research Cluster, Health Research Institute, University of Limerick, Limerick, Ireland

Maire Curran
Roles: Conceptualization, Data Curation, Formal Analysis, Investigation, Methodology, Project Administration, Resources, Software, Validation, Visualization, Writing – Original Draft Preparation

Audrey C. Tierney
Roles: Conceptualization, Funding Acquisition, Methodology, Project Administration, Resources, Supervision, Validation, Visualization, Writing – Review & Editing

Louise Collins
Roles: Conceptualization, Investigation, Methodology, Writing – Review & Editing

Lauren Kennedy
Roles: Conceptualization, Investigation, Methodology, Writing – Review & Editing

Ciara McDonnell
Roles: Conceptualization, Investigation, Methodology, Writing – Review & Editing

Andrew J. Jurascheck
Roles: Investigation, Methodology, Writing – Review & Editing

Ali Sheikhi
Roles: Data Curation, Formal Analysis, Writing – Review & Editing

Cathal Walsh
Roles: Data Curation, Formal Analysis, Writing – Review & Editing

Brenda Button
Roles: Conceptualization, Supervision, Writing – Review & Editing

Rose Galvin
Roles: Supervision, Writing – Review & Editing

Brian Casserly
Roles: Conceptualization, Methodology, Supervision, Writing – Review & Editing

Roisin Cahalan
Roles: Conceptualization, Funding Acquisition, Methodology, Project Administration, Supervision, Validation, Visualization, Writing – Review & Editing

OPEN PEER REVIEW

REVIEWER STATUS

Abstract

Background: Physical activity (PA) and exercise are widely documented as key components in the management of cystic fibrosis (CF). In recent years there have been significant improvements in telehealth, in particular; wearable technology, smartphone use and remote monitoring, all of which may have potential to impact on PA in adults with CF. The objective of this pilot randomised trial is to explore the effect of wearable technology, which is remotely monitored, combined with personalised text message feedback and goal setting, on PA in adults with CF. Secondary endpoints include lung function, aerobic capacity, quality of life, body composition, wellbeing and sleep.

Methods: This is a pilot randomised trial which will be conducted at the University Hospital Limerick, Ireland. Participants will be randomised to the intervention or active comparator after their baseline assessment. The 12-week intervention will consist of wearable technology (Fitbit Charge 2) which is linked to an online monitoring system (Fitabase) that enables the physiotherapist to remotely monitor participant data. The CF physiotherapist will set individualised PA goals with each participant at baseline and will send text message feedback each week. The text messages will be personalised, one-way texts with positive reinforcement on step count attained by the participant. The active comparator group will receive this wearable technology which is also linked to Fitabase; however, no feedback will be provided to participants in this group. Both groups will be re-assessed at 12 weeks. After this point, both groups will continue with the Fitbit alone for a further 12 weeks. Both groups will be re-assessed at 24 weeks. A semi structured interview will assess satisfaction and acceptability of the intervention.

Discussion: This is a novel concept which utilises modern technology, remote monitoring and personalised feedback to investigate the effect on PA in adults with CF.

Trial registration: ClinicalTrials.gov NCT03672058 (14/09/2018)

Keywords

Physical activity, Randomised trial, Cystic fibrosis, fitness tracker, telehealth

Corresponding author: Maire Curran

Competing interests: No competing interests were disclosed.

Grant information: This research is supported by the Seed Funding Programme 2018 by the Health Research Institute, University of Limerick and Truck Run 4 Katie, a local charitable organisation.
The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Copyright: © 2020 Curran M et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

How to cite: Curran M, Tierney AC, Collins L et al. Steps Ahead: optimising physical activity in adults with cystic fibrosis: Study Protocol for a pilot randomised trial using wearable technology, goal setting and text message feedback. [version 3; peer review: 2 approved]. HRB Open Res 2020, 3:21 (https://doi.org/10.12688/hrbopenres.13025.3) First published: 05 May 2020, 3:21 (https://doi.org/10.12688/hrbopenres.13025.1) Latest published: 16 Nov 2020, 3:21 (https://doi.org/10.12688/hrbopenres.13025.3)

Revised Amendments from Version 2

The title of this article has been amended.

See the authors' detailed response to the review by Kenneth Wu
See the authors' detailed response to the review by Sarah Rand

Background

Cystic fibrosis (CF) is a life limiting, progressive disease which requires lifelong management. The prevalence of CF is 7 per 100,000 in the European Union, with Ireland reporting the highest incidence of CF in the world (Farrell, 2008). CF is a multisystem disease, primarily affecting the respiratory system which leads to recurrent pulmonary infections with retained secretions, airway obstruction and hyperinflation (Chmiel & Davis, 2003). There is significant burden associated with CF for the individual with CF, their family and wider society. Issues related to treatment adherence (Sawicki et al., 2009) and psychological wellbeing (Quittner et al., 2016), are frequently reported in the literature, especially in adults that are balancing family, work and education, as well as managing their chronic disease (Boyle, 2003). Despite the complexity in the management of CF, much of the regime can be completed from home, enabling the individual with CF to integrate treatment into everyday routines with monitoring from the CF team (Calthorpe et al., 2020).

Physical activity (PA) can be described as any bodily movement that causes an increase in energy expenditure above that of resting energy expenditure including leisure-time PA, occupational PA and exercise (Caspersen et al., 1985). Exercise and PA are widely documented in consensus statements as key components in the management of CF (Castellani et al., 2018). PA has several positive benefits in this population as it has been shown to improve sputum clearance (Dwyer et al., 2009), bone mineral density (Gupta et al., 2019) and muscle strength (Burtin et al., 2013). More importantly, PA can improve aerobic capacity (Hebestreit et al., 2010) and it can slow the rate of decline in lung function (Schneiderman et al., 2014), both of which are linked to increased survival in CF (Nixon et al., 1992). As a result, the optimisation of PA among adults with CF is important, however, a Cochrane review found that there was a lack of evidence regarding strategies to promote PA in this population and consideration should be given towards telemedicine applications and health coaching (Cox et al., 2013b).

Numerous subjective and objective methods are reported in the literature for the assessment of PA in adults with CF. Step count measurement can be used to quantify and monitor PA behaviours (Tudor-Locke & Bassett, 2004). Despite the clear benefits of PA in CF, a recent systematic review found that adults with CF fail to meet recommended PA and step count guidelines (Shelley et al., 2019). Pedometers can increase PA in other populations (Bravata et al., 2007; Hospes et al., 2009; Lubans et al., 2009). Therefore, interventions which aim to increase PA in adults with CF are of considerable interest.

The evolution of telehealth in CF management is significant in recent years. Previous studies have investigated the effect of telehealth on monitoring health status (Grzincich et al., 2010), detecting exacerbations (Lechtzin et al., 2017; Wood et al., 2017), assessing exercise capacity (Cox et al., 2013a) and providing outpatient appointments (Wood et al., 2017). Telehealth is well accepted by adults with CF (Cox et al., 2012). While home monitoring via telehealth seems to be a progressing area of CF management, to date, no studies have evaluated the effect of telehealth on PA and health outcomes in adults with CF. Smartphones and wearable technology may assist CF physiotherapists as they can access PA data remotely (Tagliente et al., 2016). Remote monitoring and home-based PA interventions in adults with CF are advantageous for several reasons. It enables the intervention to be easily implemented, participants’ personal preferences can be considered, it is more accessible to all participants and it can involve family/friends (Hebestreit et al., 2010). As a result, these benefits may increase adherence to the intervention. Wearable technology and text message feedback has had positive health outcomes amongst other study populations (Cadmus-Bertram et al., 2015; Cook et al., 2013; Moy et al., 2012; Nguyen et al., 2009; Vaes et al., 2013), however limited research has been conducted among adults with CF to date.

In addition to telehealth, goal setting and reviewing goals regularly should be considered to support patients with chronic illness (Coleman & Newton, 2005). In order for goals to be achieved, feedback should be provided that reveals progress in relation to the goal (Locke & Latham, 2002). Furthermore, setting specific goals should offer a plan to break PA goals into more practical, manageable steps (Shilts et al., 2004) which should increase self-efficacy and hence promote continued regular PA levels (Bandura, 2004). Previous literature from patient preference research and effective PA promotion approaches reports that successful strategies include specifically targeting PA (Conn et al., 2008), the use of behavioural strategies such as feedback and goal setting (Conn et al., 2008; Kosma et al., 2005) (George et al., 2012) and the ability to self-monitor (Conn et al., 2008). The Irish national framework for self-management includes goal setting and action planning in chronic disease management (Chronic Conditions Working Group, 2017). PA interventions using pedometers have been shown to be more effective at increasing PA if they include step goals (Bravata et al., 2007). However, goal setting to increase PA in adults with CF is poorly investigated.

This pilot randomised trial aims to explore the impact of wearable technology, text message personalised feedback and goal setting on PA and health outcomes in adults with CF. For the purpose of this study these specific health outcomes include lung function, aerobic capacity, body composition, quality of life, well-being and sleep. Poor sleep quality has been previously highlighted as an issue in adults with CF (Milross et al., 2002) and PA interventions can improve sleep quality in other populations (Lan et al., 2014; Yang et al., 2012).

In addition, it is important to conduct a qualitative analysis to evaluate the implementation, delivery and acceptability of the intervention as this is the key to the development of future research which this pilot study aims to inform. Therefore, semi structured interviews will be conducted with the study participants and with the healthcare professionals providing the intervention. This will aim to inform future studies in this evolving research area. The current protocol serves to:

Describe the methodology that will be implemented to evaluate a 12-week intervention consisting of wearable technology with remote monitoring, personalised text message feedback and goal setting amongst adults with CF attending University Hospital Limerick
Describe the health outcomes in adults with CF that will be evaluated in the trial including PA levels, lung function, aerobic capacity, body composition, quality of life, wellbeing and sleep
Describe the nested process evaluation through the conduct of semi structured interviews amongst adults with CF and healthcare practitioners regarding the implementation, delivery and acceptability of the intervention.

Methods

Study design

This study represents a single centre pilot randomised trial which will compare the effect of wearable technology with personalised text message feedback and goal setting to wearable technology alone in adults with CF. The CONSORT standardised reporting guidelines will be followed to ensure the standardised conduct and reporting of the research (Schulz et al., 2010). This protocol was registered on ClinicalTrials.gov (NCT03672058) on 14^th September 2018 and prepared in accordance with the Standard Protocol Items: Recommendations for Interventional Trials (SPIRIT) guidelines (see Figure 1 and Reporting guidelines).

Figure 1. Study Schedule.

Setting

The study will take place in the Adult CF Unit, University Hospital Limerick, Ireland. Baseline and follow-up assessments will take place via routine clinic outpatient appointments. Each adult with CF attends their routine clinic appointment every three months. Therefore, we chose this duration for our intervention to dovetail with routine CF care and limit the need for the adult with CF to attend on a more regular basis for testing appointments. This was decided through public and patient involvement (PPI) (completed with adults with CF) and through clinician experience. If the participant cannot attend on a particular clinic day, then they will be offered an additional appointment to suit their schedule. Due to the nature of the intervention, blinding of participants is not possible.

Ethical approval

Ethical Approval was obtained from the University Hospital Limerick Research Ethics Committee (Approval number 054/18).

Population and recruitment

Recruitment strategy. Participants deemed eligible for inclusion to the study based on the inclusion/exclusion criteria will be approached by the study gatekeeper (CF Physiotherapist – LC) and provided with an outline of the study during their routine clinic outpatient appointment. Participants will be provided with an information leaflet and will be offered an opportunity to ask questions about participation in the study. Prospective participants will then be asked to sign a consent form. Consent and mechanisms relating to data controlling and processing will be compliant with the EU General Data Protection Regulation 2016/679 and in compliance with the Data Protection Act 2018 [(Section 36(2)) (Health Research) Regulations 2018].

Sample size

As this is the first study of its kind a sample size cannot be determined. There are 80 adults with CF attending this CF clinic. Based on inclusion/exclusion criteria at this CF centre in University Hospital Limerick, it is intended to recruit up to 50 participants.

Inclusion criteria

Age ≥ 18 years
Confirmed diagnosis of CF (based on CF-causing mutations and/or a sweat chloride concentration during two tests of > 60 mmol/l)
Clinically stable patients with CF attending University Hospital Limerick, determined by those who are not experiencing a pulmonary exacerbation. For the purpose of this study pulmonary exacerbation will be defined as acute or subacute worsening of respiratory symptoms which warrant change in treatment (i.e., new oral or intravenous antibiotics), as per previous research (Savi et al., 2015).
Access to a smartphone/tablet to access and ability to upload to Fitbit Application
Capacity and willingness to give explicit informed consent

Exclusion criteria

FEV₁ < 25%. Individuals with FEV₁ <25% would typically require supplemental oxygen for exercise and at this point may require transplant assessment. Furthermore, they are more likely to experience exacerbations and would not be suitable for a study over 24 weeks. This is a lower cutoff FEV₁ than most studies would include (Hebestreit et al., 2010; Klijn et al., 2004; Kriemler et al., 2013).
Patients on the waiting list for lung transplantation and those who have undergone lung transplantation.
Patients with an exacerbation in the four weeks prior to the study. Patients can undergo testing once they are finished their antibiotics and deemed clinically stable by the Respiratory Consultant (BC).
Patients dependent on supplemental oxygen for exercise.
Adults with CF who are pregnant
Patients with any cardiac, neurological or musculoskeletal impairment that may impact on their ability to participate in the PA intervention will not be eligible to take part in this study
Participation in another clinical trial up to 4 weeks prior to the first baseline visit

Randomisation

Should participants explicitly consent to participate in the study, they will undergo baseline testing. To minimise the possibility of selection bias, a researcher independent of the recruitment process (MC) will complete the first random allocation using a sealed opaque envelope. Following this a minimisation randomisation procedure will be completed based on lung function, where FEV₁ of >80% predicted lung function will be classified as having mild lung disease. While those with an FEV₁ of 50–79% predicted lung function will be classified as having moderate lung disease, 30–49% as severe lung disease and <30% indicating very severe lung disease (Ranu et al., 2011). Allocation will be revealed after recruitment and baseline assessments have occurred. Participants will then either receive the intervention (Fitbit with text messaging feedback and goal setting) or the active comparator (Fitbit only).

Experimental and active comparator intervention

Intervention

The intervention consists of wearable technology, text message feedback and goal setting.

Wearable technology:

If the participant is allocated to the intervention, they will be provided with wearable technology (Fitbit Charge 2), educated on how to use it, and this will also be linked to an online monitoring system (Fitabase). Participants will be encouraged to enable Bluetooth and upload data regularly. Fitabase, the online monitoring system enables the physiotherapists to access step count data remotely. When a participant enables Bluetooth and syncs their Fitbit through the Fitbit app, this automatically updates participant data on the Fitabase website. Engagement with the technology will be monitored through systematic review of online data. Participants in both groups will receive a “reminder” message on his or her mobile phone if their data has not been synced via the Fitbit App in the previous seven days. This ensures that data is continuously collected over the full study duration. The data collected through the Fitbit Charge 2 and recorded on the Fitabase system are step count, activity minutes and sleep. However, for the purpose of this study, the researchers are only investigating step count alone. Any further research would require the Fitbit to be assessed under each of these conditions to ensure validity and reliability. This is outside the scope of this research.

Goal setting:

The physiotherapist will discuss the participant’s PA levels (as measured at baseline by an accelerometer) and individual patient centred PA goals will be set with each participant. These will be discussed with their physiotherapist to ensure they are specific, measurable, achievable, realistic and timed (SMART). They will be encouraged to write a minimum of three goals. Participants will be asked to set a step count target for week four, eight and 12 and consider ways to achieve these goals, both of which will be discussed with the physiotherapist during the baseline appointment. Goals will be individualised to the participant taking into account their preferences. Participants may also set goals related to health outcomes being assessed – for example, a participant may have a goal to improve lung function, aerobic capacity, sleep etc. during the study period. The text message feedback will refer to step goals only. The participant will be given a copy of their goals.

Text message feedback:

Every week participants will be sent a one-way personalised text message by their CF physiotherapist for 12 weeks overall. The text messages in this study will be personalised, one-way texts with positive reinforcement on step count attained by the participant.

A metanalysis found personalisation strategies, such as using a participant name has been proven to increase intervention efficacy (Head et al., 2013) and tailoring messages is a key ingredient in text messaging interventions (Noar et al., 2007). Furthermore, one way communication is as effective as two-way dialogue (Head et al., 2013). Therefore, this study investigated one-way messages only.

This individualised message will be sent to each participant once a week, at a day and time chosen by the participant at the start of the intervention. The authors will follow a standardised approach. The message will address the participant by name and will have positive feedback in the form of encouragement and praise messages (Adams et al., 2013) in relation to their step count attained in the previous week. It will then focus on a PA related goal set by the subject and will sign off with a further positive comment. Research has indicated that it is crucial to reinforce improvements to develop new behaviour or to strengthen a habit (Bandura, 2004; Glanz et al., 2008; Hovell et al., 2009). Each time a participant meets his/her goal they will receive positive feedback. Participants who do not meet the goal will be provided with a positive comment in relation to their step count achieved to date and provided their next step goal. This is to avoid negative messages that could be discouraging (Adams et al., 2013). If the participant does not achieve their target step count goal then the physiotherapist will set a target increase of 10% from the mean step count achieved in the previous week.

A sample text message is as follows:

Hi Paul, Well done on achieving an average daily step count of 7,600 steps this week. Next week aim to hit your goal of 8,000 steps. Keep up the good work!

Comparison

If the participant is allocated to the active comparator, they will be provided with a Fitbit Charge 2 and educated on how to use it and this will also be linked to “Fitabase” for data collection purposes. However, no feedback will be provided to the participants on their PA levels throughout the study period.

Follow Up

At week 12 both groups will have outcome measures re-assessed. Both groups will continue with the Fitbit Charge 2 only for the following 12 weeks. At the end of the 24 weeks participants will have all outcome measures repeated.

Subsequently, a qualitative assessment will be conducted through semi structured individual interviews to determine participants’ satisfaction and feedback on the intervention and their suggestions going forward. The interview guide is available as extended data to this manuscript (Curran, 2020). These interviews will be completed by a CF Physiotherapist involved in the study (LK) using a digital voice recorder and will be transcribed verbatim. The transcribed texts will be coded independently by two investigators who will develop code books. These will be compared and agreed upon. Data will be analysed using NVIVO V.11 Plus (QSR International Pty Ltd) and using the six steps for thematic analysis, in order to highlight the central themes to this study (Braun & Clarke, 2006).

Exacerbations

If the participant has an exacerbation of CF during the study period, their involvement in the study will be paused, and re-started 1 month later.

Baseline Assessment of step count

The ActivPAL accelerometer (PAL technologies) will be used to assess step count at baseline. This will be used to inform goal setting only. This forms part of another study which assessed PA behaviour in adults with CF. Participants will wear the accelerometer for seven days. Based on PPI it was reported by the participants that they did not want to wear an ActivPAL other than at baseline as it is a thigh worn device which is not ‘fashionable’. Similar concerns have been cited previously in the research (Dias et al., 2012). Data will be included if at least four full days (at least three weekdays and one weekend day) of measurements with a minimum of 10 hours (h) for the weekdays and 10 h for the weekends are measured (Freedson et al., 2005).

Usual Care

Usual care will be provided to all participants in both groups. This would typically include PA and exercise advice as per Australian and New Zealand Cystic Fibrosis guidelines. People with CF are advised to exercise for at least 30 minutes, five days a week. They are advised to include a combination of aerobic and resistance training. It is personalised depending on patient preference, as per recommendations (Button et al., 2016).

Instrumentation/outcome measures

A range of outcome measures will be employed to identify the potential impact of this study on health outcomes in adults with CF. Each of these outcomes will be assessed at baseline, at 12 weeks and 24 weeks.

Primary

Fitbit step count data

The Fitbit Charge 2 (Fitbit Inc.) will be used to record step count during this study with data uploaded to Fitabase (Small Steps Labs LLC). Prior to this intervention, the validity and reliability of the Fitbit Charge 2 to measure step count in CF was assessed by the same research group. Twenty-one participants were recruited from an adult CF Centre for a single session of testing. Participants walked for five minutes at five pre-determined speeds in a controlled testing environment (2, 2.5, 3, 3.5 and 4 miles per hour on a treadmill) and at three self-selected speeds on a corridor (slow, medium and fast). The Fitbit Charge 2 was compared to visual observation. It was found that the Fitbit Charge 2 ranged from weak to very strong correlations when compared to visual observation (0.34–0.84). The Fitbit Charge 2 underestimated step count by 2.8%–9.2%. This is within acceptable limits of variability based on previous research (Schneider et al., 2004). Therefore, the Fitbit Charge 2 is a valid and reliable measure to assess step count in adults with CF (Curran et al., 2020).

Secondary

Cardiopulmonary exercise testing

The reference standard exercise test is an incremental cardiopulmonary exercise test (CPET), utilising a ramp protocol. The ramp protocol ensures that work rate is progressively and linearly incremented until maximal effort is achieved (Herdy et al., 2016). All standard CPET outcomes will be considered including VO₂ max, duration, load, pulmonary ventilation (VE), Respiratory Exchange Ratio (RER), ventilatory equivalents for oxygen (VE/VO₂) and for carbon dioxide (VE/VCO₂). This will be conducted using the Medisoft Ergocard Professional CPET equipment and analysed by ExpAir, the Medisoft software. Maximal exercise testing is an independent predictor of mortality in CF (Nixon et al., 1992). Breath-by-breath ventilatory gas analysis allows the accurate measurement of maximal oxygen uptake (VO₂max) – the gold standard measure of exercise capacity (Urquhart, 2011). Supramaximal verification be conducted to ensure a maximal effort during the CPET. After an incremental CPET, participants will be provided with a ten-minute break. They will then be asked to complete a supramaximal exercise test (Causer et al., 2018; Saynor et al., 2013) whereby participants will exercise at 110% of their power output (as determined by CPET test previously). This test has been conducted amongst adults with CF previously and has been deemed safe and ensures validity of the results which are obtained in a CPET test.

Spirometry

Spirometry will be performed according to American Thoracic Society (ATS) standard techniques (Miller et al., 2005) using the Carefusion Microlab spirometer. Values will be expressed as a percentage of the predicted value for height, sex and age for adults (Hankinson et al., 1999). Forced expiratory volume in one second (FEV₁) will be used to classify the severity of CF lung disease for each participant. It will also be used to determine the effect the intervention may have on pulmonary function. Other pulmonary function measures such as % forced vital capacity (FVC) and forced expiratory flow (FEF_25–75) will also be considered.

International Physical Activity Questionnaire (IPAQ)

The IPAQ is a self-reported measure of PA and relies on user recall over the previous seven days. This tool was developed to assess PA levels using a questionnaire, has very good repeatability and is as reliable as other measures for self-reported PA (Craig et al., 2003). This nine-item questionnaire relies on participant recall and records PA at four levels: vigorous (e.g. aerobics), moderate (e.g. leisure cycling), walking and sitting.

Hand dynamometry

Grip strength will be recorded as a measure of general musculoskeletal strength, independent of lower limb strength. Previous research has shown that grip strength is correlated to lung function and VO2 peak (Wells et al., 2014). This will be conducted using a Jamar Hydraulic Hand Dynamometer. Test – retest reliability has been proven in respiratory patients (Dowman et al., 2016). The participant will be asked to stand and hold the dynamometer in by their side, with their elbow at 90 degrees and forearm in neutral. They will be instructed to squeeze the device as hard as possible. They will be provided with a 30 second rest period between each trial. The greater of two trials from each hand will be used and added together to give overall handgrip strength. This will be measured in kilograms (Martínez-García et al., 2020).

Bioelectrical Impedance Analysis (BIA)

BIA is an easily available, quick method to assess body composition. A low voltage current will be passed through the body, whereby impedance (tissue resistance and reactance) is measured. This will be conducted using the Seca 515 Medical Body Composition Analyser. BIA will be performed with the participant standing barefoot on the instrument platform as per manufacturers guidelines (Seca, Birmingham, United Kingdom). The device has an integrated scale and uses four pairs of electrodes of stainless steel that are positioned at each hand and foot, through which the current enters the limbs.

CF Quality of Life Questionnaire Revised (CFQR)

The CFQR questionnaire is a fully validated disease specific measure consisting of 52 items across nine domains of functioning which have been identified by, and are of importance to, adolescents and adults with CF. This questionnaire is valid, sensitive and has strong test-retest reliability (Gee et al., 2000). The minimum clinically important difference for the CFQR – respiratory score is 4 points (Quittner et al., 2009).

Pittburgh Sleep Quality Index (PSQI)

The PSQI is a self-rated questionnaire used to measure the quality and patterns of sleep in adults. It differentiates “poor” from “good” sleep quality by measuring seven areas (components): subjective sleep quality, sleep latency, sleep duration, habitual sleep efficiency, sleep disturbances, use of sleeping medications, and daytime dysfunction over the last month. The PSQI is effective in assessing sleep quality in CF (Milross et al., 2002).

The University of California San Diego (UCSD) Shortness of Breath Questionnaire

This questionnaire assesses dyspnoea associated with activities of daily living (ADLs). There are 24 items on this questionnaire. Each item is assessed on a 6-point scale (0 = “not at all” to 5 = “maximal or unable to do because of breathlessness”). Scores range from 0 to 120 with higher scores indicating activities of daily living are extremely limited by shortness of breath. It has been validated to assess dyspnoea over time in respiratory patients (Swigris et al., 2012)

Awescore

This questionnaire assesses state of wellness to assist in providing best health care (Button et al., 2014). There are ten questions, which are scored from 0–10. 10 reflects most well state of being possible while zero reflects least well state. Scores range from 0–100 with higher scores indicating good state of wellness. This is a reliable tool for measurement of multidimensional wellness in adults with CF that is appealing to patients (Button et al., 2014).

Data collection & management

Outcome assessment will be conducted by qualified physiotherapists in the Adult CF Unit. Assessors cannot be blinded as the intervention involves the CF physiotherapists for the delivery of weekly text messages, who will also be assisting with repeating objective outcome measures. All self-report measures will be completed by the participants independently, however a research assistant (RA) (AJ) will be available if there are any queries or concerns. These subjective assessments will be analysed by the RA who is blinded to group allocation.

Each participant in the study will be assigned a numerical identifier code. Aggregate data will be anonymised. Paper copies of all measures will be identifiable only by the identifier code. All data will be stored in locked filing cabinets in locked offices in the Adult CF Unit at University Hospital Limerick. All identifying paper data (e.g. signed consent forms and forms listing participant codes) will be stored in a separate locked filing cabinet to all other anonymised data and will be accessible only to the research team. All interviews will be coded and entered to a study data file. These computer files will be stored on the hard drive of a password protected desktop computer by the study lead investigator (MC). All audio and electronic data will be stored on encrypted hard drives.

Data analysis

Step count data will be collected over seven days and an average weekly step count will be obtained. It is anticipated that this step count data will be analysed to assess for a novelty effect in the first two weeks, at week six and 12 during the intervention and at week 18 and Week 24 for the follow up. Appropriate descriptive statistics will be used to describe the baseline characteristics of study participants. These will include proportions, percentages, ranges, means and standard deviations and medians and interquartile ranges (where data are not normally distributed). Data will be assessed for normality. Parametric tests will be used to compare differences across groups where data are normally distributed, and the non-parametric equivalent will be applied in cases where data are not normally distributed. A p-value <0.05 will be considered significant. Primary analyses will be performed according to intention-to-treat (ITT) principles with all participants who were originally allocated by randomisation and those who dropped out from the study. In case of missing values, a multiple imputation method, inverse probability weighing or mixed models will be used to handle the missing data. Data will be presented as means and SDs for data that is normalised and medians (IQR) for data that is skewed. A repeated measures ANOVA, controlling for baseline values and other potential confounders will be conducted. Bonferroni correction will be applied for multiple testing.

Dissemination of information

The results of this study will be disseminated via peer-reviewed publications and conference presentations.

Study status

Recruitment began in January 2019. It is anticipated this will be completed by June 2020.

Discussion

This is the first study to assess the effect of wearable technology with personalised text message feedback and goal setting on PA and key health outcomes in adults with CF. Previous research has investigated the feasibility and acceptability of a telehealth intervention in adults with CF with positive results reported for such an intervention (Cox et al., 2015). The use of wearable technology with remote monitoring is a novel concept in CF.

Regular PA is a well-accepted and valued part of CF care (Dwyer et al., 2011; Rand & Prasad, 2012). The primary aim of this research is to increase PA in adults with CF. Adherence to any PA intervention is a vital component of any study, particularly in chronic disease. The use of pedometers to provide feedback on PA levels can increase awareness of daily PA, provide motivation and visual feedback (Lauzon et al., 2008). Pedometers can increase PA in an adult population (Bravata et al., 2007), in a young population (Lubans et al., 2009) and in chronic obstructive pulmonary disease (Hospes et al., 2009). To date, there is limited research conducted assessing wearable technology such as Fitbits in this population.

Previous literature has demonstrated that a partially supervised programme in CF can improve health outcomes and is easily implemented (Hebestreit et al., 2010). Other partially supervised interventions have investigated the effect of providing personalised text message feedback on PA levels which has enhanced adherence to home based programmes in other populations (Blaauwbroek et al., 2009; Strath et al., 2011). Furthermore, a systematic review found that having a step goal was the key predictor of increasing PA. Studies which did not include a step goal as part of their intervention showed no significant improvement in PA in comparison to those that set step goals (Bravata et al., 2007).

The secondary aims of this research is to consider the effect of this intervention on other important endpoints such as lung function, aerobic capacity, quality of life, wellbeing and sleep. The broad range of outcomes assessed in this study will facilitate a comprehensive review on the impact of this research on participants with CF, both subjectively and objectively. A strength of this study is the use of the Fitbit Charge 2 which will allow participants to update their PA levels through the Fitbit App which will enable the assessors to review data remotely and this will also provide feedback on compliance to the intervention.

There is no true control group in this study for a couple of reasons. Firstly, the primary aim of this study was to determine if a partially supervised programme would be effective in improving PA and health, and it is unknown if any of these key outcomes could be improved with the provision of a Fitbit alone. Therefore, it was deemed more appropriate to compare the intervention with the Fitbit alone rather than a true control group. Secondly, based on clinical experience and PPI, both the CF Physiotherapists and adults with CF felt that this would be a limitation to recruitment and retention if only one group received the Fitbit.

Gene modifiers and potentiators may be a confounder in this study. This will be monitored throughout the study duration and will be controlled for during statistical analysis, if necessary. The research team will also monitor exacerbation rates (participants requiring oral or IV antibiotics during the study period), hospital admission rate and colonisation status.

Limitations

It is not possible to blind participants in PA intervention research. Due to lack of resources it is not possible to blind the CF Physiotherapists who will be assisting with text messaging feedback and repeating objective outcome measures, however self-report measures will be analysed by a research assistant blinded to group allocation. There may be a selection bias towards more physically active adults with CF as those who are more active may be more likely to partake in this study.

The results of this study may provide valuable insights into the development of a larger definitive trial exploring the use of wearable technology for optimising PA and health outcomes in adults with CF.

Ethics approval and consent to participate

The study received ethical approval from the University Hospital Limerick Research Ethics Committee (Ref: 054/18). Written informed consent will be obtained from all study participants.

Data availability

Underlying data

No data are associated with this article

Extended data

Open Science Framework: Steps Ahead: optimising physical activity and health in people with cystic fibrosis. Study protocol for a pilot randomised trial https://doi.org/10.17605/OSF.IO/DEGHT (Curran, 2020)

This project contains the following extended data:

Participant Consent Form
Participant Information leaflet
Interview Guide

Reporting guidelines

Spirit Checklist for Steps Ahead: optimising physical activity and health in people with cystic fibrosis. Study protocol for a pilot randomised trial https://doi.org/10.17605/OSF.IO/DEGHT (Curran, 2020)

Data are available under the terms of the Creative Commons Zero “No rights reserved” data waiver (CC0 1.0 Public domain dedication).

Faculty Opinions recommended

References

Adams MA, Sallis JF, Norman GJ, et al.: An adaptive physical activity intervention for overweight adults: a randomized controlled trial. PLoS One. 2013; 8(12): e82901. PubMed Abstract | Publisher Full Text | Free Full Text
Bandura A: Health promotion by social cognitive means. Health Educ Behav. 2004; 31(2): 143–164. PubMed Abstract | Publisher Full Text
Blaauwbroek R, Bouma MJ, Tuinier W, et al.: The effect of exercise counselling with feedback from a pedometer on fatigue in adult survivors of childhood cancer: a pilot study. Support Care Cancer. 2009; 17(8): 1041–1048. PubMed Abstract | Publisher Full Text | Free Full Text
Boyle MP: So many drugs, so little time: the future challenge of cystic fibrosis care. Chest. 2003; 123(1): 3–5. PubMed Abstract | Publisher Full Text
Braun V, Clarke V: Using thematic analysis in psychology. Qual Res Psychol. 2006; 3(2): 77–101. Publisher Full Text
Bravata DM, Smith-Spangler C, Sundaram V, et al.: Using pedometers to increase physical activity and improve health: a systematic review. JAMA. 2007; 298(19): 2296–2304. PubMed Abstract | Publisher Full Text
Burtin C, Van Remoortel H, Vrijsen B, et al.: Impact of exacerbations of cystic fibrosis on muscle strength. Respir Res. 2013; 14(1): 46. PubMed Abstract | Publisher Full Text | Free Full Text
Button B, Gufler A, Clark D, et al.: 230 The development of a new quick/easy CF wellness score (Alfred Wellness Score for CF,“AweScore-CF”) to improve delivery of clinical care in the outpatient and inpatient settings suggests patients acclimatise to low lung function. J Cyst Fibros. 2014; 13: S105. Publisher Full Text
Button BM, Wilson C, Dentice R, et al.: Physiotherapy for cystic fibrosis in Australia and New Zealand: a clinical practice guideline. Respirology. 2016; 21(4): 656–667. PubMed Abstract | Publisher Full Text | Free Full Text
Cadmus-Bertram L, Marcus BH, Patterson RE, et al.: Use of the Fitbit to measure adherence to a physical activity intervention among overweight or obese, postmenopausal women: self-monitoring trajectory during 16 weeks. JMIR Mhealth Uhealth. 2015; 3(4): e96. PubMed Abstract | Publisher Full Text | Free Full Text
Calthorpe RJ, Smith S, Gathercole K, et al.: Using digital technology for home monitoring, adherence and self-management in cystic fibrosis: a state-of-the-art review. Thorax. 2020; 75(1): 72–77. PubMed Abstract | Publisher Full Text
Caspersen CJ, Powell KE, Christenson GM: Physical activity, exercise, and physical fitness: definitions and distinctions for health-related research. Public health rep. 1985; 100(2): 126–31. PubMed Abstract | Free Full Text
Castellani C, Duff AJA, Bell SC, et al.: ECFS best practice guidelines: the 2018 revision. J Cyst Fibros. 2018; 17(2): 153–178. PubMed Abstract | Publisher Full Text
Causer AJ, Shute JK, Cummings MH, et al.: Cardiopulmonary exercise testing with supramaximal verification produces a safe and valid assessment of VO2max in people with cystic fibrosis: a retrospective analysis. J Appl Physiol (1985). 2018; 125(4): 1277–1283. PubMed Abstract | Publisher Full Text
Chmiel JF, Davis PB: State of the art: why do the lungs of patients with cystic fibrosis become infected and why can't they clear the infection? Respir Res. 2003; 4(1): 8. PubMed Abstract | Publisher Full Text | Free Full Text
Chronic Conditions Working Group: Living Well with a Chronic Condition: Framework for Self-management Support National Framework and Implementation Plan for Self-management Support for Chronic Conditions: COPD, Asthma, Diabetes and Cardiovascular disease. 2017. Reference Source
Coleman MT, Newton KS: Supporting self-management in patients with chronic illness. Am Fam Physician. 2005; 72(8): 1503–1510. PubMed Abstract
Cook DJ, Thompson JE, Prinsen SK, et al.: Functional recovery in the elderly after major surgery: assessment of mobility recovery using wireless technology. Ann Thorac Surg. 2013; 96(3): 1057–1061. PubMed Abstract | Publisher Full Text
Conn VS, Hafdahl AR, Brown SA, et al.: Meta-analysis of patient education interventions to increase physical activity among chronically ill adults. Patient Educ Couns. 2008; 70(2): 157–172. PubMed Abstract | Publisher Full Text | Free Full Text
Cox NS, Alison JA, Button BM, et al.: Feasibility and acceptability of an internet-based program to promote physical activity in adults with cystic fibrosis. Respir Care. 2015; 60(3): 422–429. PubMed Abstract | Publisher Full Text
Cox NS, Alison JA, Button BM, et al.: Assessing exercise capacity using telehealth: a feasibility study in adults with cystic fibrosis. Respir Care. 2013a; 58(2): 286–290. PubMed Abstract | Publisher Full Text
Cox NS, Alison JA, Holland AE: Interventions for promoting physical activity in people with cystic fibrosis. Cochrane Database Syst Rev. 2013b; (12): CD009448. PubMed Abstract | Publisher Full Text
Cox NS, Alison JA, Rasekaba T, et al.: Telehealth in cystic fibrosis: a systematic review. J Telemed Telecare. 2012; 18(2): 72–78. PubMed Abstract | Publisher Full Text
Craig CL, Marshall AL, Sjörström M, et al.: International physical activity questionnaire: 12-country reliability and validity. Med Sci Sports Exerc. 2003; 35(8): 1381–1395. PubMed Abstract | Publisher Full Text
Curran M: Steps Ahead: optimising physical activity and health in people with cystic fibrosis. Study protocol for a pilot randomised trial. 2020. http://www.doi.org/10.17605/OSF.IO/DEGHT
Curran M, Tierney A, Collins L, et al.: Validity and Reliability of the ActivPAL and Fitbit Charge 2 as a measure of step count in Cystic Fibrosis. Under Review. 2020.
Dias A, Gorzelniak L, Jörres RA, et al.: Assessing physical activity in the daily life of cystic fibrosis patients. Pervasive Mob Comput. 2012; 8(6): 837–844. Publisher Full Text
Dowman L, McDonald CF, Hill CJ, et al.: Reliability of the hand held dynamometer in measuring muscle strength in people with interstitial lung disease. Physiotherapy. 2016; 102(3): 249–255. PubMed Abstract | Publisher Full Text
Dwyer TJ, Alison JA, McKeough ZJ, et al.: Evaluation of the SenseWear activity monitor during exercise in cystic fibrosis and in health. Respir Med. 2009; 103(10): 1511–1517. PubMed Abstract | Publisher Full Text
Dwyer TJ, Elkins MR, Bye PT: The role of exercise in maintaining health in cystic fibrosis. Curr Opin Pulm Med. 2011; 17(6): 455–460. PubMed Abstract | Publisher Full Text
Farrell PM: The prevalence of cystic fibrosis in the European Union. J Cyst Fibros. 2008; 7(5): 450–453. PubMed Abstract | Publisher Full Text
Freedson P, Pober D, Janz KF: Calibration of accelerometer output for children. Med Sci Sports Exerc. 2005; 37(11 Suppl): S523–S530. PubMed Abstract | Publisher Full Text
Gee L, Abbott J, Conway SP, et al.: Development of a disease specific health related quality of life measure for adults and adolescents with cystic fibrosis. Thorax. 2000; 55(11): 946–954. PubMed Abstract | Publisher Full Text | Free Full Text
George ES, Kolt GS, Duncan MJ, et al.: A review of the effectiveness of physical activity interventions for adult males. Sports Med. 2012; 42(4): 281–300. PubMed Abstract | Publisher Full Text
Grzincich G, Gagliardini R, Bossi A, et al.: Evaluation of a home telemonitoring service for adult patients with cystic fibrosis: a pilot study. J Telemed Telecare. 2010; 16(7): 359–362. PubMed Abstract | Publisher Full Text
Glanz K, Rimer BK, Viswanath K: Health behavior and health education: theory, research, and practice. John Wiley & Sons. 2008. Reference Source
Gupta S, Mukherjee A, Lodha R, et al.: Effects of exercise intervention program on bone mineral accretion in children and adolescents with cystic fibrosis: a randomized controlled trial. Indian J Pediatr. 2019; 86(11): 987–994. PubMed Abstract | Publisher Full Text
Hankinson JL, Odencrantz JR, Fedan KB: Spirometric reference values from a sample of the general U.S. population. Am J Respir Crit Care Med. 1999; 159(1): 179–187. PubMed Abstract | Publisher Full Text
Head KJ, Noar SM, Iannarino NT, et al.: Efficacy of text messaging-based interventions for health promotion: a meta-analysis. Soc Sci Med. 2013; 97: 41–48. PubMed Abstract | Publisher Full Text
Hebestreit H, Kieser S, Junge S, et al.: Long-term effects of a partially supervised conditioning programme in cystic fibrosis. Eur Respir J. 2010; 35(3): 578–583. PubMed Abstract | Publisher Full Text
Herdy AH, Ritt LEF, Stein R, et al.: Cardiopulmonary exercise test: background, applicability and interpretation. Arq Bras Cardiol. 2016; 107(5): 467–481. PubMed Abstract | Publisher Full Text | Free Full Text
Hospes G, Bossenbroek L, ten Hacken NH, et al.: Enhancement of daily physical activity increases physical fitness of outclinic COPD patients: results of an exercise counseling program. Patient Educ Couns. 2009; 75(2): 274–278. PubMed Abstract | Publisher Full Text
Hovell M, Wahlgren D, Adams M: The logical and empirical basis for the behavioral ecological model. Emerging theories in health promotion practice and research. 2009; 2: 347–385. Reference Source
Klijn PH, Oudshoorn A, van der Ent CK, et al.: Effects of anaerobic training in children with cystic fibrosis: a randomized controlled study. Chest. 2004; 125(4): 1299–1305. PubMed Abstract | Publisher Full Text
Kosma M, Cardinal BJ, McCubbin JA: A pilot study of a web-based physical activity motivational program for adults with physical disabilities. Disabil Rehabil. 2005; 27(23): 1435–1442. PubMed Abstract | Publisher Full Text
Kriemler S, Kieser S, Junge S, et al.: Effect of supervised training on FEV1 in cystic fibrosis: a randomised controlled trial. J Cyst Fibros. 2013; 12(6): 714–720. PubMed Abstract | Publisher Full Text
Lan CC, Huang HC, Yang MC, et al.: Pulmonary rehabilitation improves subjective sleep quality in COPD. Respir Care. 2014; 59(10): 1569–1576. PubMed Abstract | Publisher Full Text
Lauzon N, Chan CB, Myers AM, et al.: Participant experiences in a workplace pedometer-based physical activity program. J Phys Act Health. 2008; 5(5): 675–687. PubMed Abstract | Publisher Full Text
Lechtzin N, Mayer-Hamblett N, West NE, et al.: Home Monitoring of Patients with Cystic Fibrosis to Identify and Treat Acute Pulmonary Exacerbations. eICE Study Results. Am J Respir Crit Care Med. 2017; 196(9): 1144–1151. PubMed Abstract | Publisher Full Text | Free Full Text
Locke EA, Latham GP: Building a practically useful theory of goal setting and task motivation. A 35-year odyssey. Am Psychol. 2002; 57(9): 705–17. PubMed Abstract | Publisher Full Text
Lubans DR, Morgan PJ, Tudor-Locke C: A systematic review of studies using pedometers to promote physical activity among youth. Prev Med. 2009; 48(4): 307–315. PubMed Abstract | Publisher Full Text
Martínez-García MDM, Rodríguez-Juan JJ, Ruiz-Cárdenas JD: Influence of sex gap on muscle strength and functional mobility in patients with cystic fibrosis. Appl Physiol Nutr Metab. 2020; 45(4): 387–392. PubMed Abstract | Publisher Full Text
Miller MR, Hankinson J, Brusasco V, et al.: Standardisation of spirometry. Eur Respir J. 2005; 26(2): 319–338. PubMed Abstract | Publisher Full Text
Milross MA, Piper AJ, Norman M, et al.: Subjective sleep quality in cystic fibrosis. Sleep Med. 2002; 3(3): 205–212. PubMed Abstract | Publisher Full Text
Moy ML, Weston NA, Wilson EJ, et al.: A pilot study of an Internet walking program and pedometer in COPD. Respir Med. 2012; 106(9): 1342–1350. PubMed Abstract | Publisher Full Text
Nguyen HQ, Gill DP, Wolpin S, et al.: Pilot study of a cell phone-based exercise persistence intervention post-rehabilitation for COPD. Int J Chron Obstruct Pulmon Dis. 2009; 4: 301–13. PubMed Abstract | Publisher Full Text | Free Full Text
Nixon PA, Orenstein DM, Kelsey SF, et al.: The prognostic value of exercise testing in patients with cystic fibrosis. N Engl J Med. 1992; 327(25): 1785–1788. PubMed Abstract | Publisher Full Text
Noar SM, Benac CN, Harris MS: Does tailoring matter? Meta-analytic review of tailored print health behavior change interventions. Psychol Bull. 2007; 133(4): 673–93. PubMed Abstract | Publisher Full Text
Quittner AL, Modi AC, Wainwright C, et al.: Determination of the minimal clinically important difference scores for the Cystic Fibrosis Questionnaire-Revised respiratory symptom scale in two populations of patients with cystic fibrosis and chronic Pseudomonas aeruginosa airway infection. Chest. 2009; 135(6): 1610–1618. PubMed Abstract | Publisher Full Text | Free Full Text
Quittner AL, Saez-Flores E, Barton JD: The psychological burden of cystic fibrosis. Curr Opin Pulm Med. 2016; 22(2): 187–191. PubMed Abstract | Publisher Full Text
Rand S, Prasad SA: Exercise as part of a cystic fibrosis therapeutic routine. Expert Rev Respir Med. 2012; 6(3): 341–51; quiz 352. PubMed Abstract | Publisher Full Text
Ranu H, Wilde M, Madden B: Pulmonary function tests. Ulster Med J. 2011; 80(2): 84–90. PubMed Abstract | Free Full Text
Savi D, Simmonds N, Di Paolo M, et al.: Relationship between pulmonary exacerbations and daily physical activity in adults with cystic fibrosis. BMC Pulm Med. 2015; 15(1): 151. PubMed Abstract | Publisher Full Text | Free Full Text
Saynor ZL, Barker AR, Oades PJ, et al.: A protocol to determine valid V˙ O2max in young cystic fibrosis patients. J Sci Med Sport. 2013; 16(6): 539–544. PubMed Abstract | Publisher Full Text
Sawicki GS, Sellers DE, Robinson WM: High treatment burden in adults with cystic fibrosis: challenges to disease self-management. J Cyst Fibros. 2009; 8(2): 91–96. PubMed Abstract | Publisher Full Text | Free Full Text
Sawyer MG, Reynolds KE, Couper JJ, et al.: Health-related quality of life of children and adolescents with chronic illness--a two year prospective study. Qual Life Res. 2004; 13(7): 1309–1319. PubMed Abstract | Publisher Full Text
Schneider PL, Crouter SE, Bassett DR: Pedometer measures of free-living physical activity: comparison of 13 models. Med Sci Sports Exerc. 2004; 36(2): 331–335. PubMed Abstract | Publisher Full Text
Schneiderman JE, Wilkes DL, Atenafu EG, et al.: Longitudinal relationship between physical activity and lung health in patients with cystic fibrosis. Eur Respir J. 2014; 43(3): 817–823. PubMed Abstract | Publisher Full Text
Schulz KF, Altman DG, Moher D, et al.: CONSORT 2010 statement: updated guidelines for reporting parallel group randomised trials. BMC Med. 2010; 8(1): 18. PubMed Abstract | Publisher Full Text | Free Full Text
Shelley J, Boddy LM, Knowles ZR, et al.: Physical activity and associations with clinical outcome measures in adults with cystic fibrosis; a systematic review. J Cyst Fibros. 2019; 18(5): 590–601. PubMed Abstract | Publisher Full Text
Shilts MK, Horowitz M, Townsend MS: Goal setting as a strategy for dietary and physical activity behavior change: a review of the literature. Am J Health Promot. 2004; 19(2): 81–93. PubMed Abstract | Publisher Full Text
Strath SJ, Swartz AM, Parker SJ, et al.: A pilot randomized controlled trial evaluating motivationally matched pedometer feedback to increase physical activity behavior in older adults. J Phys Act Health. 2011; 8 Suppl 2: S267–S274. PubMed Abstract | Free Full Text
Swigris JJ, Han M, Vij R, et al.: The UCSD shortness of breath questionnaire has longitudinal construct validity in idiopathic pulmonary fibrosis. Respir Med. 2012; 106(10): 1447–1455. PubMed Abstract | Publisher Full Text | Free Full Text
Tagliente I, Solvoll T, Trieste L, et al.: Which indicators for measuring the daily physical activity? An overview on the challenges and technology limits for telehealth applications. Technol Health Care. 2016; 24(5): 665–672. PubMed Abstract | Publisher Full Text
Tudor-Locke C, Bassett DR Jr: How many steps/day are enough? Preliminary pedometer indices for public health Sports Med. 2004; 34(1): 1–8. PubMed Abstract | Publisher Full Text
Urquhart DS: Exercise testing in cystic fibrosis: why (and how)? J R Soc Med. 2011; 104 Suppl 1: S6–S14. PubMed Abstract | Publisher Full Text | Free Full Text
Vaes AW, Cheung A, Atakhorrami, M, et al.: Effect of 'activity monitor-based' counseling on physical activity and health-related outcomes in patients with chronic diseases: A systematic review and meta-analysis. Ann Med. 2013; 45(5–6): 397–412. PubMed Abstract | Publisher Full Text
Wells GD, Wilkes DL, Schneiderman JE, et al.: Physiological correlates of pulmonary function in children with cystic fibrosis. Pediatr Pulmonol. 2014; 49(9): 878–884. PubMed Abstract | Publisher Full Text
Wilkes DL, Schneiderman JE, Nguyen T, et al.: Exercise and physical activity in children with cystic fibrosis. Paediatr Respir Rev. 2009; 10(3): 105–109. PubMed Abstract | Publisher Full Text
Wood J, Mulrennan S, Hill K, et al.: Telehealth clinics increase access to care for adults with cystic fibrosis living in rural and remote Western Australia. J Telemed Telecare. 2017; 23(7): 673–679. PubMed Abstract | Publisher Full Text
Yang PY, Ho KH, Chen HC, et al.: Exercise training improves sleep quality in middle-aged and older adults with sleep problems: a systematic review. J Physiother. 2012; 58(3): 157–163. PubMed Abstract | Publisher Full Text

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