Types of studies

We will include all randomized controlled trials (RCTs) or quasi‐RCTs (including cross‐over RCTs). We will include trials reported in full text, those published as an abstract only, as well as any unpublished data identified.

Types of participants

Individuals with CF of all ages and degrees of disease severity, diagnosed based on clinical criteria and sweat testing or genotype analysis. We will not employ any restrictions based on exacerbation status.

Types of interventions

The review will include studies that compare the use of DHT for two purposes, which we will report separately:

1. DHT for delivering exercise programs in CF;

2. DHT for physical activity monitoring in CF.

We will include trials comparing interventions based on any type of DHT. Comparisons may include any DHT (such as smartphones and computer applications) used alone or in combination versus any type of comparator (such as delivering exercise programs in‐person or monitoring physical activity, usual care, or a different type of DHT intervention (i.e. comparisons of two active methods of digital support using different frequency of digital monitoring or different modes of delivery)). We will define exercise as a planned regimen of physical activity or exercise training, either alone or in combination, of defined types (e.g. resistance, endurance, flexibility, or neuromotor exercise), duration (e.g. minutes or hours), frequency (e.g. how many training sessions are performed per week), intensity (e.g. light, moderate, or vigorous), and volume (e.g. metabolic equivalent of task (MET)/min/week) and with the possibility of progression of the exercise regimen delivered via DHT. Trials will be excluded if the interventions do not have a duration of at least two weeks.

Types of outcome measures

To assess the effects of DHT for delivering exercise programs and for monitoring physical activity, we plan to analyse the following outcome measures.

Electronic searches

The Cochrane Cystic Fibrosis and Genetic Disorders Group's Information Specialist will conduct a systematic search of the Group's Cystic Fibrosis Trials Register for relevant trials using the following terms: (physiotherapies & exercising:kw) AND (telehealth:kw).

The Cystic Fibrosis Trials Register is compiled from electronic searches of the Cochrane Central Register of Controlled Trials (CENTRAL) (updated each new issue of the Cochrane Library), weekly searches of MEDLINE, a search of Embase to 1995 and the prospective handsearching of two journals ‐ Pediatric Pulmonology and the Journal of Cystic Fibrosis. Unpublished work is identified by searching the abstract books of three major cystic fibrosis conferences: the International Cystic Fibrosis Conference; the European Cystic Fibrosis Conference and the North American Cystic Fibrosis Conference. For full details of all searching activities for the register, please see the relevant section of the Cochrane Cystic Fibrosis and Genetic Disorders Group's website.

We will also undertake separate searches of the following databases, registers and trial registries:

• CINAHL (EBSCO) (Cumulative Index to Nursing and Allied Health Literature);

• PEDro (Physiotherapy Evidence Database pedro.org.au/);

• US National Institutes of Health Ongoing Trials Register ClinicalTrials.gov (www.clinicaltrials.gov);

• The WHO International Clinical Trials Registry Platform (www.who.int/trialsearch).

Details of the search strategies are presented in the appendices (Appendix 1).

Searching other resources

We will check the bibliographies of included trials and any relevant systematic reviews identified for further references to relevant trials. We will contact experts and organisations in the field to obtain additional information on relevant trials. We will also search for errata or retractions from included trials and will report within the review the date this was done.

Selection of studies

Two authors (ACPNP and APR) will independently screen the titles and abstracts of all the potential trials identified from the search for inclusion in the review. If disagreement arises on the suitability of a trial, the authors will reach a consensus by discussion or if necessary, by consulting a third author (SRP). Since each trial, rather than each report, is the unit of interest in the review, we will exclude duplicates and collate multiple reports of the same trial. We will record the selection process in sufficient detail to complete a PRISMA flow diagram and we will list details of excluded trials with the reason for exclusion in the 'Characteristics of excluded studies' table (Lefebvre 2020). A draft PRISMA flowchart is shown in Figure 1.

Figure 1

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Trial flow diagram

Data extraction and management

Two authors (ACPNP and APR) will independently extract data using a standard data acquisition form that has been piloted on at least one trial in the review to record the following details: study design (parallel or cross‐over or multi‐arm; single‐center or multicenter, participants and trial characteristics ‐ age, gender, the severity of condition, diagnostic criteria ‐ for baseline equality between groups, details on the number of participants screened for eligibility, randomized, analyzed, excluded, lost to follow‐up and dropped out, method of randomization and allocation concealment, blinding of personnel and outcome assessors, use of stratification, incomplete outcome data, selective reporting, use of intention‐to‐treat (ITT) analysis); the setting; the detailed intervention; duration of studies; and outcome measures (continuous and dichotomous) and time points reported; funding for the trial, and notable conflicts of interest of trial authors. We will resolve disagreements by consensus or if necessary, by consulting a third author (VFMT) (Li 2020). One author will enter the data into the Cochrane software Review Manager (RevMan 2021) and a second author will review it (HS). We will contact the authors of the included trials in case of unclear or missing data and information.

Assessment of risk of bias in included studies

Two review authors (ACPNP and APR) will independently assess the risk of bias for each outcome using the Risk of Bias tool 2.0 (RoB 2) outlined in the Cochrane Handbook for Systematic Reviews of Interventions (Higgins 2020a).  We will assess both the effect of assignment to the intervention and the effect of adhering to the intervention for each of the main outcomes and time points specified in the summary of findings table. We will assess risk of bias according to the following domains:

1. bias arising from the randomization process;

2. bias due to deviations from intended interventions;

3. bias due to missing outcome data;

4. bias in measurement of the outcome; and

5. bias in selection of the reported result.

We will address special issues in the risk of bias tool for cross‐over trials as proposed in the Cochrane Handbook for Systematic Reviews of Interventions (Higgins 2020b). We will judge each potential source of bias as 'low', 'some concerns', or 'high risk of bias', based on answers to the signalling questions. We will use the Excel tool to record and manage RoB 2 assessments (riskofbias.info) and make the RoB 2 consensus decisions for the signalling questions available as additional appendices. We will resolve any disagreements by discussion or by involving another review author (ANA).

We will summarize the risk of bias judgements for each outcome across all domains, with a justification for the judgements in the 'Risk of bias' table. We will consider the overall risk of bias for each outcome assessed to be the least favorable assessment across the domains of bias (Higgins 2020a). We will use the overall RoB 2 judgements for the specified outcomes for GRADE assessments.

Measures of treatment effect

For continuous outcomes (adherence, pulmonary function, QoL, usability, healthcare utilization, number of pulmonary exacerbations, participation in physical activity ‐ number of steps, time spent in physical activity, energy expenditure, intensity of physical activity, muscle strength, exercise capacity, self‐management behavior), we will report the mean difference (MD) with 95% confidence intervals (CIs) as the measure of treatment effect. If more than one trial measures the same outcome using different tools or units of measurement, we will calculate the pooled standardised mean difference (SMD) and 95% CI weighted. For time‐to‐event outcomes (time to subsequent exacerbation), we will use hazard ratios (HR) with 95% CIs. For dichotomous outcomes (adverse events), we will present results as risk ratios (RR) with 95% CIs (Deeks 2020). If we find skewed data, we plan to perform transformations of the original outcome data, where possible. If transformation is not possible, we plan to narratively describe any skewed data as medians, interquartile ranges, and range (Higgins 2020c). We will consider using change‐from‐baseline or post‐intervention value scores, according to the data availability; however, we plan to summarise these types of results separately.

Unit of analysis issues

Where trials randomly allocate individual participants to a DHT or to a control intervention, we will consider the participant as the unit of analysis (Higgins 2020b). For RCTs with a cross‐over design, we plan to use the methods suggested by Elbourne (Elbourne 2002). The reporting of data from cross‐over trials is generally variable with limited data published that are required for a paired analysis (Higgins 2020b). If the required data are not available, we will use data from the first period of the trial and treat it as a parallel trial (Higgins 2020b).

Dealing with missing data

In cases of incomplete data or a lack of data from included trials, we will contact the primary authors. If they do not answer or do not send the requested information, we will still include the trial and attempt to clarify the reason why the access to the missing data was not possible. We will perform sensitivity analyses to explore the impact of including such trials in the overall assessment of results (Li 2020).

Where possible, we will perform an ITT analysis, considering all randomized participants in the treatment arm to which they were originally assigned. We will assess the extent to which trial investigators have employed an ITT analysis and, where possible, will report the numbers of participants who dropped out of each arm of the trial (Higgins 2020b).

For outcomes with continuous data that are missing standard deviations (SD), we will either calculate these from other available data such as standard errors (SE), or will impute them, on the basis of SDs for the same outcome using the same scale, or from other similar trials, if possible (Higgins 2020c).

Assessment of heterogeneity

For trials with similar interventions and participants, assessing similar outcomes, we will pool the data into meta‐analyses and depict them in forest plots. We will assess the level of heterogeneity using the I² statistic. The I² statistic, as defined in the Cochrane Handbook for Systematic Reviews of Interventions (Deeks 2020), measures heterogeneity as a percentage and is categorized as below:

• 0% to 40%: might not be important;

• 30% to 60%: may represent moderate heterogeneity;

• 50% to 90%: may represent substantial heterogeneity;

• 75% to 100%: considerable heterogeneity.

If we identify substantial heterogeneity, we will report it and explore the possible causes using pre‐specified subgroup analyses.

Assessment of reporting biases

If we are able to include and combine a sufficient number of trials (n = 10) in a meta‐analysis, we plan to assess publication bias, initially by visual inspection of a funnel plot. To test for asymmetry, we will perform a regression‐based method as suggested by Page (Page 2020). As we may not be able to detect publication biases via asymmetrical funnel plots, to minimize publication bias, we will use multiple search strategies, search trial registries, and attempt to contact investigators for identifying unpublished data.

We will also assess outcome reporting bias. To reduce this type of bias and to ensure all variables are reported, we will attempt to identify the relevant trial protocols; if these are not available we will compare the methods section to the results section of each included trial.

Data synthesis

For data from included trials that are clinically homogenous, we will perform a pooled quantitative synthesis using a random‐effects model to account for between‐trial heterogeneity (Deeks 2020). We will assess clinical homogeneity between studies by comparing trial characteristics and participant demographics. Trials will be grouped according to similarity of intervention, populations and the outcomes measured. We will conduct separate meta‐analyses using the Review Manager software (RevMan 2021) to examine effects of:

• interventions for exercise prescription; and

• interventions for physical activity monitoring.

Where trials examine effects of multiple interventions, we will include participants from each arm in separate meta‐analyses. Where the trials are clinically heterogeneous or sufficient data are not available for a given outcome we will conduct a narrative synthesis as it would not be appropriate in these cases to combine results in a meta‐analysis (McKenzie 2019).

Subgroup analysis and investigation of heterogeneity

We plan to carry out the following subgroup analyses on the primary outcomes so as to investigate their influence on the size of the treatment effect (if appropriate data are available):

• age: pediatric (up to 18 years old) versus adult (over 18 years);

• duration of intervention: up to 12 weeks versus more than 12 weeks;

• type of intervention;

• disease severity based on lung function (FEV₁% predicted, over 90%, 50% to 89%, below 50%)

Sensitivity analysis

We plan to summarise each type of intervention (DHT for exercise prescription and DHT for physical activity monitoring) separately. To answer the question on whether DHT is effective for exercise prescription, we will perform a primary analysis including all eligible studies using DHT for exercise training prescription in people with CF. We will include all trials on DHT for physical activity monitoring in a separate primary analysis. We plan to perform a sensitivity analyses by repeating each of the analyses after excluding trials with high risk of bias from the overall analyses, provided there are sufficient numbers of trials included (Deeks 2020). We will also attempt to examine the effect of cross‐over trials on the results by carrying out a sensitivity analysis to include and exclude them. To compare the results derived from a random‐effects model versus those obtained from a fixed‐effect model, we will also perform a sensitivity analysis by using a fixed‐effect model.

Summary of findings and assessment of the certainty of the evidence

We will determine and rate the quality of evidence for each outcome at time points as defined above by using the GRADE approach (Schünemann 2020). This will be presented in the summary of findings tables (one for each comparison). Where no data for individual outcomes are available, we will identify this for that row in the table, by stating 'data not reported'. We will report the following outcomes for each individual comparison, since we feel these are patient‐important outcomes:

• adherence to exercise training (number of completed exercise sessions divided by the number of prescribed exercise sessions) (long term);

• self‐management behavior (long term);

• time to subsequent pulmonary exacerbation (medium term);

• usability of DHT to people with CF (medium term);

• QoL (long term);

• lung function (FEV₁ % predicted) (medium term);

• exercise capacity (long term).