Computer and mobile technology interventions for self management in chronic obstructive pulmonary disease
Abstract
This is a protocol for a Cochrane Review (Intervention). The objectives are as follows:
To evaluate the effectiveness of computer‐ and mobile technology‐delivered interventions versus face‐to‐face or hard copy/digital documentary‐delivered interventions, or both, in facilitating, supporting, and sustaining self management in people with COPD.
Background
Description of the condition
Chronic obstructive pulmonary disease (COPD) is characterised by airflow obstruction due to an abnormal inflammatory response of the lungs to noxious particles or gases, for example cigarette smoke. The obstruction is not fully reversible and is generally progressive (GOLD 2014). Globally, it is estimated that approximately 210 million people have COPD; evidence based on a systematic review of 29 countries suggests that the prevalence is higher in tobacco smokers or those who are exposed to tobacco smoke and people over 40 years of age. The evidence suggests that it affects men and women almost equally (GOLD 2014). Symptoms include increasing breathlessness, wheezing, weight loss, fatigue, and prolonged forced expiration of air (Corroon 2014). A clinical diagnosis of COPD is made using spirometry, the details of which are outlined in the Types of participants section. The pattern of care for people with moderate to very severe COPD often involves regular lengthy hospital admissions, which result in high healthcare costs and an undesirable effect on sufferers' quality of life (Oostenbrink 2004; Seemungal 2000).
Research in the last decade has focused on innovative methods to develop enabling and assistive technologies that facilitate patient self management. Self management refers to strategies a person uses or lifestyle changes a person makes to control their disease, have a good quality of life, and avoid exacerbations and hospitalisation (Audulv 2013; Schulman‐Green 2012). It is based on the premise that similar health and social issues exist for individuals across many chronic conditions and the understanding that people with chronic conditions are partners in managing their disease. However, in order for patients to self manage, they need skills, knowledge, and confidence, and must be self motivated (Audulv 2013; Lorig 2003).
Description of the intervention
Studies evaluating the use of remote technology in home‐based healthcare settings have demonstrated the potential of information and communication technology (ICT) to facilitate and support behaviour change and self management of chronic conditions (Nguyen 2013; Noar 2007). ICT is increasingly being used in the management of many chronic illnesses, such as asthma (Marcano 2013), cardiac disease (Inglis 2010), and COPD (Zwerink 2014). ICT facilitates and supports behavioural change by providing motivating educational programmes and other online resource materials that are accessible at all times and are generally available at low cost. As a possible method of producing sustainable behaviour change and self management, ICT may minimise hospital re‐admissions and provide the patient a better quality of life (Annandale 2011; Evers 2006; Voncken‐Brewster 2013). ICT that is remote and Web 2.0 based generally incorporates the use of video content and multimedia, primarily via the use of the Internet and mobile technology, for example smartphones and tablet computers. ICT‐delivered educational self management programmes are commonly provided through the use of application software (apps).
The content of self management education programmes is generally patient directed, for example comprising motivational and educational content related to smoking cessation, exercise, diet, and symptom management. Peer learning and social activity/connection aspects may also be included. Support programmes usually have a minimum duration of three months (Smit 2012; Wempe 2004). Most studies report improvements during and up to three to six months following the intervention; however, some studies? conclude that regardless of whether the programmes are delivered using ICT or face to face contact, these improvements are not maintained (Krebs 2010; Nguyen 2013; Smeets 2008; Smit 2012).
How the intervention might work
Self management interventions vary, but the most prominent patient‐directed applications of ICT in the home are delivered through personal computers and the use of applications for mobile technology, such as the iPad, Android tablets, smartphones, and Skype (Lindberg 2013). These self management interventions focus on providing information, instruction, goal setting, and self monitoring. They may use one or more approaches, such as video, audio, digital images, hard or digital copies, to deliver educational and motivational content related to issues such as smoking cessation, exercise, diet, and symptom management.
Why it is important to do this review
COPD is the fourth‐leading cause of death worldwide, with over 3 million people dying each year from the disease (GOLD 2014). These figures are conservative due to under‐recognition and under‐diagnosis, particularly in developing countries (GOLD 2014; WHO 2013). In the United Kingdom, 835,000 individuals were diagnosed between 2008 and 2009, and an estimated two million remain undiagnosed (NICE 2010). Six percent of the European Union's total health budget targets respiratory health; 56% of this is devoted solely to COPD. In the United States, direct costs for COPD are estimated at USD29.5 billion and indirect costs at USD20.4 billion. In Australia in 2008, the economic burden of COPD was estimated to be AUD98.2 billion, of which AUD8.8 billion was attributed to financial costs and AUD89.4 billion to loss of well‐being (Lung Foundation Australia 2014).The cost to the NHS for COPD treatment currently stands at an unsustainable annual figure of GBP930 million per year (DOH 2010). In Ireland, approximately 440,000 people are thought to have COPD, with each having up to six hospital admissions per year due to exacerbations, at an average cost of EUR6,000 per admission (Ryan 2010).
A systematic review that included 29 studies on self management for people with COPD (23 studies on 3189 participants compared self management versus usual care; 6 studies on 499 participants compared different components of self management on a head‐to‐head basis) concluded that self management interventions improve health‐related quality of life (HRQoL), reduce respiratory‐related hospital admissions, and improve dyspnoea (Zwerink 2014). Each intervention comprised two or more interaction episodes between the participants and healthcare providers. Information was delivered verbally, using written material or audiovisual media. This review did not include studies of ICT‐based self management interventions.
A Cochrane Review of 25 trials involving either telephone support (16 studies, 5613 participants), telemonitoring devices (11 studies, 2710 participants), or both (2 studies) concluded that telemonitoring programmes for patients living with chronic illness can reduce the risk of all‐cause mortality by 12% and reduce all‐cause hospitalisation by 8% to 9% (Inglis 2010). Additional findings reveal significant improvements in quality‐of‐life scores and overall cost reduction due to a decrease in hospitalisation rates. The cost savings ranged from 14% to 86%. However, telemonitoring devices, similar to telephone support, may require clinical support on a regular basis, and the available evidence suggests that further clarity on the economic benefits is required (Inglis 2010). Telephone support and telemonitoring devices are costly, and therefore is not readily available. Although technology‐based, telephone support and telemonitoring devices are conceptually different in terms of purpose and functionality than ICT‐based self management interventions that aim to effect sustained behavioural change.
The use of remote and Web 2.0‐based interventions provide patients with relevant, individualised, motivational, and educational material that encourages, supports, and facilitates self management and may reduce hospital re‐admission, acute exacerbations and costs (McCabe 2014). However, a systematic review (2 randomised controlled trials (RCT), 408 participants) on the effectiveness, cost effectiveness, and feasibility of smartphone and tablet self management apps for asthma using a narrative synthesis was inconclusive due to insufficient evidence (Marcano 2013).
The uptake of mobile broadband due to the increasing use of smartphones, tablets, and apps is also an important reason for conducting this review, as it has made information more accessible to the general population. By the end of 2014, the number of mobile‐connected devices will exceed the number of people on earth, and by 2018 there will be nearly 1.4 mobile devices per capita (Cisco 2014). This indicates that the continued development and growth of remote and Web 2.0‐based interventions for self management in many chronic illnesses is a realistic and feasible healthcare strategy.
Our review will evaluate the effect of remote and Web 2.0‐based interventions using computer and mobile technology versus face‐to‐face or hard copy/digital documentary interventions in facilitating, supporting, and sustaining self management in people living at home with COPD. The evidence may inform future research and technology related to self management of COPD.
Objectives
To evaluate the effectiveness of computer‐ and mobile technology‐delivered interventions versus face‐to‐face or hard copy/digital documentary‐delivered interventions, or both, in facilitating, supporting, and sustaining self management in people with COPD.
Methods
Criteria for considering studies for this review
Types of studies
We will include randomised controlled trials (RCTs) and cluster‐randomised trials. We will include studies reported as full text, those published as abstract only, and unpublished data. We will use study results that are published or available on request by the trialists.
Types of participants
Adult patients over age 18 with a clinical diagnosis of COPD according to the Global Initiative for Chronic Obstructive Lung Disease criteria and at any stage of illness will be included, that is people with chronic respiratory symptoms such as coughing, dyspnoea, and sputum (GOLD 2014). The stage of disease progression is determined on post‐bronchodilator forced expiratory volume in one second (FEV1) to forced vital capacity (FVC) ratio of less than 0.7.
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Stage l, post‐bronchodilator FEV1/FVC numbers at less than 80% of normal lung function;
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Stage ll, post‐bronchodilator FEV1/FVC is 79% to 50% percent of normal lung function;
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Stage lll post‐bronchodilator FEV1/FVC is 49% to 30% of normal lung function; and
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Stage lV, post‐bronchodilator FEV1/FVC reveals less than 30% of normal lung function.
We will include participants who live either at home or in a non‐healthcare residential setting (sheltered housing) and either use, or have access to, technology, for example a personal computer, tablet, or smartphone, to manage their illness. However, studies that include people from different care settings will only be included if the results of those participants living at home are identified or available separately in the study report.
We will include mixed‐participant studies, for example COPD, emphysema, asthma, lung cancer, or other conditions affecting breathing, only if participants with COPD are identified or available separately in the study report.
Types of interventions
We will include remote and Web 2.0‐based interventions delivered using technologies that give patients access to ehealth information to change behaviour towards self management of their COPD. These technologies include personal computers (PCs) and applications (apps) for mobile technology such as iPad, Android tablets, smartphones, and Skype.
The comparison group interventions will include face‐to‐face and/or hard copy/digital documentary educational/self management support. When undertaking our review, we will base comparisons on educational programmes of similar content, structure, and duration in the intervention (computer/mobile technology) and comparison groups.
We will exclude studies that focus on monitoring devices such as telemonitoring/telehealth or assistive technologies, because they involve the participation of more than one user, for example, the patient and the healthcare professional. We will focus this review on individual self management and behavioural change. We will also exclude studies that do not have an ICT arm.
Types of outcome measures
Primary outcomes
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Hospital admissions
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Acute exacerbations requiring general practitioner (GP) visit or additional treatment, or both
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Health‐related quality of life (HQoL) (as measured by the SGRQ, CCQ, SF‐36 or any validated instrument)
Secondary outcomes
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Self efficacy (as measured by the COPD Self Efficacy Scale or any validated instrument)
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Cost‐effectiveness (cost of the intervention and time lost from work)
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Functional capacity (6‐minute walking test or similar tests)
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Lung function (Forced expiratory volume in one second (FEV1) and FEV1 %predicted)
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Anxiety and depression (Hospital Anxiety and Depression Scale, CES‐D)
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Sustained behaviour change (smoking cessation and increased physical activity)
Reporting one or more of the outcomes listed here in the trial is not an inclusion criterion for the review. The time points of measurement are six months or less versus more than six months.
Search methods for identification of studies
Electronic searches
We will identify trials from the Cochrane Airways Group Specialised Register (CAGR), which is maintained by the Trials Search Co‐ordinator for the Group. We will search all records in the CAGR using the search strategy in Appendix 1.The CAGR contains trial reports identified through systematic searches of bibliographic databases including the Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE, Embase, CINAHL, AMED, and PsycINFO, and handsearching of respiratory journals and meeting abstracts (please see Appendix 2 for further details).
We will also conduct a search of ClinicalTrials.gov (www.ClinicalTrials.gov) and the World Health Organization trials portal (www.who.int/ictrp/en/). We will search all databases from their inception to the present, and we will impose no restrictions on language of publication.
Searching other resources
We will check reference lists of all primary studies and review articles for additional references. We will search relevant manufacturers' websites for trial information.
We will search for errata or retractions from included studies published in full text on PubMed (www.ncbi.nlm.nih.gov/pubmed) and report the date this was done in the review.
Data collection and analysis
Selection of studies
Two review authors (CMcC and MMcC) will independently screen titles and abstracts for inclusion of all the potential studies we identify as a result of the search and code them as 'retrieve' (eligible or potentially eligible/unclear) or 'do not retrieve'. We will retrieve the full‐text study reports/publication and two review authors (CMcC and MMcC) will independently screen the full text and identify studies for inclusion, and identify and record reasons for exclusion of the ineligible studies. We will resolve any disagreement through discussion or, if required, we will consult a third person (AMB). We will identify and exclude duplicates and collate multiple reports of the same study so that each study, rather than each report, is the unit of interest in the review. We will record the selection process in sufficient detail to complete a PRISMA flow diagram and 'Characteristics of excluded studies' table.
Data extraction and management
We will use a data collection form for study characteristics and outcome data that has been piloted on at least one study in the review. Two review authors (CMcC and AMB) will extract study characteristics from included studies. We will extract the following study characteristics.
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Methods: study design, total duration of study, details of any 'run in' period, number of study centres and location, study setting, withdrawals, and date of study.
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Participants: N, mean age, age range, gender, severity of condition, diagnostic criteria, baseline lung function, smoking history, inclusion criteria, and exclusion criteria.
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Interventions: intervention, comparison, concomitant medications, and duration of intervention.
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Outcomes: primary and secondary outcomes specified and collected, and time points reported.
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Notes: funding for trial and notable conflicts of interest of trial authors.
Two review authors (CMcC and AMB) will independently extract outcome data from included studies. We will note in the 'Characteristics of included studies' table if outcome data was not reported in a usable way. We will resolve disagreements by consensus or by involving a third person (MMcC). One review author (CMcC) will transfer data into the Review Manager (Review Manager 2012) file. We will double‐check that data is entered correctly by comparing the data presented in the systematic review with the study reports. A second review author (AMB) will spot‐check study characteristics for accuracy against the trial report.
Where the study is published in a language other than English, we will seek assistance from a native speaker/translator with content.
Assessment of risk of bias in included studies
Based on the criteria in the Cochrane Handbook for Systematic Reviews of Interventions, two members of the review team (CMcC and AMB) will use the Cochrane criteria (Higgins 2011) to independently assess risk of bias in relation to the following issues:
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Generation of sequence allocation
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Concealment
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Blinding re: intervention and outcome assessment
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Incomplete outcome data
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Selective reporting
Additional assessment criteria for cluster trials related to design issues include:
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Recruitment bias
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Unbalanced groups
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Analysis appropriate for cluster trials
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Loss of follow‐up
The presence/degree of bias will be identified as low, high, or unclear risk. We (CMcC and AMB) will discuss any differences with MMcC who will adjudicate and make a final decision. The team will use kappa statistics to calculate the percentage agreement between the team members and discuss/explain reasons for disagreement. Kappa values of 0.60 and above are considered good agreement (Higgins 2011). Members of the review team will not be blinded to authorship or journal.
Assessment of bias in conducting the systematic review
We will conduct the review according to this published protocol and report any deviations from it in the 'Differences between protocol and review' section of the systematic review.
Measures of treatment effect
We will use RevMan 5 software to analyse data. Results from each RCT will be represented as odds ratios, with a 95% confidence interval for dichotomous data and mean differences (MD) for continuous data. We will use standardised mean differences (SMDs) for studies using different outcome measurement scales. If data are sufficiently homogenous (clinically and statistically) they will be summarised in a meta‐analysis. We will convert combined estimates of risk ratios, MD, SMDs into measures that are relevant to practice if the outcome of the meta‐analysis is statistically significant.
Unit of analysis issues
For dichotomous data, we will divide the number of participants and the intervention group by the same design effect. For continuous data only, we will reduce the sample sizes. Means and standard deviations will remain the same.
Dealing with missing data
If necessary, members of the review team (CMcC and AMB) will contact the researchers for information about missing numerical outcome data related to individual participants. Where this is not possible, and the missing data are thought to introduce serious bias, we will explore the impact of including such studies in the overall assessment of results by a sensitivity analysis. We will assume missing values to have a poor outcome. For both continuous and dichotomous outcomes, effect size (odds ratio (OR), MD, SMD) will be calculated on the number of participants included in the analysis at the time point or at baseline.
Assessment of heterogeneity
We will assess statistical variation using the Chi2 (Q) test and I2 statistical tests. A P value of less than 0.10 or an I2 of more than 50% suggests substantial heterogeneity. In such cases we will explore data further in order to provide additional explanation.
Assessment of reporting biases
We will identify reporting biases by determining if the protocol was published before the study commenced. We will also ascertain the presence of selective reporting of outcomes for each study. If there are sufficient trials, attempts will be made to determine publication bias using funnel plots and screening all online clinical trial registers (Sterne 2011).
Data synthesis
We will use GRADEprofiler (GRADEpro) software to prepare the 'Summary of findings’ table (Higgins 2011).Findings from clinically and statistically homogeneous studies will be combined using the random‐effects model. We will apply ratings to the quality of evidence for all outcomes and five factors that may limit it, for example we will identify study limitations, clinical heterogeneity, inconsistent or unexplained results, and probability of publication bias.
Summary of findings table
We will create a 'Summary of findings' table using the following outcomes:
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Hospital admissions
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Acute exacerbations
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Health‐related quality of life (HQoL)
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Self efficacy
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Functional capacity
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Anxiety and depression
We will use the five GRADE considerations (study limitations, consistency of effect, imprecision, indirectness, and publication bias) to assess the quality of a body of evidence as it relates to the studies that contribute data to the meta‐analyses for the prespecified outcomes. We will employ methods and recommendations described in Section 8.5 and Chapter 12 of the Cochrane Handbook for Systematic Reviews of Interventions using GRADEpro software (Higgins 2011). We will justify all decisions to down‐ or upgrade the quality of studies using footnotes, and we will make comments to aid readers' understanding of the review where necessary.
Subgroup analysis and investigation of heterogeneity
We will assess the heterogeneity among the studies using subgroup analysis, for example the control group will be assessed for usual treatment, which may be written information in the form of leaflets/booklets, attendance at rehabilitation programme or other disease management program. We will assess the intervention group in relation to the type of technology, content, purpose, duration, and cost. We will also undertake subgroup analysis to determine the influence of the digital divide. This will be done using age and educational level, as these factors may be key influences on the uptake and use of technology.
We plan to carry out the following subgroup analyses where appropriate.
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Severity of COPD
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Duration of follow‐up (≤ 6 months versus > 6 months)
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Age > 60 versus < 60
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Educational level (primary, secondary,tertiary level)
We will use the formal test for subgroup interactions in Review Manager (Review Manager 2012).
Sensitivity analysis
We will conduct sensitivity analysis to investigate differences in effect size and strength of conclusions. We will conduct sensitivity analysis on the basis of risk of bias and methods of analysis for primary outcomes only.
