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Computer and mobile technology interventions for self-management in chronic obstructive pulmonary disease

Overview of attention for article published in Cochrane database of systematic reviews, May 2017
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (90th percentile)
  • Good Attention Score compared to outputs of the same age and source (65th percentile)

Mentioned by

1 news outlet
24 tweeters
2 Facebook pages


39 Dimensions

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6 Mendeley
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Computer and mobile technology interventions for self-management in chronic obstructive pulmonary disease
Published in
Cochrane database of systematic reviews, May 2017
DOI 10.1002/14651858.cd011425.pub2
Pubmed ID

Catherine McCabe, Margaret McCann, Anne Marie Brady


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 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 quality of life. Research over the past decade has focused on innovative methods for developing enabling and assistive technologies that facilitate patient self-management. To evaluate the effectiveness of interventions delivered by computer and by mobile technology versus face-to-face or hard copy/digital documentary-delivered interventions, or both, in facilitating, supporting, and sustaining self-management among people with COPD. In November 2016, we searched the Cochrane Airways Group Specialised Register (CAGR), which 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 we handsearched respiratory journals and meeting abstracts. We included randomised controlled trials that measured effects of remote and Web 2.0-based interventions defined as technologies including personal computers (PCs) and applications (apps) for mobile technology, such as iPad, Android tablets, smart phones, and Skype, on behavioural change towards self-management of COPD. Comparator interventions included face-to-face and/or hard copy/digital documentary educational/self-management support. Two review authors (CMcC and MMcC) independently screened titles, abstracts, and full-text study reports for inclusion. Two review authors (CMcC and AMB) independently assessed study quality and extracted data. We expressed continuous data as mean differences (MDs) and standardised mean differences (SMDs) for studies using different outcome measurement scales. We included in our review three studies (Moy 2015; Tabak 2013; Voncken-Brewster 2015) with a total of 1580 randomised participants. From Voncken-Brewster 2015, we included the subgroup of individuals with a diagnosis of COPD (284 participants) and excluded those at risk of COPD who had not received a diagnosis (1023 participants). As a result, the total population available for analysis included 557 participants; 319 received smart technology to support self-management and 238 received face-to-face verbal/written or digital information and education about self-management. The average age of participants was 64 years. We included more men than women because the sample from one of the studies consisted of war veterans, most of whom were men. These studies measured five of our nine defined outcomes. None of these studies included outcomes such as self-efficacy, cost-effectiveness, functional capacity, lung function, or anxiety and depression.All three studies included our primary outcome - health-related quality of life (HRQoL) as measured by the Clinical COPD Questionnaire (CCQ) or St George's Respiratory Questionnaire (SGRQ). One study reported our other primary outcomes - hospital admissions and acute exacerbations. Two studies included our secondary outcome of physical activity as measured by daily step counts. One study addressed smoking by providing a narrative analysis. Only one study reported adverse events and noted significant differences between groups, with 43 events noted in the intervention group and eight events in the control group (P = 0.001). For studies that measured outcomes at week four, month four, and month six, the effect of smart technology on self-management and subsequent HRQoL in terms of symptoms and health status was significantly better than when participants received face-to-face/digital and/or written support for self-management of COPD (SMD -0.22, 95% confidence interval (CI) -0.40 to -0.03; P = 0.02). The single study that reported HRQoL at 12 months described no significant between-group differences (MD 1.1, 95% CI -2.2 to 4.5; P = 0.50). Also, hospitalisations (logistic regression odds ratio (OR) 1.6, 95% CI 0.8 to 3.2; P = 0.19) and exacerbations (logistic regression OR 1.4, 95% CI 0.7 to 2.8; P = 0.33) did not differ between groups in the single study that reported these outcomes at 12 months. The activity level of people with COPD at week four, month four, and month six was significantly higher when smart technology was used than when face-to-face/digital and/or written support was provided (MD 864.06 daily steps between groups, 95% CI 369.66 to 1358.46; P = 0.0006). The only study that measured activity levels at 12 months reported no significant differences between groups (mean -108, 95% CI -720 to 505; P = 0.73). Participant engagement in this study was not sustained between four and 12 months. The only study that included smoking cessation found no significant treatment effect (OR 1.06, 95%CI 0.43 to 2.66; P = 0.895). Meta-analyses showed no significant heterogeneity between studies (Chi² = 0.39, P = 0.82; I² = 0% and Chi² = 0.01, P = 0.91; I² = 0%, respectively). Although our review suggests that interventions aimed at facilitating, supporting, and sustaining self-managment in people with COPD and delivered via smart technology significantly improved HRQoL and levels of activity up to six months compared with interventions given through face-to-face/digital and/or written support, no firm conclusions can be drawn. This improvement may not be sustained over a long duration. The only included study that measured outcomes up to 12 months highlighted the need to ensure sustained engagement with the technology over time. Limited evidence suggests that using computer and mobile technology for self-management for people with COPD is not harmful and may be more beneficial for some people than for others, for example, those with an interest in using technology may derive greater benefit.The evidence, provided by three studies at high risk of bias, is of poor quality and is insufficient for advising healthcare professionals, service providers, and members of the public with COPD about the health benefits of using smart technology as an effective means of supporting, encouraging, and sustaining self-management. Further research that focuses on outcomes relevant to different stages of COPD is needed. Researchers should provide clear information on how self-management is assessed and should include longitudinal measures that allow comment on behavioural change.

Twitter Demographics

The data shown below were collected from the profiles of 24 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 6 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 6 100%

Demographic breakdown

Readers by professional status Count As %
Unspecified 2 33%
Student > Ph. D. Student 1 17%
Student > Master 1 17%
Professor > Associate Professor 1 17%
Unknown 1 17%
Readers by discipline Count As %
Unspecified 3 50%
Social Sciences 1 17%
Medicine and Dentistry 1 17%
Unknown 1 17%

Attention Score in Context

This research output has an Altmetric Attention Score of 22. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 21 November 2018.
All research outputs
of 13,190,464 outputs
Outputs from Cochrane database of systematic reviews
of 10,519 outputs
Outputs of similar age
of 265,907 outputs
Outputs of similar age from Cochrane database of systematic reviews
of 246 outputs
Altmetric has tracked 13,190,464 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 94th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 10,519 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 20.6. This one has done well, scoring higher than 77% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 265,907 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 90% of its contemporaries.
We're also able to compare this research output to 246 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 65% of its contemporaries.