Summary of findings
This review focused on remote and web 2.0 interventions that promote physical activity (PA). It is part of a suite of three complementary reviews that provide both an update and a progression for the previously completed Cochrane review titled 'Interventions for promoting physical activity' (Foster 2005a). The titles of the other reviews in this suite are:
- 'Face-to-face interventions for promoting physical activity';
- 'Face-to-face versus remote and web 2.0 interventions for promoting physical activity'.
The evidence base for both face-to-face PA promotion and remote and web 2.0 interventions is rapidly growing and it is diverging. Consequently, we divided this Cochrane update into two separate reviews that focus on each of these delivery methods compared to true control groups. The third review enabled a head-to-head comparison of these intervention approaches for promoting PA. In all of the reviews we also considered how the effectiveness of PA interventions is influenced by implementing the intervention via a group or individually. The paradigm through which we approached these different methods of PA intervention delivery in this suite of reviews is summarised below (Figure 1).
|Figure 1. Delivery of PA interventions described according to interaction with implementer and other participants.|
Description of the condition
The health benefits of adequate levels of PA have been well documented (WHO 2010a). Previous systematic reviews and meta-analyses of observational studies have demonstrated the role of PA in the prevention and treatment of coronary heart disease, hypertension, stroke, type II diabetes, obesity, metabolic syndrome, breast cancer, colon cancer, osteoporosis, falls, depression, anxiety and negative self-concept (Haskell 2007; Janssen 2010; Kesaniemi 2001; Nelson 2007; Strong 2005; Warburton 2006; Williams 2001). It is estimated that in 2008 physical inactivity caused 9% of the premature mortality and 5.3 million deaths worldwide (Lee 2012); this included between 6% and 10% of all deaths from major non-communicable diseases globally. The burden of such diseases is increasing rapidly in low- and middle-income countries (Lee 2012; WHO 2010b).
The World Health Organization (WHO) recommends that adults should accumulate at least 150 minutes of moderate intensity, or 75 minutes of vigorous intensity, or an equivalent combination of aerobic PA throughout the week (WHO 2010a). This should be achieved in bouts of at least 10 minutes duration (WHO 2010a). Muscle strengthening activities involving the major muscle groups are also recommended on at least two days per week (WHO 2010a). Investigations into the dose-response relationship indicate that PA at levels higher than the minimum recommendations confer greater health benefits (Kesaniemi 2001; WHO 2010a).
The available data suggest that 31.1% of the world's adult population are not meeting the minimum recommendations for PA (Hallal 2012). The direct economic burden of physical inactivity is 1.5% to 3.0% of healthcare system costs and it is an emerging expense in low-and middle-income countries (Oldridge 2008). It has been estimated that increasing by 10% or 25% the number of people that achieve the WHO PA recommendations would prevent more than 553,000 and 1.3 million deaths, respectively, globally each year (Lee 2012).
Description of the intervention
It has long been accepted that various interventions can promote PA participation and improve health (Dishman 1996). This has prompted growing global interest and investment in PA interventions by different stakeholders using a variety of methods (Heath 2012). It is evident that there are opportunities to influence personal, social and environmental determinants of PA in different contexts and populations (Bauman 2012). A previous Cochrane review found that PA interventions had a moderate effect on participation levels (Foster 2005a). However, conclusions could not be drawn about the effectiveness of isolated components for achieving and maintaining recommended levels of PA in the population.
For the purposes of this review an intervention is any deliberate attempt to increase the PA levels of the participants. It may be delivered using various methods and implemented through a broad range of professions (for example health professional, exercise specialist, PA researchers). This is consistent with the principles of the previous versions of this review (Foster 2005a). The additional critical component of remote and web 2.0 interventions is that the interaction with the implementer does not occur in person. These interventions can be delivered to groups or individually, and several examples are presented below ( Table 1).
How the intervention might work
One of the earliest reviews of the determinants of PA stated that few interventions or adherence studies were based on any theoretical or psychological models (Dishman 1990). However, when the review was repeated four years later the authors noted a marked increase in the use of theories in the studies and interventions (Dishman 1994). It is now accepted that well designed PA interventions are based upon behavioural theories (Bartholomew 2001) but understanding how these are translated into practical strategies needs further evaluation (Foster 2005a). Behavioural theories provide a foundation for an intervention that can explain the drivers of PA behaviour and potential pathways for change (Foster 2005b). They inform the planning, development and implementation of PA interventions, and the majority of studies have also adopted social psychology theories (Biddle 2011).
The use of new media technologies to deliver PA interventions has required implementers to consider the relevance of the existing theories and evidence base. Remote and web 2.0 interventions have emerged from the behavioural theories and strategies that underpin face-to-face interventions, but differ in their delivery. This digital shift has its own brand of science called captology, which is the study of computers as persuasive technologies (Fogg 2002). It includes the design, research and analysis of interactive computing products (for example computers, mobile phones, websites, wireless technologies, mobile applications, video games) created for the purpose of changing people’s attitudes or behaviours. Although captology itself is not a theory, it is the application of different theoretical approaches to deliver the intervention via interactive computing products. Captology has been increasingly observed in trials testing different media delivery systems that take behavioural theories and translate them into cognitive-behavioural strategies (Fogg 2007).
Remote and web 2.0 strategies typically involve 'pushing' tailored information via e-mail or short message service (SMS) from a central source to the participants (Waller 2006). This could include assessment of current behaviour and feedback on current PA levels versus recommendations, motivation and confidence building messages and goal setting prompts (Biddle 2011). Specific examples of remote and web 2.0 interventions targeted at individuals and groups were described previously ( Table 1). These types of approaches are dependent on varying the dose of the intervention components. Changing the dose could include altering the frequency of contacts and duration of the participant’s interaction with the intervention, similar to the frequency and contact time found in face-to-face interventions. However, the frequency and duration of the intervention may be different when implemented remotely and may also be augmented by flexibility in the delivery timing (Waller 2006).
Recent systematic reviews consistently describe the effectiveness of internet based PA interventions as short rather than long term, with little data to support what elements of the intervention are related to any changes (Norman 2007; Portnoy 2008; Vandelanotte 2007). The reviews found a range of behavioural theories underpinning these interventions, which are similar to those described for face-to-face interventions. These include the Health Belief Model (HBM) (Becker 1974); the Theory of Reasoned Action/Planned Behaviour (TRA) (Fishbein 1975); Social Cognitive Theory (SCT) (Bandura 1986); and the Transtheoretical Model of behaviour change (TTM) (Prochaska 1982). A recent meta-analysis that tried to determine which internet delivered strategies were particularly effective in producing behaviour change identified the inclusion of educational components as the only factor that contributed significantly to increased intervention effectiveness (Davies 2012).
Why it is important to do this review
Although it is known that the behaviour of individuals can be influenced by PA interventions, the most effective delivery method is not clear (Foster 2005a). In recent times there has been an emergence of remotely delivered interventions that has accelerated with the advent of web 2.0 technology (van den Berg 2007). This impetus has displaced several more traditional face-to-face methods of implementing PA interventions (van den Berg 2007).
It is intended that this review will provide an up-to-date indication of the effectiveness of remote and web 2.0 PA interventions. Understanding the effectiveness of these newer approaches to implementation should influence PA policy makers and professionals. Completing this update ensures that the most effective implementation methods are identified and is integral to optimising health related outcomes associated with the promotion of PA participation.
To compare the effectiveness of remote and web 2.0 interventions for physical activity (PA) promotion in community dwelling adults (aged 16 years and above) with a control group exposed to placebo or no or minimal intervention.
If sufficient data exist, the following secondary objectives were assessed.
- Does delivering the intervention to a group versus individually versus mixed (a combination of group and individually) influence the effectiveness in changing PA?
- Does the professional delivering the intervention (for example health professional, exercise specialist) influence the effectiveness in changing PA?
- Does specifying PA type (for example walking, jogging, aerobics) influence the effectiveness in changing PA?
- Does generating the prescribed PA using an automated computer programme influence the effectiveness in changing PA?
- Does including pedometers as part of the intervention influence the effectiveness in changing PA?
Criteria for considering studies for this review
Types of studies
Randomised controlled trials (RCTs) that compared remote and web 2.0 PA interventions for community dwelling adults with a placebo or no or minimal intervention control group. We included studies if the principal component of the intervention was delivered using remote and web 2.0 methods. To assess behavioural change over time the included studies had a minimum of 12 months follow-up from the start of the intervention to the final results. We excluded studies that had more than a 20% loss to follow-up if they did not apply an intention-to-treat analysis.
Types of participants
Community dwelling adults, aged from 16 years to any age, who were free from pre-existing medical conditions or with no more than 10% of participants with pre-existing medical conditions that may have limited participation in PA.
We excluded interventions on trained athletes or sports students.
We only included studies that measured PA at an individual level.
Types of interventions
Remote and web 2.0 PA interventions could be delivered using recently developed technologies (for example internet, smart phones) or more traditional methods (for example telephone, mail-outs), or both. Web 2.0 interventions have been categorised as more interactive applications that encourage higher levels of user involvement than web 1.0 Internet programmes (O'Reilly 2005). The interventions could be delivered to groups or individuals. They could involve one-off or ongoing interactions between the implementer and the participants that included:
- counselling or advice, or both;
- self-directed or prescribed exercise, or both;
- home based or facility based exercise, or both;
- written education or motivational support material, or both.
We excluded mass media and multiple risk factor interventions.
The comparison was with a control group exposed to placebo or no or minimal intervention.
Types of outcome measures
The primary outcomes of this review included data that assessed change between baseline and follow-up for:
- cardio-respiratory fitness (CF), which is often used as a marker for PA and demonstrates similar associations with health related outcomes (Blair 2001). It was either estimated from a submaximal fitness test or recorded directly from a maximal fitness test. CF was typically expressed as a VO
2max score, which is an abbreviation for maximal oxygen uptake (ml/kg/min or ml/min);
- PA levels, expressed as an estimate of total energy expenditure (kcal/kg/week or kcal/week), total minutes completed at a moderate or vigorous intensity, proportion that reached a predetermined threshold level (for example meeting current public health recommendations), or frequency of participation as a dichotomous or continuous outcome variable. PA could be assessed using objective methods (for example accelerometers, pedometers) or more subjective tools (for example PA diary, survey).
Both 12 and 24 month outcomes were included in the analysis.
The secondary outcomes of this review included data relevant to:
- quality of life (for example quality-adjusted life years (QALYs));
- cost (for example cost-benefit, cost-utility);
- adverse events (for example musculoskeletal injury, cardiovascular event).
Search methods for identification of studies
We searched the following databases between the 9 October 2012 and 11 October 2012:
- CENTRAL (Issue 9 of 12, 2012) in The Cochrane Library;
- MEDLINE (Ovid) (1946 to week 4 September 2012);
- EMBASE Classic and EMBASE (Ovid) (1947 to week 40 2012);
- CINAHL Plus with Full Text (EBSCO);
- PsycINFO (Ovid) (1806 to week 1 October 2012);
- Web of Science.
We based the search on the previous methods used for the 'Interventions for promoting physical activity' Cochrane review (Foster 2005a) (Appendix 1) and updated them with some amendments (Appendix 2).
The Cochrane RCT filter (sensitivity maximising) was applied to MEDLINE (Ovid), and search terms as suggested in the Cochrane Handbook for Systematic Reviews of Interventions were used to limit studies to RCTs in EMBASE (Ovid) (Lefebvre 2011). Adaptations of these filters were used in the other databases except for CENTRAL.
We did not apply any language restriction to the searches.
Searching other resources
We conducted handsearching for the International Journal of Behavioural Nutrition and Physical Activity (February 2004 to October 2012). The reference lists of all relevant articles identified during the search were checked by the authors. We also used published systematic reviews of PA interventions as a source for identifying RCTs.
We communicated directly with authors to identify and request unpublished studies and data. A comprehensive list of relevant articles along with the inclusion criteria for the review were sent to the first author of each paper that met the inclusion criteria to ask if they knew of any additional published or unpublished studies which were relevant.
Data collection and analysis
Selection of studies
Two authors (CF, JR) independently manually screened the titles identified in the initial search to exclude those that were obviously outside the scope of the review. The authors were conservative at this stage and where disagreement occurred the citation was included for abstract review. Two authors (CF, JR) independently reviewed the abstracts of all citations that passed the initial title screening. They applied the inclusion criteria in the following way to determine if the full paper was needed for further scrutiny.
Did the study:
- aim to examine the effectiveness of a PA or CF promotion strategy to increase PA or cardiovascular fitness (CVF) levels;
- use principally remote or web 2.0 methods to promote PA to the intervention group;
- allocate participants to the intervention or control group using a method of randomisation;
- have a control group that was exposed to placebo, or no or minimal intervention;
- include adults aged 16 years and older;
- recruit community dwelling adults that were free of chronic disease or with no more than 10% of participants with pre-existing medical conditions that may limit participation in PA;
- have a follow-up period of at least 12 months between commencing the intervention and measuring the outcomes;
- analyse the results by intention to treat or, failing that, was there less than 20% loss to follow-up.
The authors were conservative at this stage and where disagreement occurred the citation was included for full text review. Two authors (CF, JR) reviewed the full texts of all studies that passed the abstract screening, using the inclusion criteria described above, to identify a final set of eligible studies. The studies included in the previous 'Interventions for promoting physical activity' Cochrane review were also allocated within the new suite of reviews by two authors (CF, JR) (Foster 2005a). When there was persisting disagreement it was resolved by consensus after a third author (MH or MT) reviewed the study in question. Publications and reports that utilised the same data were linked to avoid replication in the analysis.
Data extraction and management
The data extraction form was piloted independently by two authors (CF, JR) and subsequently adjusted to ensure it captured the relevant data. One author (CF or JR) and a Research Fellow from the Warwick Medical School (NF) independently extracted the data from all of the selected studies using the standard form. When there was disagreement a third author reviewed the study and consensus was reached (CF or JR: the author out of these two that did not do the initial data extraction). We extracted data from multiple publications of the same study separately and then combined them to avoid replication. Any missing or ambiguous data were clarified with the study first author via e-mail.
Assessment of risk of bias in included studies
The risk of bias was only assessed and reported for studies that met the inclusion criteria (Higgins 2011).
Two authors (CF, JR) assessed the risk of bias. Where there was disagreement between review authors in the risk of bias assessment, a third author (MH or MT) was asked to independently appraise the study and discrepancies were resolved by consensus between all three authors.
We assessed the studies for the five general domains of bias: selection, performance, attrition, detection, and reporting. Quality scores were allocated for:
- allocation sequence generation;
- allocation concealment;
- incomplete outcome data;
- selective outcome reporting;
- comparable groups at baseline;
- contamination between groups;
- validated outcome measures;
- outcome measure applied appropriately;
- final analysis adjusted for baseline PA levels;
- outcome assessment independent and blinded;
- intention-to-treat analysis.
When sufficient information was available, we classified each study as at 'high' or 'low' risk of bias for each item. When there was a lack of information or uncertainty over the potential for bias, we described the domain as 'unclear'. We judged the quality of the evidence as 'low', 'medium', or 'high' given the consideration of the study design and size, and the potential impact of the identified weakness noted in the risk of bias table for each study.
Measures of treatment effect
For each study with dichotomous outcomes, we expressed the effect size using an odds ratio (OR). For each study with continuous outcomes, we expressed the effect size using the standardised mean difference (SMD) between the post-intervention values of the randomised groups. We completed a narrative summary of the study results and when there were sufficient data we completed a formal meta-analysis of the included studies.
Unit of analysis issues
When possible, we analysed the studies using the mean and standard deviation (SD) and visualised the results using forest plots. Alternatively, we reported only the point estimate with confidence intervals (CIs) and P values.
When a study had more than one study arm relevant to this review, we examined the overall effects of the intervention versus control by combining the data from the related study arms. We calculated the mean and SD according to the overall numbers within each arm using established approaches (Higgins 2011).
For each study with dichotomous outcomes we calculated an OR and 95% CI. We used the numbers of participants in each arm that were reported as an event (for example active at a predetermined level) or no event (for example not active). Where appropriate, we calculated individual study effects and then the pooled effect sizes as ORs with 95% CIs using a random-effects model. We calculated any missing 95% CIs using established approaches (Higgins 2008).
Dealing with missing data
We excluded studies that had a high degree of incomplete data (that is less than 40% of data) during the risk of bias assessment or when it appeared that missing data were likely to be associated with the reported intervention effect. We contacted the authors of the potentially included studies if missing data were unclear or data had not been fully reported. Missing data were captured in the data extraction form and reported in the risk of bias table.
Assessment of heterogeneity
We quantified and evaluated the amount of heterogeneity to determine whether the observed variation in the study results was compatible with the variation expected by chance alone (Deeks 2011). Heterogeneity was assessed through examination of the forest plots and was quantified using the I
Assessment of reporting biases
We plotted trial effect against standard error and presented it as a funnel plot (Sterne 2011). Asymmetry could be caused by a relationship between effect size and sample size or by publication bias, we also examined any observed effect for clinical heterogeneity (Sterne 2011).
When possible we reported all continuous outcomes on the original scale. If the outcomes were combined from different scales we standardised them as required for the analysis. We only completed a meta-analysis when the data were clinically homogeneous and we followed established Cochrane methods (Deeks 2011). If data were available, sufficiently similar, and of adequate quality, we used the Cochrane Collaboration's statistical software, Review Manager 2012, to perform the statistical analyses. We used a random-effects model as the default to incorporate heterogeneity between studies. We did not combine evidence from differing study designs and outcome types in the same forest plot (Christinsen 2009).
Subgroup analysis and investigation of heterogeneity
We performed subgroup analyses to compare interventions that were delivered:
- to a group versus individually versus mixed (a combination of group and individually);
- by a health professional versus a non-health professional;
- with a PA type that was specified versus not specified;
- with a computer generated prescription versus a human generated prescription;
- with a pedometer versus without a pedometer.
We conducted a sensitivity analysis for studies that definitively met at least 50% of the applicable criteria reported in the 'Risk of bias' tables.
Description of studies
See 'Characteristics of included studies'; 'Characteristics of excluded studies'; 'Characteristics of studies awaiting classification'; 'Characteristics of ongoing studies'
Results of the search
From 27,299 de-duplicated hits, the full texts of 193 papers were retrieved for examination against the inclusion criteria (Figure 2). There were 30 papers describing 11 studies that met the inclusion criteria (Castro 2011; Elley 2003; King 1991; King 2007; Kinmonth 2008; Kolt 2007; Lawton 2008; Marcus 2007; Martinson 2010; Napolitano 2006; van Stralen 2011).
|Figure 2. Study flow diagram.|
All searches were completed in October to November 2012. The results of the searches of the electronic databases are detailed in Table 2.
There were 5862 apparently healthy adults who participated in the 11 included studies. The majority of studies recruited both genders with three studies recruiting women only (Elley 2003; Lawton 2008; Napolitano 2006). The stated age range of participants was from 18 to 74 plus years. Details on the ethnic group of participants were reported in seven studies (Castro 2011; King 1991; Kinmonth 2008; Lawton 2008; Marcus 2007; Martinson 2010; Napolitano 2006), with proportions of participants in ethnic minorities ranging from 7% to 33%. Participants were recruited from two settings, primary health care and the community. All of the studies took place in high-income countries.
The interventions were primarily delivered individually and without direct supervision of PA. PA type was specified in one study (King 2007) and delivered by a health professional in two studies (Elley 2003; King 2007). The PA prescription was computer generated in four studies (King 2007; Marcus 2007; Napolitano 2006; van Stralen 2011) and a pedometer was used in three studies (King 2007; Kinmonth 2008; Martinson 2010).
Nine studies included PA self-report at 12 months as an outcome measure (Castro 2011; Elley 2003; King 2007; Kinmonth 2008; Kolt 2007; Marcus 2007; Martinson 2010; Napolitano 2006; van Stralen 2011) and this was sustained for 24 months in one of these studies (Martinson 2010). One study reported a dichotomous outcome variable for PA at both 12 and 24 months (Lawton 2008). There were two studies that reported cardiovascular fitness (CVF) at 12 months (King 2007; Kinmonth 2008).
Two studies were found to be eligible for inclusion from the Foster 2005a review (Elley 2003; King 1991) and nine studies were identified by the updated search (Castro 2011; King 2007; Kinmonth 2008; Kolt 2007; Lawton 2008; Marcus 2007; Martinson 2010; Napolitano 2006; van Stralen 2011).
The reasons for excluding papers that underwent full text review are outlined in the 'Characteristics of excluded studies' table. Three main reasons contributed to almost 80% of exclusions. The most prevalent was less that 12 months follow-up (n = 78), followed by no appropriate control or intervention group (n = 37) or a face-to-face intervention only (n = 14). There was also one ongoing study (McAuley 2012) and one study awaiting classification (Peels 2012) at the time of this review. The Peels 2012 data were recently published, outside the search period, and will be included in an update of this review.
Risk of bias in included studies
We assessed the risk of bias of the included studies as moderate in three studies (Martinson 2010; Napolitano 2006; van Stralen 2011) and low in the remaining included studies (Castro 2011; Elley 2003; King 1991; King 2007; Kinmonth 2008; Kolt 2007; Lawton 2008; Marcus 2007), see Table 3 and Table 4.
All studies used randomised controlled designs. Three studies were assessed to have an adequate approach to allocation sequence generation (Castro 2011; Elley 2003; King 1991), with all other studies classified as having an unclear risk of bias in their allocation concealment approaches with the exception of Lawton 2008. Six studies were assessed as at low risk of selection bias as they reported comparable groups at baseline for important confounders or covariates (Castro 2011; Elley 2003; King 1991; King 2007; Kinmonth 2008; Marcus 2007).
We did not rate studies on whether participants were blinded to their group allocation. This would not be appropriate for studies of this type because it is very difficult to blind participants to a PA intervention. We did assess studies on their performance bias, which included whether their outcome assessments were performed independently and by an assessor who was blinded to participant allocation status. Nine studies were assessed to have low risk of performance bias with these criteria (Castro 2011; King 1991; King 2007; Kinmonth 2008; Kolt 2007; Lawton 2008; Marcus 2007; Martinson 2010; Napolitano 2006). Elley 2003 was assessed to have a high risk of bias for blinding and independence of outcome assessment, with van Stralen 2011 assessed as unclear.
All studies were judged to have a low risk of detection bias. This was an assessment of the validity and quality of outcome measures, plus the appropriateness of their application to the participants.
Incomplete outcome data
Six studies were assessed as being at low risk of attrition bias as they reported complete outcome data and presented reasons for any participant dropouts (Castro 2011; Elley 2003; King 2007; Kinmonth 2008; Lawton 2008; Marcus 2007). Four studies were assessed as being at high risk of bias for not reporting attrition data (King 1991; Kolt 2007; Napolitano 2006; van Stralen 2011).
Other potential sources of bias
Other potential sources of bias included two criteria used in our earlier version of this review (Foster 2005a). These were adjusting the final results for the baseline values of PA and adopting an intention-to-treat analysis approach.
Adjusting for baseline values of PA is particularly important in behaviour change studies as there is a likelihood of overestimating effects if baseline adjustment is not performed when using dichotomous outcome measures (for example per cent of adults achieving recommended level of PA). Only six studies had a low risk of bias for this criterion (King 1991; King 2007; Kinmonth 2008; Kolt 2007; Lawton 2008; Marcus 2007) and, from the remaining five studies, four were assessed as being unclear (Castro 2011; Martinson 2010; Napolitano 2006; van Stralen 2011); Elley 2003 was assessed as not adjusting for baseline values.
Intention-to-treat analysis underpins the principles of an RCT design to minimise bias. Therefore, we considered failure to include all randomised participants in the final outcome analysis within their allocated group as a critical risk of bias. Seven studies were assessed to have conducted an intention-to-treat analysis (Castro 2011; Elley 2003; King 2007; Kinmonth 2008; Lawton 2008; Marcus 2007; Martinson 2010), with three studies not meeting this criterion (King 1991; Kolt 2007; Napolitano 2006) and van Stralen 2011 assessed as unclear. The proportion of participants in the studies that did not perform an intention-to-treat analysis who were lost to follow-up ranged from 7.1% to 15.9%.
Effects of interventions
Cardio-respiratory fitness (CF)
Two studies (444 participants) reported the effect of their intervention on CF (King 1991; Kinmonth 2008). The pooled effect was positive and moderate with significant heterogeneity in the observed effects (SMD 0.40; 95% CI 0.04 to 0.76), see Analysis 1.1. King 1991 reported a significant difference in VO
Self-reported physical activity - reported as a dichotomous measure
One study (1089 participants) reported PA as a dichotomous measure, which indicated whether a predetermined level of PA was achieved or not (Lawton 2008), see Analysis 1.2, Analysis 1.3. The Women's Lifestyle Study reported significant increases in the proportion of women participants reporting they had achieved the recommended level of 150 minutes of at least moderate intensity PA, as assessed by the NZPAQ-LF at two years (OR 1.33; 95% CI 1.03 to 1.70). This effect was a decline from the levels reported at one year (OR 1.73; 95% CI 1.34 to 2.21). Participants were inactive women aged 40 to 74 years and were recruited via primary care. The participants received written advice from a primary care nurse and a discussion on increasing PA and goal setting, lasting 7 to 13 minutes. The participants received a green prescription card stating their recommended PA. After this meeting a local exercise specialist called all participants (on average five calls each lasting 15 minutes) to encourage PA, using motivational interviewing techniques, over a nine month period. An additional 30 minute visit with a nurse was offered at six months, plus fridge magnets and activity record charts. We noted that although participants were recruited through primary care, their participation was by special invitation and the delivery of the intervention was not part of routine care. The focus on older women, the self-selected nature of participants, and the overall participation rate in this group of 19.5% seemed relatively low in terms of reach.
Self-reported physical activity - reported as a continuous measure
Nine studies (4547 participants) reported their main outcome as one of several continuous measures of PA (Castro 2011; Elley 2003; King 2007; Kinmonth 2008; Kolt 2007; Marcus 2007; Martinson 2010; Napolitano 2006; van Stralen 2011). Measures included estimated energy expenditure (kcals/day, kcals/week of moderate or vigorous PA (MVPA)), total time of PA (mean mins/week of MVPA), and mean number of occasions of PA in past four weeks. The pooled effect of these studies at one year was positive and moderate (SMD 0.20; 95% CI 0.11 to 0.28), see Analysis 1.4. There was no significant heterogeneity in the observed effects (I
Martinson 2010 was the only study to report outcomes at 24 months, from the Keep Active Minnesota intervention. The outcome measure was minutes of MVPA as assessed by the CHAMPS questionnaire. Inactive adults aged 50 to 70 years were recruited using the health data of members of a health mainenance organisation (HMO). Intervention participants all received a group introduction session, written materials, and an appointment with a phone coach (an exercise sports scientist). This was followed by seven 20 minute phone calls, plus mailed workbooks and pedometers. Then after a review of progress they received monthly phone calls up to 12 months then six calls over the next 12 months. In addition, three motivational challenges were held that included prizes, incentives, DVDs and videos. This study reported a high level of intervention compliance (at six months) with nearly 92% of intervention participants completing at least one phone course session. Nearly 40% of intervention participants completed all seven phone sessions, but these participants were more educated, in better self-reported health, older, had a lower BMI, and were less likely to be in full time employment than participants who did not complete all calls.
Studies with positive SMDs used a range of different intervention approaches, with varying effect sizes. Castro 2011 recruited inactive adults, aged 50 years and older, and delivered telephone based advice by either trained professional staff or volunteer peer mentors. Telephone calls were delivered twice per month for the first two months and then monthly (up to 14 calls) until 12 months. This followed an initial face-to-face meeting with the staff or peer mentor. Change in MVPA was assessed by using the CHAMPS questionnaire but it was only validated by objective measures at six months. Both peer and professional mentors achieved significant increases in minutes of MVPA compared to the outcome in control participants (SMD 0.47; 95% CI 0.15 to 0.78).
Elley 2003 recruited inactive adults, aged 40 to 79 years, via primary care. Participants received motivation counselling from their general practitioner. This included discussion on increasing PA and goal setting. The participants received a green prescription card stating their recommended PA. After this meeting a local exercise specialist called all participants at least three times to encourage PA using motivational interviewing techniques. Written materials were also sent to participants every three months. These materials included information about local PA opportunities and motivational material. Increases in total energy expenditure assessed by self report were significant (SMD 0.19; 95% CI 0.06 to 0.32).
King 2007 evaluated the effectiveness of PA advice delivered by humans versus advice delivered by computers in the Telephone (CHAT) trial. Sedentary 55 year old adults were recruited to receive either telephone-assisted PA counselling by a health educator or automated computer system generated advice for 30 to 40 minutes plus 15 (10 to 15 minute) phone calls over 12 months. Participants were also sent mail-outs, a pedometer and daily step logs. The computer advice group interacted by touch phone key pads. Both intervention arms achieved nearly 40 minutes per week additional MVPA compared to the control participants with a significant pooled effect (SMD 0.36; 95% CI 0.05 to 0.66).
Kolt 2007 recruited older adults (aged 65 years and older) to the Telewalk intervention. Participants received eight telephone counselling calls over 12 weeks (weekly for the first four weeks and then every two weeks for the remaining eight weeks of the intervention) encouraging them to increase their participation in all forms of PA. The outcome measure was assessed by telephone using the Auckland Heart Study Physical Activity Questionnaire (AHSPAQ) and the mean difference of leisure time PA (mins/week) between the intervention and control groups was approximately 130 minutes at one year (SMD 0.45; 95% CI 0.15 to 0.76).
Marcus 2007 recruited a younger sample compared to other studies of adults. The participants were aged 18 to 65 years and participated in Project STRIDE. All participants received baseline written materials recommending 150 minutes a week of moderate PA and completed PA logs and questionnaires each month. Each participant's response generated tailored feedback containing theory based counselling messages. This feedback was communicated back to each participant, either via mail or by telephone, by a health educator. Contacts were phased at weekly for the first four weeks, biweekly for eight weeks, monthly for three months, and bimonthly for six months. Both intervention groups reported more mins of MVPA per week than controls with the print group nearly 50 minutes more than the phone group (SMD 0.36; 95% CI 0.09 to 0.63).
Martinson 2010 reported slight, significant differences between the intervention and control groups at one year (SMD 0.14; 95% CI 0.02 to 0.26).
|Figure 3. Funnel plot of comparison: 1 Remote and web 2.0 interventions versus control, outcome: 1.4 Self-reported physical activity: 12 months.|
Sensitivity analysis by study quality
We examined the pooled effects for the three types of outcome data (self-reported PA, dichotomous and CF outcomes) by an assessment of study risk of bias. We stratified studies on their risk of bias assessments (ROB), see Table 3 and Table 4, by only pooling estimates of effects for studies that had a lower risk of bias (≥ 50% of ROB criteria). Pooled estimates are presented for each outcome type, see Analysis 2.1, Analysis 2.2, Analysis 2.3, Analysis 2.4. Six studies were included (3403 participants) in the sensitivity analysis. A positive and significant pooled estimate was found for self-reported PA effects at 12 months (SMD 0.28; 95% CI 0.16 to 0.40), see Analysis 2.4. This was an increase in the estimated pooled effect compared to the nine studies (SMD 0.20; 95% CI 0.11 to 0.28).
Quality of life
Five studies reported quality of life outcomes, with four of them using the SF-36 measure (Elley 2003; Kinmonth 2008; Kolt 2007; Lawton 2008) and King 2007 using a Vitality Plus Scale of general well-being, see Table 5. From the four studies that reported increases in PA, positive changes in quality of life were reported by King 2007 (human advice arm) and Lawton 2008 in the SF-36 physical functioning and mental health subscales. Elley 2003 reported that the SF-36 scores of self-rated ‘general health’, ‘role physical’, ‘vitality’, and ‘bodily pain’ improved significantly more in the intervention group compared with the control group. Kolt 2007 reported that no differences in SF-36 measures were observed between the groups at 12 months. Although Kinmonth 2008 reported no impact of PA between the intervention and control groups, SF-36 scores for the intervention participants were better than in the control group for six out of eight SF-36 scales. Small effect sizes were reported for physical function, general health and anxiety. Small to moderate effect sizes were reported for social function, energy levels and change in health. Moderate effects were reported for aspects of mental health and impact on daily activities. These effects occurred independently of any change in PA.
Three studies reported data for cost effectiveness (Elley 2003; Lawton 2008; Marcus 2007), see Table 6. All three studies reported positive findings for both PA and quality of life measures which appeared to be linked to the calculations of cost effectiveness. Using a different outcome for their intervention Elley 2003 reported that the programme-cost per patient was NZD 170 from a funder’s perspective. The monthly cost effectiveness ratio for total energy expenditure achieved was NZD 11 per kcal/kg/day. The incremental cost of converting one additional ‘sedentary’ adult to an ‘active’ state over a 12 month period was NZD 1756 in programme costs. Lawton 2008 adapted the Green Prescription approach used in the earlier Elley 2003 study but applied a dichotomous measures of PA (% achieving a recommended level). The exercise programme cost was NZD 93.68 (GBP 45.90) per participant. There was no significant difference in indirect costs over the course of the trial between the two groups (rate ratio 0.99; 95% CI 0.81 to 1.2 at 12 months and 1.01; 95% CI 0.83 to 1.23 at 24 months, P = 0.9). Cost effectiveness ratios using programme costs were NZD 687 (EU 331) per person made ‘active’ and sustained at 12 months and NZD 1407 (EU 678) per person made ‘active’ and sustained at 24 months. Finally Marcus 2007 reported that the phone group’s cost effectiveness was $3.53/month/min of improvement, and the print group’s cost effectiveness was $0.35/month/min of improvement in PA recall. At 12 months the cost of moving one person out of sedentary status was $3967 for the phone group and $955 for the print group.
Seven studies reported data on adverse events, see Table 7 (Castro 2011; Elley 2003; King 1991; King 2007; Kinmonth 2008; Kolt 2007; Lawton 2008). King 2007 reported that PA related non-cardiac injuries were few and were similar in number across study arms. These included mild muscular fatigue, strain, or soreness during the initial three to four months of the intervention. Kinmonth 2008 provided detailed data on adverse events for 32 participants who within a year of randomisation had visited either a family doctor, emergency department, or hospital outpatients department for pain or injury to muscles, joints, or bones during or after PA. Kolt 2007 reported that there was no evidence of more falls in the intervention group than in the control group over the 12 month trial period. Lawton 2008 reported the number of falls and injuries at 12 and 24 months and the proportions of participants reporting either a fall or injury were significantly higher in the intervention compared to the control group at both time points. Three studies reported no significant difference in adverse events or no major adverse events (fractures and sprains), falls, illness and potential cardiovascular events between groups (Castro 2011; Elley 2003; King 1991).
Does delivering the intervention to a group versus individually versus mixed (combined group and individually) influence the effectiveness in changing PA?
No studies adopted a consistent group based approach as part of their intervention, see Analysis 3.1. Although Martinson 2010 did offer a group approach to orientate participants to their intervention, we found few group based approaches, which may reflect the individual nature of the communication mechanisms (telephone or computer) used in remote and web 2.0 interventions.
Does the professional delivering the intervention (for example health professional, exercise specialist) influence the effectiveness in changing PA?
Two studies delivered their interventions via a health professional (Elley 2003; King 2007) while the remaining seven did not (Castro 2011; Kinmonth 2008; Kolt 2007; Marcus 2007; Martinson 2010; Napolitano 2006; van Stralen 2011), see Analysis 3.2, Analysis 3.3. The pooled estimate effect for non-health professionals (SMD 0.19; 95% CI 0.09 to 0.30) was very simlar to health professionals (SMD 0.21; 95% CI 0.09 to 0.34).
Does specifying physical activity type (for example walking, jogging, aerobics) influence the effectiveness in changing PA?
Only one study specified the type of PA for its participants (King 2007), with the majority allowing participants a choice (Castro 2011; Elley 2003; Kinmonth 2008; Kolt 2007; Marcus 2007; Martinson 2010; Napolitano 2006; van Stralen 2011), see Analysis 3.4, Analysis 3.5. King 2007 did report a large increase in PA between the intervention and control groups (SMD 0.36; 95% CI 0.05 to 0.66), but more studies are needed to assess if this can be replicated.
Does generating the prescribed physical activity using an automated computer programme influence the effectiveness in changing PA?
We found no difference in pooled estimates between studies that generated the prescribed PA using an automated computer programme versus a human approach. Four studies generated their PA prescriptions by computer (King 2007; Marcus 2007; Napolitano 2006; van Stralen 2011), with a pooled positive estimate (SMD 0.18; 95% CI 0.04 to 0.33) that was similar to the remaining studies that generated and delivered their prescriptions via humans (SMD 0.22; 95% CI 0.10 to 0.34). However, the similarity of the pooled estimates of effect raised the issue that one approach may be more cost effective than the other. This observation was supported by the results of Marcus 2007 and warrants further investigation.
Does including pedometers as part of the intervention influence the effectiveness in changing PA?
We found no difference between studies that included pedometers as part of their intervention and those that did not. Three studies included pedometers as part of their intervention (King 2007; Kinmonth 2008; Martinson 2010) (SMD 0.16; 95% CI 0.05 to 0.27). However, both King 2007 and Martinson 2010 placed emphasis on encouraging participants to use the pedometers as a behavioural tool to self-monitor walking levels whereas Kinmonth 2008 let participants use pedometers if appropriate. The pooled estimate for the non-pedometer studies was positive and significant (SMD 0.23; 95% CI 0.11 to 0.35).
Summary of main results
We were able to find consistent evidence to support the effectiveness of remote and web 2.0 interventions for promoting PA. These interventions have positive, moderate sized effects on increasing self-reported PA and measured cardio-respiratory fitness (CF), at least at 12 months. The effectiveness of these interventions was supported by moderate and high quality studies. We were not able to assess the longer term effectiveness of remote and web 2.0 interventions to promote PA beyond 12 months.
The most effective interventions applied a tailored approach to the type of PA and used telephone contact to provide feedback and to support changes in PA levels. We were not able to identify if the person who initiates (health professional or exercise counsellor) or who implements the intervention (human versus machine) has any positive or negative differential impact on outcomes. We were unable to determine the effectiveness of interventions with any specific groups beyond older and well educated adults. The participants in the studies that were reviewed were generally white, well educated and middle aged, and it is possible that the observed effects may be different in the wider population. There were no studies in this review that examined the effectiveness of interventions in minority groups of any kind.
We did not find any randomised controlled studies (RCTs) with at least 12 months follow-up that assessed web or computer based interventions. This reflected that our excluded studies either did not have sufficient follow-up (at least 12 months) or had inadequate study designs that commonly lacked true control groups.
We were not able to assess if the most effective interventions could be easily translated into existing practice. This is an important step as some interventions included components that would be difficult to deliver in usual practice due to resource demand, necessary follow-up, and extensive contact time. Our findings indicate that further investigation is needed to examine the cost effectiveness of automated systems to generate PA prescriptions and to deliver feedback remotely. Such systems may be attractive to practice, particularly if effectiveness is comparable to more expensive approaches. This is a priority as only three studies presented data on the long term cost effectiveness of their intervention.
Overall completeness and applicability of evidence
Our conclusions are limited because studies were all delivered in high-income countries, but this may be due to the technology focus of this review. Our review demonstrates that there is high quality evidence to support the effectiveness of remote and web 2.0 interventions for promoting PA, but we note that the majority of studies targeted older adults (50 plus years) rather than younger adults.
The participants in the studies that were reviewed were generally white, well educated and middle or older aged, and it is possible that the observed effects may be different in the wider population. There were no studies in this review that examined the effectiveness of interventions that targeted minority groups of any kind.
The potential applicability of this evidence is potentially high as interventions were initiated either by phone calls or face-to-face contacts and sustained by phone calls or web based technologies. There is clearly a need to replicate these effective interventions across different communities in high-, middle- and low-income countries. We did not find any evidence of publication bias in this review.
Quality of the evidence
The overall quality of studies was higher than our previous review of interventions to promote PA to adults (Foster 2005a). Studies were all consistently using validated outcome measures applied appropriately. This is particularly important given the small differences in changing levels of PA between the intervention and control groups, as intervention effects wane. We recognise that most studies used self-report measures of PA, which are subject to recall bias and may lack precision, but any misclassification is non-differential (as both the intervention and control groups complete the measure) and will attenuate the effect of the intervention. This problem did not apply to measures of cardio-respiratory fitness. The majority of studies adopted sound designs in addressing blinding, independence of outcome assessment and data analysis. It is important to recognise that none of the studies were able to blind participants to their group allocation and we felt this criterion was not appropriate to our studies because it is very difficult to be blinded to PA intervention. We assessed that the risk of bias of included studies was moderate in three studies (Martinson 2010; Napolitano 2006; van Stralen 2011) or low across all the remaining included studies (Castro 2011; Elley 2003; King 1991; King 2007; Kinmonth 2008; Kolt 2007; Lawton 2008; Marcus 2007).
Potential biases in the review process
One limitation of this review is potential publication bias. Other types of interventions may exist but have not been submitted or accepted for publication, or only those with positive results have been published. We did not see any indication of publication bias from our funnel plots.
Agreements and disagreements with other studies or reviews
Our results appear consistent with previous systematic reviews of technology based intervention and PA interventions focusing on middle aged or older adults. What is novel about our review, compared to these other reviews, is our more robust criteria regarding duration of follow-up (12 months) and comparison of remote intervention to a true control group.
Our pooled effect estimate is consistent with other recent meta-analyses or systematic reviews of PA interventions, particularly our pooled estimate of effects for self-reported PA outcomes at 12 months (SMD 0.20; 95% CI 0.11 to 0.28). Our previous review of interventions to promote PA to adults (Foster 2005a) found small to moderate effects of interventions at six months (SMD 0.28; 95% CI 0.15 to 0.41). Our new results have extended the duration of pooled effects to 12 months, from a high quality group of studies. When studies were stratified by low risk of bias studies (8 studies; 3403 participants) the effects were increased (SMD 0.28; 95% CI 0.16 to 0.40).
Conn 2011 (99,011 participants) reported that the overall mean effect size for comparisons of intervention groups versus control groups was 0.19 (95% CI –0.14 to 0.53) (higher mean for intervention participants than for control participants). This review included many non-randomised studies. Hobbs 2013 reported a similar effect size for self-reported PA duration 12 months after randomisation for interventions targeting older adults (SMD 0.19; 95% CI 0.10 to 0.28). They reported that effective interventions involved individual tailoring with personalized activity goals or provision of information about local opportunities in the environment. Only LaPlante 2011 conducted a systematic literature review of e-health interventions targeting PA and reported that only seven studies used pure control groups, and of those four demonstrated support for e-health but the others showed no significant differences. This review echoed our own and Conn 2011 concerns with the heterogeneity of intervention approaches, and poor research design, outcome measures and power analyses.
Our results reflect the outcomes from studies with optimal study design and 12 month duration. They are consistent with other reviews that included interventions with shorter follow-up periods. We are unaware of similar reviews with such strict inclusion criteria but recognise that this has resulted in exclusion of many shorter term studies of internet based interventions. Davies 2012 conducted a recent meta-analysis of internet-delivered PA behaviour change programs (n = 34 studies) and concluded that effect sizes were small and studies were short term in duration. The authors advocated evaluating intervention fidelity by comparing the participation of the intervention group with the actual web based materials and activities. This focus on compliance was not well reported among our studies. Assessing the dose and response relationship between intervention and outcome is important, particularly where the interaction may be virtual and machine not human based. Short 2011 reviewed the effectiveness of of the tailored print literature to identify key factors relating to efficacy in tailored print PA interventions. Using a narrative synthesis of 12 interventions, Short 2011 reached a similar conclusion to our own that tailored print based interventions with multiple intervention follow-up contacts had moderate positive effects on PA. However, they were unable to tease out the key factors relating to efficacy and to determine if this approach was cost effective (only two included studies reported cost effectiveness data) or sustainable in the long term.
We found very few web based or Smart phone interventions that met our inclusion criteria. We suspect that short term efficacy studies have been performed with such technologies but to date these types of interventions have not been fully evaluated by long term RCTs. Future studies should consider including common commercial web based and sensor systems, that could integrate push and pull technologies, plus incentives.
Implications for practice
There is high quality evidence to suggest that interventions designed to increase PA using remote and web 2.0 technologies can lead to longer term increases in PA, certainly for older adults. Due to the clinical and statistical heterogeneity of the studies, only limited conclusions can be drawn about the effectiveness of individual components of such interventions (that is which strategies were most effective). Nevertheless, interventions which deliver by phone or mail and provide people with professional and tailored guidance about starting an exercise programme and then provide ongoing support are more effective in encouraging the uptake of PA. Initiation of PA must be supported by frequent and focused follow-up. There is no evidence that such interventions will reduce PA or cause other harm. There is also limited evidence of the long term effectiveness of interventions.
Implications for research
There is high quality evidence to support the effectiveness of PA interventions for sedentary adults in the general populations. Effects are maintained at one year but there remain gaps in the quality and breadth of the evidence base for PA promotion using remote and web 2.0 approaches. There is a very clear need for studies using appropriate control groups rather than running comparison studies between different variants of technological interventions. Furthermore, there continues to be a paucity of cost effectiveness data and studies that include participants from varying socioeconomic or ethnic groups. In order to better understand the independent effect of individual programme components, longer studies with at least one year follow-up and greater power are required. In this review we have been able to describe what was done within interventions but were unable to unpick what elements were most effective.
The authors wish to acknowledge Karen Rees, Nadine Flowers and the Cochrane Heart Group for their contributions and support during the planning of this suite of reviews.
Data and analyses
- Top of page
- Summary of findings [Explanations]
- Authors' conclusions
- Data and analyses
- Contributions of authors
- Declarations of interest
- Sources of support
- Differences between protocol and review
Appendix 1. Search strategies 2005
1 exp Exertion/
2 Physical fitness/
3 exp "Physical education and training"/
4 exp Sports/
5 exp Dancing/
6 exp Exercise therapy/
7 (physical$ adj5 (fit$ or train$ or activ$ or endur$)).tw.
8 (exercis$ adj5 (train$ or physical$ or activ$)).tw.
12 (exercise$ adj aerobic$).tw.
13 (("lifestyle" or life-style) adj5 activ$).tw.
14 (("lifestyle" or life-style) adj5 physical$).tw.
16 Health education/
17 Patient education/
18 Primary prevention/
19 Health promotion/
20 Behaviour therapy
21 Cognitive therapy
22 Primary health care
28 15 and 27
RCT filter (Dickersin 1995)
1.((((health-education) or (health-education-research)) or ((patient-education) or (patient-education-and-counseling)) or ((health-promotion) or (health-promotion-international)) or (primary-health-care) or ((workplace) or (workplace-)) or (promot*) or ((promot*) or ((educat*) or ((program*) and ((((exertion) or (fitness) or (fitness-) or ((fitness) or (fitness-)) or (exercise) or ((exercise) or (sport) or (walk*)))
2.((research) or (((((random-controlled) or (random-sample) or (randomisation) or (randomised) or (randomised-controlled) or (randomization) or (randomization-) or (randomizd) or (randomize) or (randomized) or (randomized-block) or (randomized-controlled) or (randomized-controlled-trial) or (randomized-control)) or ((double-blind) or (double-blind-procedure)) or ((single-blind) or (single-blind-procedure))) and (ec=human)) or (clinical) or (clin*) or (trial*) or (((clin* near trial*) in ti) and (ec=human)) or (clin*) or (trial*) or (((clin* near trial*) in ab) and (ec=human)) or (sing*) or (doubl*) or (trebl*) or (tripl*) or (blind*) or (mask*) or (((sing* or doubl* or trebl* or tripl*) near (blind* or mask*)) and (ec=human)) or ((placebos) or (placebo-controlled)) or ((placebo* in ti) and (ec=human)) or ((placebo* in ab) and (ec=human)) or ((random* in ti) and (ec=human)) or ((random in ab) and (ec=human)) or (research)) ec=human)
3.((((studies) or (prospective-study) or (follow-up) or (comparative) or (evaluation)) and (ec=human))
6.#1 or #2 or #3 or #4 or #5
9.#6 not #7
11.(clin* near trial*) in ti
12.(clin* near trial*) in ab
13.(singl* or doubl* or trebl* or tripl*) near (blind* or mask*)
14.(#13 in ti) or (#13 in ab)
16.placebo* in ti
17.placebo* in ab
18.random* in ti
19.random* in ab
21.#10 or #11 or #12 or #13 or #14 or #15 or #16 or #17
22.#18 or #19 or #20
23.#21 or #22
26.#23 not #24
27.#26 or #9 or #8 or #25
30.#28 and #29
33.#31 and #32
36.#35 and #32
37.control* or prosepctiv* or volunteer*
38.(#37 in ti) or (#37 in ab)
39.#38 or #36 or #33 or #30
40.#39 not #24
41.#39 or #27 or #9
42.explode "exertion/"/ all subheadings
44.explode "physical education and training"/ all subheadings
45.explode "sports"/ all subheadings
46.explode "dancing"/ all subheadings
47.explode "exercise therapy"/ all subheadings
48.(physical$ adj5 (fit$ or train$ or activ$ or endur$)).tw.
49.(exercis$ adj5 (train$ or physical$ or activ$)).tw.
53.(exercise$ adj aerobic$).tw.
54.(("lifestyle" or life-style) adj5 activ$).tw.
55.(("lifestyle" or life-style) adj5 physical$).tw.
56.#42 or #43 or #44 or #45 or #46 or #47 or #48 or #49 or (exercise$) or (aerobic$) or ("lifestyle") or (activ$) or ("lifestyle") or (life-style) or (physical$)
63.primary health care
68.#57 or #58 or #59 or #60 or #61 or #62 or #63 or #64 or #65 or #66 or #67
69.#68 and #56
70.#69 and #41
8.#1 or #2 or #3 or #4 or #5 or #6 or #7
15.primary health care
20.#9 or #10 or #11 or #12 or #13 or #14 or #15 or #16 or #17 or #18 or #19
21.#8 and #20
27.#22 or #23 or #24 or #25 or #26
30.#27 not #28
32.(clin* near trial*) in ti
33.clin* near trial*) in ab
34.(singl* or doubl* or trebl* or tripl*) near (blind* or mask*)
35.(#34 in ti) or (#34 in ab)
37.placebo* in ti
38.placebo* in ab
39.random* in ti
40.random* in ab
42.#31 or #32 or #33 or #34 or #35 or #36 or #37 or #38
43.#39 or #40 or #41
44.#42 or #43
47.#44 not #45
48.#47 or #30 or #29 or #46
51.#49 and #50
54.#52 and #53
57.#56 and #53
58.control* or prosepctiv* or volunteer*
59.(#58 in ti) or (#58 in ab)
60.#59 or #57 or #54 or #51
61.#60 not #45
62.#60 or #48 or #30
63.#62 and #21
6.aerobics or circuits or swimming or aqua or jogging or running or cycling or fitness or yoga or walking or sport
12.primary health care
1.explode "Exertion/"/ all subheadings
3.explode "Physical education and training"/ all subheadings
4.explode "Sports"/ all subheadings
5.explode "Dancing"/ all subheadings
6.explode "Exercise therapy"/ all subheadings
7.(physical$ adj5 (fit$ or train$ or activ$ or endur$)).tw.
8.(exercis$ adj5 (train$ or physical$ or activ$)).tw.
12.(exercise$ adj aerobic$).tw.
13.(("lifestyle" or life-style) adj5 activ$).tw.
14.(("lifestyle" or life-style) adj5 physical$).tw.
15.#1 or #2 or #3 or #4 or #5 or #6 or #7 or #8 or (exercise$) or (aerobic$) or ("lifestyle") or (activ$) or ("lifestyle") or (life-style) or (physical$)
22.Primary health care
27.#16 or #17 or #18 or #19 or #20 or #21 or #22 or #23 or #24 or #25 or #26
28.#15 and #27
1.((promot$ or uptake or encourag$ or increas$ or start) near (physical adj activity))
2.(promot$ or uptake or encourag$ or increas$ or start) near exercise
3.(promot$ or uptake or encourag$ or increas$ or start) near (aerobics or circuits or swimming or aqua$)
4.(promot$ or uptake or encourag$ or increas$ or start) near (jogging or running or cycling)
5.(promot$ or uptake or encourag$ or increas$ or start) near ((keep adj fit) or (fitness adj class$) or yoga)
6.(promot$ or uptake or encourag$ or increas$ or start) near walking
7.(promot$ or uptake or encourag$ or increas$ or start) near sport$
Appendix 2. Search strategies 2012
#1MeSH descriptor: [Physical Fitness] this term only
#2MeSH descriptor: [Physical Exertion] this term only
#3MeSH descriptor: [Physical Education and Training] explode all trees
#4MeSH descriptor: [Sports] explode all trees
#5MeSH descriptor: [Dancing] this term only
#6MeSH descriptor: [Exercise Therapy] explode all trees
#7physical* near activ*
#8physical* near train*
#9physical* near fit*
#10exercise* near train*
#11exercise* near activ*
#12exercise* near physical*
#16exercise* near aerobic*
#17((life next style*) near activ*)
#18life-style* near activ*
#19lifestyle* near activ*
#20((life next style*) near physical*)
#21life-style* near physical*
#22lifestyle* near physical*
#23#1 or #2 or #3 or #4 or #5 or #6 or #7 or #8 or #9 or #10 or #11
#24#12 or #13 or #14 or #15 or #16 or #17 or #18 or #19 or #20 or #21 or #22
#25#23 or #24
#26MeSH descriptor: [Health Education] this term only
#27MeSH descriptor: [Patient Education as Topic] this term only
#28MeSH descriptor: [Primary Prevention] this term only
#29MeSH descriptor: [Health Promotion] explode all trees
#30MeSH descriptor: [Behavior Therapy] this term only
#31MeSH descriptor: [Cognitive Therapy] this term only
#32MeSH descriptor: [Primary Health Care] this term only
#33MeSH descriptor: [Workplace] this term only
#37#26 or #27 or #28 or #29 or #30 or #31 or #32 or #33 or #34 or #35 or #36
#38#25 and #37
1. Physical Exertion/
2. Physical Fitness/
3. exp "Physical Education and Training"/
4. exp Sports/
6. exp Exercise Therapy/
7. exp Exercise/
8. (physical$ adj5 (fit$ or train$ or activ$ or endur$ or exertion$)).tw.
9. (exercis$ adj5 (train$ or physical$ or activ$)).tw.
13. ((exercise$ adj3 aerobic$) or aerobics).tw.
14. ((lifestyle or life-style) adj5 activ$).tw.
15. ((lifestyle or life-style) adj5 physical$).tw.
17. Health Education/
18. Patient Education as Topic/
19. Primary Prevention/
20. exp Health Promotion/
21. Behavior Therapy/
22. Cognitive Therapy/
23. Primary Health Care/
29. 16 and 28
30. randomized controlled trial.pt.
31. controlled clinical trial.pt.
34. drug therapy.fs.
38. 30 or 31 or 32 or 33 or 34 or 35 or 36 or 37
39. exp animals/ not humans.sh.
40. 38 not 39
41. 29 and 40
42. (200412$ or 2005$ or 2006$ or 2007$ or 2008$ or 2009$ or 2010$ or 2011$ or 2012$).ed.
43. 41 and 42
1. exp exercise/
3. physical education/
4. exp sport/
6. exp kinesiotherapy/
7. (physical* adj5 (fit* or train* or activ* or endur* or exert*)).tw.
8. (exercis* adj5 (train* or physical* or activ*)).tw.
11. ((exercise* adj aerobic*) or aerobic*).tw.
12. ((lifestyle or life-style) adj5 activ*).tw.
14. ((lifestyle or life-style) adj5 physical*).tw.
16. health education/
17. patient education/
18. primary prevention/
19. health promotion/
20. behavior therapy/
21. cognitive therapy/
22. primary health care/
28. 15 and 27
32. cross over$.tw.
35. (doubl$ adj blind$).tw.
36. (singl$ adj blind$).tw.
40. crossover procedure/
41. double blind procedure/
42. randomized controlled trial/
43. single blind procedure/
44. 29 or 30 or 31 or 32 or 33 or 34 or 35 or 36 or 37 or 38 or 39 or 40 or 41 or 42 or 43
45. (animal/ or nonhuman/) not human/
46. 44 not 45
47. 28 and 46
48. (200412* or 2005* or 2006* or 2007* or 2008* or 2009* or 2010* or 2011* or 2012*).dd.
49. 47 and 48
50. limit 49 to embase
CINAHL Plus with Full Text EBSCO
S34 S33 Limiters - Exclude MEDLINE records
S33 S31 and S32
S32 EM 20041201-20121010
S31 S20 and S30
S30 S21 or S22 or S23 or S24 or S25 or S26 or S27 or S28 or S29
S29 TX allocat*
S28 TX control*
S27 TX assign*
S26 TX placebo*
S25 (MH "Placebos")
S24 TX random*
S23 TX (clinic* N1 trial?)
S22 PT clinical trial
S21 (MH "Clinical Trials+")
S20 S10 and S19
S19 S11 or S12 or S13 or S14 or S15 or S16 or S17 or S18
S18 (TI promot* or educat* or program*) or (AB promot* or educat* or program*)
S17 (MH "Work Environment")
S16 (MH "Primary Health Care")
S15 (MH "Behavior Therapy+")
S14 (MH "Health Promotion")
S13 (MH "Preventive Health Care")
S12 (MH "Patient Education")
S11 (MH "Health Education")
S10 S1 or S2 or S3 or S4 or S5 or S6 or S7 or S8 or S9
S9 (TI sport* or walk* or bicycle* or exercis* or aerobic*) or (AB sport* or walk* or bicycle* or exercis* or aerobic*)
S8 (TI physical N5 (fit* or train* or activ* or endur* or exert*)) or (AB physcial* N5 (fit* or train* or activ* or endur* or exert*))
S7 (TI exercis* N5 (train* or physical* or activ*)) or (AB exercis* N5 (train* or physical* or activ*))
S6 (MH "Exercise+") or (MH "Therapeutic Exercise+")
S5 (TI (lifestyle* or life-style*) N5 (activ* or physical*)) or (AB (lifestyle* or life-style*) N5 (activ* or physical*))
S4 (MH "Sports+") or (MH "Dancing+")
S3 (MH "Physical Education and Training")
S2 (MH "Physical Fitness")
S1 (MH "Exertion")
1. exp exercise/
2. physical fitness/
3. physical activity/
4. exp sports/
5. physical education/
6. (physical$ adj5 (fit$ or train$ or activ$ or endur$ or exertion$)).tw.
7. (exercis$ adj5 (train$ or physical$ or activ$)).tw.
11. ((exercise$ adj3 aerobic$) or aerobics).tw.
12. ((lifestyle or life-style) adj5 activ$).tw.
13. ((lifestyle or life-style) adj5 physical$).tw.
15. health education/
16. client education/
17. health promotion/
19. primary health care/
20. behavior therapy/
21. cognitive therapy/
22. cognitive behavior therapy/
28. 14 and 27
34. cross over$.tw.
40. clinical trials/
41. (doubl$ adj blind$).tw.
42. (singl$ adj blind$).tw.
44. 28 and 43
45. (200412* or 2005* or 2006* or 2007* or 2008* or 2009* or 2010* or 2011* or 2012*).up.
46. 44 and 45
Web of Science
# 20 #19 AND #18
# 19 TS=(random* or blind* or allocat* or assign* or trial* or placebo* or crossover* or cross-over*)
# 18 #17 AND #8
# 17 #16 OR #15 OR #14 OR #13 OR #12 OR #11 OR #10 OR #9
# 16 TI=(promot* or educat* or program*)
# 15 TS=(workplace)
# 14 TS=(primary health care)
# 13 TS=(cognitive therap*)
# 12 TS=((behaviour or behavior) NEAR/2 therap*)
# 11 TS=(health NEAR/2 promot*)
# 10 TS=(primary prevent*)
# 9 TS=((health educat*) or (patient* educat*))
# 8 #7 OR #6 OR #5 OR #4 OR #3 OR #2 OR #1
# 7 TS=((lifestyle* or life-style*) NEAR/5 (activ* or physcial*))
# 6 TS=((exercis* NEAR/2 aerobic*) or aerobic*)
# 5 TS=(sport* or danc* or walk* or bicycle*)
# 4 TS=(physical* educat*)
# 3 TS=(exercis* NEAR/5 (train* or physical* or activ*))
# 2 TS=(physical NEAR/5 (fit* or train* or activ* or endur* or exert*))
# 1 TS=(exercis* therap*)
Contributions of authors
All named authors contributed to the conceptual planning of this suite of reviews to update the previously completed Cochrane review assessing 'Interventions for promoting physical activity' (Foster 2005a). This manuscript was initially drafted by Charlie Foster and Justin Richards. Editorial contributions were received from Margaret Thorogood and Melvyn Hillsdon.
Declarations of interest
Melvyn Hillsdon has received a research council grant to investigate the feasibility of a primary care PA intervention. This was not a study of outcomes and therefore had no bearing on this review. He has been a member of a NICE programme development group on walking and cycling and was paid for travel expenses.
No other authors have any known conflict of interest.
Sources of support
- British Heart Foundation Core Grant (021/P&C/Core/2010/HPRG), UK.
- NIHR Cochrane Incentive Scheme 2012, UK.
Differences between protocol and review
The six month follow-up period was extended to 12 months in response to the recommendations from the previous versions of this review that called for better study quality with longer follow-up periods (Foster 2005a).
The identified authors undertaking this task were modified.
Assessing the risk of bias
The identified authors undertaking this task were modified and the criteria for completing this task were explicitly identified.
Unit of analysis
The method for dealing with multiple intervention arms in a study was changed and these were not compared to a split control group. Instead, the relevant intervention arms were combined for comparison against the existing control group using established approaches (Higgins 2011).
The following refinements were made to the subgroup analysis based on the data that were available in the identified studies.
- The inclusion of a comparison of group versus individual versus mixed (group and individual) was removed from the primary outcome measures section and more appropriately included as a subgroup analysis. This comparison also became a secondary rather than a primary objective.
- The prescription of the intervention was changed to focus on whether the type of PA was specified and if it was human or computer generated.
- The intensity of the intervention delivery was changed to focus on whether the PA was continuously monitored using a pedometer.
The threshold for 'low' risk was specified as meeting at least 50% of the applicable risk of bias criteria
* Indicates the major publication for the study