Interventions Using Wearable Physical Activity Trackers Among Adults With Cardiometabolic Conditions: A Systematic Review and Meta-analysis.

Importance: Wearable physical activity (PA) trackers, such as accelerometers, fitness trackers, and pedometers, are accessible technologies that may encourage increased PA levels in line with current recommendations. However, whether their use is associated with improvements in PA levels in participants who experience 1 or more cardiometabolic conditions, such as diabetes, prediabetes, obesity, and cardiovascular disease, is unknown. Objective: To assess the association of interventions using wearable PA trackers (accelerometers, fitness trackers, and pedometers) with PA levels and other health outcomes in adults with cardiometabolic conditions. Data Sources: For this systematic review and meta-analysis, searches of MEDLINE, Embase, Cochrane Central Register of Controlled Trials, and PsycINFO were performed from January 1, 2000, until December 31, 2020, with no language restriction. A combination of Medical Subject Heading terms and text words of diabetes, obesity, cardiovascular disease, pedometers, accelerometers, and Fitbits were used. Study Selection: Randomized clinical trials or cluster randomized clinical trials that evaluated the use of wearable PA trackers, such as pedometers, accelerometers, or fitness trackers, were included. Trials were excluded if they assessed the trackers only as measuring tools of PA before and after another intervention, they required participants to be hospitalized, assessors were not blinded to the trackers, or they used a tracker to measure the effect of a pharmacological treatment on PA among individuals. Data Extraction and Synthesis: The study followed the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) reporting guideline. A random-effects model was used for the meta-analysis. Main Outcomes and Measures: The primary outcome was mean difference in PA levels. When the scale was different across studies, standardized mean differences were calculated. Heterogeneity was quantified using the I2 statistic and explored using mixed-effects metaregression. Results: A total of 38 randomized clinical trials with 4203 participants were eligible in the systematic review; 29 trials evaluated pedometers, and 9 evaluated accelerometers or fitness trackers. Four studies did not provide amenable outcome data, leaving 34 trials (3793 participants) for the meta-analysis. Intervention vs comparator analysis showed a significant association of wearable tracker use with increased PA levels overall (standardized mean difference, 0.72; 95% CI, 0.46-0.97; I2 = 88%; 95% CI, 84.3%-90.8%; P < .001) in studies with short to medium follow-up for median of 15 (range, 12-52) weeks. Multivariable metaregression showed an association between increased PA levels and interventions that involved face-to-face consultations with facilitators (23 studies; ß = -0.04; 95% CI, -0.11 to -0.01), included men (23 studies; ß = 0.48; 95% CI, 0.01-0.96), and assessed pedometer-based interventions (26 studies; ß = 0.20; 95% CI, 0.02-0.32). Conclusions and Relevance: In this systematic review and meta-analysis, interventions that combined wearable activity trackers with health professional consultations were associated with significant improvements in PA levels among people with cardiometabolic conditions.

Accelerometer- and Pedometer-Based Physical Activity Interventions Among Adults With Cardiometabolic Conditions: A Systematic Review and Meta-analysis.

Importance: Accelerometers and pedometers are accessible technologies that could have a role in encouraging physical activity (PA) in line with current recommendations. However, there is no solid evidence of their association with PA in participants with 1 or more cardiometabolic conditions such as diabetes, prediabetes, obesity, and cardiovascular disease. Objectives: To assess the association of accelerometer- and pedometer-based interventions with increased activity and other improved health outcomes in adults with cardiometabolic conditions and to examine characteristics of the studies that could influence the association of both interventions in improving PA. Data Sources: Records from MEDLINE, Embase, the Cochrane Central Register of Controlled Trials, the Cumulative Index to Nursing and Allied Health, and PsycINFO were searched from inception until August 2018 with no language restriction. Study Selection: Randomized clinical trials or cluster randomized clinical trials evaluating the use of wearable technology devices such as pedometers and accelerometers as motivating and monitoring tools for increasing PA were included. After removing duplicates, the searches retrieved 5762 references. Following abstract and title screening of 1439 references and full-text screening of 107 studies, 36 studies met inclusion criteria. Data Extraction and Synthesis: Mean difference in PA was assessed by random-effects meta-analysis. Where the scale was different across studies, the standardized mean difference was used instead. Heterogeneity was quantified using the I2 statistic and explored using mixed-effects metaregression. This study was registered with PROSPERO and followed the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) reporting guideline. Main Outcomes and Measures: The primary outcome was objectively measured PA in the short to medium term (postintervention to 8 months' follow-up). Results: Thirty-six randomized clinical trials (20 using accelerometers and 16 using pedometers) involving 5208 participants were eligible for review. Meta-analysis involving 32 of these trials (4856 participants) showed medium improvements in PA: accelerometers and pedometers combined vs comparator showed a small significant increase in PA overall (standardized mean difference, 0.39 [95% CI, 0.28-0.51]; I2 = 60% [95% CI, 41%-73%]) in studies of short to medium follow-up over a mean (SD) of 32 (28.6) weeks. Multivariable metaregression showed improved association with PA for complex interventions that involved face-to-face consultation sessions with facilitators (ß = 0.36; 95% CI, 0.17-0.55; P < .001) and pedometer-based interventions (ß = 0.30; 95% CI, 0.08-0.52; P = .002). Conclusions and Relevance: In this study, complex accelerometer- and pedometer-based interventions led to significant small to medium improvements in PA levels of people with cardiometabolic conditions. However, longer-term trials are needed to assess their performance over time. This study found no evidence that simple self-monitored interventions using either pedometers or accelerometers are associated with improvements in PA.

The 'cognitive behavioural model' of chronic fatigue syndrome: Critique of a flawed model.

Chronic fatigue syndrome/myalgic encephalomyelitis is a debilitating illness that greatly impacts the lives of sufferers. A cognitive behavioural model attempts to explain illness onset and continuance with a hypothesis that the illness is perpetuated by patients' irrational beliefs and avoidance behaviours. This theory underpins the promotion of cognitive behavioural therapy, a treatment that aims to change beliefs and behaviours. This article reports on a detailed review of the cognitive behavioural model. Our review finds that the model lacks high-quality evidential support, conflicts with accounts given by most patients and fails to account for accumulating biological evidence of pathological and physiological abnormalities found in patients. There is little scientific credibility in the claim that psycho-behavioural therapies are a primary treatment for this illness.

The Importance of Accurate Diagnosis of ME/CFS in Children and Adolescents: A Commentary.

Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a chronic illness that causes a range of debilitating symptoms. While most research has focused on adults, the illness also presents in children and adolescents. Many physicians find it difficult to diagnose the illness. In this commentary paper, we discuss a range of salient themes that have emerged from our ongoing research into the prevalence of ME/CFS in children and adolescents. We discuss reasons why pediatric prevalence estimates vary widely in the literature, from almost 0% to as high as 3%. We argue that there is considerable misdiagnosis of pediatric cases and over-inflation of estimates of pediatric ME/CFS. Many children and teenagers with general fatigue and other medical complaints may meet loose diagnostic criteria for ME/CFS. We make recommendations for improving epidemiological research and identifying pediatric ME/CFS in clinical practice.

Efficacy and safety of metformin in the management of type 2 diabetes mellitus in older adults: a systematic review for the development of recommendations to reduce potentially inappropriate prescribing.

BACKGROUND: Metformin is usually prescribed as first line therapy for type 2 diabetes mellitus (DM2). However, the benefits and risks of metformin may be different for older people. This systematic review examined the available evidence on the safety and efficacy of metformin in the management of DM2 in older adults. The findings were used to develop recommendations for the electronic decision support tool of the European project PRIMA-eDS. METHODS: The systematic review followed a staged approach, initially searching for systematic reviews and meta-analyses first, and then individual studies when prior searches were inconclusive. The target population was older people (≥65 years old) with DM2. Studies were included if they reported safety or efficacy outcomes with metformin (alone or in combination) for the management of DM2 compared to placebo, usual or no treatment, or other antidiabetics. Using the evidence identified, recommendations were developed using GRADE methodology. RESULTS: Fifteen studies were included (4 intervention and 11 observational studies). In ten studies at least 80% of participants were 65 years or older and 5 studies reported subgroup analyses by age. Comorbidities were reported by 9 studies, cognitive status was reported by 4 studies and functional status by 1 study. In general, metformin showed similar or better safety and efficacy than other specific or non-specific active treatments. However, these findings were mainly based on retrospective observational studies. Four recommendations were developed suggesting to discontinue the use of metformin for the management of DM2 in older adults with risk factors such as age > 80, gastrointestinal complaints during the last year and/or GFR ≤60 ml/min. CONCLUSIONS: On the evidence available, the safety and efficacy profiles of metformin appear to be better, and certainly no worse, than other treatments for the management of DM2 in older adults. However, the quality and quantity of the evidence is low, with scarce data on adverse events such as gastrointestinal complaints or renal failure. Further studies are needed to more reliably assess the benefits and risks of metformin in very old (>80), cognitively and functionally impaired older people.

What are the core predictors of 'hassles' among patients with multimorbidity in primary care? A cross sectional study.

BACKGROUND: A limitation of service delivery in primary care in the United Kingdom is that services are often organised to manage discrete long-term conditions, using guidelines related to single conditions, and managed in clinics organised around single conditions. However, many older patients have more than one condition (so called multimorbidity). Qualitative research suggests that these patients experience 'hassles' in their care, including multiple appointments, poor co-ordination, and conflicting recommendations. However, there is limited quantitative evidence on the 'hassles' that patients with multimorbidity experience, or factors predicting 'hassles' in patients with multimorbidity. METHODS: We conducted a cross sectional study, mailing questionnaires to 1460 patients with multimorbidity identified from the disease registers of four general practices in the UK. Patients were asked to complete a range of self-report measures including measures of multimorbidity, measures of their experience of multimorbidity and service delivery. Data were analysed using regression modelling to assess the factors predicting 'hassles' in patients with multimorbidity. RESULTS: In total 33% (n = 486) of patients responded to the baseline survey. The 'hassles' most often reported by patients related to lack of information about conditions and treatment options, poor communication among health professionals, and poor access to specialist care. There was a significant relationship between numbers of conditions, and reports of 'hassles'. In multivariate analysis, 5 variables predicted more 'hassles': more long-term conditions, symptoms of anxiety and depression, younger age, being in paid employment, and not having a discussion with their GP in the last 12 months. CONCLUSION: Hassles are frequently reported by patients with multimorbidity in primary care. A priority for future research should be on the development of new models of care that better cater for these patients. This research highlights core hassles that need to be addressed, and the patient groups that are most at risk, which may aid in the design of these new models.