Objective To determine the comparative effectiveness and safety of psychological interventions for chronic low back pain. Design Systematic review with network meta-analysis. Data sources Medline, Embase, PsycINFO, Cochrane Central Register of Controlled Trials, Web of Science, SCOPUS, and CINAHL from database inception to 31 January 2021. Eligibility criteria for study selection Randomised controlled trials comparing psychological interventions with any comparison intervention in adults with chronic, non-specific low back pain. Two reviewers independently screened studies, extracted data, and assessed risk of bias and confidence in the evidence. Primary outcomes were physical function and pain intensity. A random effects network meta-analysis using a frequentist approach was performed at post-intervention (from the end of treatment to <2 months post-intervention); and at short term (≥2 to <6 months post-intervention), mid-term (≥6 to <12 months post-intervention), and long term follow-up (≥12 months post-intervention). Physiotherapy care was the reference comparison intervention. The design-by-treatment interaction model was used to assess global inconsistency and the Bucher method was used to assess local inconsistency. Results 97 randomised controlled trials involving 13 136 participants and 17 treatment nodes were included. Inconsistency was detected at short term and mid-term follow-up for physical function, and short term follow-up for pain intensity, and were resolved through sensitivity analyses. For physical function, cognitive behavioural therapy (standardised mean difference 1.01, 95% confidence interval 0.58 to 1.44), and pain education (0.62, 0.08 to 1.17), delivered with physiotherapy care, resulted in clinically important improvements at post-intervention (moderate quality evidence). The most sustainable effects of treatment for improving physical function were reported with pain education delivered with physiotherapy care, at least until mid-term follow-up (0.63, 0.25 to 1.00; low quality evidence). No studies investigated the long term effectiveness of pain education delivered with physiotherapy care. For pain intensity, behavioural therapy (1.08, 0.22 to 1.94), cognitive behavioural therapy (0.92, 0.43 to 1.42), and pain education (0.91, 0.37 to 1.45), delivered with physiotherapy care, resulted in clinically important effects at post-intervention (low to moderate quality evidence). Only behavioural therapy delivered with physiotherapy care maintained clinically important effects on reducing pain intensity until mid-term follow-up (1.01, 0.41 to 1.60; high quality evidence). Conclusions For people with chronic, non-specific low back pain, psychological interventions are most effective when delivered in conjunction with physiotherapy care (mainly structured exercise). Pain education programmes (low to moderate quality evidence) and behavioural therapy (low to high quality evidence) result in the most sustainable effects of treatment; however, uncertainty remains as to their long term effectiveness. Although inconsistency was detected, potential sources were identified and resolved. Systematic review registration PROSPERO CRD42019138074.
IntroductionPsychological factors such as fear avoidance beliefs, depression, anxiety, catastrophic thinking and familial and social stress, have been associated with high disability levels in people with chronic low back pain (LBP). Guidelines endorse the integration of psychological interventions in the management of chronic LBP. However, uncertainty surrounds the comparative effectiveness of different psychological approaches. Network meta-analysis (NMA) allows comparison and ranking of numerous competing interventions for a given outcome of interest. Therefore, we will perform a systematic review with a NMA to determine which type of psychological intervention is most effective for adults with chronic non-specific LBP.Methods and analysisWe will search electronic databases (MEDLINE, Embase, PsycINFO, Cochrane Central Register of Controlled Trials, Web of Science, SCOPUS and CINAHL) from inception until 22 August 2019 for randomised controlled trials comparing psychological interventions to any comparison interventions in adults with chronic non-specific LBP. There will be no restriction on language. The primary outcomes will include physical function and pain intensity, and secondary outcomes will include health-related quality of life, fear avoidance, intervention compliance and safety. Risk of bias will be assessed using the Revised Cochrane risk-of-bias tool for randomised trials (RoB 2) tool and confidence in the evidence will be assessed using the Confidence in NMA (CINeMA) framework. We will conduct a random-effects NMA using a frequentist approach to estimate relative effects for all comparisons between treatments and rank treatments according to the mean rank and surface under the cumulative ranking curve values. All analyses will be performed in Stata.Ethics and disseminationNo ethical approval is required. The research will be published in a peer-reviewed journal.PROSPERO registration numberCRD42019138074.
Background: Previous studies have only investigated how symptom presentation and socio-demographic factors influence care-seeking for low back pain (LBP).However, the influence of health and lifestyle factors remains unclear, and the potential confounding effects of aggregated familial factors (including genetics and the early shared environment) has not been considered extensively. Methods: A cross-sectional analysis was performed on 1605 twins enrolled in the Murcia Twin Registry (Spain). The outcome was seeking medical care for LBP and various self-reported demographic, health and lifestyle factors were considered predictors. All variables except sleep quality and diabetes were collected in 2013, which were cross-referenced from 2009 to 2010. A multivariate logistic regression model was performed on the total sample, followed by a co-twin case-control analysis. Results: The only significant factor found to increase the odds of seeking medical care for LBP without being affected by familial factors was poor sleep quality (total sample OR = 1.58, 95%CI 1.24-2.01; case-control OR = 1.75, 95%CI 1.14-2.69).The factors that were associated with reduced odds of seeking medical care for LBP and not confounded by familial factors were male sex (case-control OR = 0.55, 95%CI 0.33-0.93), alcohol intake (case-control OR = 0.90, 95%CI 0.82-0.99) and a history of diabetes (case-control OR = 0.50, 95%CI 0.25-0.97). No other factors significantly influenced medical care-seeking for LBP. Conclusions: People reporting poor sleep quality are more likely to seek medical care for LBP in the long term, with this relationship being independent from aggregated familial factors. Conversely, males, people reporting higher alcohol intake, and people with a history of diabetes are less likely to seek medical care for LBP. Significance: This is the first study investigating the factors that influence seeking medical care for LBP, while adjusting for the influence of familial factors using a co-twin control design. Poor sleep quality is associated with seeking medical care for LBP in the long term and does not appear to be confounded by familial factors. Early screening for indicators of poor sleep quality and appropriate referral to interventions for improving sleep quality or reducing pain in sleep may improve LBP management.
Income and living standards measures have long been used in market research and marketing in Africa. This study examined a set of lifestyle indicators (both belongings and behaviors) to determine their success in profiling middle-class consumers in sub-Saharan Africa. The African middle class exhibits robust growth and the definition of the lifestyle of these consumers is a major topic for debate between researchers and marketing organizations. Existing absolute monetary definitions do not adequately provide insights into the true nature of middle-class consumer behavior in sub-Saharan Africa. Similarly, current living standards measures are very focused on capturing consumer durables but do not consider other daily lifestyle factors. By analyzing six key lifestyle indicators (housing, income and expenditure, education, employment, mobile and internet penetration, and health care), middle-class lifestyle was assessed in 10 cities across sub-Saharan Africa. The research used a multi-method approach by designing a structured questionnaire that was completed by a probability sample of 6,465 participants from the sample cities. The study found large lifestyle differences between cities and that no single lifestyle indicator could be applied to all middle-class consumers across the cities. The implications of these findings relate directly to understanding broad middle-class consumer behavior. Specifically, international businesses targeting middle-class growth in Africa must consider both the similarities and differences between countries when proposing strategies to successfully engage middle-class consumers in sub-Saharan Africa.
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