Interpretive analysis of 85 systematic reviews suggests that narrative syntheses and meta-analyses are incommensurate in argumentation

Friendships and peer relationships and self-harm ideation and behaviour among young people: a systematic review and narrative synthesis

Friendships and peer relationships have an important role in the experience of self-harm ideation and behaviour in young people, yet they typically remain overlooked. This systematic review and narrative synthesis explores the extant literature on this topic to identify important relationships between these constructs. We did a keyword search of peer-reviewed empirical articles relating to friendships and peer relationships and self-harm ideation and behaviour in young people (aged 11-25 years). We identified 90 articles with evidence primarily from adolescents aged 11-18 years, including mixed genders and a majority of White individuals. Findings highlight substantive relationships between the key constructs, showing that: characteristics of friends and peers, including their self-harm ideation and behaviour, relate to and predict ego self-harm ideation and behaviour; friends and peers are important sources of support; and evidence on causal mechanisms is scarce but highlights potential peer selection and influence processes. Studies of the friends and peers of young people with self-harm ideation and behaviour highlight that: friends' attitudes to self-harm and suicide influence their responses to peers with self-harm ideation and behaviour; and friends who are bereaved and friend supporters experience negative outcomes such as symptoms of depression, anxiety, PTSD, and grief, alongside difficult emotions. Despite substantial heterogeneity across samples, study designs, and definition or measurement of the primary constructs, this work presents an initial step in organising a complex literature on a crucially important topic, which can help to inform future research and evidence-based interventions.

Effectiveness of physical activity interventions on undergraduate students' mental health: systematic review and meta-analysis

This systematic review and meta-analysis assessed the effectiveness of physical activity interventions on undergraduate students' mental health. Seven databases were searched and a total of 59 studies were included. Studies with a comparable control group were meta-analysed, and remaining studies were narratively synthesized. The included studies scored very low GRADE and had a high risk of bias. Meta-analyses indicated physical activity interventions are effective in reducing symptoms of anxiety (n = 20, standardized mean difference (SMD) = -0.88, 95% CI [-1.23, -0.52]), depression (n = 14, SMD = -0.73, 95% CI [-1.00, -0.47]) and stress (n = 10, SMD = -0.61, 95% CI [-0.94, -0.28]); however, there was considerable heterogeneity (anxiety, I2 = 90.29%; depression I2 = 49.66%; stress I2 = 86.97%). The narrative synthesis had mixed findings. Only five studies reported being informed by a behavioural change theory and only 30 reported intervention fidelity. Our review provides evidence supporting the potential of physical activity interventions in enhancing the mental health of undergraduate students. More robust intervention design and implementation are required to better understand the effectiveness of PA interventions on mental health outcomes.

Artificial Intelligence Applications in Space Medicine

INTRODUCTION:During future interplanetary space missions, a number of health conditions may arise, owing to the hostile environment of space and the myriad of stressors experienced by the crew. When managing these conditions, crews will be required to make accurate, timely clinical decisions at a high level of autonomy, as telecommunication delays and increasing distances restrict real-time support from the ground. On Earth, artificial intelligence (AI) has proven successful in healthcare, augmenting expert clinical decision-making or enhancing medical knowledge where it is lacking. Similarly, deploying AI tools in the context of a space mission could improve crew self-reliance and healthcare delivery.METHODS: We conducted a narrative review to discuss existing AI applications that could improve the prevention, recognition, evaluation, and management of the most mission-critical conditions, including psychological and mental health, acute radiation sickness, surgical emergencies, spaceflight-associated neuro-ocular syndrome, infections, and cardiovascular deconditioning.RESULTS: Some examples of the applications we identified include AI chatbots designed to prevent and mitigate psychological and mental health conditions, automated medical imaging analysis, and closed-loop systems for hemodynamic optimization. We also discuss at length gaps in current technologies, as well as the key challenges and limitations of developing and deploying AI for space medicine to inform future research and innovation. Indeed, shifts in patient cohorts, space-induced physiological changes, limited size and breadth of space biomedical datasets, and changes in disease characteristics may render the models invalid when transferred from ground settings into space.Cheung HC, De Louche C, Komorowski M. Artificial intelligence applications in space medicine. Aerosp Med Hum Perform. 2023; 94(8):610-622.

Sepsis biomarkers and diagnostic tools with a focus on machine learning

Over the last years, there have been advances in the use of data-driven techniques to improve the definition, early recognition, subtypes characterisation, prognostication and treatment personalisation of sepsis. Some of those involve the discovery or evaluation of biomarkers or digital signatures of sepsis or sepsis sub-phenotypes. It is hoped that their identification may improve timeliness and accuracy of diagnosis, suggest physiological pathways and therapeutic targets, inform targeted recruitment into clinical trials, and optimise clinical management. Given the complexities of the sepsis response, panels of biomarkers or models combining biomarkers and clinical data are necessary, as well as specific data analysis methods, which broadly fall under the scope of machine learning. This narrative review gives a brief overview of the main machine learning techniques (mainly in the realms of supervised and unsupervised methods) and published applications that have been used to create sepsis diagnostic tools and identify biomarkers.

Economic evaluations of mammography to screen for breast cancer in low- and middle-income countries: A systematic review

Background

Low- and middle-income countries (LMICs) have limited resources compared to high-income countries (HICs). Therefore, it is critical that LMICs implement cost-effective strategies to reduce the burden of breast cancer. This study aimed to answer the question of whether mammography is a cost-effective breast cancer screening method in LMICs.

Methods

A systematic article search was conducted through Medline, Embase, Web of Science, and Econlit. Studies were included only if they conducted a full economic evaluation and focused on mammography screening in LMICs. Two reviewers screened through the title and abstract of each article and continued with full-text selection. Data were extracted and synthesized narratively. Quality assessment for each included study was conducted using the Consensus Health Economic Criteria (CHEC) extended checklist.

Results

This review identified 21 studies economically evaluating mammography as a breast cancer screening method in LMICs. Eighteen of these studies concluded that mammography screening was a cost-effective strategy. Most studies (71%) were conducted in upper-middle-income countries (Upper MICs). The quality of the studies varied from low to good. Important factors determining cost-effectiveness are the target age group (eg, 50-59 years), the screening interval (eg, biennial or triennial), as well as any combination with other breast cancer control strategies (eg, combination with treatment strategy for breast cancer patients).

Conclusions

Mammography screening appeared to be a cost-effective strategy in LMICs, particularly in Upper MICs. More studies conducted in lower-middle-income and low-income countries are needed to better understand the cost-effectiveness of mammography screening in these regions.

An overview of methodological approaches in systematic reviews

AIM

The aim of this overview is to identify and collate evidence from existing published systematic review (SR) articles evaluating various methodological approaches used at each stage of an SR.

METHODS

The search was conducted in five electronic databases from inception to November 2020 and updated in February 2022: MEDLINE, Embase, Web of Science Core Collection, Cochrane Database of Systematic Reviews, and APA PsycINFO. Title and abstract screening were performed in two stages by one reviewer, supported by a second reviewer. Full-text screening, data extraction, and quality appraisal were performed by two reviewers independently. The quality of the included SRs was assessed using the AMSTAR 2 checklist.

RESULTS

The search retrieved 41,556 unique citations, of which 9 SRs were deemed eligible for inclusion in final synthesis. Included SRs evaluated 24 unique methodological approaches used for defining the review scope and eligibility, literature search, screening, data extraction, and quality appraisal in the SR process. Limited evidence supports the following (a) searching multiple resources (electronic databases, handsearching, and reference lists) to identify relevant literature; (b) excluding non-English, gray, and unpublished literature, and (c) use of text-mining approaches during title and abstract screening.

CONCLUSION

The overview identified limited SR-level evidence on various methodological approaches currently employed during five of the seven fundamental steps in the SR process, as well as some methodological modifications currently used in expedited SRs. Overall, findings of this overview highlight the dearth of published SRs focused on SR methodologies and this warrants future work in this area.

Next-Generation Meta-analysis for Next-Generation Questions: Introducing the Prevention Science Special Issue on Modern Meta-analytic Methods

This commentary accompanies the special issue of Prevention Science on modern meta-analytic methods. The papers that comprise this special issue are considered in terms of the next-generation meta-analytic questions they support: questions about multivariate relationships, drawing on real-life data structures, with improved usability, and answered openly. The contributions to this special issue illustrate a range of methods to address these questions, including meta-analytic structural equation modelling; robust variance estimation and network meta-analysis methods; transportability and causal inference; Bayesian methods; and open science. This special issue collectively represents a step forward in the field's ability to address questions of use to improving human welfare through preventing ill health, supporting uptake of these next-generation methods by applied researchers in prevention science. Future methodological developments in meta-analysis should be synergistic with the questions prevention scientists seek to answer, both creating new possibilities and meeting the challenges of improving human health and wellbeing.

Modern, exogenous exposures associated with altered mammary gland development: A systematic review

BACKGROUND

Many women report low milk supply as the reason for premature breastfeeding cessation. Altered mammary gland development may impact a woman's lactation ability.

OBJECTIVE

This review identifies modern exogenous exposures which alter mammary gland development during embryonic life, puberty and pregnancy.

METHODS

A systematic review was undertaken whereby Medline, CINAHL and Embase articles published from January 1, 2005 to November 20, 2020 were searched using the keywords puberty or embry* or fetal or foetal or foetus or fetus or pregnan* or gestation* AND "mammary gland development" or "breast development" or "mammary development" or "mammary gland function" or "mammary function" or "insufficient glandular tissue" or "mammary hypoplasia" or "breast hypoplasia" or "mammary gland hypoplasia" or "tubular breast*" or "tuberous breast*" or "glandular tissue" or "breast composition" or "mammary composition" or "mammary gland composition". After initial screening of 1207 records, 60 full texts were assessed for eligibility; 6 were excluded due to lack of information about exposure or outcome, leaving 54 studies.

RESULTS

The review included results from 52 animal (rats and mice, monkeys, rabbits, sheep, goats pigs and cows) and 2 human studies. Various endocrine disrupting chemicals and an obesogenic diet were found to be associated with altered mammary gland morphology during key development stages.

CONCLUSIONS

To improve lactation outcomes, future studies need to focus on lactation as the endpoint and be conducted in a standardised manner to allow for a more significant contribution to the literature that allows for better comparison across studies.

The use of 'PICO for synthesis' and methods for synthesis without meta-analysis: protocol for a survey of current practice in systematic reviews of health interventions

Introduction: Systematic reviews involve synthesis of research to inform decision making by clinicians, consumers, policy makers and researchers. While guidance for synthesis often focuses on meta-analysis, synthesis begins with specifying the ’PICO for each synthesis’ (i.e. the criteria for deciding which populations, interventions, comparators and outcomes are eligible for each analysis). Synthesis may also involve the use of statistical methods other than meta-analysis (e.g. vote counting based on the direction of effect, presenting the range of effects, combining P values) augmented by visual display, tables and text-based summaries. This study examines these two aspects of synthesis.

Objectives: To identify and describe current practice in systematic reviews of health interventions in relation to: (i) approaches to grouping and definition of PICO characteristics for synthesis; and (ii) methods of summary and synthesis when meta-analysis is not used.

Methods: We will randomly sample 100 systematic reviews of the quantitative effects of public health and health systems interventions published in 2018 and indexed in the Health Evidence and Health Systems Evidence databases. Two authors will independently screen citations for eligibility. Two authors will confirm eligibility based on full text, then extract data for 20% of reviews on the specification and use of PICO for synthesis, and the presentation and synthesis methods used (e.g. statistical synthesis methods, tabulation, visual displays, structured summary). The remaining reviews will be confirmed as eligible and data extracted by a single author. We will use descriptive statistics to summarise the specification of methods and their use in practice. We will compare how clearly the PICO for synthesis is specified in reviews that primarily use meta-analysis and those that do not.

Conclusion: This study will provide an understanding of current practice in two important aspects of the synthesis process, enabling future research to test the feasibility and impact of different approaches.

The use of 'PICO for synthesis' and methods for synthesis without meta-analysis: protocol for a survey of current practice in systematic reviews of health interventions

Introduction: Systematic reviews involve synthesis of research to inform decision making by clinicians, consumers, policy makers and researchers. While guidance for synthesis often focuses on meta-analysis, synthesis begins with specifying the 'PICO for each synthesis' (i.e. the criteria for deciding which populations, interventions, comparators and outcomes are eligible for each analysis). Synthesis may also involve the use of statistical methods other than meta-analysis (e.g. vote counting based on the direction of effect, presenting the range of effects, combining P values) augmented by visual display, tables and text-based summaries. This study examines these two aspects of synthesis. Objectives: To identify and describe current practice in systematic reviews of health interventions in relation to: (i) approaches to grouping and definition of PICO characteristics for synthesis; and (ii) methods of summary and synthesis when meta-analysis is not used. Methods: We will randomly sample 100 systematic reviews of the quantitative effects of public health and health systems interventions published in 2018 and indexed in the Health Evidence and Health Systems Evidence databases. Two authors will independently screen citations for eligibility. Two authors will confirm eligibility based on full text, then extract data for 20% of reviews on the specification and use of PICO for synthesis, and the presentation and synthesis methods used (e.g. statistical synthesis methods, tabulation, visual displays, structured summary). The remaining reviews will be confirmed as eligible and data extracted by a single author. We will use descriptive statistics to summarise the specification of methods and their use in practice. We will compare how clearly the PICO for synthesis is specified in reviews that primarily use meta-analysis and those that do not. Conclusion: This study will provide an understanding of current practice in two important aspects of the synthesis process, enabling future research to test the feasibility and impact of different approaches.

Low-level laser therapy for carpal tunnel syndrome: systematic review and network meta-analysis

BACKGROUND

Splinting is recommended by various organisations as a non-surgical first-line treatment for carpal tunnel syndrome (CTS), despite the limited evidence supporting its effectiveness. Previous studies on the effectiveness of low-level laser therapy (LLLT) have reported mixed results, and this systematic review aimed to resolve this controversy.

OBJECTIVE

To perform a network meta-analysis (NMA) for evaluating the effectiveness of LLLT compared with other conservative treatments for CTS.

METHODS

Eighteen electronic databases were searched for potential randomised controlled trials (RCTs). RCTs evaluating LLLT or other non-surgical treatments as an add-on to splinting were included. Included RCTs measured at least one of the following three outcomes with validated instruments: pain, symptom severity and functional status.

RESULTS

Six RCTs (418 patients) were included. NMA suggested that LLLT plus splinting has the highest probability (75%) of pain reduction, compared with sham laser plus splinting (61%), ultrasound plus splinting (57%) and splinting alone (8%). However, while LLLT plus splinting is significantly more effective than sham laser plus splinting for pain reduction, the magnitude is not clinically significant (Visual Analogue Scale mean difference -0.53cm, 95% confidence interval -1.01 to -0.05cm; P=0.03, I²=25%). The effect of LLLT plus splinting on symptom severity and functional status was not superior to splinting alone.

CONCLUSION

The use of LLLT in addition to splinting for the management of CTS is not recommended, as LLLT offers limited additional benefits over splining alone in terms of pain reduction, reduction of symptom severity or improved functional status. PROSPERO for systematic reviews and meta-analyses registration number CRD42017082650.

Clinical applications of artificial intelligence in sepsis: A narrative review

Many studies have been published on a variety of clinical applications of artificial intelligence (AI) for sepsis, while there is no overview of the literature. The aim of this review is to give an overview of the literature and thereby identify knowledge gaps and prioritize areas with high priority for further research. A literature search was conducted in PubMed from inception to February 2019. Search terms related to AI were combined with terms regarding sepsis. Articles were included when they reported an area under the receiver operator characteristics curve (AUROC) as outcome measure. Fifteen articles on diagnosis of sepsis with AI models were included. The best performing model reached an AUROC of 0.97. There were also seven articles on prognosis, predicting mortality over time with an AUROC of up to 0.895. Finally, there were three articles on assistance of treatment of sepsis, where the use of AI was associated with the lowest mortality rates. Of the articles, twenty-two were judged to be at high risk of bias or had major concerns regarding applicability. This was mostly because predictor variables in these models, such as blood pressure, were also part of the definition of sepsis, which led to overestimation of the performance. We conclude that AI models have great potential for improving early identification of patients who may benefit from administration of antibiotics. Current AI prediction models to diagnose sepsis are at major risks of bias when the diagnosis criteria are part of the predictor variables in the model. Furthermore, generalizability of these models is poor due to overfitting and a lack of standardized protocols for the construction and validation of the models. Until these problems have been resolved, a large gap remains between the creation of an AI algorithm and its implementation in clinical practice.

Lack of transparency in reporting narrative synthesis of quantitative data: a methodological assessment of systematic reviews

OBJECTIVE

To assess the adequacy of reporting and conduct of narrative synthesis of quantitative data (NS) in reviews evaluating the effectiveness of public health interventions.

STUDY DESIGN AND SETTING

A retrospective comparison of a 20% (n = 474/2,372) random sample of public health systematic reviews from the McMaster Health Evidence database (January 2010-October 2015) to establish the proportion of reviews using NS. From those reviews using NS, 30% (n = 75/251) were randomly selected and data were extracted for detailed assessment of: reporting NS methods, management and investigation of heterogeneity, transparency of data presentation, and assessment of robustness of the synthesis.

RESULTS

Most reviews used NS (56%, n = 251/446); meta-analysis was the primary method of synthesis for 44%. In the detailed assessment of NS, 95% (n = 71/75) did not describe NS methods; 43% (n = 32) did not provide transparent links between the synthesis data and the synthesis reported in the text; of 14 reviews that identified heterogeneity in direction of effect, only one investigated the heterogeneity; and 36% (n = 27) did not reflect on limitations of the synthesis.

CONCLUSION

NS methods are rarely reported in systematic reviews of public health interventions and many NS reviews lack transparency in how the data are presented and the conclusions are reached. This threatens the validity of much of the evidence synthesis used to support public health. Improved guidance on reporting and conduct of NS will contribute to improved utility of NS systematic reviews.

Just how plain are plain tobacco packs: re-analysis of a systematic review using multilevel meta-analysis suggests lessons about the comparative benefits of synthesis methods

BACKGROUND

Comparisons between narrative synthesis and meta-analysis as synthesis methods in systematic reviews are uncommon within the same systematic review. We re-analysed a systematic review on the effects of plain packaging of tobacco on attractiveness. We sought to compare different synthesis approaches within the same systematic review and shed light on the comparative benefits of each approach.

METHODS

In our re-analysis, we included results relating to attractiveness in included reports. We extracted findings from studies and converted all estimates of differences in attractiveness to Cohen's d. We used multilevel meta-analysis to account for clustering of effect sizes within studies.

RESULTS

Of the 19 studies reporting results on attractiveness, seven studies that included between-subjects analyses could be included in the meta-analysis. Plain packs were less attractive than branded packs (d = - 0.59, 95% CI [- 0.71, - 0.47]), with negligible but uncertain between-studies heterogeneity (I² = 0%, 95% CI [0.00, 70.81]) and high within-study heterogeneity (I² = 92.6%, 95% CI [91.04, 93.90]).

CONCLUSIONS

The meta-analysis found, similar to the narrative synthesis, that respondents typically rated plain packaging as less attractive than alternative (e.g. branded) tobacco packs. However, there were several trade-offs between analysis methods in the types and bodies of evidence each one contained and in the difference between partial precision and breadth of conclusions. Analysis methods were different in respect of the role of judgement and contextual variation and in terms of estimation and unexpected effect modification. In addition, we noted that analysis methods were different in how they accounted for heterogeneity and consistency.

What are the patterns of compliance with Early Warning Track and Trigger Tools: A narrative review

BACKGROUND

Early Warning Scores were introduced into acute hospitals in 2000. 99% of acute hospitals employ a EWS to monitor deteriorating patients with 97.9% of these linked to a referral protocol. Despite this high level of adoption, there has been little improvement in the recognition and response to deteriorating patients over the last decade.

OBJECTIVE

To explore the patterns of compliance with Early Warning Track and Trigger Tools.

DESIGN

A narrative review.

DATA SOURCES

Electronic databases (Medline, CIHAHL, EmBase, the Cochrane library, the Centre for Reviews and Dissemination (CRD) and PROSPERO) were searched from 1 January 2000 to 5 July 2018. Titles, abstracts and full text papers were screened (two independent reviewers) against inclusion criteria and seven papers were included in the review. Data were extracted by one reviewer and checked by a second reviewer using a bespoke data collection sheet.

REVIEW METHODS

All papers were quantitative in design but demonstrated clinical and methodological heterogeneity therefore a meta-analysis was not possible. A qualitative approach was undertaken to synthesise findings using a framework analysis and narrative synthesis. Themes were identified, named, defined and reported according to outcome measure.

RESULTS

7/27 papers representing over 3000 patients and 963,000 data points were included in the analysis. Reported studies were conducted in the United Kingdom (n = 4), Denmark (n = 2) and Amsterdam (n = 1). Three key themes were identified, early warning score calculation accuracy, monitoring frequency and clinical response. This review identifies poor compliance with the Early Warning Score (EWS) protocol in all three themes. There is significant scoring inaccuracy with omitted EWS, missing elements of the EWS and incorrectly calculated EWS. Adherence to monitoring frequency is poor with a higher EWS being associated with reduced compliance with the escalation protocol. There is inadequate compliance with the escalation element of the EWS protocol with concerning extended delays to clinical review. There is evidence of worsening clinical response with increasing EWS. Although significant improvement is demonstrated in clinical response with the use of electronic EWS protocols, non-compliance still occurs at all EWS stages.

CONCLUSION

Compliance with EWS is poor but the cause is unidentified. Outcomes can only improve if staff complete the EWS fully, calculate the score accurately, monitor according to protocol and escalate according to clinical response. Social, environmental and professional behaviours that affect effective use of track and trigger tools should be explored to improve our understanding of suboptimal management of the deteriorating patient.

Interpretive analysis of 85 systematic reviews suggests that narrative syntheses and meta-analyses are incommensurate in argumentation

Using Toulmin's argumentation theory, we analysed the texts of systematic reviews in the area of workplace health promotion to explore differences in the modes of reasoning embedded in reports of narrative synthesis as compared with reports of meta‐analysis. We used framework synthesis, grounded theory and cross‐case analysis methods to analyse 85 systematic reviews addressing intervention effectiveness in workplace health promotion. Two core categories, or ‘modes of reasoning’, emerged to frame the contrast between narrative synthesis and meta‐analysis: practical–configurational reasoning in narrative synthesis (‘what is going on here? What picture emerges?’) and inferential–predictive reasoning in meta‐analysis (‘does it work, and how well? Will it work again?’). Modes of reasoning examined quality and consistency of the included evidence differently. Meta‐analyses clearly distinguished between warrant and claim, whereas narrative syntheses often presented joint warrant–claims. Narrative syntheses and meta‐analyses represent different modes of reasoning. Systematic reviewers are likely to be addressing research questions in different ways with each method. It is important to consider narrative synthesis in its own right as a method and to develop specific quality criteria and understandings of how it is carried out, not merely as a complement to, or second‐best option for, meta‐analysis. © 2016 The Authors. Research Synthesis Methods published by John Wiley & Sons Ltd.