OBJECTIVES:Human papillomavirus (HPV), particularly high-risk types such as HPV 16 and 18, is a major cause of cervical cancer and other cancers. Despite the United Kingdom's (UK's) commitment to cervical cancer elimination by 2040, participation in HPV screening is declining, disproportionately affecting underserved groups, including those experiencing poverty, people from minoritized racial, ethnic, gender, or sexual identity groups, and people living with HIV. METHODS:We conducted a mixed-methods study to explore awareness, barriers, and facilitators to HPV self-sampling from clinician and public perspectives. A multi-stakeholder survey (n = 105) and two online focus groups with clinicians (n = 4) and members of the public (n = 5) were undertaken. RESULTS:Survey respondents identified accuracy, cost-free availability, ease of use, accessibility, clear instructions, and adequate follow-up as critical test features. Participants emphasized that disability, cultural context, language, and socioeconomic status strongly influence barriers and facilitators to uptake. Focus groups provided contextual depth, illustrating how privacy, logistical and emotional impacts, and supportive follow-up pathways shaped acceptability and trust. Clinicians highlighted the need for integration into healthcare infrastructure to maintain trust and ensure support. Public participants recommended community-driven engagement, including multilingual instructions and tailored communication to encourage adoption among diverse groups. Concerns were raised about unintended consequences, such as anxiety following asymptomatic HPV diagnoses and challenges in managing clinical pathways after positive results. Suggestions included leveraging community organizations to reduce hesitancy. CONCLUSIONS:Findings highlight policy and implementation considerations for embedding HPV self-sampling within care pathways to improve uptake and reduce inequalities.

ABSTRACT Conference abstracts are commonly included in systematic reviews of evidence. Due to limitations in word count, conference abstracts often lack data or information. This causes issues for the assessment of risk of bias (RoB). We therefore aimed to compare the RoB rating, using the Cochrane RoB tool, for abstracts and full texts. This was accomplished using previously published Cochrane reviews and comparing RoB ratings for included studies originally included as an abstract and later as full text. To accomplish this, we searched the Cochrane Database of Systematic Reviews for reviews with updates across numerous disciplines (depression, anxiety, surgical, Parkinson's disease, Alzheimer's disease, multiple sclerosis, motor neuron disease, cancer, cardiovascular disease, and musculoskeletal disease). We identified 29 reviews, with 52 randomized controlled trials included, which had an abstract and subsequent full text available. If abstracts and full texts were not assessed using the Cochrane RoB tool, we obtained the texts and performed the assessment (n = 32). To assess the likelihood of changing the domain assessment rating (low, unclear, or high) from conference abstract to full text, we performed a Bayesian categorical multinomial model for each domain (i.e., signaling question) of the Cochrane tool. At the abstract assessment stage, the most common decision was unclear. Using unclear as the reference level in the model led to increased odds of being rated high at full text, compared to abstract assessment, for domains 2 (allocation concealment: odds ratio [OR] = 3.09, 95% credible intervals (CrI) 1.01 to 9.84) and 3 (blinding: OR = 5.09, 95% CrI 1.67 to 16.20). Domain 2 also had odds of being rated low (OR: 2.93, 95% CrI: 1.13 to 7.87). This suggests an impact of changing conference abstract to full text assessments on RoB. The numerous unclear ratings observed at the abstract assessment were usually due to a lack of reporting. While the findings of this study should be interpreted within the context of small numbers, the evidence still suggests that, in some instances, such as allocation concealment and blinding, it is likely that the decision could change based on full‐text assessment. This also has implications for the certainty of the evidence, which is impacted by the RoB assessments, with having abstracts only or full texts available potentially changing the overall certainty. Current RoB tools may not be suitable for assessing conference abstracts.

RESURRECTION: Extraordinary Evidence for an Extraordinary Claim by Nick Meader. Eugene, OR: Resource Publications, 2024. 286 pages. Paperback; $29.98. ISBN: 9781666783056. *In Resurrection, statistician and health psychologist Nick Meader notes: "Christians and atheists discussing Jesus' resurrection can sometimes resemble young children on a play date. They use the same toys but play alongside each other--rather than with each other" (p. 11). The brilliance of his book is precisely that it encourages Christians and atheists to come face-to-face. In doing so, Meader plays, and plays well, the role of the rational parent who gets these children to interact directly with each other by providing them with a universal language for conversation: the language of probability. *The primary thesis of the book is that if you apply probability-based statistical modeling (common tools in my own field of psychology) to atheists' claims that the resurrection of Jesus is not probable, those models show that atheists are wrong. In fact, these probability models reveal that the traditional Christian explanation of the widespread belief that Jesus miraculously rose from the dead is more probable than the other explanations that have been offered over the years as alternatives. *To make this case, the book opens with one of the cleverest applications of probabilistic reasoning to apologetics I have ever seen: Meader uses statistical modeling to evaluate a famous example given by atheist philosopher David Hume. To illustrate the kind of evidence he believed we ought to see if something unusual was true, Hume argued that if an eight-day period of darkness had truly occurred in 1600, this extraordinary fact would be matched by equally powerful evidence demonstrating its validity; expected evidence that Hume himself subsequently articulated. Meader, however, beats Hume at his own game by showing that probability modeling suggests Hume's own hypothetical evidence would not be enough to make the hypothetically true event probable! *After that opening salvo, the book turns its attention to atheists' Hume-like arguments that Christians should have extraordinary evidence for such an extraordinary claim as the resurrection of Christ. Because probability modeling is based on the prior likelihood of an explanation being true, much of the book focuses on establishing the prior probabilities associated with things that contribute to our understanding of Jesus's resurrection, ranging from naturalistic worldviews to psychological mechanisms involved in interpretations of the event. At the close of the book, Meader then quantifies all of these probabilities into a series of statistical models that consistently show that the Christian explanation is the most likely. *The primary strength of the book lies in its much-welcome application of the probabilistic method to apologetics. Even if one disagrees with the conclusions--and Meader acknowledges the limitations, quite admirably calling the model a "work in progress"--the application of probabilistic models to such an important religious event is (at a minimum) a meaningful conversation starter. It forces both sides to truly evaluate the probability estimates that, in reality, are already a part of their argument calculus. *The primary weakness of the book is an offshoot of this strength: Meader (who is an extremely successful and highly cited scientist) is of course aware of that the output of any probability model is only as good as the prior probability estimates that go into it; this explains why the book spends the majority of its energy defending the specific probabilities that go into the model. I imagine, however, that many of these probability estimates will be the source of future debate. For the sake of brevity, I will here limit my own comments to specific examples from my own areas of expertise within psychology. *In almost every psychological case (ranging from cognitive dissonance to mass psychosis), I agreed with Meader's prior probability estimates. However, two possible difficulties stood out to me. First, in chapter 8, Meader argues that Christian theology has a higher probability of being true because it is simpler than naturalism. I have spent my entire career studying psychological complexity,1 and I find this argument lacking. Something is not more likely to be true because it is simpler. As I argued in my Christian apologetics book Complex Simplicity (2017), the world is, in fact, quite complex. Mere psychological or structural simplicity does not increase the probability of a match with that reality. Further, Christian doctrine is (as Meader acknowledges) often quite complex, and theism is almost by definition more complex than naturalism in that it posits everything naturalism posits plus the supernatural. *Second, Meader discusses many psychological arguments that might offer alternative accounts of the spread of Christian belief, but in my view he fails to clearly articulate the most probable one: an explanation based not in mass psychosis or cognitive dissonance, but in the much more mundane psychological properties of selective communication. Research suggests, for example, that information is passed on because it is communicable or interesting independent of its truth value.2 As anyone who has played the game "telephone" can attest, it does not take very long in a communication chain for reality to be reshaped. Of course, communication often does work, and most of what we know that is true about our world is because of accurate communication from other people. But even though I disagree with atheists' ultimate conclusions, I have nonetheless thought communication distortion was their best argument--and it seems omitted from Meader's probability models. *To help offset these difficulties inherent in estimating prior probabilities, Meader provides multiple estimates in which he changes the parameters in a more atheist-friendly way. On balance, these alternative estimates--despite being biased toward atheism--still show a pro-Christian conclusion. (Indeed, I wanted more of this kind of analysis; the most useful part of the technique is to illuminate exactly what it would take for each side to "win" the probability debate). However, I could not entirely shake the feeling that the overall result seemed at times like a large kitchen sink that is in danger of running the very risk Meader is trying to overcome: If the final probability estimate is dependent on the author being right on this many things, perhaps the model itself cannot be trusted? *No work is perfect, especially one that attempts such a grand undertaking as Meader does. But in the final analysis, this book is well worth reading. Indeed, Resurrection accomplishes an amazing double: It provides an excellent summary of the burgeoning area of probabilistic apologetics for the curious outsider and simultaneously offers a remarkable novel contribution for the knowledgeable insider. I have never read anything quite like it, and I hope it inspires a generation of Christian apologists to use probability theory to honestly explore--and defend--our faith. *Notes *1For example, Lucian Gideon Conway III and Alivia Zubrod, "Are US Presidents Becoming Less Rhetorically Complex? Evaluating the Integrative Complexity of Joe Biden and Donald Trump in Historical Context," Journal of Language and Social Psychology 41, no. 5 (2022): 613-25, https://doi.org/10.1177/0261927X221081126. *2For a summary, see Lucian Gideon Conway III and Mark Schaller, "How Communication Shapes Culture," in Frontiers of Social Psychology: Social Communication, ed. K. Fiedler (Psychology Press, 2007), 107-27. *Reviewed by Lucian Gideon Conway III, PhD, Department of Psychology, Grove City College, PA.

Rapid evidence synthesis plays a valuable role in healthcare. However, rapid reviews commonly do not undertake risk of bias assessment, even using truncated implementation approaches, despite its importance. In this work, we aimed to evaluate a rapid QUADAS-2 risk of bias method and compare the results with a standard QUADAS-2 assessment performed on 47 diagnostic test accuracy (DTA) studies for mild cognitive impairment (MCI). We also explored use of a rapid GRADE approach. The overall risk of bias agreed for the majority (29, 61.7%) of studies using the two methods, with major disagreements (high versus low) for two studies (4.3%), and minor disagreements (unclear vs high/low) for 16 studies (34.0%). For the 18 studies which had disagreements, using the QUADAS-2 rather than rapid assessment did not affect the GRADE certainty of evidence for five, five decreased by one grade, and two decreased by two grades. None increased due to the nature of the ‘one strike’ method adopted in the rapid approach. The collaborative nature of the rapid method may be beneficial in terms of robustness due to the inherent subjectiveness involved with any risk of bias assessment. In conclusion, this research demonstrated the suitability of using a rapid method to assess the risk of bias of DTAs. This method could be valuable for incorporating into rapid reviews to provide an evidence synthesis in a short timeframe without overly sacrificing robustness.

Over 500,000 people in England have a recorded diagnosis of dementia, of whom at least 40% have Alzheimer’s disease (AD) in isolation or in combination with other pathologies. Timely diagnosis ensures that people get the help and support they need. Mild cognitive impairment (MCI) is a term for subtle changes in memory, language and behaviour that do not impact on a person’s ability to function. People with MCI may develop AD or other dementias. This horizon scan, alongside an ultra-rapid evidence synthesis review, aimed to identify digital tests and devices which support the identification of MCI associated with early-stage AD. We searched clinical trial registries, news websites, patent databases, funding and regulatory agencies, and company websites, as well as three recently published systematic reviews. Eligible technologies were any digital tools to detect MCI or cognitive decline in adults without a current diagnosis of AD. 79 technologies were identified, classified as digitised versions of standard cognitive tests, newly developed digital cognitive tests, and digital devices that incorporate detection of MCI/cognitive decline. This work outlines digital technologies, at various development stages, that might complement emerging treatments in the care pathway by facilitating identification of AD at the earlier stages of clinical presentation.

Background:Heart failure is a clinical syndrome caused by any structural or functional cardiac disorder that impairs the heart's ability to function efficiently and pump blood around the body. Function can also be monitored using cardiac implantable electronic devices, some of which may also deliver a therapeutic benefit (e.g. pacemakers), while others only monitor metrics over time. Implantable devices can include algorithms that aim to predict the occurrence of a heart failure event. They are intended to be used alongside clinical judgement and make treatment decisions. Objectives:To determine the clinical and cost-effectiveness of the four remote monitoring algorithms (CorVue, HeartInsight, HeartLogic and TriageHF) for detecting heart failure in people with cardiac implantable electronic devices. Methods:We performed systematic reviews of clinical, cost-effectiveness, quality of life and cost outcomes. We searched MEDLINE and other sources of published and unpublished literature, including manufacturers' websites and Clinical Trials Registries between June and August 2023. For the clinical effectiveness review, study selection was completed by two independent reviewers at both title and abstract, and full-text screening stages. Data extraction and study quality appraisal were completed by a single reviewer and checked for accuracy by a second. Due to heterogeneity, no statistical analyses were performed, and a narrative synthesis was reported. A de novo two-state Markov model (with alive and dead states) was used to estimate the cost-effectiveness of algorithm-based remote monitoring of heart failure risk data in people with cardiac implantable electronic devices over a lifetime. Results:There was reasonable evidence to suggest HeartLogic and TriageHF can accurately predict heart failure events. CorVue's prognostic accuracy is less clear due to high heterogeneity in findings between studies. There was only a single published HeartInsight study, which suggested similar accuracy to the other algorithms. Cost-effectiveness estimates could only be produced for HeartLogic and TriageHF, which were less costly and more effective compared to the respective cardiac implantable electronic device without the algorithms. For all technologies, only a small reduction in hospitalisation rates were required for them to be cost-effective. Limitations:The evidence for each algorithm was limited in terms of comparative evidence. Additionally, available evidence was often of low quality. The comparative outcome evidence for economic model was very limited. Conclusions:There was a lack of comparative evidence across all technologies included in the scope. Evidence for HeartLogic and TriageHF suggests that they may have acceptable prognostic accuracy for predicting heart failure events. However, further evidence is required to confirm these results. Specifically, further comparative evidence (e.g. randomised controlled trials) is required to show the benefit of the algorithms compared to standard practice in intermediate and clinical outcomes. For example, some studies suggested high false positive rates and low sensitivity. Only a single published study was identified for HeartInsight, therefore there are insufficient data to draw conclusions on prognostic accuracy and the benefits on clinical and intermediate outcomes. It is likely remote monitoring systems for CorVue, HeartInsight, HeartLogic and TriageHF would be cost-effective were they to result in fewer hospitalisations in heart failure patients; however, in general, this may apply to any device lowering the hospital visit. In addition, any potential benefits of reduced hospitalisation need to be carefully balanced with chances of overtreatment resulting from alerts. Future work:Prospective studies on effectiveness of remote monitoring as well as consideration of patient voice and preferences would facilitate a more complete evaluation of technology benefits. Study registration:This study is registered as PROSPERO CRD42023447089. Funding:This award was funded by the National Institute for Health and Care Research (NIHR) Evidence Synthesis programme (NIHR award ref: NIHR135894) and is published in full in Health Technology Assessment; Vol. 29, No. 50. See the NIHR Funding and Awards website for further award information.

OBJECTIVES:The National Institute for Health and Care Excellence (NICE) in England introduced early value assessments (EVAs) as an evidence-based method of accelerating access to promising health technologies that could address unmet needs and contribute to the National Health Service's Long Term Plan. However, there are currently no published works considering differences and commonalities in methods used between Assessment Reports for EVAs. METHODS:This rapid scoping review included all completed EVAs published on the NICE website up to 23 July 2024. One reviewer screened potentially relevant records for eligibility, checked by a second reviewer. Pairs of independent reviewers extracted information on the methods used in included EVAs using a prepiloted form; these were checked for accuracy. Data were described in graphical or tabular format with an accompanying narrative summary. RESULTS:In total, seventeen EVA Reports of sixteen EVAs were included in this scoping review. Five Reports did not specify how many reviewers undertook screening, whereas five did not report data extraction methods. Five EVAs planned to conduct meta-analyses, nine planned narrative syntheses, and seven planned narrative summaries. Eleven conceptual decision models were presented, with available evidence used to construct cost-utility analyses (N = 5); cost-effectiveness analyses (CEAs; N = 4); a mix of CEAs and cost-consequence analyses (CCA; N = 2); one CCA; and one cost-comparison. CONCLUSION:Future EVA Reports should enhance the transparency of the methods used. Furthermore, EVAs could provide opportunities for the adoption of innovative methodological approaches and more flexible communication between EVA authors and key stakeholders, including patients and clinicians, companies, and NICE.

The growing threat of antimicrobial resistance has led to efforts to improve the responsible use of antimicrobials (antimicrobial stewardship - AMS). AMS education and training is essential for providing healthcare professionals with the knowledge and skills required to change prescribing behaviours, but the design and delivery of education and training varies, and it is unclear what content, and methods make for more effective education and training. The aim of this systematic review was to apply behavioural science frameworks to specify the content of AMS education and training interventions in hospital settings to determine ‘what works’ and to evaluate their effectiveness and cost-effectiveness. We searched MEDLINE, EMBASE, and CENTRAL and hand searched studies included in a previous Cochrane review for studies published from January 2015 to February 2025. We applied behavioural science frameworks (Action, Actor, Context, Target and Time framework, Behaviour Change Wheel and Behaviour Change Technique Taxonomy) to code intervention descriptions and supplementary materials from published papers into target behaviours, modes of delivery and behaviour change strategies used. Meta-regressions were used to explore the (cost-)effectiveness of different target behaviours, modalities, and behaviour change strategies on reducing antibiotic consumption. Of the 1845 studies identified, 64 were included in the review and 26 included in the meta-regression. Education/training was more effective in reducing antibiotic consumption when delivered face-to-face (β= − 2.65, 95

In a recent article published in this journal, Stephen Smith acknowledges that bereavement hallucination is an unlikely explanation for Jesus' post-resurrection appearances, and suggests supplementing it with theories concerning collective delusion, distorted memory, and cognitive dissonance. Our response contributes to the discussion by bringing our expertise in psychology and New Testament studies together to advance interdisciplinary study on this important topic. We show that Smith's discussion confounds real-life cases and laboratory experiments on memory, and mass psychogenic illness with illusions. Moreover, Smith fails to consider a number of important differences between the case concerning Jesus' post-resurrection appearances and cases of cognitive dissonance and other psychological theories, which indicate that these theories are not plausible explanations concerning Jesus' post-resurrection appearances.

OBJECTIVES:The objective of this rapid review is to understand the reporting, role and quality of patient and public involvement and engagement (PPIE) in real world data and evidence (RWDE) research across the medicines development cycle. METHODS:We comprehensively searched, with no date restrictions, Medline and Embase databases for peer-reviewed literature and conference abstracts (Embase only) reporting PPIE in RWD studies. We also assessed PPIE in a sample of 100 NICE technology appraisals (TAs) comprising both single technology appraisals (STAs) and highly specialized technologies (HSTs). We used standard methods for screening and data extraction. In addition, we used the Patient Focused Medicines Development (PFMD)'s Patient Engagement Quality Guidance (PEQG) as a framework to assess the quality of PPIE. We planned to conduct narrative synthesis of included studies, however there were insufficient studies and data reported. RESULTS:We included three RWD studies that reported PPIE from the peer-reviewed literature and two NICE HSTs. One of the HSTs included data from one of the peer-reviewed journal articles. Reporting of PPIE in included studies was limited. No studies reported a PPIE framework and it was unclear how integrated and meaningful PPIE was. Four out of seven of PFMD's quality criteria for PPIE were poorly reported by included studies. This suggests reporting and/or conduct of PPIE requires improvement in RWD studies. CONCLUSIONS:Our review found that PPIE was rarely reported in RWDE research and uncovers a need for consistent reporting. For most publications there was insufficient information to judge the extent to which patients and carers, were considered meaningful partners. However, our review provided preliminary evidence that PPIE can influence protocol development, recruitment, and retention methods in RWD studies. More inclusive approaches to PPIE would help interpretation of RWE regarding relevance and importance to patients and carers.

Background:Neonates with suspected sepsis are commonly treated with gentamicin, an aminoglycoside. These antibiotics are associated with high risk of ototoxicity, including profound bilateral deafness, in people with the m.1555A>G mitochondrial genetic variant. Objective:This early value assessment summarised and critically assessed the clinical effectiveness and cost-effectiveness of the Genedrive MT-RNR1 ID Kit for identifying the gene m.1555A>G variant in neonates and mothers of neonates needing antibiotics or anticipated to need antibiotics. Following feedback from the scoping workshop and specialist assessment subgroup meeting, we also considered the Genedrive MT-RNR1 ID Kit for identifying the m.1555A>G variant in mothers prior to giving birth. Data sources:For clinical effectiveness, we searched three major databases in October 2022: MEDLINE, EMBASE and CINAHL (Cumulative Index to Nursing and Allied Health Literature). For cost-effectiveness, in addition to the three mentioned databases we searched Cochrane and RePEc-IDEAS. Study selection:Study selection and risk-of-bias assessment were conducted by two independent reviewers (Ryan PW Kenny and Akvile Stoniute for clinical effectiveness and Hosein Shabaninejad and Tomos Robinson for cost-effectiveness). Any differences were resolved through discussion, or by a third reviewer (Nick Meader). Study appraisal:Risk of bias was assessed using Quality Assessment of Diagnostic Accuracy Studies-2. One study (n = 751 neonates recruited) was included in the clinical effectiveness review and no studies were included in the cost-effectiveness review. All except one outcome (test failure rate: low risk of bias) were rated as being at moderate risk of bias. The study reported accuracy of the test (sensitivity 100%, 95% confidence interval 29.2% to 100%; specificity 99.2%, 95% confidence interval 98% to 99.7%), number of neonates successfully tested (n = 424/526 admissions), test failure rate (17.1%, although this was reduced to 5.7%), impact on antibiotic use (all those with a m.1555A>G genotype avoided aminoglycosides), time taken to obtain a sample (6 minutes), time to genotyping (26 minutes), time to antibiotic treatment (55.18 minutes) and the number of neonates with m.1555A>G (n = 3). Limitations:The economic component of this work identified key evidence gaps for which further data are required before a robust economic evaluation can be conducted. These include the sensitivity of the Genedrive MT-RNR1 ID Kit for identifying the gene m.1555A>G variant in neonates, the magnitude of risk for aminoglycoside-induced hearing loss in neonates with m.1555A>G, and the prevalence of the m.1555A>G variant. Other potentially important gaps include how data regarding maternal inheritance may potentially be used in the clinical pathway. Conclusions:This early value assessment suggests that the Genedrive MT-RNR1 ID Kit has the potential to identify the m.1555A>G variant and to be cost-effective. The Genedrive MT-RNR1 ID Kit dominates the current standard of care over the lifetime, as it is less costly and more effective. For a 50-year time horizon, the Genedrive MT-RNR1 ID Kit was also the dominant strategy. For a 10-year time horizon, the incremental cost-effectiveness ratio was estimated to be £103 per quality-adjusted life-year gained. Nevertheless, as anticipated, there is insufficient evidence to conduct a full diagnostic assessment of the clinical effectiveness and cost-effectiveness of the Genedrive MT-RNR1 ID Kit in neonates directly or in their mothers. This report includes a list of research priorities to reduce the uncertainty around this early value assessment and to provide the additional data needed to inform a full diagnostic assessment, including cost-effectiveness modelling. Study registration:This study is registered as PROSPERO (CRD42022364770). Funding:This award was funded by the National Institute for Health and Care Research (NIHR) Evidence Synthesis programme (NIHR award ref: NIHR135636) and is published in full in Health Technology Assessment; Vol. 28, No. 75. See the NIHR Funding and Awards website for further award information.

BACKGROUND:Relapse of depression is common and contributes to the overall associated morbidity and burden. We lack evidence-based tools to estimate an individual's risk of relapse after treatment in primary care, which may help us more effectively target relapse prevention. OBJECTIVE:The objective was to develop and validate a prognostic model to predict risk of relapse of depression in primary care. METHODS:Multilevel logistic regression models were developed, using individual participant data from seven primary care-based studies (n=1244), to predict relapse of depression. The model was internally validated using bootstrapping, and generalisability was explored using internal-external cross-validation. FINDINGS:Residual depressive symptoms (OR: 1.13 (95% CI: 1.07 to 1.20), p<0.001) and baseline depression severity (OR: 1.07 (1.04 to 1.11), p<0.001) were associated with relapse. The validated model had low discrimination (C-statistic 0.60 (0.55-0.65)) and miscalibration concerns (calibration slope 0.81 (0.31-1.31)). On secondary analysis, being in a relationship was associated with reduced risk of relapse (OR: 0.43 (0.28-0.67), p<0.001); this remained statistically significant after correction for multiple significance testing. CONCLUSIONS:We could not predict risk of depression relapse with sufficient accuracy in primary care data, using routinely recorded measures. Relationship status warrants further research to explore its role as a prognostic factor for relapse. CLINICAL IMPLICATIONS:Until we can accurately stratify patients according to risk of relapse, a universal approach to relapse prevention may be most beneficial, either during acute-phase treatment or post remission. Where possible, this could be guided by the presence or absence of known prognostic factors (eg, residual depressive symptoms) and targeted towards these. TRIAL REGISTRATION NUMBER:NCT04666662.

Clear communication is vital for adopting public health interventions that promote protective behaviours against respiratory infections. This systematic review and network meta-analysis assessed the effectiveness of these interventions using behavioural science frameworks, including MINDSPACE contextual influencers and behaviour change techniques (BCTs), to identify key components and mechanisms of action (MoAs). The interventions primarily focused on social distancing, mask-wearing, handwashing, diverse-behavioural intentions, and actual behaviours. The network meta-analysis revealed that prosocial messages, especially those involving loved ones, significantly reduced the risk of respiratory infections (d=0.09; 95% CrI=0.06-0.14; CINeMA: Low). Interventions typically included three contextual influencers (salience, affect, ego) and five BCTs (Information about health consequences; Salience of consequences; Information about social and environmental consequences; Demonstration of the behaviour; Avoidance/reducing exposure to cues for the behaviour). Behaviour intention was the most common MoA. Although further research is needed, this review provides insights into designing effective public health messages for respiratory infection control.

OBJECTIVES:It is vital that horizon scanning organizations can capture and disseminate intelligence on new and repurposed medicines in clinical development. To our knowledge, there are no standardized classification systems to capture this intelligence. This study aims to create a novel classification system to allow new and repurposed medicines horizon scanning intelligence to be disseminated to healthcare organizations. METHODS:A multidisciplinary working group undertook literature searching and an iterative, three-stage piloting process to build consensus on a classification system. Supplementary data collection was carried out to facilitate the implementation and validation of the system on the National Institute of Health and Care Research (NIHR) Innovation Observatory (IO)'s horizon scanning database, the Medicines Innovation Database (MInD). RESULTS:Our piloting process highlighted important issues such as the patency and regulatory approval status of individual medicines and how combination therapies interact with these characteristics. We created a classification system with six values (New Technology, Repurposed Technology (Off-patent/Generic), Repurposed Technology (On-patent/Branded), Repurposed Technology (Never commercialised), New + Repurposed Technology (Combinations-only), Repurposed Technology (Combinations-only)) that account for these characteristics to provide novel horizon scanning insights. We validated our system through application to over 20,000 technology records on the MInD. CONCLUSIONS:Our system provides the opportunity to deliver concise yet informative intelligence to healthcare organizations and those studying the clinical development landscape of medicines. Inbuilt flexibility and the use of publicly available data sources ensure that it can be utilized by all, regardless of location or resource availability.

BACKGROUND:When sufficient maternal milk is not available, donor human milk or formula are the alternative forms of enteral nutrition for very preterm or very low-birthweight (VLBW) infants. Donor human milk may retain the non-nutritive benefits of maternal milk and has been proposed as a strategy to reduce the risk of necrotising enterocolitis (NEC) and associated mortality and morbidity in very preterm or VLBW infants. OBJECTIVES:To assess the effectiveness of donor human milk compared with formula for preventing NEC and associated morbidity and mortality in very preterm or VLBW infants when sufficient maternal milk is not available. SEARCH METHODS:We searched the Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE, Embase, the Maternity and Infant Care (MIC) database, and the Cumulative Index to Nursing and Allied Health Literature (CINAHL), from the earliest records to February 2024. We searched clinical trials registries and examined the reference lists of included studies. SELECTION CRITERIA:Randomised or quasi-randomised controlled trials comparing feeding with donor human milk versus formula in very preterm (< 32 weeks' gestation) or VLBW (< 1500 g) infants. DATA COLLECTION AND ANALYSIS:Two review authors evaluated the risk of bias in the trials, extracted data, and synthesised effect estimates using risk ratio, risk difference, and mean difference, with associated 95% confidence intervals. The primary outcomes were NEC, late-onset invasive infection, and all-cause mortality before hospital discharge. The secondary outcomes were growth parameters and neurodevelopment. We used the GRADE approach to assess the certainty of the evidence for our primary outcomes. MAIN RESULTS:Twelve trials with a total of 2296 infants fulfilled the inclusion criteria. Most trials were small (average sample size was 191 infants). All trials were performed in neonatal units in Europe or North America. Five trials were conducted more than 40 years ago; the remaining seven trials were conducted in the year 2000 or later. Some trials had methodological weaknesses, including concerns regarding masking of investigators and selective reporting. Meta-analysis showed that donor human milk reduces the risk of NEC (risk ratio (RR) 0.53, 95% confidence interval (CI) 0.37 to 0.76; I² = 4%; risk difference (RD) -0.03, 95% CI -0.05 to -0.01; 11 trials, 2261 infants; high certainty evidence). Donor human milk probably has little or no effect on late-onset invasive infection (RR 1.12, 0.95 to 1.31; I² = 27%; RD 0.03, 95% CI -0.01 to -0.07; 7 trials, 1611 infants; moderate certainty evidence) or all-cause mortality (RR 1.00, 95% CI 0.76 to 1.31; I² = 0%; RD -0.00, 95% CI -0.02 to 0.02; 9 trials, 2116 infants; moderate certainty evidence). AUTHORS' CONCLUSIONS:The evidence shows that donor human milk reduces the risk of NEC by about half in very preterm or VLBW infants. There is probably little or no effect on late-onset invasive infection or all-cause mortality before hospital discharge.

Abstract In a recent article published in this journal, Stephen Smith acknowledges that bereavement hallucination is an unlikely explanation for Jesus’ post-resurrection appearances, and suggests supplementing it with theories concerning collective delusion, distorted memory, and cognitive dissonance. Our response contributes to the discussion by bringing our expertise in psychology and New Testament studies together to advance interdisciplinary study on this important topic. We show that Smith’s discussion confounds real-life cases and laboratory experiments on memory, and mass psychogenic illness with illusions. Moreover, Smith fails to consider a number of important differences between the case concerning Jesus’ post-resurrection appearances and cases of cognitive dissonance and other psychological theories, which indicate that these theories are not plausible explanations concerning Jesus’ post-resurrection appearances.

Background: Parkinson's disease is a brain condition causing a progressive loss of co ordination and movement problems. Around 145,500 people have Parkinson's disease in the United Kingdom. Levodopa is the most prescribed treatment for managing motor symptoms in the early stages. Patients should be monitored by a specialist every 6-12 months for disease progression and treatment of adverse effects. Wearable devices may provide a novel approach to management by directly monitoring patients for bradykinesia, dyskinesia, tremor and other symptoms. They are intended to be used alongside clinical judgement. Objectives: To determine the clinical and cost-effectiveness of five devices for monitoring Parkinson's disease: Personal KinetiGraph, Kinesia 360, KinesiaU, PDMonitor and STAT-ON. Methods: We performed systematic reviews of all evidence on the five devices, outcomes included: diagnostic accuracy, impact on decision-making, clinical outcomes, patient and clinician opinions and economic outcomes. We searched MEDLINE and 12 other databases/trial registries to February 2022. Risk of bias was assessed. Narrative synthesis was used to summarise all identified evidence, as the evidence was insufficient for meta-analysis. One included trial provided individual-level data, which was re-analysed. A de novo decision-analytic model was developed to estimate the cost-effectiveness of Personal KinetiGraph and Kinesia 360 compared to standard of care in the UK NHS over a 5-year time horizon. The base-case analysis considered two alternative monitoring strategies: one-time use and routine use of the device. Results: Fifty-seven studies of Personal KinetiGraph, 15 of STAT-ON, 3 of Kinesia 360, 1 of KinesiaU and 1 of PDMonitor were included. There was some evidence to suggest that Personal KinetiGraph can accurately measure bradykinesia and dyskinesia, leading to treatment modification in some patients, and a possible improvement in clinical outcomes when measured using the Unified Parkinson's Disease Rating Scale. The evidence for STAT-ON suggested it may be of value for diagnosing symptoms, but there is currently no evidence on its clinical impact. The evidence for Kinesia 360, KinesiaU and PDMonitor is insufficient to draw any conclusions on their value in clinical practice. The base-case results for Personal KinetiGraph compared to standard of care for one-time and routine use resulted in incremental cost-effectiveness ratios of 67,856 pound and 57,877 pound per quality-adjusted lifeyear gained, respectively, with a beneficial impact of the Personal KinetiGraph on Unified Parkinson's Disease Rating Scale domains III and IV. The incremental cost-effectiveness ratio results for Kinesia 360 compared to standard of care for one-time and routine use were 38,828 pound and 67,203 pound per quality adjusted life-year gained, respectively. Limitations: The evidence was limited in extent and often low quality. For all devices, except Personal KinetiGraph, there was little to no evidence on the clinical impact of the technology. Conclusions: Personal KinetiGraph could reasonably be used in practice to monitor patient symptoms and modify treatment where required. There is too little evidence on STAT-ON, Kinesia 360, KinesiaU or PDMonitor to be confident that they are clinically useful. The cost-effectiveness of remote monitoring appears to be largely unfavourable with incremental cost-effectiveness ratios in excess of 30,000 pound per quality-adjusted life-year across a range of alternative assumptions. The main driver of cost-effectiveness was the durability of improvements in patient symptoms.

The amount of grey literature and 'softer' intelligence from social media or websites is vast. Given the long lead-times of producing high-quality peer-reviewed health information, this is causing a demand for new ways to provide prompt input for secondary research. To our knowledge, this is the first review of automated data extraction methods or tools for health-related grey literature and soft data, with a focus on (semi)automating horizon scans, health technology assessments (HTA), evidence maps, or other literature reviews. We searched six databases to cover both health- and computer-science literature. After deduplication, 10% of the search results were screened by two reviewers, the remainder was single-screened up to an estimated 95% sensitivity; screening was stopped early after screening an additional 1000 results with no new includes. All full texts were retrieved, screened, and extracted by a single reviewer and 10% were checked in duplicate. We included 84 papers covering automation for health-related social media, internet fora, news, patents, government agencies and charities, or trial registers. From each paper, we extracted data about important functionalities for users of the tool or method; information about the level of support and reliability; and about practical challenges and research gaps. Poor availability of code, data, and usable tools leads to low transparency regarding performance and duplication of work. Financial implications, scalability, integration into downstream workflows, and meaningful evaluations should be carefully planned before starting to develop a tool, given the vast amounts of data and opportunities those tools offer to expedite research.

AIMS:There is substantial evidence showing an association between parental substance use and child substance use and/or mental health problems. Most research focuses upon maternal substance use, with the influence of paternal substance use often being overlooked. We aimed to investigate the differential effects of maternal and paternal substance use upon children aged 0-18 years. METHODS:We used systematic review methods to identify observational studies examining the association between either maternal or paternal substance use and child substance use and/or mental health problems. The odds ratio (OR) effect measure was used, for ease of computation. We used a random-effects model with the inverse variance method to meta-analyse the findings from eligible studies. RESULTS:We included 17 unique studies with a total of 47 374 child participants. Maternal and paternal substance use were both associated with increased odds of child any drug use [OR = 2.09; 95% confidence interval (CI) = 1.53, 2.86; n = 12 349 participants; three studies and OR = 2.86; 95% CI = 1.25, 6.54; n = 5692 participants; three studies, respectively], child alcohol problem use (OR = 2.16; 95% CI = 1.73, 2.71; n = 7339 participants; four studies and OR = 1.70; 95% CI = 1.36, 2.12; n = 14 219 participants; six studies), child externalizing problems (OR = 1.81; 95% CI = 1.01, 3.22; n = 1748 participants; three studies and OR = 1.60; 95% CI = 1.18, 2.17; n = 2508 participants; six studies) and child internalizing problems (OR = 1.60; 95% CI = 1.25, 2.06; n = 1748 participants; three studies and OR = 1.42; 95% CI = 1.12, 1.81; n = 2248 participants; five studies). Child any alcohol use was associated with maternal substance use only (OR = 2.26; 95% CI = 1.08, 4.70; n = 28 691 participants; five studies). CONCLUSIONS:Both maternal and paternal substance use are associated with child substance use and mental health problems.