Survivor, family and professional experiences of psychosocial interventions for sexual abuse and violence: a qualitative evidence synthesis.

It is well-established that experiencing sexual abuse and violence can have a range of detrimental impacts; a wide variety of interventions exist to support survivors in the aftermath. Understanding the experiences and perspectives of survivors receiving such interventions, along with those of their family members, and the professionals who deliver them is important for informing decision making as to what to offer survivors, for developing new interventions, and enhancing their acceptability. This review sought to: 1. identify, appraise and synthesise qualitative studies exploring the experiences of child and adult survivors of sexual abuse and violence, and their caregivers, regarding psychosocial interventions aimed at supporting survivors and preventing negative health outcomes in terms of benefits, risks/harms and barriers; 2. identify, appraise and synthesise qualitative studies exploring the experiences of professionals who deliver psychosocial interventions for sexual abuse and violence in terms of perceived benefits, risks/harms and barriers for survivors and their families/caregivers; 3. develop a conceptual understanding of how different factors influence uptake, dropout or completion, and outcomes from psychosocial interventions for sexual abuse and violence; 4. develop a conceptual understanding of how features and types of interventions responded to the needs of different user/survivor groups (e.g. age groups; types of abuse exposure; migrant populations) and contexts (healthcare/therapeutic settings; low- and middle-income countries (LMICs)); 5. explore how the findings of this review can enhance our understanding of the findings from the linked and related reviews assessing the effectiveness of interventions aimed at supporting survivors and preventing negative health outcomes. In August 2021 we searched MEDLINE, Embase, PsycINFO and nine other databases. We also searched for unpublished reports and qualitative reports of quantitative studies in a linked systematic review, together with reference checking, citation searches and contacting authors and other researchers to identify relevant studies. We included qualitative and mixed-methods studies (with an identifiable qualitative component) that were linked to a psychosocial intervention aimed at supporting survivors of sexual abuse and violence. Eligible studies focused on at least one of three participant groups: survivors of any age, gender, sexuality, ethnicity or [dis]ability who had received a psychosocial intervention; their carers, family members or partners; and professionals delivering such interventions. We placed no restrictions in respect of settings, locations, intervention delivery formats or durations. Six review authors independently assessed the titles, abstracts and full texts identified. We extracted data using a form designed for this synthesis, then used this information and an appraisal of data richness and quality in order to stratify the studies using a maximum variation approach. We assessed the methodological limitations using the Critical Skills Appraisal Programme (CASP) tool. We coded directly onto the sampled papers using NVivo and synthesised data using a thematic synthesis methodology and used the GRADE-CERQual (Confidence in the Evidence from Reviews of Qualitative research) approach to assess our confidence in each finding. We used a narrative synthesis and matrix model to integrate our qualitative evidence synthesis (QES) findings with those of intervention review findings. We identified 97 eligible studies and sampled 37 of them for our analysis. Most sampled studies were from high-income countries, with four from middle-income and two from low-income countries. In 27 sampled studies, the participants were survivors, in three they were intervention facilitators. Two included all three of our stakeholder groups, and five included two of our groups. The studies explored a wide range of psychosocial interventions, with only one type of intervention explored in more than one study. The review indicates that features associated with the context in which interventions were delivered had an impact on how individuals accessed and experienced interventions. This included organisational features, such as staff turnover, that could influence survivors' engagement with interventions; the setting or location in which interventions were delivered; and the characteristics associated with who delivered the interventions. Studies that assess the effectiveness of interventions typically assess their impact on mental health; however, as well as finding benefits to mental health, our QES found that study participants felt interventions also had positive impacts on their physical health, mood, understanding of trauma, interpersonal relationships and enabled them to re-engage with a wide range of areas in their lives. Participants explained that features of interventions and their contexts that best enabled them to benefit from interventions were also often things that could be a barrier to benefiting from interventions. For example, the relationship with the therapist, when open and warm was a benefit, but if such a relationship could not be achieved, it was a barrier. Survivors' levels of readiness and preparedness to both start and end interventions could have positive (if they were ready) or negative (if they were not) impacts. Study participants identified the potential risks and harms associated with completing interventions but felt that it was important to face and process trauma. Some elements of interventions were specific to the intervention type (e.g. faith-based interventions), or related to an experience of an intervention that held particular relevance to subgroups of survivors (e.g. minority groups); these issues could impact how individuals experienced delivering or receiving interventions. We had high or moderate confidence in all but one of our review findings. Further research in low- and middle-income settings, with male survivors of sexual abuse and violence and those from minority groups could strengthen the evidence for low and moderate confidence findings. We found that few interventions had published quantitative and qualitative evaluations. Since this QES has highlighted important aspects that could enable interventions to be more suitable for survivors, using a range of methodologies would provide valuable information that could enhance intervention uptake, completion and effectiveness. This study has shown that although survivors often found interventions difficult, they also appreciated that they needed to work through trauma, which they said resulted in a wide range of benefits. Therefore, listening to survivors and providing appropriate interventions, at the right time for them, can make a significant difference to their health and well-being.

Brown SJ ，Carter GJ ，Halliwell G ，Brown K ，Caswell R ，Howarth E ，Feder G ，O'Doherty L ... -  《Cochrane Database of Systematic Reviews》

Folic acid supplementation and malaria susceptibility and severity among people taking antifolate antimalarial drugs in endemic areas.

Description of the condition Malaria, an infectious disease transmitted by the bite of female mosquitoes from several Anopheles species, occurs in 87 countries with ongoing transmission (WHO 2020). The World Health Organization (WHO) estimated that, in 2019, approximately 229 million cases of malaria occurred worldwide, with 94% occurring in the WHO's African region (WHO 2020). Of these malaria cases, an estimated 409,000 deaths occurred globally, with 67% occurring in children under five years of age (WHO 2020). Malaria also negatively impacts the health of women during pregnancy, childbirth, and the postnatal period (WHO 2020). Sulfadoxine/pyrimethamine (SP), an antifolate antimalarial, has been widely used across sub-Saharan Africa as the first-line treatment for uncomplicated malaria since it was first introduced in Malawi in 1993 (Filler 2006). Due to increasing resistance to SP, in 2000 the WHO recommended that one of several artemisinin-based combination therapies (ACTs) be used instead of SP for the treatment of uncomplicated malaria caused by Plasmodium falciparum (Global Partnership to Roll Back Malaria 2001). However, despite these recommendations, SP continues to be advised for intermittent preventive treatment in pregnancy (IPTp) and intermittent preventive treatment in infants (IPTi), whether the person has malaria or not (WHO 2013). Description of the intervention Folate (vitamin B9) includes both naturally occurring folates and folic acid, the fully oxidized monoglutamic form of the vitamin, used in dietary supplements and fortified food. Folate deficiency (e.g. red blood cell (RBC) folate concentrations of less than 305 nanomoles per litre (nmol/L); serum or plasma concentrations of less than 7 nmol/L) is common in many parts of the world and often presents as megaloblastic anaemia, resulting from inadequate intake, increased requirements, reduced absorption, or abnormal metabolism of folate (Bailey 2015; WHO 2015a). Pregnant women have greater folate requirements; inadequate folate intake (evidenced by RBC folate concentrations of less than 400 nanograms per millilitre (ng/mL), or 906 nmol/L) prior to and during the first month of pregnancy increases the risk of neural tube defects, preterm delivery, low birthweight, and fetal growth restriction (Bourassa 2019). The WHO recommends that all women who are trying to conceive consume 400 micrograms (µg) of folic acid daily from the time they begin trying to conceive through to 12 weeks of gestation (WHO 2017). In 2015, the WHO added the dosage of 0.4 mg of folic acid to the essential drug list (WHO 2015c). Alongside daily oral iron (30 mg to 60 mg elemental iron), folic acid supplementation is recommended for pregnant women to prevent neural tube defects, maternal anaemia, puerperal sepsis, low birthweight, and preterm birth in settings where anaemia in pregnant women is a severe public health problem (i.e. where at least 40% of pregnant women have a blood haemoglobin (Hb) concentration of less than 110 g/L). How the intervention might work Potential interactions between folate status and malaria infection The malaria parasite requires folate for survival and growth; this has led to the hypothesis that folate status may influence malaria risk and severity. In rhesus monkeys, folate deficiency has been found to be protective against Plasmodium cynomolgi malaria infection, compared to folate-replete animals (Metz 2007). Alternatively, malaria may induce or exacerbate folate deficiency due to increased folate utilization from haemolysis and fever. Further, folate status measured via RBC folate is not an appropriate biomarker of folate status in malaria-infected individuals since RBC folate values in these individuals are indicative of both the person's stores and the parasite's folate synthesis. A study in Nigeria found that children with malaria infection had significantly higher RBC folate concentrations compared to children without malaria infection, but plasma folate levels were similar (Bradley-Moore 1985). Why it is important to do this review The malaria parasite needs folate for survival and growth in humans. For individuals, adequate folate levels are critical for health and well-being, and for the prevention of anaemia and neural tube defects. Many countries rely on folic acid supplementation to ensure adequate folate status in at-risk populations. Different formulations for folic acid supplements are available in many international settings, with dosages ranging from 400 µg to 5 mg. Evaluating folic acid dosage levels used in supplementation efforts may increase public health understanding of its potential impacts on malaria risk and severity and on treatment failures. Examining folic acid interactions with antifolate antimalarial medications and with malaria disease progression may help countries in malaria-endemic areas determine what are the most appropriate lower dose folic acid formulations for at-risk populations. The WHO has highlighted the limited evidence available and has indicated the need for further research on biomarkers of folate status, particularly interactions between RBC folate concentrations and tuberculosis, human immunodeficiency virus (HIV), and antifolate antimalarial drugs (WHO 2015b). An earlier Cochrane Review assessed the effects and safety of iron supplementation, with or without folic acid, in children living in hyperendemic or holoendemic malaria areas; it demonstrated that iron supplementation did not increase the risk of malaria, as indicated by fever and the presence of parasites in the blood (Neuberger 2016). Further, this review stated that folic acid may interfere with the efficacy of SP; however, the efficacy and safety of folic acid supplementation on these outcomes has not been established. This review will provide evidence on the effectiveness of daily folic acid supplementation in healthy and malaria-infected individuals living in malaria-endemic areas. Additionally, it will contribute to achieving both the WHO Global Technical Strategy for Malaria 2016-2030 (WHO 2015d), and United Nations Sustainable Development Goal 3 (to ensure healthy lives and to promote well-being for all of all ages) (United Nations 2021), and evaluating whether the potential effects of folic acid supplementation, at different doses (e.g. 0.4 mg, 1 mg, 5 mg daily), interferes with the effect of drugs used for prevention or treatment of malaria. To examine the effects of folic acid supplementation, at various doses, on malaria susceptibility (risk of infection) and severity among people living in areas with various degrees of malaria endemicity. We will examine the interaction between folic acid supplements and antifolate antimalarial drugs. Specifically, we will aim to answer the following. Among uninfected people living in malaria endemic areas, who are taking or not taking antifolate antimalarials for malaria prophylaxis, does taking a folic acid-containing supplement increase susceptibility to or severity of malaria infection? Among people with malaria infection who are being treated with antifolate antimalarials, does folic acid supplementation increase the risk of treatment failure? Criteria for considering studies for this review Types of studies Inclusion criteria Randomized controlled trials (RCTs) Quasi-RCTs with randomization at the individual or cluster level conducted in malaria-endemic areas (areas with ongoing, local malaria transmission, including areas approaching elimination, as listed in the World Malaria Report 2020) (WHO 2020) Exclusion criteria Ecological studies Observational studies In vivo/in vitro studies Economic studies Systematic literature reviews and meta-analyses (relevant systematic literature reviews and meta-analyses will be excluded but flagged for grey literature screening) Types of participants Inclusion criteria Individuals of any age or gender, living in a malaria endemic area, who are taking antifolate antimalarial medications (including but not limited to sulfadoxine/pyrimethamine (SP), pyrimethamine-dapsone, pyrimethamine, chloroquine and proguanil, cotrimoxazole) for the prevention or treatment of malaria (studies will be included if more than 70% of the participants live in malaria-endemic regions) Studies assessing participants with or without anaemia and with or without malaria parasitaemia at baseline will be included Exclusion criteria Individuals not taking antifolate antimalarial medications for prevention or treatment of malaria Individuals living in non-malaria endemic areas Types of interventions Inclusion criteria Folic acid supplementation Form: in tablet, capsule, dispersible tablet at any dose, during administration, or periodically Timing: during, before, or after (within a period of four to six weeks) administration of antifolate antimalarials Iron-folic acid supplementation Folic acid supplementation in combination with co-interventions that are identical between the intervention and control groups. Co-interventions include: anthelminthic treatment; multivitamin or multiple micronutrient supplementation; 5-methyltetrahydrofolate supplementation. Exclusion criteria Folate through folate-fortified water Folic acid administered through large-scale fortification of rice, wheat, or maize Comparators Placebo No treatment No folic acid/different doses of folic acid Iron Types of outcome measures Primary outcomes Uncomplicated malaria (defined as a history of fever with parasitological confirmation; acceptable parasitological confirmation will include rapid diagnostic tests (RDTs), malaria smears, or nucleic acid detection (i.e. polymerase chain reaction (PCR), loop-mediated isothermal amplification (LAMP), etc.)) (WHO 2010). This outcome is relevant for patients without malaria, given antifolate antimalarials for malaria prophylaxis. Severe malaria (defined as any case with cerebral malaria or acute P. falciparum malaria, with signs of severity or evidence of vital organ dysfunction, or both) (WHO 2010). This outcome is relevant for patients without malaria, given antifolate antimalarials for malaria prophylaxis. Parasite clearance (any Plasmodium species), defined as the time it takes for a patient who tests positive at enrolment and is treated to become smear-negative or PCR negative. This outcome is relevant for patients with malaria, treated with antifolate antimalarials. Treatment failure (defined as the inability to clear malaria parasitaemia or prevent recrudescence after administration of antimalarial medicine, regardless of whether clinical symptoms are resolved) (WHO 2019). This outcome is relevant for patients with malaria, treated with antifolate antimalarials. Secondary outcomes Duration of parasitaemia Parasite density Haemoglobin (Hb) concentrations (g/L) Anaemia: severe anaemia (defined as Hb less than 70 g/L in pregnant women and children aged six to 59 months; and Hb less than 80 g/L in other populations); moderate anaemia (defined as Hb less than 100 g/L in pregnant women and children aged six to 59 months; and less than 110 g/L in others) Death from any cause Among pregnant women: stillbirth (at less than 28 weeks gestation); low birthweight (less than 2500 g); active placental malaria (defined as Plasmodium detected in placental blood by smear or PCR, or by Plasmodium detected on impression smear or placental histology). Search methods for identification of studies A search will be conducted to identify completed and ongoing studies, without date or language restrictions. Electronic searches A search strategy will be designed to include the appropriate subject headings and text word terms related to each intervention of interest and study design of interest (see Appendix 1). Searches will be broken down by these two criteria (intervention of interest and study design of interest) to allow for ease of prioritization, if necessary. The study design filters recommended by the Scottish Intercollegiate Guidelines Network (SIGN), and those designed by Cochrane for identifying clinical trials for MEDLINE and Embase, will be used (SIGN 2020). There will be no date or language restrictions. Non-English articles identified for inclusion will be translated into English. If translations are not possible, advice will be requested from the Cochrane Infectious Diseases Group and the record will be stored in the "Awaiting assessment" section of the review until a translation is available. The following electronic databases will be searched for primary studies. Cochrane Central Register of Controlled Trials. Cumulative Index to Nursing and Allied Health Literature (CINAHL). Embase. MEDLINE. Scopus. Web of Science (both the Social Science Citation Index and the Science Citation Index). We will conduct manual searches of ClinicalTrials.gov, the International Clinical Trials Registry Platform (ICTRP), and the United Nations Children's Fund (UNICEF) Evaluation and Research Database (ERD), in order to identify relevant ongoing or planned trials, abstracts, and full-text reports of evaluations, studies, and surveys related to programmes on folic acid supplementation in malaria-endemic areas. Additionally, manual searches of grey literature to identify RCTs that have not yet been published but are potentially eligible for inclusion will be conducted in the following sources. Global Index Medicus (GIM). African Index Medicus (AIM). Index Medicus for the Eastern Mediterranean Region (IMEMR). Latin American & Caribbean Health Sciences Literature (LILACS). Pan American Health Organization (PAHO). Western Pacific Region Index Medicus (WPRO). Index Medicus for the South-East Asian Region (IMSEAR). The Spanish Bibliographic Index in Health Sciences (IBECS) (ibecs.isciii.es/). Indian Journal of Medical Research (IJMR) (journals.lww.com/ijmr/pages/default.aspx). Native Health Database (nativehealthdatabase.net/). Scielo (www.scielo.br/). Searching other resources Handsearches of the five journals with the highest number of included studies in the last 12 months will be conducted to capture any relevant articles that may not have been indexed in the databases at the time of the search. We will contact the authors of included studies and will check reference lists of included papers for the identification of additional records. For assistance in identifying ongoing or unpublished studies, we will contact the Division of Nutrition, Physical Activity, and Obesity (DNPAO) and the Division of Parasitic Diseases and Malaria (DPDM) of the CDC, the United Nations World Food Programme (WFP), Nutrition International (NI), Global Alliance for Improved Nutrition (GAIN), and Hellen Keller International (HKI). Data collection and analysis Selection of studies Two review authors will independently screen the titles and abstracts of articles retrieved by each search to assess eligibility, as determined by the inclusion and exclusion criteria. Studies deemed eligible for inclusion by both review authors in the abstract screening phase will advance to the full-text screening phase, and full-text copies of all eligible papers will be retrieved. If full articles cannot be obtained, we will attempt to contact the authors to obtain further details of the studies. If such information is not obtained, we will classify the study as "awaiting assessment" until further information is published or made available to us. The same two review authors will independently assess the eligibility of full-text articles for inclusion in the systematic review. If any discrepancies occur between the studies selected by the two review authors, a third review author will provide arbitration. Each trial will be scrutinized to identify multiple publications from the same data set, and the justification for excluded trials will be documented. A PRISMA flow diagram of the study selection process will be presented to provide information on the number of records identified in the literature searches, the number of studies included and excluded, and the reasons for exclusion (Moher 2009). The list of excluded studies, along with their reasons for exclusion at the full-text screening phase, will also be created. Data extraction and management Two review authors will independently extract data for the final list of included studies using a standardized data specification form. Discrepancies observed between the data extracted by the two authors will be resolved by involving a third review author and reaching a consensus. Information will be extracted on study design components, baseline participant characteristics, intervention characteristics, and outcomes. For individually randomized trials, we will record the number of participants experiencing the event and the number analyzed in each treatment group or the effect estimate reported (e.g. risk ratio (RR)) for dichotomous outcome measures. For count data, we will record the number of events and the number of person-months of follow-up in each group. If the number of person-months is not reported, the product of the duration of follow-up and the number of children evaluated will be used to estimate this figure. We will calculate the rate ratio and standard error (SE) for each study. Zero events will be replaced by 0.5. We will extract both adjusted and unadjusted covariate incidence rate ratios if they are reported in the original studies. For continuous data, we will extract means (arithmetic or geometric) and a measure of variance (standard deviation (SD), SE, or confidence interval (CI)), percentage or mean change from baseline, and the numbers analyzed in each group. SDs will be computed from SEs or 95% CIs, assuming a normal distribution of the values. Haemoglobin values in g/dL will be calculated by multiplying haematocrit or packed cell volume values by 0.34, and studies reporting haemoglobin values in g/dL will be converted to g/L. In cluster-randomized trials, we will record the unit of randomization (e.g. household, compound, sector, or village), the number of clusters in the trial, and the average cluster size. The statistical methods used to analyze the trials will be documented, along with details describing whether these methods adjusted for clustering or other covariates. We plan to extract estimates of the intra-cluster correlation coefficient (ICC) for each outcome. Where results are adjusted for clustering, we will extract the treatment effect estimate and the SD or CI. If the results are not adjusted for clustering, we will extract the data reported. Assessment of risk of bias in included studies Two review authors (KSC, LFY) will independently assess the risk of bias for each included trial using the Cochrane 'Risk of bias 2' tool (RoB 2) for randomized studies (Sterne 2019). Judgements about the risk of bias of included studies will be made according to the recommendations outlined in the Cochrane Handbook for Systematic Reviews of Interventions (Higgins 2021). Disagreements will be resolved by discussion, or by involving a third review author. The interest of our review will be to assess the effect of assignment to the interventions at baseline. We will evaluate each primary outcome using the RoB2 tool. The five domains of the Cochrane RoB2 tool include the following. Bias arising from the randomization process. Bias due to deviations from intended interventions. Bias due to missing outcome data. Bias in measurement of the outcome. Bias in selection of the reported result. Each domain of the RoB2 tool comprises the following. A series of 'signalling' questions. A judgement about the risk of bias for the domain, facilitated by an algorithm that maps responses to the signalling questions to a proposed judgement. Free-text boxes to justify responses to the signalling questions and 'Risk of bias' judgements. An option to predict (and explain) the likely direction of bias. Responses to signalling questions elicit information relevant to an assessment of the risk of bias. These response options are as follows. Yes (may indicate either low or high risk of bias, depending on the most natural way to ask the question). Probably yes. Probably no. No. No information (may indicate no evidence of that problem or an absence of information leading to concerns about there being a problem). Based on the answer to the signalling question, a 'Risk of bias' judgement is assigned to each domain. These judgements include one of the following. High risk of bias Low risk of bias Some concerns To generate the risk of bias judgement for each domain in the randomized studies, we will use the Excel template, available at www.riskofbias.info/welcome/rob-2-0-tool/current-version-of-rob-2. This file will be stored on a scientific data website, available to readers. Risk of bias in cluster randomized controlled trials For the cluster randomized trials, we will be using the RoB2 tool to analyze the five standard domains listed above along with Domain 1b (bias arising from the timing of identification or recruitment of participants) and its related signalling questions. To generate the risk of bias judgement for each domain in the cluster RCTs, we will use the Excel template available at https://sites.google.com/site/riskofbiastool/welcome/rob-2-0-tool/rob-2-for-cluster-randomized-trials. This file will be stored on a scientific data website, available to readers. Risk of bias in cross-over randomized controlled trials For cross-over randomized trials, we will be using the RoB2 tool to analyze the five standard domains listed above along with Domain 2 (bias due to deviations from intended interventions), and Domain 3 (bias due to missing outcome data), and their respective signalling questions. To generate the risk of bias judgement for each domain in the cross-over RCTs, we will use the Excel template, available at https://sites.google.com/site/riskofbiastool/welcome/rob-2-0-tool/rob-2-for-crossover-trials, for each risk of bias judgement of cross-over randomized studies. This file will be stored on a scientific data website, available to readers. Overall risk of bias The overall 'Risk of bias' judgement for each specific trial being assessed will be based on each domain-level judgement. The overall judgements include the following. Low risk of bias (the trial is judged to be at low risk of bias for all domains). Some concerns (the trial is judged to raise some concerns in at least one domain but is not judged to be at high risk of bias for any domain). High risk of bias (the trial is judged to be at high risk of bias in at least one domain, or is judged to have some concerns for multiple domains in a way that substantially lowers confidence in the result). The 'risk of bias' assessments will inform our GRADE evaluations of the certainty of evidence for our primary outcomes presented in the 'Summary of findings' tables and will also be used to inform the sensitivity analyses; (see Sensitivity analysis). If there is insufficient information in study reports to enable an assessment of the risk of bias, studies will be classified as "awaiting assessment" until further information is published or made available to us. Measures of treatment effect Dichotomous data For dichotomous data, we will present proportions and, for two-group comparisons, results as average RR or odds ratio (OR) with 95% CIs. Ordered categorical data Continuous data We will report results for continuous outcomes as the mean difference (MD) with 95% CIs, if outcomes are measured in the same way between trials. Where some studies have reported endpoint data and others have reported change-from-baseline data (with errors), we will combine these in the meta-analysis, if the outcomes were reported using the same scale. We will use the standardized mean difference (SMD), with 95% CIs, to combine trials that measured the same outcome but used different methods. If we do not find three or more studies for a pooled analysis, we will summarize the results in a narrative form. Unit of analysis issues Cluster-randomized trials We plan to combine results from both cluster-randomized and individually randomized studies, providing there is little heterogeneity between the studies. If the authors of cluster-randomized trials conducted their analyses at a different level from that of allocation, and they have not appropriately accounted for the cluster design in their analyses, we will calculate the trials' effective sample sizes to account for the effect of clustering in data. When one or more cluster-RCT reports RRs adjusted for clustering, we will compute cluster-adjusted SEs for the other trials. When none of the cluster-RCTs provide cluster-adjusted RRs, we will adjust the sample size for clustering. We will divide, by the estimated design effects (DE), the number of events and number evaluated for dichotomous outcomes and the number evaluated for continuous outcomes, where DE = 1 + ((average cluster size 1) * ICC). The derivation of the estimated ICCs and DEs will be reported. We will utilize the intra-cluster correlation coefficient (ICC), derived from the trial (if available), or from another source (e.g., using the ICCs derived from other, similar trials) and then calculate the design effect with the formula provided in the Cochrane Handbook for Systematic Reviews of Interventions (Higgins 2021). If this approach is used, we will report it and undertake sensitivity analysis to investigate the effect of variations in ICC. Studies with more than two treatment groups If we identify studies with more than two intervention groups (multi-arm studies), where possible we will combine groups to create a single pair-wise comparison or use the methods set out in the Cochrane Handbook to avoid double counting study participants (Higgins 2021). For the subgroup analyses, when the control group was shared by two or more study arms, we will divide the control group (events and total population) over the number of relevant subgroups to avoid double counting the participants. Trials with several study arms can be included more than once for different comparisons. Cross-over trials From cross-over trials, we will consider the first period of measurement only and will analyze the results together with parallel-group studies. Multiple outcome events In several outcomes, a participant might experience more than one outcome event during the trial period. For all outcomes, we will extract the number of participants with at least one event. Dealing with missing data We will contact the trial authors if the available data are unclear, missing, or reported in a format that is different from the format needed. We aim to perform a 'per protocol' or 'as observed' analysis; otherwise, we will perform a complete case analysis. This means that for treatment failure, we will base the analyses on the participants who received treatment and the number of participants for which there was an inability to clear malarial parasitaemia or prevent recrudescence after administration of an antimalarial medicine reported in the studies. Assessment of heterogeneity Heterogeneity in the results of the trials will be assessed by visually examining the forest plot to detect non-overlapping CIs, using the Chi2 test of heterogeneity (where a P value of less than 0.1 indicates statistical significance) and the I2 statistic of inconsistency (with a value of greater than 50% denoting moderate levels of heterogeneity). When statistical heterogeneity is present, we will investigate the reasons for it, using subgroup analysis. Assessment of reporting biases We will construct a funnel plot to assess the effect of small studies for the main outcome (when including more than 10 trials). Data synthesis The primary analysis will include all eligible studies that provide data regardless of the overall risk of bias as assessed by the RoB2 tool. Analyses will be conducted using Review Manager 5.4 (Review Manager 2020). Cluster-RCTs will be included in the main analysis after adjustment for clustering (see the previous section on cluster-RCTs). The meta-analysis will be performed using the Mantel-Haenszel random-effects model or the generic inverse variance method (when adjustment for clustering is performed by adjusting SEs), as appropriate. Subgroup analysis and investigation of heterogeneity The overall risk of bias will not be used as the basis in conducting our subgroup analyses. However, where data are available, we plan to conduct the following subgroup analyses, independent of heterogeneity. Dose of folic acid supplementation: higher doses (4 mg or more, daily) versus lower doses (less than 4 mg, daily). Moderate-severe anaemia at baseline (mean haemoglobin of participants in a trial at baseline below 100 g/L for pregnant women and children aged six to 59 months, and below 110 g/L for other populations) versus normal at baseline (mean haemoglobin above 100 g/L for pregnant women and children aged six to 59 months, and above 110 g/L for other populations). Antimalarial drug resistance to parasite: known resistance versus no resistance versus unknown/mixed/unreported parasite resistance. Folate status at baseline: Deficient (e.g. RBC folate concentration of less than 305 nmol/L, or serum folate concentration of less than 7nmol/L) and Insufficient (e.g. RBC folate concentration from 305 to less than 906 nmol/L, or serum folate concentration from 7 to less than 25 nmol/L) versus Sufficient (e.g. RBC folate concentration above 906 nmol/L, or serum folate concentration above 25 nmol/L). Presence of anaemia at baseline: yes versus no. Mandatory fortification status: yes, versus no (voluntary or none). We will only use the primary outcomes in any subgroup analyses, and we will limit subgroup analyses to those outcomes for which three or more trials contributed data. Comparisons between subgroups will be performed using Review Manager 5.4 (Review Manager 2020). Sensitivity analysis We will perform a sensitivity analysis, using the risk of bias as a variable to explore the robustness of the findings in our primary outcomes. We will verify the behaviour of our estimators by adding and removing studies with a high risk of bias overall from the analysis. That is, studies with a low risk of bias versus studies with a high risk of bias. Summary of findings and assessment of the certainty of the evidence For the assessment across studies, we will use the GRADE approach, as outlined in (Schünemann 2021). We will use the five GRADE considerations (study limitations based on RoB2 judgements, consistency of effect, imprecision, indirectness, and publication bias) to assess the certainty of the body of evidence as it relates to the studies which contribute data to the meta-analyses for the primary outcomes. The GRADEpro Guideline Development Tool (GRADEpro) will be used to import data from Review Manager 5.4 (Review Manager 2020) to create 'Summary of Findings' tables. The primary outcomes for the main comparison will be listed with estimates of relative effects, along with the number of participants and studies contributing data for those outcomes. These tables will provide outcome-specific information concerning the overall certainty of evidence from studies included in the comparison, the magnitude of the effect of the interventions examined, and the sum of available data on the outcomes we considered. We will include only primary outcomes in the summary of findings tables. For each individual outcome, two review authors (KSC, LFY) will independently assess the certainty of the evidence using the GRADE approach (Balshem 2011). For assessments of the overall certainty of evidence for each outcome that includes pooled data from included trials, we will downgrade the evidence from 'high certainty' by one level for serious (or by two for very serious) study limitations (risk of bias, indirectness of evidence, serious inconsistency, imprecision of effect estimates, or potential publication bias).

Crider K ，Williams J ，Qi YP ，Gutman J ，Yeung L ，Mai C ，Finkelstain J ，Mehta S ，Pons-Duran C ，Menéndez C ，Moraleda C ，Rogers L ，Daniels K ，Green P ... -  《Cochrane Database of Systematic Reviews》

Impact of summer programmes on the outcomes of disadvantaged or 'at risk' young people: A systematic review.

Many intervention studies of summer programmes examine their impact on employment and education outcomes, however there is growing interest in their effect on young people's offending outcomes. Evidence on summer employment programmes shows promise on this but has not yet been synthesised. This report fills this evidence gap through a systematic review and meta-analysis, covering summer education and summer employment programmes as their contexts and mechanisms are often similar. The objective is to provide evidence on the extent to which summer programmes impact the outcomes of disadvantaged or 'at risk' young people. The review employs mixed methods: we synthesise quantitative information estimating the impact of summer programme allocation/participation across the outcome domains through meta-analysis using the random-effects model; and we synthesise qualitative information relating to contexts, features, mechanisms and implementation issues through thematic synthesis. Literature searches were largely conducted in January 2023. Databases searched include: Scopus; PsychInfo; ERIC; the YFF-EGM; EEF's and TASO's toolkits; RAND's summer programmes evidence review; key academic journals; and Google Scholar. The review employed PICOSS eligibility criteria: the population was disadvantaged or 'at risk' young people aged 10-25; interventions were either summer education or employment programmes; a valid comparison group that did not experience a summer programme was required; studies had to estimate the summer programme's impact on violence and offending, education, employment, socio-emotional and/or health outcomes; eligible study designs were experimental and quasi-experimental; eligible settings were high-income countries. Other eligibility criteria included publication in English, between 2012 and 2022. Process/qualitative evaluations associated with eligible impact studies or of UK-based interventions were also included; the latter given the interests of the sponsors. We used standard methodological procedures expected by The Campbell Collaboration. The search identified 68 eligible studies; with 41 eligible for meta-analysis. Forty-nine studies evaluated 36 summer education programmes, and 19 studies evaluated six summer employment programmes. The number of participants within these studies ranged from less than 100 to nearly 300,000. The PICOSS criteria affects the external applicability of the body of evidence - allowances made regarding study design to prioritise evidence on UK-based interventions limits our ability to assess impact for some interventions. The risk of bias assessment categorised approximately 75% of the impact evaluations as low quality, due to attrition, losses to follow up, interventions having low take-up rates, or where allocation might introduce selection bias. As such, intention-to-treat analyses are prioritised. The quality assessment rated 93% of qualitative studies as low quality often due to not employing rigorous qualitative methodologies. These results highlight the need to improve the evidence. Quantitative synthesis The quantitative synthesis examined impact estimates across 34 outcomes, through meta-analysis (22) or in narrative form (12). We summarise below the findings where meta-analysis was possible, along with the researchers' judgement of the security of the findings (high, moderate or low). This was based on the number and study-design quality of studies evaluating the outcome; the consistency of findings; the similarity in specific outcome measures used; and any other specific issues which might affect our confidence in the summary findings.Below we summarise the findings from the meta-analyses conducted to assess the impact of allocation to/participation in summer education and employment programmes (findings in relation to other outcomes are also discussed in the main body, but due to the low number of studies evaluating these, meta-analysis was not performed). We only cover the pooled results for the two programme types where there are not clear differences in findings between summer education and summer employment programmes, so as to avoid potentially attributing any impact to both summer programme types when this is not the case. We list the outcome measure, the average effect size type (i.e., whether a standardised mean difference (SMD) or log odds ratio), which programme type the finding is in relation to and then the average effect size along with its 95% confidence interval and the interpretation of the finding, that is, whether there appears to be a significant impact and in which direction (positive or negative, clarifying instances where a negative impact is beneficial). In some instances there may be a discrepancy between the 95% confidence interval and whether we determine there to be a significant impact, which will be due to the specifics of the process for constructing the effect sizes used in the meta-analysis. We then list the I 2 statistic and the p-value from the homogeneity test as indications of the presence of heterogeneity. As the sample size used in the analysis are often small and the homogeneity test is known to be under-powered with small sample sizes, it may not detect statistically significant heterogeneity when it is in fact present. As such, a 90% confidence level threshold should generally be used when interpreting this with regard to the meta-analyses below. The presence of effect size heterogeneity affects the extent to which the average effects size is applicable to all interventions of that summer programme type. We also provide an assessment of the relative confidence we have in the generalisability of the overall finding (low, moderate or high) - some of the overall findings are based on a small sample of studies, the studies evaluating the outcome may be of low quality, there may be wide variation in findings among the studies evaluating the outcome, or there may be specific aspects of the impact estimates included or the effect sizes constructed that affect the generalisability of the headline finding. These issues are detailed in full in the main body of the review. -Engagement with/participation in/enjoyment of education (SMD):∘Summer education programmes: +0.12 (+0.03, +0.20); positive impact; I 2 = 48.76%, p = 0.10; moderate confidence.-Secondary education attendance (SMD):∘Summer education programmes: +0.26 (+0.08, +0.44); positive impact; I 2 = N/A; p = N/A; low confidence.∘Summer employment programmes: +0.02 (-0.03, +0.07); no impact; I 2 = 69.98%; p = 0.03; low confidence.-Passing tests (log OR):∘Summer education programmes: +0.41 (-0.13, +0.96); no impact; I 2 = 95.05%; p = 0.00; low confidence.∘Summer employment programmes: +0.02 (+0.00, +0.04); positive impact; I 2 = 0.01%; p = 0.33; low confidence.-Reading test scores (SMD):∘Summer education programmes: +0.01 (-0.04, +0.05); no impact; I 2 = 0.40%; p = 0.48; high confidence.-English test scores (SMD):∘Summer education programmes: +0.07 (+0.00, +0.13); positive impact; I 2 = 27.17%; p = 0.33; moderate confidence.∘Summer employment programmes: -0.03 (-0.05, -0.01); negative impact; I 2 = 0.00%; p = 0.76; low confidence.-Mathematics test scores (SMD):∘All summer programmes: +0.09 (-0.06, +0.25); no impact; I 2 = 94.53%; p = 0.00; high confidence.∘Summer education programmes: +0.14 (-0.09, +0.36); no impact; I 2 = 94.15%; p = 0.00; moderate confidence.∘Summer employment programmes: +0.00 (-0.04, +0.05); no impact; I 2 = 0.04%; p = 0.92; moderate confidence.-Overall test scores (SMD):∘Summer employment programmes: -0.01 (-0.08, +0.05); no impact; I 2 = 32.39%; p = 0.20; high confidence.-All test scores (SMD):∘Summer education programmes: +0.14 (+0.00, +0.27); positive impact; I 2 = 91.07%; p = 0.00; moderate confidence.∘Summer employment programmes: -0.01 (-0.04, +0.01); no impact; I 2 = 0.06%; p = 0.73; high confidence.-Negative behavioural outcomes (log OR):∘Summer education programmes: -1.55 (-3.14, +0.03); negative impact; I 2 = N/A; p = N/A; low confidence.∘Summer employment programmes: -0.07 (-0.33, +0.18); no impact; I 2 = 88.17%; p = 0.00; moderate confidence.-Progression to HE (log OR):∘All summer programmes: +0.24 (-0.04, +0.52); no impact; I 2 = 97.37%; p = 0.00; low confidence.∘Summer education programmes: +0.32 (-0.12, +0.76); no impact; I 2 = 96.58%; p = 0.00; low confidence.∘Summer employment programmes: +0.10 (-0.07, +0.26); no impact; I 2 = 76.61%; p = 0.02; moderate confidence.-Complete HE (log OR):∘Summer education programmes: +0.38 (+0.15, +0.62); positive impact; I 2 = 52.52%; p = 0.06; high confidence.∘Summer employment programmes: +0.07 (-0.19, +0.33); no impact; I 2 = 70.54%; p = 0.07; moderate confidence.-Entry to employment, short-term (log OR):∘Summer employment programmes: -0.19 (-0.45, +0.08); no impact; I 2 = 87.81%; p = 0.00; low confidence.∘Entry to employment, full period (log OR)∘Summer employment programmes: -0.15 (-0.35, +0.05); no impact; I 2 = 78.88%; p = 0.00; low confidence.-Likelihood of having a criminal justice outcome (log OR):∘Summer employment programmes: -0.05 (-0.15, +0.05); no impact; I 2 = 0.00%; p = 0.76; low confidence.-Likelihood of having a drug-related criminal justice outcome (log OR):∘Summer employment programmes: +0.16 (-0.57, +0.89); no impact; I 2 = 65.97%; p = 0.09; low confidence.-Likelihood of having a violence-related criminal justice outcome (log OR):∘Summer employment programmes: +0.03 (-0.02, +0.08); no impact; I 2 = 0.00%; p = 0.22; moderate confidence.-Likelihood of having a property-related criminal justice outcome (log OR):∘Summer employment programmes: +0.09 (-0.17, +0.34); no impact; I 2 = 45.01%; p = 0.18; low confidence.-Number of criminal justice outcomes, during programme (SMD):∘Summer employment programmes: -0.01 (-0.03, +0.00); no impact; I 2 = 2.17%; p = 0.31; low confidence.-Number of criminal justice outcomes, post-programme (SMD):∘Summer employment programmes: -0.01 (-0.03, +0.00); no impact; I 2 = 23.57%; p = 0.37; low confidence.-Number of drug-related criminal justice outcomes, post-programme (SMD):∘Summer employment programmes: -0.01 (-0.06, +0.06); no impact; I 2 = 55.19%; p = 0.14; moderate confidence.-Number of violence-related criminal justice outcomes, post-programme (SMD):∘Summer employment programmes: -0.02 (-0.08, +0.03); no impact; I 2 = 44.48%; p = 0.18; low confidence.-Number of property-related criminal justice outcomes, post-programme (SMD):∘Summer employment programmes: -0.02 (-0.10, +0.05); no impact; I 2 = 64.93%; p = 0.09; low confidence. We re-express instances of significant impact by programme type where we have moderate or high confidence in the security of findings by translating this to a form used by one of the studies, to aid understanding of the findings. Allocation to a summer education programme results in approximately 60% of individuals moving from never reading for fun to doing so once or twice a month (engagement in/participation in/enjoyment of education), and an increase in the English Grade Point Average of 0.08. Participation in a summer education programme results in an increase in overall Grade Point Average of 0.14 and increases the likelihood of completing higher education by 1.5 times. Signs are positive for the effectiveness of summer education programmes in achieving some of the education outcomes considered (particularly on test scores (when pooled across types), completion of higher education and STEM-related higher education outcomes), but the evidence on which overall findings are based is often weak. Summer employment programmes appear to have a limited impact on employment outcomes, if anything, a negative impact on the likelihood of entering employment outside of employment related to the programme. The evidence base for impacts of summer employment programmes on young people's violence and offending type outcomes is currently limited - where impact is detected this largely results in substantial reductions in criminal justice outcomes, but the variation in findings across and within studies affects our ability to make any overarching assertions with confidence. In understanding the effectiveness of summer programmes, the order of outcomes also requires consideration - entries into education from a summer employment programme might be beneficial if this leads towards better quality employment in the future and a reduced propensity of criminal justice outcomes. Various shared features among different summer education programmes emerged from the review, allowing us to cluster specific types of these interventions which then aided the structuring of the thematic synthesis. The three distinct clusters for summer education programmes were: catch-up programmes addressing attainment gaps, raising aspirations programmes inspiring young people to pursue the next stage of their education or career, and transition support programmes facilitating smooth transitions between educational levels. Depending on their aim, summer education programme tend to provide a combination of: additional instruction on core subjects (e.g., English, mathematics); academic classes including to enhance specialist subject knowledge (e.g., STEM-related); homework help; coaching and mentoring; arts and recreation electives; and social and enrichment activities. Summer employment programmes provide paid work placements or subsidised jobs typically in entry-level roles mostly in the third and public sectors, with some summer employment programmes also providing placements in the private sector. They usually include components of pre-work training and employability skills, coaching and mentoring. There are a number of mechanisms which act as facilitators or barriers to engagement in summer programmes. These include tailoring the summer programme to each young person and individualised attention; the presence of well-prepared staff who provide effective academic/workplace and socio-emotional support; incentives of a monetary (e.g., stipends and wages) or non-monetary (e.g., free transport and meals) nature; recruitment strategies, which are effective at identifying, targeting and engaging participants who can most benefit from the intervention; partnerships, with key actors who can help facilitate referrals and recruitment, such as schools, community action and workforce development agencies; format, including providing social activities and opportunities to support the formation of connections with peers; integration into the workplace, through pre-placement engagement, such as through orientation days, pre-work skills training, job fairs, and interactions with employers ahead of the beginning of the summer programme; and skill acquisition, such as improvements in social skills. In terms of the causal processes which lead from engagement in a summer programme to outcomes, these include: skill acquisition, including academic, social, emotional, and life skills; positive relationships with peers, including with older students as mentors in summer education programmes; personalised and positive relationships with staff; location, including accessibility and creating familiar environments; creating connections between the summer education programme and the students' learning at home to maintain continuity and reinforce learning; and providing purposeful and meaningful work through summer employment programmes (potentially facilitated through the provision of financial and/or non-financial incentives), which makes participants more likely to see the importance of education in achieving their life goals and this leads to raised aspirations. It is important to note that no single element of a summer programme can be identified as generating the causal process for impact, and impact results rather from a combination of elements. Finally, we investigated strengths and weaknesses in summer programmes at both the design and implementation stages. In summer education programmes, design strengths include interactive and alternative learning modes; iterative and progressive content building; incorporating confidence building activities; careful lesson planning; and teacher support which is tailored to each student. Design weaknesses include insufficient funding or poor funding governance (e.g., delays to funding); limited reach of the target population; and inadequate allocation of teacher and pupil groups (i.e., misalignment between the education stage of the pupils and the content taught by staff). Implementation strengths include clear programme delivery guidance and good governance; high quality academic instruction; mentoring support; and strong partnerships. Implementation weaknesses include insufficient planning and lead in time; recruitment challenges; and variability in teaching quality. In summer employment programmes, design strengths include use of employer orientation materials and supervisor handbooks; careful consideration of programme staff roles; a wide range of job opportunities; and building a network of engaged employers. Design weaknesses are uncertainty over funding and budget agreements; variation in delivery and quality of training between providers; challenges in recruitment of employers; and caseload size and management. Implementation strengths include effective job matching; supportive relationships with supervisors; pre-work training; and mitigating attrition (e.g., striving to increase take up of the intervention among the treatment group). Implementation weaknesses are insufficient monitors for the number of participants, and challenges around employer availability.

Muir D ，Orlando C ，Newton B 《-》

Factors that influence participation in physical activity for people with bipolar disorder: a synthesis of qualitative evidence.

Mental health problems contribute significantly to the overall disease burden worldwide and are major causes of disability, suicide, and ischaemic heart disease. People with bipolar disorder report lower levels of physical activity than the general population, and are at greater risk of chronic health conditions including cardiovascular disease and obesity. These contribute to poor health outcomes. Physical activity has the potential to improve quality of life and physical and mental well-being. To identify the factors that influence participation in physical activity for people diagnosed with bipolar disorder from the perspectives of service users, carers, service providers, and practitioners to help inform the design and implementation of interventions that promote physical activity. We searched MEDLINE, PsycINFO, and eight other databases to March 2021. We also contacted experts in the field, searched the grey literature, and carried out reference checking and citation searching to identify additional studies. There were no language restrictions. We included qualitative studies and mixed-methods studies with an identifiable qualitative component. We included studies that focused on the experiences and attitudes of service users, carers, service providers, and healthcare professionals towards physical activity for bipolar disorder. We extracted data using a data extraction form designed for this review. We assessed methodological limitations using a list of predefined questions. We used the "best fit" framework synthesis based on a revised version of the Health Belief Model to analyse and present the evidence. We assessed methodological limitations using the CASP Qualitative Checklist. We used the GRADE-CERQual (Confidence in the Evidence from Reviews of Qualitative research) guidance to assess our confidence in each finding. We examined each finding to identify factors to inform the practice of health and care professionals and the design and development of physical activity interventions for people with bipolar disorder. We included 12 studies involving a total of 592 participants (422 participants who contributed qualitative data to an online survey, 170 participants in qualitative research studies). Most studies explored the views and experiences of physical activity of people with experience of bipolar disorder. A number of studies also reported on personal experiences of physical activity components of lifestyle interventions. One study included views from family carers and clinicians. The majority of studies were from high-income countries, with only one study conducted in a middle-income country. Most participants were described as stable and had been living with a diagnosis of bipolar disorder for a number of years. We downgraded our confidence in several of the findings from high confidence to moderate or low confidence, as some findings were based on only small amounts of data, and the findings were based on studies from only a few countries, questioning the relevance of these findings to other settings. We also had very few perspectives of family members, other carers, or health professionals supporting people with bipolar disorder. The studies did not include any findings from service providers about their perspectives on supporting this aspect of care. There were a number of factors that limited people's ability to undertake physical activity. Shame and stigma about one's physical appearance and mental health diagnosis were discussed. Some people felt their sporting skills/competencies had been lost when they left school. Those who had been able to maintain exercise through the transition into adulthood appeared to be more likely to include physical activity in their regular routine. Physical health limits and comorbid health conditions limited activity. This included bipolar medication, being overweight, smoking, alcohol use, poor diet and sleep, and these barriers were linked to negative coping skills. Practical problems included affordability, accessibility, transport links, and the weather. Workplace or health schemes that offered discounts were viewed positively. The lack of opportunity for exercise within inpatient mental health settings was a problem. Facilitating factors included being psychologically stable and ready to adopt new lifestyle behaviours. There were positive benefits of being active outdoors and connecting with nature. Achieving balance, rhythm, and routine helped to support mood management. Fitting physical activity into a regular routine despite fluctuating mood or motivation appeared to be beneficial if practised at the right intensity and pace. Over- or under-exercising could be counterproductive and accelerate depressive or manic moods. Physical activity also helped to provide a structure to people's daily routines and could lead to other positive lifestyle benefits. Monitoring physical or other activities could be an effective way to identify potential triggers or early warning signs. Technology was helpful for some. People who had researched bipolar disorder and had developed a better understanding of the condition showed greater confidence in managing their care or providing care to others. Social support from friends/family or health professionals was an enabling factor, as was finding the right type of exercise, which for many people was walking. Other benefits included making social connections, weight loss, improved quality of life, and better mood regulation. Few people had been told of the benefits of physical activity. Better education and training of health professionals could support a more holistic approach to physical and mental well-being. Involving mental health professionals in the multidisciplinary delivery of physical activity interventions could be beneficial and improve care. Clear guidelines could help people to initiate and incorporate lifestyle changes. There is very little research focusing on factors that influence participation in physical activity in bipolar disorder. The studies we identified suggest that men and women with bipolar disorder face a range of obstacles and challenges to being active. The evidence also suggests that there are effective ways to promote managed physical activity. The research highlighted the important role that health and care settings, and professionals, can play in assessing individuals' physical health needs and how healthy lifestyles may be promoted. Based on these findings, we have provided a summary of key elements to consider for developing physical activity interventions for bipolar disorder.

McCartan CJ ，Yap J ，Best P ，Breedvelt J ，Breslin G ，Firth J ，Tully MA ，Webb P ，White C ，Gilbody S ，Churchill R ，Davidson G ... -  《Cochrane Database of Systematic Reviews》

A meta-ethnography of how children and young people with chronic non-cancer pain and their families experience and understand their condition, pain services, and treatments.

Chronic non-cancer pain in childhood is widespread, affecting 20% to 35% of children and young people worldwide. For a sizeable number of children, chronic non-cancer pain has considerable negative impacts on their lives and quality of life, and leads to increased use of healthcare services and medication. In many countries, there are few services for managing children's chronic non-cancer pain, with many services being inadequate. Fourteen Cochrane Reviews assessing the effects of pharmacological, psychological, psychosocial, dietary or physical activity interventions for managing children's chronic non-cancer pain identified a lack of high-quality evidence to inform pain management. To design and deliver services and interventions that meet the needs of patients and their families, we need to understand how children with chronic non-cancer pain and their families experience pain, their views of services and treatments for chronic pain, and which outcomes are important to them. 1. To synthesise qualitative studies that examine the experiences and perceptions of children with chronic non-cancer pain and their families regarding chronic non-cancer pain, treatments and services to inform the design and delivery of health and social care services, interventions and future research. 2. To explore whether our review findings help to explain the results of Cochrane Reviews of intervention effects of treatments for children's chronic non-cancer pain. 3. To determine if programme theories and outcomes of interventions match children and their families' views of desired treatments and outcomes. 4. To use our findings to inform the selection and design of patient-reported outcome measures for use in chronic non-cancer pain studies and interventions and care provision to children and their families. The review questions are: 1. How do children with chronic non-cancer pain and their families conceptualise chronic pain? 2. How do children with chronic non-cancer pain and their families live with chronic pain? 3. What do children with chronic non-cancer pain and their families think of how health and social care services respond to and manage their child's chronic pain? 4. What do children with chronic non-cancer pain and their families conceptualise as 'good' chronic pain management and what do they want to achieve from chronic pain management interventions and services? Review strategy: we comprehensively searched 12 bibliographic databases including MEDLINE, CINAHL, PsycInfo and grey literature sources, and conducted supplementary searches in 2020. We updated the database searches in September 2022. To identify published and unpublished qualitative research with children aged 3 months to 18 years with chronic non-cancer pain and their families focusing on their perceptions, experiences and views of chronic pain, services and treatments. The final inclusion criteria were agreed with a patient and public involvement group of children and young people with chronic non-cancer pain and their families. We conducted a qualitative evidence synthesis using meta-ethnography, a seven-phase, systematic, interpretive, inductive methodology that takes into account the contexts and meanings of the original studies. We assessed the richness of eligible studies and purposively sampled rich studies ensuring they addressed the review questions. Cochrane Qualitative Methods Implementation Group guidance guided sampling. We assessed the methodological limitations of studies using the Critical Appraisal Skills Programme tool. We extracted data on study aims, focus, characteristics and conceptual findings from study reports using NVivo software. We compared these study data to determine how the studies related to one another and grouped studies by pain conditions for synthesis. We used meta-ethnography to synthesise each group of studies separately before synthesising them all together. Analysis and interpretation of studies involved children with chronic non-cancer pain and their families and has resulted in theory to inform service design and delivery. Sampling, organising studies for synthesis, and analysis and interpretation involved our patient and public involvement group who contributed throughout the conduct of the review. We used the GRADE-CERQual (Confidence in the Evidence from Reviews of Qualitative research) approach to assess our confidence in each review finding. We used a matrix approach to integrate our findings with existing Cochrane Reviews on treatment effectiveness for children's chronic non-cancer pain. We synthesised 43 studies sampled from 170 eligible studies reported in 182 publications. Included studies involved 633 participants. GRADE-CERQual assessments of findings were mostly high (n = 21, 58%) or moderate (n = 12, 33%) confidence with three (8%) low or very low confidence. Poorly managed, moderate or severe chronic non-cancer pain had profound adverse impacts on family dynamics and relationships; family members' emotions, well-being, autonomy and sense of self-identity; parenting strategies; friendships and socialising; children's education and future employment prospects; and parental employment. Most children and parents understood chronic non-cancer pain as having an underlying biological cause and wanted curative treatment. However, families had difficulties seeking and obtaining support from health services to manage their child's pain and its impacts. Children and parents felt that healthcare professionals did not always listen to their experiences and expertise, or believe the child's pain. Some families repeatedly visited health services seeking a diagnosis and cure. Over time, some children and families gave up hope of effective treatment. Outcomes measured within trials and Cochrane Reviews of intervention effects did not include some outcomes of importance to children and families, including impacts of pain on the whole family and absence of pain. Cochrane Reviews have mainly neglected a holistic biopsychosocial approach, which specifies the interrelatedness of biological, psychological and social aspects of illness, when selecting outcome measures and considering how chronic pain management interventions work. We had high or moderate confidence in the evidence contributing to most review findings. Further research, especially into families' experiences of treatments and services, could strengthen the evidence for low or very low confidence findings. Future research should also explore families' experiences in low- to middle-income contexts; of pain treatments including opioid use in children, which remains controversial; and of social care services. We need development and testing of family-centred interventions and services acceptable to families. Future trials of children's chronic non-cancer pain interventions should include family-centred outcomes.

France E ，Uny I ，Turley R ，Thomson K ，Noyes J ，Jordan A ，Forbat L ，Caes L ，Silveira Bianchim M ... -  《Cochrane Database of Systematic Reviews》