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Background:It is well established that screening can prevent cervical cancer, but the magnitude of the impact of regular screening on cervical cancer mortality is unknown.Methods:Population-based case–control study using prospectively recorded cervical screening data, England 1988–2013. Case women had cervical cancer diagnosed during April 2007–March 2013 aged 25–79 years (N=11 619). Two cancer-free controls were individually age matched to each case. We used conditional logistic regression to estimate the odds ratio (OR) of developing stage-specific cancer for women regularly screened or irregularly screened compared with women not screened in the preceding 15 years. Mortality was estimated from excess deaths within 5 years of diagnosis using stage-specific 5-year relative survival from England with adjustment for age within stage based on SEER (Surveillance, Epidemiology and End Results, USA) data.Results:In women aged 35–64 years, regular screening is associated with a 67% (95% confidence interval (CI): 62–73%) reduction in stage 1A cancer and a 95% (95% CI: 94–97%) reduction in stage 3 or worse cervical cancer: the estimated OR comparing regular (⩽5.5yearly) screening to no (or minimal) screening are 0.18 (95% CI: 0.16–0.19) for cancer incidence and 0.08 (95% CI: 0.07–0.09) for mortality. It is estimated that in England screening currently prevents 70% (95% CI: 66–73%) of cervical cancer deaths (all ages); however, if everyone attended screening regularly, 83% (95% CI: 82–84%) could be prevented.Conclusions:The association between cervical cancer screening and incidence is stronger in more advanced stage cancers, and screening is more effective at preventing death from cancer than preventing cancer itself.

INSPIRE and Brief INSPIRE demonstrate adequate psychometric properties, and can be recommended for research and clinical use.

(2015) Supporting recovery in patients with psychosis using adult mental health teams (REFOCUS): a multi-site cluster randomised controlled trial. The Lancet Psychiatry, 2 (6). pp. 503-514. ISSN 2215-0374 Access from the University of Nottingham repository: http://eprints.nottingham.ac.uk/34258/1/AFD%20Lancet%20Psychiatry%20REFOCUS %20Cost-effectiveness.pdf Copyright and reuse:The Nottingham ePrints service makes this work by researchers of the University of Nottingham available open access under the following conditions. This article is made available under the University of Nottingham End User licence and may be reused according to the conditions of the licence. For more details see: http://eprints.nottingham.ac.uk/end_user_agreement.pdf A note on versions:The version presented here may differ from the published version or from the version of record. If you wish to cite this item you are advised to consult the publisher's version. Please see the repository url above for details on accessing the published version and note that access may require a subscription. Abstract BackgroundMental health policy in many countries is oriented around recovery. The evidence base for service-level pro-recovery interventions is lacking. MethodsTwo-site cluster randomised controlled trial in England (ISRCTN02507940). REFOCUS is a one-year team-level intervention targeting staff behaviour (increasing focus on patient values, preferences, strengths, goal-striving) and staff-patient relationships (coaching, partnership). 27 community-based adult mental health teams were randomly allocated to treatment-as-usual (n=13) or treatment-as-usual plus REFOCUS (n=14).Baseline (n=403) and one-year follow-up (n=297) outcomes were assessed for randomly selected patients with psychosis, representing 88% of target recruitment. Primary outcome was recovery, assessed using Questionnaire about Processes of Recovery (QPR). FindingsIntention-to-treat analysis using multiple imputation found no difference in QPR Total (control 40·0 (s.d.10·2), intervention 40·6 (s.d.10·1), adjusted difference 0·68, 95%CI: -1·7 to 3·1, p=·58), or sub-scales. Secondary outcomes which improved in the intervention group were functioning (adjusted difference 6·96, 95%CI 2·8 to 9·2, p<·001) and staff-rated unmet need (adjusted difference 0·80, 95%CI 0·2 to 1·4, p=·01). This pattern remained after covariate adjustment and completer analysis (n=275). Higherparticipating teams had higher staff-rated pro-recovery behaviour change (adjusted difference -0·4, 95%CI -0·7 to -0·2, p=·001) and patients had higher QPR Interpersonal scores (adjusted difference -1·6, 95%CI -2·7 to -0·5, p=·005) at follow-up. Interventiongroup patients incurred £1,062 (95%CI -£1,103 to £3,017) lower adjusted costs. InterpretationSupporting recovery may, from the staff perspective, improve functioning and reduce needs. Overcoming implementation barriers may increase staff pro-recovery behaviours and interpersonal aspects of patient-rated recovery.

Aims To assess the pharmacokinetic (PK) profile of, and users' reactions to, Juul (59 mg nicotine/ml) as an indication of its therapeutic and dependence potential. Design Cross-over, within-subjects study in which participants attended after overnight abstinence on separate sessions and smoked a cigarette or used Juul or eight other types of e-cigarettes (EC) ad libitum for 5 minutes. The Juul product used was the version available in the United States that has more nicotine in the eliquid than the one available in the European Union. Setting Laboratory setting in the United Kingdom. Participants Twenty dual users (smokers who also vape) provided data on Juul and cigarettes, with eight also providing data on other EC products. Measurements At each session, number of puffs taken was counted during the 5-minute product use period and blood samples were taken at baseline and at 2, 4, 6, 8, 10 and 30 minutes after starting smoking/vaping and analysed for nicotine. Participants also monitored their urges to smoke and rated the products on a range of characteristics. Findings Juul's PK profile was close to the PK profile of cigarettes [maximum concentration (C max ) = 20.4 versus 19.2 ng/ml; time to maximum concentration (T max ) = 4 versus 6 minutes; area under the curve (AUC): 307.9 versus 312.6, respectively]. Compared with other EC products, Juul had shorter T max [4 minutes, (IQR = 2.5-4.0) versus 6.3 minutes, (IQR = 4.7 -8.1), P = 0.012] and higher C max (28.9 (SD = 15.6) versus 10.6 (SD = 5.5), P = 0.013) despite a lower number of puffs (12.5 (SD = 4.2) versus 17.0 (SD = 4.2), P = 0.084). Compared with other e-cigarette products, it also provided faster reduction of urges to smoke and obtained more favourable subjective ratings.Conclusion Juul's PK profile and user ratings suggest that it could be more effective than other EC products in helping smokers to quit smoking, but it may also have a higher potential to generate regular use in non-smokers.