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Background: People with language problems following stroke (aphasia) benefit from speech and language therapy. Optimising speech and language therapy for aphasia recovery is a research priority. Objectives: The objectives were to explore patterns and predictors of language and communication recovery, optimum speech and language therapy intervention provision, and whether or not effectiveness varies by participant subgroup or language domain. Design: This research comprised a systematic review, a meta-analysis and a network meta-analysis of individual participant data. Setting: Participant data were collected in research and clinical settings. Interventions: The intervention under investigation was speech and language therapy for aphasia after stroke. Main outcome measures: The main outcome measures were absolute changes in language scores from baseline on overall language ability, auditory comprehension, spoken language, reading comprehension, writing and functional communication. Data sources and participants: Electronic databases were systematically searched, including MEDLINE, EMBASE, Cumulative Index to Nursing and Allied Health Literature, Linguistic and Language Behavior Abstracts and SpeechBITE (searched from inception to 2015). The results were screened for eligibility, and published and unpublished data sets (randomised controlled trials, non-randomised controlled trials, cohort studies, case series, registries) with at least 10 individual participant data reporting aphasia duration and severity were identified. Existing collaborators and primary researchers named in identified records were invited to contribute electronic data sets. Individual participant data in the public domain were extracted. Review methods: Data on demographics, speech and language therapy interventions, outcomes and quality criteria were independently extracted by two reviewers, or available as individual participant data data sets. Meta-analysis and network meta-analysis were used to generate hypotheses. Results: We retrieved 5928 individual participant data from 174 data sets across 28 countries, comprising 75 electronic (3940 individual participant data), 47 randomised controlled trial (1778 individual participant data) and 91 speech and language therapy intervention (2746 individual participant data) data sets. The median participant age was 63 years (interquartile range 53–72 years). We identified 53 unavailable, but potentially eligible, randomised controlled trials (46 of these appeared to include speech and language therapy). Relevant individual participant data were filtered into each analysis. Statistically significant predictors of recovery included age (functional communication, individual participant data: 532, n = 14 randomised controlled trials) and sex (overall language ability, individual participant data: 482, n = 11 randomised controlled trials; functional communication, individual participant data: 532, n = 14 randomised controlled trials). Older age and being a longer time since aphasia onset predicted poorer recovery. A negative relationship between baseline severity score and change from baseline (p

Background Evidencing the impact of speech and language therapy interventions is challenging. The UK’s professional body for speech and language therapists (SLTs) is supporting a consistent approach to outcome measurement and analysis using Therapy Outcome Measures (TOMs).Objective To develop a digital solution for collecting TOMs data, evaluate the impact of therapeutic interventions and explore contributing factors to outcome variation across clinical areas.Method Agile methodology was applied to software development. Organisations were recruited to provide data. Criteria were identified to exemplify outcome variability.Results A digital tool was developed. 21 organisations provided data on 16 356 individuals. Improvement in at least one domain of TOMs occurred in 77.1% of instances. Data for two clinical areas exemplify the tool’s effectiveness in highlighting the impact of speech and language therapy.Conclusion This established outcomes data set can be used to evaluate the impact of speech and language therapy, and explore variation in outcomes.

Table of contents S1 Using computerized adaptive testing Tim Croudace S2 Well-being: what is it, how does it compare to health and what are the implications of using it to inform health policy John Brazier O1 “Am I going to get better?”—Using PROMs to inform patients about the likely benefit of surgery Nils Gutacker, Andrew Street O2 Identifying Patient Reported Outcome Measures for an electronic Personal Health Record Dan Robotham, Samantha Waterman, Diana Rose, Safarina Satkunanathan, Til Wykes O3 Examining the change process over time qualitatively: transformative learning and response shift Nasrin Nasr, Pamela Enderby O4 Developing a PROM to evaluate self-management in diabetes (HASMID): giving patients a voice Jill Carlton, Donna Rowen, Jackie Elliott, John Brazier, Katherine Stevens, Hasan Basarir, Alex Labeit O5 Development of the Primary Care Outcomes Questionnaire (PCOQ) Mairead Murphy, Sandra Hollinghurst, Chris Salisbury O6 Developing the PKEX score- a multimodal assessment tool for patients with shoulder problems Dominic Marley, James Wilson, Amy Barrat, Bibhas Roy O7 Applying multiple imputation to multi-item patient reported outcome measures: advantages and disadvantages of imputing at the item, sub-scale or score level Ines Rombach, Órlaith Burke, Crispin Jenkinson, Alastair Gray, Oliver Rivero-Arias O8 Integrating Patient Reported Outcome Measures (PROMs) into routine primary care for patients with multimorbidity: a feasibility study Ian Porter, Jaheeda Gangannagaripalli, Charlotte Bramwell, Jose M. Valderas O9 eRAPID: electronic self-report and management of adverse-events for pelvic radiotherapy (RT) patients Patricia Holch, Susan Davidson, Jacki Routledge, Ann Henry, Kevin Franks, Alex Gilbert, Kate Absolom & Galina Velikova O10 Patient reported outcomes (PROMs) based recommendation in clinical guidance for the management of chronic conditions in the United Kingdom Ian Porter, Jose M.Valderas O11 Cross-sectional and longitudinal parameter shifts in epidemiological data: measurement invariance and response shifts in cohort and survey data describing the UK’s Quality of Life Jan R. Boehnke O12 Patient-reported outcomes within health technology decision making: current status and implications for future policy Andrew Trigg, Ruth Howells O13 Can social care needs and well-being be explained by the EQ-5D? Analysis of Health Survey for England dataset Jeshika Singh, Subhash Pokhrel, Louise Longworth O14 Where patients and policy meet: exploring individual-level use of the Long-Term Conditions Questionnaire (LTCQ) Caroline Potter, Cheryl Hunter, Laura Kelly, Elizabeth Gibbons, Julian Forder, Angela Coulter, Ray Fitzpatrick, Michele Peters

Background: Most of the studies have looked into the effect of typical antipsychotics on speech secondary to tardive dyskinesia. Aims: This study was aimed to explore the factors predicting the effect of atypical antipsychotic medications on the production of speech. Materials and Methods: One hundred and forty patients on stable regimen of three or more months on risperidone (92), olanzapine (28), aripiprazole (14), and clozapine (6) were recruited for the study. Speech was assessed by maximum phonation duration task, s/z ratio, diadochokinetic task, acoustic analysis and Frenchay Dysarthria Assessment (FDA). Extrapyramidal symptoms (EPS) were assessed by Simpson Angus scale. Statistical Analysis: Spearman correlation analysis was carried out to find the association between speech parameters and continuous variables. Effect of EPS, duration and dose of antipsychotic treatment on speech parameters was compared using Mann-Whitney test. Results: The risperidone group differ from other antipsychotics groups significantly in s/z ratio (0.07), FDA-total (0.23) and FDA-reflex (0.25). People who took antipsychotic for more than 2 years had lower score of FDA-palate (P = 0.042), and FDA-respiratory (P = 0.04) and higher values in noise-harmonic ratio (P = 0.011) and maximum /fundamental frequency (MFF) for males (P = 0.02). Effect of EPS was seen on MFF for males (spearman correlation coefficient = 0.34) and on almost all sections of FDA (spearman correlation coefficients = -0.2 to -0.33). Conclusion: Both duration of use and propensity of atypical antipsychotics to cause EPS can influence the speech performance of the patients. This information can be useful, particularly in people with the requirement of high quality speech.

Background: Despite many years of research, there is no certainty regarding the cause of stuttering. Although numerous interventions have been developed, a broad-based systematic review across all forms of intervention for adults and children was needed including views and perceptions of people who stutter. Objective: The aims of the study were to report the clinical effectiveness of interventions for people who stutter (or clutter), to examine evidence regarding the views of people who stutter and the views of professionals regarding interventions. Data sources: A systematic review of quantitative and qualitative literature was carried out between August 2013 and April 2014. The following electronic databases were searched: (1) MEDLINE, (2) EMBASE, (3) The Cochrane Library (including The Cochrane Database of Systematic Reviews, Cochrane Central Register of Controlled Trials, Database of Abstracts of Reviews of Effects, Health Technology Assessment Database and NHS Economic Evaluations Database), (4) PsycINFO, (5) Science Citation Index, (6) Social Science Citation Index, (7) Cumulative Index to Nursing and Allied Health Literature, (8) ASSIA, (9) Linguistics and Language Behavior Abstracts, (10) Sociological Abstracts and (11) the EPPI Centre. Reference lists of included papers and other reviews were screened and also key journals in the subject area were hand-searched. Review methods: The searches aimed to identify (1) evidence of clinical effectiveness in populations of pre-school children, school-aged children, adolescents and adults, and (2) data relating to perceptions of barriers and facilitators to intervention clinical effectiveness among staff and people who stutter. A metasynthesis of the two linked elements via development of a conceptual model was also carried out to provide further interpretation of the review findings. Results: A systematic search of the literature identified a large number of potentially relevant studies. Of these, 111 studies examining the clinical effectiveness of interventions, 25 qualitative papers and one mixed-methods paper met the criteria for inclusion in this review. Review of the effectiveness literature indicated evidence of positive outcomes across all types of interventions. Virtually all evidence we identified reported at least some positive effect for some participants. However, there was evidence of considerable individual variation in outcome for study participants. The qualitative literature highlighted the need for programmes to be tailored to individual need with variation at the levels of the intervention, the individual and interpersonal/social elements. Metasynthesis of the data highlighted the complexity of elements that need to be considered in evaluation of long-term impacts following stuttering interventions. Limitations: Around two-thirds of the studies were considered to be at higher risk of bias. The heterogeneous nature and variability in outcomes meant that we were unable to complete a meta-analysis. Conclusions: Although much of the evidence we identified was from studies at risk of bias, it is suggested that most available interventions for stuttering may be of benefit to at least some people who stutter. There is a requirement for greater clarity regarding what the core outcomes following stuttering intervention should be and also enhanced understanding of the process whereby interventions effect change. Further analysis of those for whom interventions have not produced a significant benefit may provide additional insights into the complex intervention–outcomes pathway. Study registration: This study is registered as PROSPERO CRD42013004861. Funding: The National Institute for Health Research Health Technology Assessment programme.