Dataset Information

Physical Activity Participation of Disabled Children: A Systematic Review of Conceptual and Methodological Approaches in Health Research.

ABSTRACT: Physical activity (PA) participation is widely recognized as a critical component of health and development for disabled and non-disabled children. Emergent literature reflects a paradigm shift in the conceptualization of childhood PA as a multi-dimensional construct, encompassing aspects of physical performance, and self-perceived engagement. However, ambiguity remains around how participation as a health construct is integrated into PA research. The primary objective of the present mini-review is to critically examine current conceptual and methodological approaches to evaluating PA participation among disabled children. We conducted a systematic review of contemporary literature (published between 2000 and 2016). Seventeen articles met inclusion criteria, and their research approach was classified into guiding framework, definition of the key construct, and measurement used. The primary guiding framework was the international classification of functioning, disability and health. An explicit definition of PA participation was absent from all studies. Eight studies (47%) operationalized PA and participation as independent constructs. Measurements included traditional performance-based aspects of PA (frequency, duration, and intensity), and alternative participation measures (subjective perception of involvement, inclusion, or enjoyment). Approximately 64% of included articles were published in the past 2?years (2014-2016) indicating a rising interest in the topic of PA participation. Drawing from the broader discussion of participation in the literature, we offer a working definition of PA participation as it pertains to active, health-associated behaviors. Further description of alternative approaches to framing and measuring PA participation are offered to support effective assessment of health status among disabled children.

SUBMITTER: Ross SM

PROVIDER: S-EPMC5011128 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

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Physical Activity Participation of Disabled Children: A Systematic Review of Conceptual and Methodological Approaches in Health Research.

Ross Samantha Mae SM Bogart Kathleen R KR Logan Samuel W SW Case Layne L Fine Jeremiah J Thompson Hanna H

Frontiers in public health 20160905

Physical activity (PA) participation is widely recognized as a critical component of health and development for disabled and non-disabled children. Emergent literature reflects a paradigm shift in the conceptualization of childhood PA as a multi-dimensional construct, encompassing aspects of physical performance, and self-perceived engagement. However, ambiguity remains around how participation as a health construct is integrated into PA research. The primary objective of the present mini-review ...[more]

PMID: 27656639

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Project description:BACKGROUND: Wheelchairs for disabled children (? 18 years) can provide health, developmental and social benefits. World Health Organisation and United Kingdom Government reports demonstrate the need for improved access to wheelchairs both locally and internationally. The use of health economics within this field is lacking. Provision of wheelchairs based on cost-effectiveness evidence is not currently possible. We conducted the first systematic review in this field to incorporate evidence of effectiveness, service user perspectives, policy intentions and cost-effectiveness in order to develop a conceptual framework to inform future research and service development. METHODS: We used an adapted EPPI-Centre mixed-method systematic review design with narrative summary, thematic and narrative synthesis. 11 databases were searched. Studies were appraised for quality using one of seven appropriate tools. A conceptual framework was developed from synthesised evidence. RESULTS: 22 studies and 14 policies/guidelines were included. Powered wheelchairs appear to offer benefits in reduced need for caregiver assistance; improved communicative, personal-social and cognitive development; and improved mobility function and independent movement. From 14 months of age children can learn some degree of powered wheelchair driving competence. However, effectiveness evidence was limited and low quality. Children and parents placed emphasis on improving social skill and independence. Participation in wider society and development of meaningful relationships were key desired outcomes. Policy intentions and aspirations are in line with the perspectives of children and parents, although translation of policy recommendations into practice is lacking. CONCLUSIONS: There is a distinct lack of high quality effectiveness and economic evidence in this field. Social and health needs should be seen as equally important when assessing the mobility needs of disabled children. Disabled children and parents placed highest priority on independence and psychosocial outcomes of wheelchair interventions. Translation of policy and guidelines into practice is lacking and more effective implementation strategies are required to improve services and outcomes. Future research should focus on outcome measure development, developing economic evaluation tools and incorporating these into high quality studies to address known research gaps. The novel conceptual framework maps current gaps in evidence and outlines areas for development.

Project description:BackgroundMuch research is being carried out using publicly available Twitter data in the field of public health, but the types of research questions that these data are being used to answer and the extent to which these projects require ethical oversight are not clear.ObjectiveThis review describes the current state of public health research using Twitter data in terms of methods and research questions, geographic focus, and ethical considerations including obtaining informed consent from Twitter handlers.MethodsWe implemented a systematic review, following PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines, of articles published between January 2006 and October 31, 2019, using Twitter data in secondary analyses for public health research, which were found using standardized search criteria on SocINDEX, PsycINFO, and PubMed. Studies were excluded when using Twitter for primary data collection, such as for study recruitment or as part of a dissemination intervention.ResultsWe identified 367 articles that met eligibility criteria. Infectious disease (n=80, 22%) and substance use (n=66, 18%) were the most common topics for these studies, and sentiment mining (n=227, 62%), surveillance (n=224, 61%), and thematic exploration (n=217, 59%) were the most common methodologies employed. Approximately one-third of articles had a global or worldwide geographic focus; another one-third focused on the United States. The majority (n=222, 60%) of articles used a native Twitter application programming interface, and a significant amount of the remainder (n=102, 28%) used a third-party application programming interface. Only one-third (n=119, 32%) of studies sought ethical approval from an institutional review board, while 17% of them (n=62) included identifying information on Twitter users or tweets and 36% of them (n=131) attempted to anonymize identifiers. Most studies (n=272, 79%) included a discussion on the validity of the measures and reliability of coding (70% for interreliability of human coding and 70% for computer algorithm checks), but less attention was paid to the sampling frame, and what underlying population the sample represented.ConclusionsTwitter data may be useful in public health research, given its access to publicly available information. However, studies should exercise greater caution in considering the data sources, accession method, and external validity of the sampling frame. Further, an ethical framework is necessary to help guide future research in this area, especially when individual, identifiable Twitter users and tweets are shared and discussed.Trial registrationPROSPERO CRD42020148170; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=148170.

Project description:The first emergency was to receive and treat COVID-19 patients in their acute phase; today, there is a clear need to propose appropriate post-acute rehabilitation programs. The aim of this research was to systematically review the effects of physical activity programs in the recovery of post-COVID-19 patients. The literature search followed the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) guidelines, was registered in the PROSPERO database (CRD42022289219), and was conducted between August and December 2021. A total of 35 studies out of the 1528 initially identified were finally included in the analysis. The systematic review clearly showed the health benefits of rehabilitation including physical activity in post-COVID-19 recovery, regardless of exercise modalities. These positive results were even observed using minor muscle re-mobilization for severe cases (i.e., postural changes, few steps-2 times/day) or using low volumes of exercise for mild-to-moderate cases (i.e., 120 min/week). A total of 97% of the 29 studies that performed statistical analyses demonstrated a significant increase in at least one parameter of functional capacity, and 96% of the 26 studies that statistically investigated the effects on the quality of life, mental health, and general state reported improvements. Yet, most of the studies were retrospective, uncontrolled, and enrolled aged people with comorbidities presented in severe forms of COVID-19. Physical activity programs, in addition to their high heterogeneity, remained poorly described in 83% of the studies and were part of a multidisciplinary program for 89% of the studies. Despite promising results, there is today a real need for prospective well-designed studies specifically assessing the effects of physical activity. In addition, it might appear relevant to propose standardized programs further considering the main characteristics of patients such as age, comorbidities, or the severity of COVID-19.

Project description:BackgroundArtificial intelligence (AI) is giving rise to a revolution in medicine and health care. Mental health conditions are highly prevalent in many countries, and the COVID-19 pandemic has increased the risk of further erosion of the mental well-being in the population. Therefore, it is relevant to assess the current status of the application of AI toward mental health research to inform about trends, gaps, opportunities, and challenges.ObjectiveThis study aims to perform a systematic overview of AI applications in mental health in terms of methodologies, data, outcomes, performance, and quality.MethodsA systematic search in PubMed, Scopus, IEEE Xplore, and Cochrane databases was conducted to collect records of use cases of AI for mental health disorder studies from January 2016 to November 2021. Records were screened for eligibility if they were a practical implementation of AI in clinical trials involving mental health conditions. Records of AI study cases were evaluated and categorized by the International Classification of Diseases 11th Revision (ICD-11). Data related to trial settings, collection methodology, features, outcomes, and model development and evaluation were extracted following the CHARMS (Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modelling Studies) guideline. Further, evaluation of risk of bias is provided.ResultsA total of 429 nonduplicated records were retrieved from the databases and 129 were included for a full assessment-18 of which were manually added. The distribution of AI applications in mental health was found unbalanced between ICD-11 mental health categories. Predominant categories were Depressive disorders (n=70) and Schizophrenia or other primary psychotic disorders (n=26). Most interventions were based on randomized controlled trials (n=62), followed by prospective cohorts (n=24) among observational studies. AI was typically applied to evaluate quality of treatments (n=44) or stratify patients into subgroups and clusters (n=31). Models usually applied a combination of questionnaires and scales to assess symptom severity using electronic health records (n=49) as well as medical images (n=33). Quality assessment revealed important flaws in the process of AI application and data preprocessing pipelines. One-third of the studies (n=56) did not report any preprocessing or data preparation. One-fifth of the models were developed by comparing several methods (n=35) without assessing their suitability in advance and a small proportion reported external validation (n=21). Only 1 paper reported a second assessment of a previous AI model. Risk of bias and transparent reporting yielded low scores due to a poor reporting of the strategy for adjusting hyperparameters, coefficients, and the explainability of the models. International collaboration was anecdotal (n=17) and data and developed models mostly remained private (n=126).ConclusionsThese significant shortcomings, alongside the lack of information to ensure reproducibility and transparency, are indicative of the challenges that AI in mental health needs to face before contributing to a solid base for knowledge generation and for being a support tool in mental health management.

Dataset Information

Physical Activity Participation of Disabled Children: A Systematic Review of Conceptual and Methodological Approaches in Health Research.

Publications

Physical Activity Participation of Disabled Children: A Systematic Review of Conceptual and Methodological Approaches in Health Research.

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