Aquatic therapy for children with Duchenne muscular dystrophy: a pilot feasibility randomised controlled trial and mixed-methods process evaluation.

BACKGROUND: Duchenne muscular dystrophy (DMD) is a rare disease that causes the progressive loss of motor abilities such as walking. Standard treatment includes physiotherapy. No trial has evaluated whether or not adding aquatic therapy (AT) to land-based therapy (LBT) exercises helps to keep muscles strong and children independent. OBJECTIVES: To assess the feasibility of recruiting boys with DMD to a randomised trial evaluating AT (primary objective) and to collect data from them; to assess how, and how well, the intervention and trial procedures work. DESIGN: Parallel-group, single-blind, randomised pilot trial with nested qualitative research. SETTING: Six paediatric neuromuscular units. PARTICIPANTS: Children with DMD aged 7-16 years, established on corticosteroids, with a North Star Ambulatory Assessment (NSAA) score of 8-34 and able to complete a 10-m walk without aids/assistance. Exclusions: > 20% variation between baseline screens 4 weeks apart and contraindications. INTERVENTIONS: Participants were allocated on a 1 : 1 ratio to (1) optimised, manualised LBT (prescribed by specialist neuromuscular physiotherapists) or (2) the same plus manualised AT (30 minutes, twice weekly for 6 months: active assisted and/or passive stretching regime; simulated or real functional activities; submaximal exercise). Semistructured interviews with participants, parents (n = 8) and professionals (n = 8) were analysed using Framework analysis. An independent rater reviewed patient records to determine the extent to which treatment was optimised. A cost-impact analysis was performed. Quantitative and qualitative data were mixed using a triangulation exercise. MAIN OUTCOME MEASURES: Feasibility of recruiting 40 participants in 6 months, participant and therapist views on the acceptability of the intervention and research protocols, clinical outcomes including NSAA, independent assessment of treatment optimisation and intervention costs. RESULTS: Over 6 months, 348 children were screened - most lived too far from centres or were enrolled in other trials. Twelve (30% of target) were randomised to AT (n = 8) or control (n = 4). People in the AT (n = 8) and control (n = 2: attrition because of parental report) arms contributed outcome data. The mean change in NSAA score at 6 months was -5.5 [standard deviation (SD) 7.8] for LBT and -2.8 (SD 4.1) in the AT arm. One boy suffered pain and fatigue after AT, which resolved the same day. Physiotherapists and parents valued AT and believed that it should be delivered in community settings. The independent rater considered AT optimised for three out of eight children, with other children given programmes that were too extensive and insufficiently focused. The estimated NHS costs of 6-month service were between £1970 and £2734 per patient. LIMITATIONS: The focus on delivery in hospitals limits generalisability. CONCLUSIONS: Neither a full-scale frequentist randomised controlled trial (RCT) recruiting in the UK alone nor a twice-weekly open-ended AT course delivered at tertiary centres is feasible. Further intervention development research is needed to identify how community-based pools can be accessed, and how families can link with each other and community physiotherapists to access tailored AT programmes guided by highly specialised physiotherapists. Bayesian RCTs may be feasible; otherwise, time series designs are recommended. TRIAL REGISTRATION: Current Controlled Trials ISRCTN41002956. FUNDING: This project was funded by the National Institute for Health Research (NIHR) Health Technology Assessment programme and will be published in full in Health Technology Assessment; Vol. 21, No. 27. See the NIHR Journals Library website for further project information

A causal theory of error scores

In modern test theory, response variables are a function of a common latent variable that represents the measured attribute, and error variables that are unique to the response variables. While considerable thought goes into the interpretation of latent variables in these models (e.g., validity research), the interpretation of error variables is typically left implicit (e.g., describing error variables as residuals). Yet, many psychometric assumptions are essentially assumptions about error and thus being able to reason about psychometric models requires the ability to reason about errors. We propose a causal theory of error as a framework that enables researchers to reason about errors in terms of the data-generating mechanism. In this framework, the error variable reflects myriad causes that are specific to an item and, together with the latent variable, determine the scores on that item. We distinguish two types of item-specific causes: characteristic variables that differ between people (e.g., familiarity with words used in the item), and circumstance variables that vary over occasions in which the item is administered (e.g., a distracting noise). We show that different assumptions about these unique causes (a) imply different psychometric models; (b) have different implications for the chance experiment that makes these models probabilistic models; and (c) have different consequences for item bias, local homogeneity, and reliability coefficient α and the test-retest correlation. The ability to reason about the causes that produce error variance puts researchers in a better position to motivate modeling choices

Should I Get That Jab? Exploring Influence to Encourage Vaccination via Online Social Media

This paper explores the suitability of social media networks (SMNs) as a means of influencing the public’s decision-making process regarding vaccinations, specifically a vaccination to protect girls against HPV, a virus associated with cervical cancer. Parents of girls in the target cohort were invited to online discussion forums where they could discuss their opinions on the vaccination. We varied the posts on the forums in different experimental condition, such that they were exposed to promotion of the vaccination in one of four different ways, and coming from one of two different sources, i.e., peers or government health representatives. Following the health belief model (HBM), these messages served as cues to action. After their active participation on the forums, participants filled out a ques-tionnaire with items related to the HBM. Analyses revealed no effect of our experimental manipula-tions of the cue to action. However, using an exploratory novel network analysis approach, we find that the HBM does not adequately account for influence via SMNs. Specifically we show that vaccination decisions are not taken in social isolation, a fact thus far ignored by various forms of the HBM. Implications for studies assessing the use of online channels for health communication are discussed

Encouraging Vaccination Behavior Through Online Social Media

We explore the suitability of online social media (OSM) for influencing the public’s decision-making process regarding a vaccination to protect girls against HPV, a virus associated with cervical cancer. Parents of girls in the target cohort were invited to online discussion forums where they could discuss their opinions on the vaccination. They were exposed to promotion of the vaccination in one of four different ways, and coming from one of two different sources, i.e., peers or government health representatives. Following the health belief model (HBM), these messages served as cues to action. Using a novel network analysis approach, we find that the HBM does not adequately account for influence via OSM. Specifically we show that vaccination decisions are not taken in social isolation, a fact thus far ignored by various forms of the HBM. Implications for studies assessing the use of online channels for health communication are discussed

Comparing network structures on three aspects: A permutation test

The network approach, in which psychological constructs are modeled in terms of interactions between their constituent factors, have rapidly gained popularity in psychology. Applications of such network approaches to various psychological constructs have recently moved from a descriptive stance, in which the goal is to estimate the network structure, to a more comparative stance, in which the goal is to compare network structures across groups. However, the statistical tools to do so are lacking. In this article, we present the network comparison test (NCT). NCT is a statistical test that compares two network structures on three types of characteristics. Performance of NCT is evaluated by means of a simulation study. Simulated data shows that NCT performs well in various circumstances for all three tests: when the groups are simulated to be similar, the error rate (i.e., NCT indicating that they are different, while the simulated networks are similar) is adequately low, and when the groups are simulated to be different, the ability to detect a difference is sufficiently high when the difference between simulated networks and the sample size are substantial. We illustrate NCT by comparing depression symptom networks of males and females. Possible extensions of NCT are discussed.Network approaches to psychometric constructs, in which constructs are modeled in terms of interactions between their constituent factors, have rapidly gained popularity in psychology. Applications of such network approaches to various psychological constructs have recently moved from a descriptive stance, in which the goal is to estimate the network structure that pertains to a construct, to a more comparative stance, in which the goal is to compare network structures across populations. However, the statistical tools to do so are lacking. In this article, we present the network comparison test (NCT), which uses resampling-based permutation testing to compare network structures from two independent, cross-sectional data sets on invariance of (a) network structure, (b) edge (connection) strength, and (c) global strength. Performance of NCT is evaluated in simulations that show NCT to perform well in various circumstances for all three tests: The Type I error rate is close to the nominal significance level, and power proves sufficiently high if sample size and difference between networks are substantial. We illustrate NCT by comparing depression symptom networks of males and females. Possible extensions of NCT are discussed

What is the p

Recent research has suggested that a range of psychological disorders may stem from a single underlying common factor, which has been dubbed the p-factor. This finding may spur a line of research in psychopathology very similar to the history of factor modeling in intelligence and, more recently, personality research, in which similar general factors have been proposed. We point out some of the risks of modeling and interpreting general factors, derived from the fields of intelligence and personality research. We argue that: (a) factor-analytic resolution, i.e., convergence of the literature on a particular factor structure, should not be expected in the presence of multiple highly similar models; and (b) the true underlying model may not be a factor model at all, because alternative explanations can account for the correlational structure of psychopathology