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The purpose of the present programme was to develop and validate a theoretically-grounded instrument to measure the planned and unplanned dimensions of lifestyle PA (PPA and UPA; Dunn, Andersen, & Jakicic, 1998). In Study 1, two samples of British adults (Internet: N = 742; paper: N = 563) were used to establish the content validity of the Brunel Lifestyle Physical Activity Questionnaire (BLPAQ). Exploratory factor analysis yielded a two-factor model (UPA and PPA) that produced acceptable fit indices using confirmatory factors analyses with both samples. The purpose of Study 2 was to examine the test-retest reliability of the BLPAQ over 5 weeks using a sample of leisure centre users, university staff members, and university students (N = 337). High correlations were observed between the two administrations (range = .93-.98; p < .01). Thereafter, the data were subjected to proportion of agreement (PoA) analysis as advocated by Nevill, Lane, Kilgor, Bowes, and Whyte (2001). Both PPA and UPA demonstrated satisfactorily high internal agreement (PoA > 95%). In Study 3, the BLPAQ was cross-validated using two criterion measures: the Baecke Questionnaire of Habitual Physical Activity (Baecke, Burema, & Frijters, 1982) and the Godin’s Leisure-Time Exercise Questionnaire (Godin & Shephard, 1985). Multiple linear regressions were performed to predict PPA and UPA from the subscales of the two reference measures. The predictive models differed markedly in terms of gender. Subsequently, the sample of 338 British adults was divided into two subsamples, and these were subjected to a cross-validation using the Limits of Agreement (LoA) methodology advocated by Bland and Altman (1986). The agreement plots revealed that both BLPAQ subscales demonstrated acceptable inter-sample agreement when compared to the criterion measures. In Study 4, a series of structural equation models were tested with the aim of predicting PPA and UPA using the variables that constitute the Theory of Planned Behaviour (TPB). The TPB was able to predict PPA but not UPA. The addition of a direct path between past behaviour to UPA did not result in a significant prediction. Further work is required to examine the factorial structure of the PPA subscale and to increase the number of items in the UPA subscale. In sum, the programme has contributed a valid and reliable theory-based measure of PA as well as evidence to support the utility of the TPB in PA research. However, the TPB framework may require the addition of predictors such as past behaviour and actual behavioural control.

In people with stroke, spinal cord injury, multiple sclerosis, and other upper motorneuron lesions, ankle clonus and quadriceps spasms may limit self-care and mobility tasks. The ankle clonus drop test, which measures the plantar flexor reflex threshold angle (PFRTA), and the pendulum test, which measures the quadriceps reflex threshold angle (QRTA), provide valid and reproducible measurements of ankle clonus and quadriceps hyperreflexia. However, measuring the PFRTA and QRTA requires high fidelity motion capture systems that are limited to laboratory settings by cost and complexity. The aim of this study was to evaluate a simple, single-camera based method of measuring ankle clonus and quadriceps spasticity in clinical settings. With synchronous 3-D inertial motion capture to provide a high fidelity reference, we used a smartphone camera and green stickers to measure the PFRTA and QRTA of 14 individuals with ankle clonus or quadriceps hyperreflexia in one or both legs. This resulted in test sessions on 22 impaired legs with four repetitions of each test on each leg conducted by a student physical therapist and an experienced physical therapist. We hypothesized that the smartphone camera measurements would provide clinically useful outcome measures for assessing ankle clonus and quadriceps spasticity. To assess accuracy of the camera-measurements, we computed the bias and limits of agreement between the camera and the inertial motion capture measurements. For reliability, we computed intra-rater and inter-sensor reliability coefficients in addition to the minimum detectable change. The smartphone PFRTA biases were smaller than 0.2° and the QRTA biases smaller than 1.2°. The limits of agreement for the PFRTA were ±4.66°/ ±7.49° (student/expert), and for the QRTA were ±4.40°/±4.67°. Reliability was similar between the camera and inertial measurements of tests by both rater types: intra-rater reliability ranged from 0.85-0.90 for the PFRTA and ranged from 0.96-0.98 for the QRTA. The inter-sensor reliability when measuring the PFRTA and QRTA was 0.97 and 0.99. The minimum detectable change for the PFRTA ranged from 7.10°-8.70°, while for the QRTA ranged from 7.65°-8.27°. Based on prior research, the limits of agreement and minimum detectable change were sufficiently low for purposes of interindividual, repeatable measurement. These data show that student and experienced physical therapists using ubiquitous existing hardware such as a smartphone can produce accurate, reliable assessments of ankle clonus and quadriceps hyperreflexia in a clinical environment.

We consider three problems that arise in studies comparing two or more methods that measure a continuous variable of interest. First is the basic problem of how to assess the degree of agreement between two methods (or instruments). If there is sufficient agreement between them, one can use them interchangeably or prefer the one that is cheaper or is easier to use. We employ tests of hypotheses to assess if the data have evidence for satisfactory agreement. In particular, we consider three formulations of satisfactory agreement and provide tests for the associated hypotheses. The formulations are: (i) both the mean and the standard deviation of the difference of measurements from the two instruments are close to zero; (ii) the means of the two measurements are close, their standard deviations are close, and their correlation is high; and (iii) a large proportion of the difference lies in an interval close to zero. In all the cases, the thresholds determining closeness are supplied by the investigator. The first two formulations give additional information regarding the nature and extent of disagreement when the data do not have evidence for satisfactory agreement. For the last formulation, we discuss both the parametric and nonparametric tests. Comparison of two instruments with a gold standard is the focus of the other two problems. We first consider how to select the instrument that agrees most with a gold standard in terms of mean squared deviation. This instrument is designated as the best one. For this selection problem, we present two large sample single-stage procedures and a two-stage procedure using the multiple comparisons with the best approach. Questions like which parameterization works well for the comparison and what sample sizes are adequate are answered using asymptotic theory and simulation. For the last problem, we determine, through a hypotheses test, whether the best instrument agrees sufficiently well with the gold standard before proceeding to its selection. We describe a two-stage procedure for this purpose and study its properties using the asymptotic distribution of the test statistic and simulation.