Key considerations in using the BEEP dataset for this thesis

This section discusses the BEEP sample in the context of other samples of older adults with knee pain within the literature. It considers the dataset results in terms of the thesis research questions considering sample size, missing data and

outcome measures as well as the strengths and limitations of using a RCT as a longitudinal cohort for secondary data analyses.

4.5.1 Baseline characteristics in context

Comparing the BEEP trial sample to other samples of older adults with knee pain is helpful in drawing inferences about the generalisability of the findings within later chapters of this thesis. Considering the sociodemographics and clinical

characteristics of the BEEP sample; participants were of similar age, BMI, knee pain severity and disability to other UK RCT samples of older adults with knee pain who consult in primary care (Hay et al, 2006; Foster et al, 2007) which allows confidence in generalising the sample to similar trial populations. However, BEEP trial participants had more severe knee pain and functional problems than general community samples of older adults with knee pain who may or may not be

consulting a healthcare professional (O’Reilly et al, 1999; Jinks et al, 2002;

Thomas et al, 2002; Peat et al, 2006b; Holden et al 2014). This finding is expected considering most of the BEEP trial sample came from health care consulters who often haver higher levels of pain and disability than the general community population with knee pain (Bedson et al, 2007). One difference from comparable UK samples was the roughly equal proportion of males and females within the BEEP trial sample, as many other research studies of knee pain in older adults include a higher proportion of female participants (Hay et al, 2006; Foster et al, 2007; Holden et al, 2015). Furthermore, previous research suggests that

136

participants with certain sociodemographic characteristics such as the oldest adults may be underrepresented generally within trials (Bartlett et al, 2005).

Comparing to existing surveys of older adults with knee pain in the community, who themselves may underrepresent the most elderly (Peat et al, 2006b, Holden et al, 2015), confirms this since only 5% of the BEEP trial sample were 80 years or older (compared to 6% and 10% in the referenced comparison studies).

Interpreting and comparing baseline physical activity level as measured by the PASE within the BEEP trial dataset is not straightforward as the scale does not equate simply to either minutes spent in different intensities of activity or

benchmarks of physical activity required to meet physical activity guidelines (Washburn et al, 1993). To the author’s knowledge, there are no previous UK RCTs including samples comprised exclusively of older adults with knee pain who completed the PASE. However, it is possible to compare the PASE scores to other similar international populations of older adults with knee pain who used the measure. The BEEP trial sample had roughly comparable PASE scores to similar samples from the US (Sharma et al, 2003; Neogi et al, 2010; Dunlop et al, 2011;

Bindawas & Vennu, 2015) and a cohort of Australian male older adults with knee pain (Fransen et al, 2014). This suggests the physical activity levels within the BEEP trial sample are roughly generalizable to other populations of older adults with knee pain. These samples had mean PASE scores ranging from 120 to 182.

Two comparison samples with slightly lower PASE scores either had higher BMI (Bindawas & Vennu, 2015) or older mean age (Fransen et al, 2014) which may account for this (Stubbs et al, 2015).

Comparing the attitude and belief about physical activity scales (SEE and OEE) to other populations of older adults with knee pain is challenging due to the dearth of

137

available literature. Self-efficacy for exercise at baseline within the BEEP trial sample (mean score 5.4) was slightly lower than a comparable US sample of older adults with knee pain (mean score 6.3) from a lifestyle physical activity RCT

(Sperber et al, 2014). Outcome expectations for exercise has not, to the authors knowledge, been measured in older adults with knee pain using the OEE scale (Resnick, 2005), however, the BEEP trial findings were comparable to an older US population without knee pain (Resnick, 2005) and other populations of older adults with arthritis generally report similar positive health outcome expectations with regular physical activity (Hutton et al, 2010). In conclusion, the clinical outcomes, physical activity measure and attitude and beliefs about physical activity data from the BEEP trial are roughly comparable to similar populations of older adults with knee pain.

4.5.2 Considerations for future thesis research questions

To be suitable for answering the research questions in this thesis, the dataset needed to be sufficiently large, without high loss to follow-up and demonstrate a sufficient change in mean physical activity level over time. Considering these in turn, the dataset of 514 appears sufficiently large for multivariable model building (Szklo & Nieto, 2014) and this was also further investigated with post-hoc power analyses following model building within Parts 2, 3 and 4 of the thesis. Missing data levels were generally very low at baseline, allowing complete-case analysis to be considered appropriate for thesis Part 3 (and the assumption to be made that the associations of interest between attitudes and beliefs about physical activity and physical activity level in the complete cases is likely to be very similar to that of the whole sample). Missing data over time at three and six months appears acceptable for the majority of salient variables (less than 20%) although the level

138

of missingness in the physical activity level data at three months was of more concern at 30%. Missing data at three and six month follow-ups for longitudinal data analyses were hence managed with multiple imputation. Although multiple imputation preserves sample size, risk of bias due to missing data leading to selection bias remains higher for the longitudinal data analyses especially if any of the data were not missing at random (Sterne et al, 2009). This is a limitation and particular threat to the internal validity of Part 4 of the thesis when physical activity at three and six months is the outcome variable of interest.

In addition, the analyses used to address the research questions investigating the associations between change in physical activity level and future clinical outcome (thesis Part 2) require sufficient change in PASE over time. There was modest mean change in physical activity level between baseline and three months (absolute change 15.1) but not between three months and six months (absolute change -1.6). Hence the analysis included the change in PASE measured

between baseline and three months. It was originally planned to model change in physical activity level and change in pain between three and six months in order to reduce the effects of regression to the mean immediately following trial inclusion from the analyses (this phenomenon is discussed in section 4.5.3 below).

However, in the absence of meaningful change in physical activity level in this later time period this was not possible (chapter 6 describes the selected analyses in further detail).

The BEEP trial dataset captures important variables for research questions within this thesis, however, despite the PASE, SEE and OEE being validated in older adults and the rationale previously stated for using them in an older adults with knee pain sample (see section 4.3.3), some uncertainty remains regarding

139

whether these measures have adequate content validity and are sufficiently responsive in such a sample. These points are discussed further in future chapters in relation to specific thesis analyses.

4.5.3 Using a trial as a longitudinal cohort for secondary analyses

The benefits of using the BEEP trial as a longitudinal cohort for secondary data analyses within this thesis were that the sample size was sufficiently large to consider multivariable analyses; data were readily available and included relevant variables to address the thesis research questions. Study attrition was relatively low in most variables and the sample relatively homogeneous (in terms of knee pain attributed to OA) due to the inclusion and exclusion criteria. Although it had higher levels of pain and worse function than community samples of older adults with knee pain, it was roughly similar in terms of physical activity level and attitudes and beliefs about physical activity to other samples of older adults with knee pain which allows some wider generalisability of the findings relating to these variables.

The limitations of using a trial as a longitudinal cohort are also noteworthy. The methodological design of RCTs that usually allow causation to be inferred (see chapter 3, section 3.3.2 for a full explanation) are no longer applicable when the trial data are utilised as a single longitudinal cohort. Any relationships between attitudes, beliefs, physical activity and clinical outcomes may be confounded by treatment effects or other variables. As a result statistical adjustment is required to manage confounding when interpreting associations between variables of interest to the thesis questions (Szklo & Nieto, 2014). Furthermore, since the trial was already underway with all participants recruited and in follow-up stages at the time of writing this thesis, there was no option for investigating additional attitudes

140

and beliefs about physical activity or physical activity level measures. One of the major concerns in the use of trial data as a longitudinal cohort is the risk of

regression to the mean. This statistical phenomenon occurs when unusually large or small measurements tend to be followed by measurements that are closer to the mean (Davis, 1976; Barnett et al, 2005). In the case of older adults with knee pain entering the BEEP trial, it is likely that participants consult healthcare

professionals (in two of the three methods of identification of BEEP trial

participants) and enter the trial when their symptoms are relatively severe. This may mean that their symptoms are likely to improve in the following months due to the natural fluctuation of knee pain (Neogi, 2013). Whilst this effect would tend to be evenly spread amongst intervention arms and hence not alter treatment effect size in the original trial analysis, it is more of a threat to the internal validity of the secondary data analyses within this thesis as it may impact on secondary

associations between physical activity level and clinical measures over time.

4.6 Chapter summary

This chapter summarised the BEEP trial and the key clinical, physical activity level, and attitudes and beliefs about physical activity variables from 514 older adults with knee pain within the dataset that is used in Parts 2, 3 and 4 of this thesis.

Longitudinal data at baseline, three and six month follow-ups were described.

Increases in mean self-reported physical activity level and improvements in pain and function were shown between baseline and three months, whilst attitudes and beliefs about physical activity remained relatively static over time. The next

chapter describes a second dataset of older adults with knee pain from a cross-sectional community survey that is also used for secondary data analysis within this thesis.

141

Chapter 5

The Attitudes and Behaviours Concerning Knee