Understanding and validating accelerometry as a measure of physical activity in children with intellectual disabilities

Background Physical activity in children with intellectual disabilities is a neglected area of study, which is most apparent in relation to physical activity measurement research. Although objective measures, specifically accelerometers, are widely used in research involving children with intellectual disabilities, existing research is based on measurement methods and data interpretation techniques generalised from typically developing children. However, due to physiological and biomechanical differences between these populations, questions have been raised in the existing literature on the validity of generalising data interpretation techniques from typically developing children to children with intellectual disabilities. Therefore, there is a need to conduct population-specific measurement research for children with intellectual disabilities and develop valid methods to interpret accelerometer data, which will increase our understanding of physical activity in this population. Methods Study 1: A systematic review was initially conducted to increase the knowledge base on how accelerometers were used within existing physical activity research involving children with intellectual disabilities and to identify important areas for future research. A systematic search strategy was used to identify relevant articles which used accelerometry-based monitors to quantify activity levels in ambulatory children with intellectual disabilities. Based on best practice guidelines, a novel form was developed to extract data based on 17 research components of accelerometer use. Accelerometer use in relation to best practice guidelines was calculated using percentage scores on a study-by-study and component-by-component basis. Study 2: To investigate the effect of data interpretation methods on the estimation of physical activity intensity in children with intellectual disabilities, a secondary data analysis was conducted. Nine existing sets of child-specific ActiGraph intensity cut points were applied to accelerometer data collected from 10 children with intellectual disabilities during an activity session. Four one-way repeated measures ANOVAs were used to examine differences in estimated time spent in sedentary, moderate, vigorous, and moderate to vigorous intensity activity. Post-hoc pairwise comparisons with Bonferroni adjustments were additionally used to identify where significant differences occurred. Study 3: The feasibility on a laboratory-based calibration protocol developed for typically developing children was investigated in children with intellectual disabilities. Specifically, the feasibility of activities, measurements, and recruitment was investigated. Five children with intellectual disabilities and five typically developing children participated in 14 treadmill-based and free-living activities. In addition, resting energy expenditure was measured and a treadmill-based graded exercise test was used to assess cardiorespiratory fitness. Breath-by-breath respiratory gas exchange and accelerometry were continually measured during all activities. Feasibility was assessed using observations, activity completion rates, and respiratory data. Study 4: Thirty-six children with intellectual disabilities participated in a semi-structured school-based physical activity session to calibrate accelerometry for the estimation of physical activity intensity. Participants wore a hip-mounted ActiGraph wGT3X+ accelerometer, with direct observation (SOFIT) used as the criterion measure. Receiver operating characteristic curve analyses were conducted to determine the optimal accelerometer cut points for sedentary, moderate, and vigorous intensity physical activity. Study 5: To cross-validate the calibrated cut points and compare classification accuracy with existing cut points developed in typically developing children, a sub-sample of 14 children with intellectual disabilities who participated in the school-based sessions, as described in Study 4, were included in this study. To examine the validity, classification agreement was investigated between the criterion measure of SOFIT and each set of cut points using sensitivity, specificity, total agreement, and Cohen’s kappa scores. Results Study 1: Ten full text articles were included in this review. The percentage of review criteria met ranged from 12%−47%. Various methods of accelerometer use were reported, with most use decisions not based on population-specific research. A lack of measurement research, specifically the calibration/validation of accelerometers for children with intellectual disabilities, is limiting the ability of researchers to make appropriate and valid accelerometer use decisions. Study 2: The choice of cut points had significant and clinically meaningful effects on the estimation of physical activity intensity and sedentary behaviour. For the 71-minute session, estimations for time spent in each intensity between cut points ranged from: sedentary = 9.50 (± 4.97) to 31.90 (± 6.77) minutes; moderate = 8.10 (± 4.07) to 40.40 (± 5.74) minutes; vigorous = 0.00 (± .00) to 17.40 (± 6.54) minutes; and moderate to vigorous = 8.80 (± 4.64) to 46.50 (± 6.02) minutes. Study 3: All typically developing participants and one participant with intellectual disabilities completed the protocol. No participant met the maximal criteria for the graded exercise test or attained a steady state during the resting measurements. Limitations were identified with the usability of respiratory gas exchange equipment and the validity of measurements. The school-based recruitment strategy was not effective, with a participation rate of 6%. Therefore, a laboratory-based calibration protocol was not feasible for children with intellectual disabilities. Study 4: The optimal vertical axis cut points (cpm) were ≤ 507 (sedentary), 1008−2300 (moderate), and ≥ 2301 (vigorous). Sensitivity scores ranged from 81−88%, specificity 81−85%, and AUC .87−.94. The optimal vector magnitude cut points (cpm) were ≤ 1863 (sedentary), ≥ 2610 (moderate) and ≥ 4215 (vigorous). Sensitivity scores ranged from 80−86%, specificity 77−82%, and AUC .86−.92. Therefore, the vertical axis cut points provide a higher level of accuracy in comparison to the vector magnitude cut points. Study 5: Substantial to excellent classification agreement was found for the calibrated cut points. The calibrated sedentary cut point (ĸ =.66) provided comparable classification agreement with existing cut points (ĸ =.55−.67). However, the existing moderate and vigorous cut points demonstrated low sensitivity (0.33−33.33% and 1.33−53.00%, respectively) and disproportionately high specificity (75.44−.98.12% and 94.61−100.00%, respectively), indicating that cut points developed in typically developing children are too high to accurately classify physical activity intensity in children with intellectual disabilities. Conclusions The studies reported in this thesis are the first to calibrate and validate accelerometry for the estimation of physical activity intensity in children with intellectual disabilities. In comparison with typically developing children, children with intellectual disabilities require lower cut points for the classification of moderate and vigorous intensity activity. Therefore, generalising existing cut points to children with intellectual disabilities will underestimate physical activity and introduce systematic measurement error, which could be a contributing factor to the low levels of physical activity reported for children with intellectual disabilities in previous research.

An examination of verbal descriptors of cancer-induced bone pain and neuropathic cancer pain

Aims: The aim of the thesis was to identify verbal descriptors of cancer induced bone pain (CIBP) and neuropathic cancer pain (NCP). An examination of the verbal descriptors associated with these two pain syndromes further considered the relationship between common verbal descriptors, cancer type, performance status and analgesia. Methods: The project was conducted in two phases; Phase one was a systematic review of the literature to examine current evidence of verbal descriptors in CIBP and NCP. Phase two utilised secondary data analysis methodology. Data from 120 patients with confirmed CIBP and 61 patients with confirmed NCP were deemed eligible for entry into a de novo database for secondary analysis. Key descriptive data were considered such as gender, ECOG and pain scores to characterise the patient population. Verbal descriptors of CIBP and NCP were considered in detail across the secondary de novo database. Results: Gender was not identified as a diagnostic characteristic of CIBP and NCP with similar distribution across prevalence of pain reporting and also pain severity. Patients with breast (n=52,43.3%), prostate (n=35,29.2%) and lung (n=14,11.7%) cancer were found to be at an increased risk of CIBP. Those with NCP more was found more commonly among patients with breast cancer (n=21,34.4%). Patients with CIBP were found to have an ECOG performance of 1 (n=49, 40.8%) or 2 (n=43, 35.8%) which was lower than those with NCP with an ECOG of 0 (n=32, 52.5%) or 2 (n=18, 29.5%). Comparisons were made across analgesia and treatment options for CIBP and NCP. Patients with CIBP received a greater variety of treatment options including bisphosphonates and radiotherapy while patients with NCP were more commonly treated with analgesia alone. Patients with CIBP and NCP were taking strong opioids, however those with NCP (n=45, 73.8%) were more likely to utilise strong opioids than those with CIBP (n=61, 50.8%). It was noted that those with NCP required a daily morphine equivalence of almost 50% higher than those with CIBP. Average consumption of opioids was 155.6mg, for patients with NCP, compared to 76mg in patients with CIBP. Common verbal descriptors of CIBP and NCP were identified. The most common verbal descriptors for CIBP were aching, gnawing and throbbing and the most common verbal descriptors of NCP were aching, tender and sharp. Of the most common 6 descriptors for CIBP and NCP only one descriptor was unique to each pain type, gnawing for CIBP and stabbing for NCP. Conclusions: Patients with CIBP and NCP use similar verbal descriptors to characterise their pain with gnawing being unique to CIBP and stabbing being unique to NCP in the data considered within project. Further research is required to explore verbal descriptors which are both common and unique to CIBP and NCP. Further exploration of verbal descriptors would assist development of a comprehensive pain assessment tool which would enhance pain assessment for nurses, clinicians and patients.

Identifying health inequalities in individuals with major mental illness (MMI) using routine data

Abstract and Summary of Thesis: Background: Individuals with Major Mental Illness (such as schizophrenia and bipolar disorder) experience increased rates of physical health comorbidity compared to the general population. They also experience inequalities in access to certain aspects of healthcare. This ultimately leads to premature mortality. Studies detailing patterns of physical health comorbidity are limited by their definitions of comorbidity, single disease approach to comorbidity and by the study of heterogeneous groups. To date the investigation of possible sources of healthcare inequalities experienced by individuals with Major Mental Illness (MMI) is relatively limited. Moreover studies detailing the extent of premature mortality experienced by individuals with MMI vary both in terms of the measure of premature mortality reported and age of the cohort investigated, limiting their generalisability to the wider population. Therefore local and national data can be used to describe patterns of physical health comorbidity, investigate possible reasons for health inequalities and describe mortality rates. These findings will extend existing work in this area. Aims and Objectives: To review the relevant literature regarding: patterns of physical health comorbidity, evidence for inequalities in physical healthcare and evidence for premature mortality for individuals with MMI. To examine the rates of physical health comorbidity in a large primary care database and to assess for evidence for inequalities in access to healthcare using both routine primary care prescribing data and incentivised national Quality and Outcome Framework (QOF) data. Finally to examine the rates of premature mortality in a local context with a particular focus on cause of death across the lifespan and effect of International Classification of Disease Version 10 (ICD 10) diagnosis and socioeconomic status on rates and cause of death. Methods: A narrative review of the literature surrounding patterns of physical health comorbidity, the evidence for inequalities in physical healthcare and premature mortality in MMI was undertaken. Rates of physical health comorbidity and multimorbidity in schizophrenia and bipolar disorder were examined using a large primary care dataset (Scottish Programme for Improving Clinical Effectiveness in Primary Care (SPICE)). Possible inequalities in access to healthcare were investigated by comparing patterns of prescribing in individuals with MMI and comorbid physical health conditions with prescribing rates in individuals with physical health conditions without MMI using SPICE data. Potential inequalities in access to health promotion advice (in the form of smoking cessation) and prescribing of Nicotine Replacement Therapy (NRT) were also investigated using SPICE data. Possible inequalities in access to incentivised primary healthcare were investigated using National Quality and Outcome Framework (QOF) data. Finally a pre-existing case register (Glasgow Psychosis Clinical Information System (PsyCIS)) was linked to Scottish Mortality data (available from the Scottish Government Website) to investigate rates and primary cause of death in individuals with MMI. Rate and primary cause of death were compared to the local population and impact of age, socioeconomic status and ICD 10 diagnosis (schizophrenia vs. bipolar disorder) were investigated. Results: Analysis of the SPICE data found that sixteen out of the thirty two common physical comorbidities assessed, occurred significantly more frequently in individuals with schizophrenia. In individuals with bipolar disorder fourteen occurred more frequently. The most prevalent chronic physical health conditions in individuals with schizophrenia and bipolar disorder were: viral hepatitis (Odds Ratios (OR) 3.99 95% Confidence Interval (CI) 2.82-5.64 and OR 5.90 95% CI 3.16-11.03 respectively), constipation (OR 3.24 95% CI 3.01-3.49 and OR 2.84 95% CI 2.47-3.26 respectively) and Parkinson’s disease (OR 3.07 95% CI 2.43-3.89 and OR 2.52 95% CI 1.60-3.97 respectively). Both groups had significantly increased rates of multimorbidity compared to controls: in the schizophrenia group OR for two comorbidities was 1.37 95% CI 1.29-1.45 and in the bipolar disorder group OR was 1.34 95% CI 1.20-1.49. In the studies investigating inequalities in access to healthcare there was evidence of: under-recording of cardiovascular-related conditions for example in individuals with schizophrenia: OR for Atrial Fibrillation (AF) was 0.62 95% CI 0.52 - 0.73, for hypertension 0.71 95% CI 0.67 - 0.76, for Coronary Heart Disease (CHD) 0.76 95% CI 0.69 - 0.83 and for peripheral vascular disease (PVD) 0.83 95% CI 0.72 - 0.97. Similarly in individuals with bipolar disorder OR for AF was 0.56 95% CI 0.41-0.78, for hypertension 0.69 95% CI 0.62 - 0.77 and for CHD 0.77 95% CI 0.66 - 0.91. There was also evidence of less intensive prescribing for individuals with schizophrenia and bipolar disorder who had comorbid hypertension and CHD compared to individuals with hypertension and CHD who did not have schizophrenia or bipolar disorder. Rate of prescribing of statins for individuals with schizophrenia and CHD occurred significantly less frequently than in individuals with CHD without MMI (OR 0.67 95% CI 0.56-0.80). Rates of prescribing of 2 or more anti-hypertensives were lower in individuals with CHD and schizophrenia and CHD and bipolar disorder compared to individuals with CHD without MMI (OR 0.66 95% CI 0.56-0.78 and OR 0.55 95% CI 0.46-0.67, respectively). Smoking was more common in individuals with MMI compared to individuals without MMI (OR 2.53 95% CI 2.44-2.63) and was particularly increased in men (OR 2.83 95% CI 2.68-2.98). Rates of ex-smoking and non-smoking were lower in individuals with MMI (OR 0.79 95% CI 0.75-0.83 and OR 0.50 95% CI 0.48-0.52 respectively). However recorded rates of smoking cessation advice in smokers with MMI were significantly lower than the recorded rates of smoking cessation advice in smokers with diabetes (88.7% vs. 98.0%, p<0.001), smokers with CHD (88.9% vs. 98.7%, p<0.001) and smokers with hypertension (88.3% vs. 98.5%, p<0.001) without MMI. The odds ratio of NRT prescription was also significantly lower in smokers with MMI without diabetes compared to smokers with diabetes without MMI (OR 0.75 95% CI 0.69-0.81). Similar findings were found for smokers with MMI without CHD compared to smokers with CHD without MMI (OR 0.34 95% CI 0.31-0.38) and smokers with MMI without hypertension compared to smokers with hypertension without MMI (OR 0.71 95% CI 0.66-0.76). At a national level, payment and population achievement rates for the recording of body mass index (BMI) in MMI was significantly lower than the payment and population achievement rates for BMI recording in diabetes throughout the whole of the UK combined: payment rate 92.7% (Inter Quartile Range (IQR) 89.3-95.8 vs. 95.5% IQR 93.3-97.2, p<0.001 and population achievement rate 84.0% IQR 76.3-90.0 vs. 92.5% IQR 89.7-94.9, p<0.001 and for each country individually: for example in Scotland payment rate was 94.0% IQR 91.4-97.2 vs. 96.3% IQR 94.3-97.8, p<0.001. Exception rate was significantly higher for the recording of BMI in MMI than the exception rate for BMI recording in diabetes for the UK combined: 7.4% IQR 3.3-15.9 vs. 2.3% IQR 0.9-4.7, p<0.001 and for each country individually. For example in Scotland exception rate in MMI was 11.8% IQR 5.4-19.3 compared to 3.5% IQR 1.9-6.1 in diabetes. Similar findings were found for Blood Pressure (BP) recording: across the whole of the UK payment and population achievement rates for BP recording in MMI were also significantly reduced compared to payment and population achievement rates for the recording of BP in chronic kidney disease (CKD): payment rate: 94.1% IQR 90.9-97.1 vs.97.8% IQR 96.3-98.9 and p<0.001 and population achievement rate 87.0% IQR 81.3-91.7 vs. 97.1% IQR 95.5-98.4, p<0.001. Exception rates again were significantly higher for the recording of BP in MMI compared to CKD (6.4% IQR 3.0-13.1 vs. 0.3% IQR 0.0-1.0, p<0.001). There was also evidence of differences in rates of recording of BMI and BP in MMI across the UK. BMI and BP recording in MMI were significantly lower in Scotland compared to England (BMI:-1.5% 99% CI -2.7 to -0.3%, p<0.001 and BP: -1.8% 99% CI -2.7 to -0.9%, p<0.001). While rates of BMI and BP recording in diabetes and CKD were similar in Scotland compared to England (BMI: -0.5 99% CI -1.0 to 0.05, p=0.004 and BP: 0.02 99% CI -0.2 to 0.3, p=0.797). Data from the PsyCIS cohort showed an increase in Standardised Mortality Ratios (SMR) across the lifespan for individuals with MMI compared to the local Glasgow and wider Scottish populations (Glasgow SMR 1.8 95% CI 1.6-2.0 and Scotland SMR 2.7 95% CI 2.4-3.1). Increasing socioeconomic deprivation was associated with an increased overall rate of death in MMI (350.3 deaths/10,000 population/5 years in the least deprived quintile compared to 794.6 deaths/10,000 population/5 years in the most deprived quintile). No significant difference in rate of death for individuals with schizophrenia compared with bipolar disorder was reported (6.3% vs. 4.9%, p=0.086), but primary cause of death varied: with higher rates of suicide in individuals with bipolar disorder (22.4% vs. 11.7%, p=0.04). Discussion: Local and national datasets can be used for epidemiological study to inform local practice and complement existing national and international studies. While the strengths of this thesis include the large data sets used and therefore their likely representativeness to the wider population, some limitations largely associated with using secondary data sources are acknowledged. While this thesis has confirmed evidence of increased physical health comorbidity and multimorbidity in individuals with MMI, it is likely that these findings represent a significant under reporting and likely under recognition of physical health comorbidity in this population. This is likely due to a combination of patient, health professional and healthcare system factors and requires further investigation. Moreover, evidence of inequality in access to healthcare in terms of: physical health promotion (namely smoking cessation advice), recording of physical health indices (BMI and BP), prescribing of medications for the treatment of physical illness and prescribing of NRT has been found at a national level. While significant premature mortality in individuals with MMI within a Scottish setting has been confirmed, more work is required to further detail and investigate the impact of socioeconomic deprivation on cause and rate of death in this population. It is clear that further education and training is required for all healthcare staff to improve the recognition, diagnosis and treatment of physical health problems in this population with the aim of addressing the significant premature mortality that is seen. Conclusions: Future work lies in the challenge of designing strategies to reduce health inequalities and narrow the gap in premature mortality reported in individuals with MMI. Models of care that allow a much more integrated approach to diagnosing, monitoring and treating both the physical and mental health of individuals with MMI, particularly in areas of social and economic deprivation may be helpful. Strategies to engage this “hard to reach” population also need to be developed. While greater integration of psychiatric services with primary care and with specialist medical services is clearly vital the evidence on how best to achieve this is limited. While the National Health Service (NHS) is currently undergoing major reform, attention needs to be paid to designing better ways to improve the current disconnect between primary and secondary care. This should then help to improve physical, psychological and social outcomes for individuals with MMI.