Abstract

Objectives This study identified disability sub-groups of patients with chronic low back pain (LBP) using the Subgroup for Targeted Treatment (or STarT) Back Screening Tool (SBST) and Simmonds Physical Performance Tests Battery (SPPTB). In addition, the study investigated the divergent validity of SBST, and compared the predictive validity of SBST and SPPTB among the patients with the aim to enhance quick and accurate prediction of disability risks among patients with chronic LBP. Methods This exploratory cross-sectional study involved 70 (52.0% female and 47.1% male) consenting patients with chronic non-specific LBP attending out-patient physiotherapy and Orthopedic Clinics at the Obafemi Awolowo University Teaching Hospitals, Ile-Ife and Ladoke Akintola University of Technology Teaching Hospital, Osogbo, Nigeria. Disability risk subgrouping and prediction were carried out using the SBST and SPPTB (comprising six functional tasks of repeated trunk flexion, sit-to-stand, 360-degree rollover, Sorenson fatigue test, unloaded reach test, and 50 foot walk test). Pain intensity was assessed using the Quadruple Visual Analogue Scale. Data on age, sex, height, weight and BMI were also collected. Descriptive and inferential statistics were used to analyze data at p<0.05 Alpha level. Results The mean age, weight, height and body mass index of the participants were 51.4 ±8.78 years, 1.61 ±0.76 m and 26.6 ±3.18 kg/m2 respectively. The mean pain intensity and duration were 5.37 ±1.37 and 21.2 ±6.68 respectively. The divergent validity of SBST with percentage overall pain intensity was r = 0.732; p = 0.001. Under SBST sub-grouping the majority of participants were rated as having medium disability risk (76%), whilst SPPTB sub-grouped the majority as having high disability risk (71.4%). There was a significant difference in disability risk subgrouping between SBST and SPPTB (χ²=12.334; p=0.015). SBST had no floor and ceiling effects, as less than 15% of the participants reached the lowest (2.9%) or highest (1.4%) possible score. Conversely, SPPBT showed both floor and ceiling effects, as it was unable to detect ‘1’ and ‘9’, the lowest and highest obtainable scores. The ‘Area Under Curve’ for sensitivity (0.83) and specificity (0.23) of the SBST to predict ‘high-disability risk’ was 0.51. The estimated prevalence for ‘high-disability risk’ prediction of SBST was 0.76. The estimate for true positive, false positive, true negative and false negative for prediction of ‘high-disability risk’ for SBST were 0.77, 0.23, 0.31, and 0.69 respectively. Conclusion The Start Back Screening Tool is able to identify the proportion of patients with low back pain with moderate disability risks, while the Simmonds Physical Performance Tests Battery is better able to identify high disability risks. Thus, SBST as a self-report measure may not adequately substitute physical performance assessment based disability risks prediction. However, SBST has good divergent predictive validity with pain intensity. In contrast to SPBBT, SBST exhibited no floor or ceiling effects in our tests, and demonstrated high sensitivity but low specificity in predicting ‘high-disability risk’.

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