Incidence of sick leave and disability pension in adults with musculoskeletal pain and co-occurring long-term conditions: data from the Norwegian HUNT study and national registries.

BACKGROUND: Musculoskeletal pain is one of the leading causes of work productivity loss. Long-term conditions (LTCs) commonly occur alongside musculoskeletal pain. However, the incidence of sick leave and disability pension according to LTC status in people with musculoskeletal pain has not been previously described. METHODS: Working-age participants (20-65 years) with persistent musculoskeletal pain who participated in the HUNT3 Study (1995-97) were included. Twenty-five LTCs were classified into 8 LTC groups according to the International Classification of Diseases version 11. Data on sickness and disability benefits were obtained from the National Insurance Database and linked to the HUNT3 data using participants' personal identification number. Age-adjusted incidence rates (IRs) (per 10,000 person-years) and hazard ratios (HRs) of sick leave during 5-year follow-up and disability pension during ~ 25-year follow-up were estimated with 95% confidence intervals (CIs) and presented according to LTC status. RESULTS: Overall, 11,080 participants with musculoskeletal pain were included. Of those, 32% reported one LTC and 45% reported ≥ 2 LTCs. During the follow up period, 1,312 participants (12%) received disability pension due to musculoskeletal conditions. The IR of sick leave and disability pension due to musculoskeletal conditions increased with number of LTCs. Specifically, the IR of sick leave was 720 (95% CI 672 to 768) in participants without any LTCs and 968 (95% CI 927 to 1,009) if they had ≥ 2 LTCs. The IRs of disability pension were 87 (95% CI 75 to 98) and 167 (95% CI 154 to 179) among those with no LTCs and ≥ 2 LTCs, respectively. The incidence of sick leave and disability pension due to musculoskeletal conditions was largely similar across LTCs, although the incidence of disability pension was somewhat higher among people with sleep disorders (IR: 223, 95% CI 194 to 252). CONCLUSIONS: Among people with persistent musculoskeletal pain, the incidence of prematurely leaving the work force due to musculoskeletal conditions was twice as high for those with multiple LTCs compared to those without any LTCs. This was largely irrespective of the type of LTC, indicating that the number of LTCs are an important feature when evaluating work participation among people with musculoskeletal pain.

The association between age and long-term quality of life after curative treatment for prostate cancer: a cross-sectional study.

OBJECTIVE: We aimed to investigate the associations between age at radical prostate cancer treatment and long-term global quality of life (QoL), physical function (PF), and treatment-related side effects. MATERIAL AND METHODS: This single-center, cross-sectional study included men treated for localized prostate cancer with robotic-assisted radical prostatectomy (RARP) or external beam radiotherapy (EBRT) in 2014-2018. Global QoL and PF were assessed by the European Organisation of Research and Treatment in Cancer Quality of life Questionnaire-C30 (QLQ-C30), side effects by the Expanded Prostate Cancer Index Composite (EPIC-26). Adjusted linear regression models were estimated to assess associations between age (continuous variable) at treatment and outcomes. QLQ-C30 scores were compared to normative data after dividing the cohort in two groups, <70 years and ≥70 years at treatment. RESULTS: Of 654 men included, 516 (79%) had undergone RARP, and 138 (21%) had undergone EBRT combined with androgen deprivation therapy for 93%. Mean time since treatment was 57 months. Median age at treatment was 68 (min-max 44-84) years. We found no statistically significant independent association between age at treatment and global QoL, PF or side effects, except for sexual function (regression coefficient [RC] -0.77; p < 0.001) and hormonal/vitality (RC 0.30; p = 0.006) function. Mean QLQ-C30 scores were slightly poorer than age-adjusted normative scores, for men <70 years (n = 411) as well as for men ≥70 years (n = 243) at treatment, but the differences were not beyond clinical significance. CONCLUSIONS: In this cohort of prostate cancer survivors, age at treatment had little impact on long-term QoL and function. Due to the cross-sectional design, short term impact or variation over time cannot be ruled out.

Physical activity and cognitive function in adults born very preterm or with very low birth weight-an individual participant data meta-analysis.

OBJECTIVE: Individuals born very preterm (<32 weeks of gestation) or with very low birthweight (<1500g) have lower cognitive function compared with term-born peers. Furthermore, some studies suggest that they are less physically active as young adults than controls, but the relationship between physical activity and cognitive function remains unclear. We performed an individual participant data meta-analysis to examine whether being born preterm/with very low birth weight is associated with physical activity in adulthood and examined if cognitive function mediates this association. STUDY DESIGN: Cohorts with data on physical activity and cognitive function in adults born very preterm/very low birth weight and term-born controls were recruited from the Research on European Children and Adults Born Preterm, and the Adults Born Preterm International Collaboration Consortia. A systematic literature search was performed in PubMed and Embase. RESULTS: Five cohorts with 1644 participants aged 22-28 years (595 very preterm/very low birth weight and 1049 controls) were included. Adults born very preterm/very low birth weight reported 1.11 (95% CI: 0.68 to 1.54) hours less moderate to vigorous physical activity per week than controls, adjusted for cohort, age and sex. The difference between individuals born very preterm/very low birth weight and controls was larger among women than among men. Neither intelligence quotient nor self-reported executive function mediated the association between very preterm/very low birth weight and moderate to vigorous physical activity. Results were essentially the same when we excluded individuals with neurosensory impairments. CONCLUSION: Adults born very preterm/very low birth weight, especially women, reported less moderate to vigorous physical activity than their term-born peers. Cognitive function did not mediate this association. Considering the risk of adverse health outcomes among individuals born preterm, physical activity could be a target for intervention.

Clinical guidelines are silent on the recommendation of physical activity and exercise therapy for low back pain: A systematic review.

OBJECTIVES: To synthesise and evaluate the quality of the recommendations for exercise therapy and physical activity from guidelines for the prevention and/or management of low back pain. DESIGN: Systematic review. METHODS: Included clinical practice guidelines for the management of low back pain published between 2014 and 2022 and searched in 9 databases until September 2022. The quality of evidence was evaluated with the Appraisal of Guidelines, Research and Evaluation tool (AGREE-II instrument). RESULTS: After screening 3448 studies, 18 clinical practice guidelines were included in this review. Only five (27 %) guidelines were judged as having a satisfactory quality of evidence (i.e., rigour of development and applicability), and 13 (72 %) of guidelines are discussed and rated as critical. Regarding physical activity, no guidelines provided recommendations for the primary prevention of low back pain or incorporated adequate physical activity aspects considering type, dosage, frequency, and intensity. For exercises, all (100 %) guidelines recommended at least one type of supervised exercise in the management of low back pain, and 16 (88 %) provided an overall recommendation for people to stay active. CONCLUSIONS: Guidelines offer minimal or, sometimes, no detail regarding physical activity or specific exercise regimens for the management and prevention of low back pain. When some guidance is provided, the recommendations typically lack specificity concerning the type, intensity, duration, and frequency of exercise and, in many cases, they represent a combination of scarce available evidence and stakeholder perspectives.

Inpatient multimodal rehabilitation and the role of pain intensity and mental distress on return-to-work: causal mediation analyses of a randomized controlled trial.

OBJECTIVE: Studies suggest that symptom reduction is not necessary for improved return-to-work after occupational rehabilitation programmes. This secondary analysis of a randomized controlled trial examined whether pain intensity and mental distress mediate the effect of an inpatient programme on sustainable return-to-work. METHODS: The randomized controlled trial compared inpatient multimodal occupational rehabilitation (n = 82) with outpatient acceptance and commitment therapy (n = 79) in patients sick-listed due to musculoskeletal and mental health complaints. Pain and mental distress were measured at the end of each programme, and patients were followed up on sick-leave for 12 months. Cox regression with an inverse odds weighted approach was used to assess causal mediation. RESULTS: The total effect on return-to-work was in favour of the inpatient programme compared with the control (hazard ratio (HR) 1.96; 95% confidence interval (95% CI) 1.15-3.35). There was no evidence of mediation by pain intensity (indirect effect HR, 0.98; 95% CI, 0.61-1.57, direct effect HR, 2.00; 95% CI, 1.02-3.90), but mental distress had a weak suppression effect (indirect effect HR, 0.89; 95% CI, 0.59-1.36, direct effect HR, 2.19; 95% CI, 1.13-4.26). CONCLUSION: These data suggest that symptom reduction is not necessary for sustainable return-to-work after an inpatient multimodal occupational rehabilitation intervention.

A Novel System for the Device-Based Measurement of Physical Activity, Sedentary Behavior, and Sleep (Motus): Usability Evaluation.

BACKGROUND: Device-based measurements of physical behavior, using the current methods, place a large burden on participants. The Motus system could reduce this burden by removing the necessity for in-person meetings, replacing diaries written on paper with digital diaries, and increasing the automation of feedback generation. OBJECTIVE: This study aims to describe the development of the Motus system and evaluate its potential to reduce participant burden in a two-phase usability evaluation. METHODS: Motus was developed around (1) a thigh-worn accelerometer with Bluetooth data transfer; (2) a smartphone app containing an attachment guide, a digital diary, and facilitating automated data transfer; (3) a cloud infrastructure for data storage; (4) an analysis software to generate feedback for participants; and (5) a web-based app for administrators. We recruited 19 adults with a mean age of 45 (SD 11; range 27-63) years, of which 11 were female, to assist in the two-phase evaluation of Motus. A total of 7 participants evaluated the usability of mockups for a smartphone app in phase 1. Participants interacted with the app while thinking aloud, and any issues raised were classified as critical, serious, or minor by observers. This information was used to create an improved and functional smartphone app for evaluation in phase 2. A total of 12 participants completed a 7-day free-living measurement with Motus in phase 2. On day 1, participants attempted 20 system-related tasks under observation, including registration on the study web page, reading the information letter, downloading and navigating the smartphone app, attaching an accelerometer on the thigh, and completing a diary entry for both work and sleep hours. Task completion success and any issues encountered were noted by the observer. On completion of the 7-day measurement, participants provided a rating from 0 to 100 on the System Usability Scale and participated in a semistructured interview aimed at understanding their experience in more detail. RESULTS: The task completion rate for the 20 tasks was 100% for 13 tasks, >80% for 4 tasks, and <50% for 3 tasks. The average rating of system usability was 86 on a 0-100 scale. Thematic analysis indicated that participants perceived the system as easy to use and remember, and subjectively pleasing overall. Participants with shift work reported difficulty with entering sleep hours, and 66% (8/12) of the participants experienced slow data transfer between the app and the cloud infrastructure. Finally, a few participants desired a greater degree of detail in the generated feedback. CONCLUSIONS: Our two-phase usability evaluation indicated that the overall usability of the Motus system is high in free-living. Issues around the system's slow data transfer, participants with atypical work shifts, and the degree of automation and detail of generated feedback should be addressed in future iterations of the Motus system. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.2196/35697.

Can the bias of self-reported sitting time be corrected? A statistical model validation study based on data from 23 993 adults in the Norwegian HUNT study.

BACKGROUND: Despite apparent shortcomings such as measurement error and low precision, self-reported sedentary time is still widely used in surveillance and research. The aim of this study was threefold; (i) to examine the agreement between self-reported and device-measured sitting time in a general adult population; (ii), to examine to what extent demographics, lifestyle factors, long-term health conditions, physical work demands, and educational level is associated with measurement bias; and (iii), to explore whether correcting for factors associated with bias improves the prediction of device-measured sitting time based on self-reported sitting time. METHODS: A statistical validation model study based on data from 23 993 adults in the Trøndelag Health Study (HUNT4), Norway. Participants reported usual sitting time on weekdays using a single-item questionnaire and wore two AX3 tri-axial accelerometers on the thigh and low back for an average of 3.8 (standard deviation [SD] 0.7, range 1-5) weekdays to determine their sitting time. Statistical validation was performed by iteratively adding all possible combinations of factors associated with bias between self-reported and device-measured sitting time in a multivariate linear regression. We randomly selected 2/3 of the data (n = 15 995) for model development and used the remaining 1/3 (n = 7 998) to evaluate the model. RESULTS: Mean (SD) self-reported and device-measured sitting time were 6.8 (2.9) h/day and 8.6 (2.2) h/day, respectively, corresponding to a mean difference of 1.8 (3.1) h/day. Limits of agreement ranged from - 8.0 h/day to 4.4 h/day. The discrepancy between the measurements was characterized by a proportional bias with participants device-measured to sit less overestimating their sitting time and participants device-measured to sit more underestimating their sitting time. The crude explained variance of device-measured sitting time based on self-reported sitting time was 10%. This improved to 24% when adding age, body mass index and physical work demands to the model. Adding sex, lifestyle factors, educational level, and long-term health conditions to the model did not improve the explained variance. CONCLUSIONS: Self-reported sitting time had low validity and including a range of factors associated with bias in self-reported sitting time only marginally improved the prediction of device-measured sitting time.

Do age, gender, and education modify the effectiveness of app-delivered and tailored self-management support among adults with low back pain?-Secondary analysis of the selfBACK randomised controlled trial.

selfBACK is an artificial intelligence based self-management app for low back pain (LBP) recently reported to reduce LBP-related disability. The aim of this study was to examine if age, gender, or education modify the effectiveness of the selfBACK intervention using secondary analysis of the selfBACK randomized controlled trial. Persons seeking care for LBP were recruited from primary care in Denmark and Norway and an outpatient clinic (Denmark). The intervention group (n = 232) received the selfBACK app adjunct to usual care. The control group (n = 229) received usual care only. Analyses were stratified by age (18-34, 35-64, ≥65 years), gender (male, female), and education (≤12, >12 years) to investigate differences in effect at three and nine months follow-up on LBP-related disability (Roland-Morris Disability Questionnaire [RMDQ]), LBP intensity and pain self-efficacy. Overall, there was no effect modification for any of the sociodemographic factors. However, data on LBP-related disability suggest that the effect of the intervention was somewhat more beneficial in older than in younger participants. The difference between the intervention and control group due to interaction was 2.6 (95% CI: 0.4 to 4.9) RMDQ points for those aged ≥65 years as compared to those aged 35-64 years. In conclusion, age, gender, or education did not influence the effect of the selfBACK intervention on LBP-related disability. However, older participants may have an additional long-term positive effect compared to younger participants. Trial registration: ClinicalTrials.gov Identifier: NCT03798288.

Interplay between chronic widespread pain and lifestyle factors on the risk of type 2 diabetes: longitudinal data from the Norwegian HUNT Study.

INTRODUCTION: Chronic widespread pain (CWP) and diabetes commonly co-occur; however, it is unclear whether CWP infers an additional risk for diabetes among those with known risk factors for type 2 diabetes. We aimed to examine if CWP magnifies the effect of adverse lifestyle factors on the risk of diabetes. RESEARCH DESIGN AND METHODS: The study comprised data on 25 528 adults in the Norwegian HUNT Study without diabetes at baseline (2006-2008). We calculated adjusted risk ratios (RRs) with 95% CIs for diabetes at follow-up (2017-2019), associated with CWP and body mass index (BMI), physical activity, and insomnia symptoms. The relative excess risk due to interaction (RERI) was calculated to investigate the synergistic effect between CWP and adverse lifestyle factors. RESULTS: Compared with the reference group without chronic pain and no adverse lifestyle factors, those with BMI ≥30 kg/m2 with and without CWP had RRs for diabetes of 10.85 (95% CI 7.83 to 15.05) and 8.87 (95% CI 6.49 to 12.12), respectively; those with physical activity <2 hours/week with and without CWP had RRs for diabetes of 2.26 (95% CI 1.78 to 2.88) and 1.54 (95% CI 1.24 to 1.93), respectively; and those with insomnia symptoms with and without CWP had RRs for diabetes of 1.31 (95% CI 1.07 to 1.60) and 1.27 (95% CI 1.04 to 1.56), respectively. There was little evidence of synergistic effect between CWP and BMI ≥30 kg/m2 (RERI=1.66, 95% CI -0.44 to 3.76), low physical activity (RERI=0.37, 95% CI -0.29 to 1.03) or insomnia symptoms (RERI=-0.09, 95% CI -0.51 to 0.34) on the risk of diabetes. CONCLUSIONS: These findings show no clear interaction between CWP and adverse lifestyle factors on the risk of diabetes.

The Role of Pain Duration and Pain Intensity on the Effectiveness of App-Delivered Self-Management for Low Back Pain (selfBACK): Secondary Analysis of a Randomized Controlled Trial.

Background: Clinical guidelines for nonspecific low back pain (LBP) recommend self-management tailored to individual needs and capabilities as a first-line treatment. Mobile health solutions are a promising method for delivering tailored self-management interventions to patients with nonspecific LBP. However, it is not clear if the effectiveness of such self-management interventions depends on patients' initial pain characteristics. High pain intensity and long-term symptoms of LBP have been associated with an unfavorable prognosis, and current best evidence indicates that long-term LBP (lasting more than 3 months) requires a more extensive treatment approach compared to more acute LBP. The artificial intelligence-based selfBACK app supports tailored and evidence-based self-management of nonspecific LBP. In a recent randomized controlled trial, we showed that individuals who received the selfBACK app in addition to usual care had lower LBP-related disability at the 3-month follow-up compared to those who received usual care only. This effect was sustained at 6 and 9 months. Objective: This study aims to explore if the baseline duration and intensity of LBP influence the effectiveness of the selfBACK intervention in a secondary analysis of the selfBACK randomized controlled trial. Methods: In the selfBACK trial, 461 adults (18 years or older) who sought care for nonspecific LBP in primary care or at an outpatient spine clinic were randomized to receive the selfBACK intervention adjunct to usual care (n=232) or usual care alone (n=229). In this secondary analysis, the participants were stratified according to the duration of the current LBP episode at baseline (≤12 weeks vs >12 weeks) or baseline LBP intensity (≤5 points vs >5 points) measured by a 0-10 numeric rating scale. The outcomes were LBP-related disability measured by the Roland-Morris Disability Questionnaire (0- to 24-point scale), average LBP intensity, pain self-efficacy, and global perceived effect. To assess whether the duration and intensity of LBP influenced the effect of selfBACK, we estimated the difference in treatment effect between the strata at the 3- and 9-month follow-ups with a 95% CI. Results: Overall, there was no difference in effect for patients with different durations or intensities of LBP at either the 3- or 9-month follow-ups. However, there was suggestive evidence that the effect of the selfBACK intervention on LBP-related disability at the 3-month follow-up was largely confined to people with the highest versus the lowest LBP intensity (mean difference between the intervention and control group -1.8, 95% CI -3.0 to -0.7 vs 0.2, 95% CI -1.1 to 0.7), but this was not sustained at the 9-month follow-up. Conclusions: The results suggest that the intensity and duration of LBP have negligible influence on the effectiveness of the selfBACK intervention on LBP-related disability, average LBP intensity, pain self-efficacy, and global perceived effect.

Physical activity and associations with health-related quality of life in adults born small for gestational age at term: a prospective cohort study.

BACKGROUND: Adults born small for gestational age (SGA) have increased risk of adverse health outcomes. Physical activity (PA) is a key determinant of health and health-related quality of life (HRQoL). We aimed to investigate if being born SGA at term is associated with lower objectively measured and self-reported PA during adulthood. We also examined if objectively measured and self-reported PA were associated with HRQoL. METHODS: As part of the 32-year follow-up in the NTNU Low Birth Weight in a Lifetime Perspective study, SGA and non-SGA control participants wore two tri-axial accelerometers for seven days (37 SGA, 43 control), and completed the International Physical Activity Questionnaire (IPAQ) (42 SGA, 49 control) and the Short Form 36 Health Survey (SF-36) (55 SGA, 67 control). Group differences in objectively measured daily metabolic equivalent of task (MET) minutes spent sedentary (lying, sitting), on feet (standing, walking, running, cycling), on the move (walking, running, cycling) and running/cycling, and group differences in self-reported daily MET minutes spent walking and in moderate and vigorous PA were examined using linear regression. Associations with SF-36 were explored in a general linear model. RESULTS: Mean (SD) daily MET minutes on the move were 218 (127) in the SGA group and 227 (113) in the control group. There were no group differences in objectively measured and self-reported PA or associations with HRQoL. In the SGA group, one MET minute higher objectively measured time on the move was associated with 4.0 (95% CI: 0.6-6.5, p = 0.009) points higher SF-36 physical component summary. CONCLUSION: We found no differences in objectively measured and self-reported PA or associations with HRQoL between term-born SGA and non-SGA control participants in adulthood.

Effect of an Artificial Intelligence-Based Self-Management App on Musculoskeletal Health in Patients With Neck and/or Low Back Pain Referred to Specialist Care: A Randomized Clinical Trial.

Importance: Self-management is a key element in the care of persistent neck and low back pain. Individually tailored self-management support delivered via a smartphone app in a specialist care setting has not been tested. Objective: To determine the effect of individually tailored self-management support delivered via an artificial intelligence-based app (SELFBACK) adjunct to usual care vs usual care alone or nontailored web-based self-management support (e-Help) on musculoskeletal health. Design, Setting, and Participants: This randomized clinical trial recruited adults 18 years or older with neck and/or low back pain who had been referred to and accepted on a waiting list for specialist care at a multidisciplinary hospital outpatient clinic for back, neck, and shoulder rehabilitation. Participants were enrolled from July 9, 2020, to April 29, 2021. Of 377 patients assessed for eligibility, 76 did not complete the baseline questionnaire, and 7 did not meet the eligibility criteria (ie, did not own a smartphone, were unable to take part in exercise, or had language barriers); the remaining 294 patients were included in the study and randomized to 3 parallel groups, with follow-up of 6 months. Interventions: Participants were randomly assigned to receive app-based individually tailored self-management support in addition to usual care (app group), web-based nontailored self-management support in addition to usual care (e-Help group), or usual care alone (usual care group). Main Outcomes and Measures: The primary outcome was change in musculoskeletal health measured by the Musculoskeletal Health Questionnaire (MSK-HQ) at 3 months. Secondary outcomes included change in musculoskeletal health measured by the MSK-HQ at 6 weeks and 6 months and pain-related disability, pain intensity, pain-related cognition, and health-related quality of life at 6 weeks, 3 months, and 6 months. Results: Among 294 participants (mean [SD] age, 50.6 [14.9] years; 173 women [58.8%]), 99 were randomized to the app group, 98 to the e-Help group, and 97 to the usual care group. At 3 months, 243 participants (82.7%) had complete data on the primary outcome. In the intention-to-treat analysis at 3 months, the adjusted mean difference in MSK-HQ score between the app and usual care groups was 0.62 points (95% CI, -1.66 to 2.90 points; P = .60). The adjusted mean difference between the app and e-Help groups was 1.08 points (95% CI, -1.24 to 3.41 points; P = .36). Conclusions and Relevance: In this randomized clinical trial, individually tailored self-management support delivered via an artificial intelligence-based app adjunct to usual care was not significantly more effective in improving musculoskeletal health than usual care alone or web-based nontailored self-management support in patients with neck and/or low back pain referred to specialist care. Further research is needed to investigate the utility of implementing digitally supported self-management interventions in the specialist care setting and to identify instruments that capture changes in self-management behavior. Trial Registration: ClinicalTrials.gov Identifier: NCT04463043.

Modified prolonged exposure therapy as Early Intervention after Rape (The EIR-study): study protocol for a multicenter randomized add-on superiority trial.

BACKGROUND: Sexual assault and rape are the traumatic life events with the highest probability for posttraumatic stress disorder (PTSD), which can have devastating consequences for those afflicted by the condition. Studies indicate that modified prolonged exposure (mPE) therapy may be effective in preventing the development of PTSD in recently traumatized individuals, and especially for people who have experienced sexual assault. If a brief, manualized early intervention can prevent or reduce post-traumatic symptoms in women who have recently experienced rape, healthcare services targeted for these populations (i.e., sexual assault centers, SACs) should consider implementing such interventions as part of routine care. METHODS/DESIGN: This is a multicenter randomized controlled add-on superiority trial that enrolls patients attending sexual assault centers within 72 h after rape or attempted rape. The objective is to assess whether mPE shortly after rape can prevent the development of post-traumatic stress symptoms. Patients will be randomized to either mPE plus treatment as usual (TAU) or TAU alone. The primary outcome is the development of post-traumatic stress symptoms 3 months after trauma. Secondary outcomes will be symptoms of depression, sleep difficulties, pelvic floor hyperactivity, and sexual dysfunction. The first 22 subjects will constitute an internal pilot trial to test acceptance of the intervention and feasibility of the assessment battery. DISCUSSION: This study will guide further research and clinical initiatives for implementing strategies for preventing post-traumatic stress symptoms after rape and provide new knowledge about which women may benefit the most from such initiatives and for revising existing treatment guidelines within this area. TRIAL REGISTRATION: ClinicalTrials.gov NCT05489133. Registered on 3 August 2022.

External validation of prediction models for patient-reported outcome measurements collected using the selfBACK mobile app.

BACKGROUND: External validation is essential in examining the disparities in the training and validation cohorts during the development of prediction models, especially when the application domain is healthcare-oriented. Currently, the use of prediction models in healthcare research aimed at utilising the under-explored potential of patient-reported outcome measurements (PROMs) is limited, and few are validated using external datasets. OBJECTIVE: To validate the machine learning prediction models developed in our previous work [29] for predicting four pain-related patient-reported outcomes from the selfBACK clinical trial datasets. METHODS: We evaluate the validity of three pre-trained prediction models based on three methods- Case-Based Reasoning, Support Vector Regression, and XGBoost Regression-using an external dataset that contains PROMs collected from patients with non-specific neck and or low back pain using the selfBACK mobile application. RESULTS: Overall, the predictive power was low, except for prediction of one of the outcomes. The results indicate that while the predictions are far from immaculate in either case, the models show ability to generalise and predict outcomes for a new dataset. CONCLUSION: External validation of the prediction models presents modest results and highlights the individual differences and need for external validation of prediction models in clinical settings. There is need for further development in this area of machine learning application and patient-centred care.

Exploratory application of machine learning methods on patient reported data in the development of supervised models for predicting outcomes.

BACKGROUND: Patient-reported outcome measurements (PROMs) are commonly used in clinical practice to support clinical decision making. However, few studies have investigated machine learning methods for predicting PROMs outcomes and thereby support clinical decision making. OBJECTIVE: This study investigates to what extent different machine learning methods, applied to two different PROMs datasets, can predict outcomes among patients with non-specific neck and/or low back pain. METHODS: Using two datasets consisting of PROMs from (1) care-seeking low back pain patients in primary care who participated in a randomized controlled trial, and (2) patients with neck and/or low back pain referred to multidisciplinary biopsychosocial rehabilitation, we present data science methods for data prepossessing and evaluate selected regression and classification methods for predicting patient outcomes. RESULTS: The results show that there is a potential for machine learning to predict and classify PROMs. The prediction models based on baseline measurements perform well, and the number of predictors can be reduced, which is an advantage for implementation in decision support scenarios. The classification task shows that the dataset does not contain all necessary predictors for the care type classification. Overall, the work presents generalizable machine learning pipelines that can be adapted to other PROMs datasets. CONCLUSION: This study demonstrates the potential of PROMs in predicting short-term patient outcomes. Our results indicate that machine learning methods can be used to exploit the predictive value of PROMs and thereby support clinical decision making, given that the PROMs hold enough predictive power.

DE-PASS Best Evidence Statement (BESt): modifiable determinants of physical activity and sedentary behaviour in children and adolescents aged 5-19 years-a protocol for systematic review and meta-analysis.

INTRODUCTION: Physical activity among children and adolescents remains insufficient, despite the substantial efforts made by researchers and policymakers. Identifying and furthering our understanding of potential modifiable determinants of physical activity behaviour (PAB) and sedentary behaviour (SB) is crucial for the development of interventions that promote a shift from SB to PAB. The current protocol details the process through which a series of systematic literature reviews and meta-analyses (MAs) will be conducted to produce a best-evidence statement (BESt) and inform policymakers. The overall aim is to identify modifiable determinants that are associated with changes in PAB and SB in children and adolescents (aged 5-19 years) and to quantify their effect on, or association with, PAB/SB. METHODS AND ANALYSIS: A search will be performed in MEDLINE, SportDiscus, Web of Science, PsychINFO and Cochrane Central Register of Controlled Trials. Randomised controlled trials (RCTs) and controlled trials (CTs) that investigate the effect of interventions on PAB/SB and longitudinal studies that investigate the associations between modifiable determinants and PAB/SB at multiple time points will be sought. Risk of bias assessments will be performed using adapted versions of Cochrane's RoB V.2.0 and ROBINS-I tools for RCTs and CTs, respectively, and an adapted version of the National Institute of Health's tool for longitudinal studies. Data will be synthesised narratively and, where possible, MAs will be performed using frequentist and Bayesian statistics. Modifiable determinants will be discussed considering the settings in which they were investigated and the PAB/SB measurement methods used. ETHICS AND DISSEMINATION: No ethical approval is needed as no primary data will be collected. The findings will be disseminated in peer-reviewed publications and academic conferences where possible. The BESt will also be shared with policy makers within the DE-PASS consortium in the first instance. SYSTEMATIC REVIEW REGISTRATION: CRD42021282874.

The joint effect of sleep duration and insomnia symptoms on the risk of recurrent spinal pain: The HUNT study.

Although sleep quantity and quality appear to be interrelated, most previous studies have considered sleep duration and insomnia symptoms as distinct entities. We therefore examined whether there is a joint effect of sleep duration and long-term changes in insomnia symptoms on the risk of recurrent chronic spinal pain. We performed a prospective study of 8,788 participants who participated in three surveys over ∼22 years and reported chronic spinal pain at the first, second, or both surveys. Adjusted risk ratios (RRs) were calculated for the risk of recurrent spinal pain at the last survey associated with self-reported sleep duration at the first survey and changes in insomnia symptoms between the two first surveys. Compared to participants with normal sleep duration (7-9 h) and no insomnia symptoms at the two first surveys, participants with insomnia symptoms over the same period had RRs of spinal pain of 1.33 (95% CI 1.26-1.41) in the last survey if they reported normal sleep duration and 1.50 (95% CI 1.34-1.67) if they reported short sleep (≤6 h). The corresponding RRs for spinal pain for participants who improved their sleep symptoms were 1.09 (95% CI 1.00-1.19) for those with normal sleep and 1.13 (95% CI 0.88-1.45) for those with short sleep. In conclusion, people who reported insomnia symptoms over ∼10 years in combination with short sleep had a particularly increased risk of recurrent spinal pain. Improvement in insomnia symptoms was associated with a favorable prognosis.