| 1. |
- Grooten, Wilhelmus Johannes Andreas, et al.
(författare)
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Summarizing the effects of different exercise types in chronic low back pain : a systematic review of systematic reviews
- 2022
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Ingår i: BMC Musculoskeletal Disorders. - : Springer Science and Business Media LLC. - 1471-2474. ; 23:1
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: In chronic LBP (CLBP), guideline-endorsed treatment is to stay active, return to normal activity, and to exercise. Several reviews on various exercise types used in CLBP have been published. We aimed to identify systematic reviews of common exercise types used in CLBP, to appraise their quality, and to summarize and compare their effect on pain and disability.METHODS: We searched the databases OVID MEDLINE, EMBASE, COCHRANE LIBRARY, and WEB OF SCIENCE (Core collection) for systematic reviews and meta-analyses on adults between 18 and 70 years of age suffering from chronic or recurrent LBP for a period of at least 12 weeks, which investigated the effects of exercises on pain and disability. All searches were conducted without language restriction. The search was performed up until 2022-01-26. The included reviews were grouped into nine exercise types: aerobic training, aquatic exercises, motor control exercises (MCE), resistance training, Pilates, sling exercises, traditional Chinese exercises (TCE), walking, and yoga. The study quality was assessed with AMSTAR-2. For each exercise type, a narrative analysis was performed, and the level of evidence for the effects of exercise was assessed through GRADE.RESULTS: Our database search resulted in 3,475 systematic reviews. Out of the 253 full texts that were screened, we included 45 systematic reviews and meta-analyses. The quality of the included reviews ranged from high to critically low. Due to large heterogeneity, no meta-analyses were performed. We found low-to-moderate evidence of mainly short-term and small beneficial effects on pain and disability for MCE, Pilates, resistance training, TCE, and yoga compared to no or minimal intervention.CONCLUSIONS: Our findings show that the effect of various exercise types used in CLBP on pain and disability varies with no major difference between exercise types. Many of the included systematic reviews were of low-to-moderate quality and based on randomized controlled trials with high risk of bias. The conflicting results seen, undermine the certainty of the results leading to very-low-to-moderate quality of evidence for our results. Future systematic reviews should be of higher quality to minimize waste of resources.TRIAL REGISTRATION: PROSPERO: Reg no 190409 Registration date 01AUG 2020.
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| 2. |
- Kuster, Roman P, et al.
(författare)
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Active sitting with backrest support : is it feasible?
- 2018
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Ingår i: Ergonomics. - Stockholm : Karolinska Institutet, Dept of Neurobiology, Care Sciences and Society. - 0014-0139 .- 1366-5847.
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Tidskriftsartikel (refereegranskat)abstract
- Ergonomics science recommends office chairs that promote active sitting to reduce sitting related complaints. Since current office chairs do not fulfil this recommendation, a new chair was developed by inverting an existing dynamic chair principle. This study compares active sitting on the inverted chair during a simulated computer based office task to two existing dynamic office chairs (n=8). Upper body stability was analysed using Friedman ANOVA (p=.01). Additionally, participants completed a questionnaire to rate their comfort and activity after half a working day. The inverted chair allowed the participants to perform a substantial range of lateral spine flexion (11.5°) with the most stable upper body posture (≤11mm, ≤2°, p≤0.01). The results of this study suggest that the inverted chair supports active sitting with backrest support during computer based office work. However, according to comfort and activity ratings, results should be verified in a future field study with 24 participants.
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| 3. |
- Kuster, Roman P, et al.
(författare)
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Detecting Prolonged Sitting Bouts with the ActiGraph GT3X.
- 2020
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Ingår i: Scandinavian Journal of Medicine and Science in Sports. - Stockholm : Wiley-Blackwell. - 0905-7188 .- 1600-0838. ; 30:3, s. 572-582
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Tidskriftsartikel (refereegranskat)abstract
- The ActiGraph has a high ability to measure physical activity, however, it lacks an accurate posture classification to measure sedentary behaviour. The aim of the present study was to develop an ActiGraph (waist-worn, 30Hz) posture classification to detect prolonged sitting bouts, and to compare the classification to proprietary ActiGraph data. The activPAL, a highly valid posture classification device, served as reference criterion.1 Both sensors were worn by 38 office workers over a median duration of 9 days. An automated feature selection extracted the relevant signal information for a minute based posture classification. The machine-learning algorithm with optimal feature number to predict the time in prolonged sitting bouts (≥5 and ≥10 minutes) was searched and compared to the activPAL using Bland-Altman statistics. The comparison included optimised and frequently used cut-points (100 and 150 counts-per-minute (cpm), with and without low-frequency-extension (LFE) filtering). The new algorithm predicted the time in prolonged sitting bouts most accurate (bias ≤7 minutes/day). Of all proprietary ActiGraph methods, only 150 cpm without LFE predicted the time in prolonged sitting bouts non-significantly different from the activPAL (bias ≤18 minutes/day). However, the frequently used 100 cpm with LFE accurately predicted total sitting time (bias ≤7 minutes/day). To study the health effects of ActiGraph measured prolonged sitting, we recommend using the new algorithm. In case a cut-point is used, we recommend 150 cpm without LFE to measure prolonged sitting, and 100 cpm with LFE to measure total sitting time. However, both cpm cut-points are not recommended for a detailed bout analysis.
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| 4. |
- Kuster, Roman P, et al.
(författare)
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How Accurate and Precise Can We Measure the Posture and the Energy Expenditure Component of Sedentary Behaviour with One Sensor?
- 2021
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Ingår i: International Journal of Environmental Research and Public Health. - : MDPI. - 1661-7827 .- 1660-4601. ; 18:11
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Tidskriftsartikel (refereegranskat)abstract
- Sedentary behaviour is an emergent public health topic, but there is still no method to simultaneously measure both components of sedentary behaviour-posture and energy expenditure-with one sensor. This study investigated the accuracy and precision of measuring sedentary time when combining the proprietary processing of a posture sensor (activPAL) with a new energy expenditure algorithm and the proprietary processing of a movement sensor (ActiGraph) with a published posture algorithm. One hundred office workers wore both sensors for an average of 7 days. The activPAL algorithm development used 38 and the subsequent independent method comparison 62 participants. The single sensor sedentary estimates were compared with Bland-Atman statistics to the Posture and Physical Activity Index, a combined measurement with both sensors. All single-sensor methods overestimated sedentary time. However, adding the algorithms reduced the overestimation from 129 to 21 (activPAL) and from 84 to 7 min a day (ActiGraph), with far narrower 95% limits of agreements. Thus, combining the proprietary data with the algorithms is an easy way to increase the accuracy and precision of the single sensor sedentary estimates and leads to sedentary estimates that are more precise at the individual level than those of the proprietary processing are at the group level.
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| 5. |
- Kuster, Roman P, et al.
(författare)
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Is Sitting Always Inactive and Standing Always Active? A Simultaneous Free-Living activPal and ActiGraph Analysis.
- 2020
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Ingår i: International Journal of Environmental Research and Public Health. - : MDPI. - 1661-7827 .- 1660-4601. ; 17:23
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Tidskriftsartikel (refereegranskat)abstract
- Sedentary Behavior (SB), defined as sitting with minimal physical activity, is an emergent public health topic. However, the measurement of SB considers either posture (e.g., activPal) or physical activity (e.g., ActiGraph), and thus neglects either active sitting or inactive standing. The aim of this study was to determine the true amount of active sitting and inactive standing in daily life, and to analyze by how much these behaviors falsify the single sensors' sedentary estimates. Sedentary time of 100 office workers estimated with activPal and ActiGraph was therefore compared with Bland-Altman statistics to a combined sensor analysis, the posture and physical activity index (POPAI). POPAI classified each activPal sitting and standing event into inactive or active using the ActiGraph counts. Participants spent 45.0% [32.2%-59.1%] of the waking hours inactive sitting (equal to SB), 13.7% [7.8%-21.6%] active sitting, and 12.0% [5.7%-24.1%] inactive standing (mean [5th-95th percentile]). The activPal overestimated sedentary time by 30.3% [12.3%-48.4%] and the ActiGraph by 22.5% [3.2%-41.8%] (bias [95% limit-of-agreement]). The results showed that sitting is not always inactive, and standing is not always active. Caution should therefore be paid when interpreting the activPal (ignoring active sitting) and ActiGraph (ignoring inactive standing) measured time as SB.
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| 6. |
- Kuster, Roman P, et al.
(författare)
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Where to place which sensor to measure sedentary behaviour? A method development and comparison among various sensor placements and signal types
- 2020
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Ingår i: Journal for the Measurement of Physical Behaviour. - Stockholm : Karolinska Institutet, Dept of Neurobiology, Care Sciences and Society. - 2575-6605 .- 2575-6613.
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Tidskriftsartikel (refereegranskat)abstract
- Background: Sedentary Behaviour (SB) is associated with several chronic diseases and especially office workers are at increased risk. SB is defined by a sitting or reclined body posture with an energy expenditure ≤1.5 METs. However, current objective methods to measure SB are not consistent with its definition. There is no consensus on which sensor placement and type to be used. Aim: To compare the accuracy of newly developed artificial intelligence models for 15 sensor placements in combination with four signal types (accelerometer only/plus gyroscope and/or magnetometer) to detect posture and physical in-/activity while desk-based activities. Method: Signal features for the model development were extracted from sensor raw data of 30 office workers performing 10 desk-based tasks, each lasting 5 minutes. Direct observation (posture) and indirect calorimetry (in-/activity) served as reference criteria. The best classification model for each sensor was identified and compared among the sensor placements, both using Friedman and post-hoc Wilcoxon tests (p≤0.05). Results: Posture was most accurately measured with a lower body sensor, while in-/activity was most accurately measured with an upper body or waist sensor. The inclusion of additional signal types improved the posture classification for some placements, while the acceleration signal already contained the relevant signal information for the in-/activity classification. Overall, the thigh accelerometer most accurately classified desk-based SB. Conclusion: This study favours, in line with previous work, the measurement of SB with a thigh worn accelerometer, and adds the information that this sensor is also accurate in measuring physical in-/activity while sitting and standing.
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| 7. |
- Rasmussen-Barr, Eva, et al.
(författare)
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Summarizing the effects of different exercise types in chronic neck pain - a systematic review and meta-analysis of systematic reviews
- 2023
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Ingår i: BMC Musculoskeletal Disorders. - 1471-2474. ; 24:1
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: To date, no consensus exists as to whether one exercise type is more effective than another in chronic neck pain. This systematic review and meta-analysis of systematic reviews aimed to summarize the literature on the effect of various exercise types used in chronic neck pain and to assess the certainty of the evidence.METHODS: We searched the databases Ovid MEDLINE, Embase, Cochrane Library, SportDiscus, and Web of Science (Core Collection) for systematic reviews and meta-analyses on adults between 18 and 70 years with chronic neck pain lasting ≥ 12 weeks which investigated the effects of exercises on pain and disability. The included reviews were grouped into motor control exercise (MCE), Pilates exercises, resistance training, traditional Chinese exercise (TCE), and yoga. Study quality was assessed with AMSTAR-2 and the level of certainty for the effects of the exercise through GRADE. A narrative analysis of the results was performed and in addition, meta-analyses when feasible.RESULTS: Our database search resulted in 1,794 systematic reviews. We included 25 systematic reviews and meta-analyses including 17,321 participants (overlap not accounted for). The quality of the included reviews ranged from critically low to low (n = 13) to moderate to high (n = 12). We found low to high certainty of evidence that MCE, Pilates exercises, resistance training, TCE, and yoga have short-term positive effects on pain and that all exercise types except resistance training, show positive effects on disability compared to non-exercise controls. We found low to moderate certainty of evidence for conflicting results on pain and disability when the exercise types were compared to other exercise interventions in the short-term as well as in intermediate/long-term apart for yoga, as no long-term results were available.CONCLUSION: Overall, our findings show low to high certainty of evidence for positive effects on pain and disability of the various exercise types used in chronic neck pain compared to non-exercise interventions, at least in the short-term. Based on our results, no optimal exercise intervention for patients with chronic neck pain can be recommended, since no large differences between the exercise types were shown here. Because the quality of the included systematic reviews varied greatly, future systematic reviews need to increase their methodological quality.TRIAL REGISTRATION: Prospero CRD42022336014.
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