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Physiological and psychological symptom management based on electronic patient-reported outcomes: the TD-WELLBEING randomized clinical trial
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The datasets supporting this study are available from the corresponding authors upon reasonable request, in compliance with FAIR data principles (Findable, Accessible, Interoperable, Reusable). All data sharing activities adhere to relevant ethical guidelines and institutional review board approvals.Supplementary information is available online at: https://www.nature.com/articles/s41416-025-03110-5#Sec17 .BACKGROUND: One-third of all lung cancer cases globally are reported in China. This study evaluated the symptom management efficacy of an electronic patient-reported outcomes (ePRO)-based intervention for postoperative symptoms like pain and psychological distress after lung cancer surgery. METHODS: We included lung cancer surgery patients (April 2022-October 2023; age, 18-75 years) with ECOG scores of 0-2 and expected survival of >6 months and randomized them into control and intervention groups. The latter completed MDASI-LC and QLQ-C30 questionnaires, wherein high symptom scores prompted treatment recommendations; the former received routine care. Changes in symptom scores, daily function, and quality of life were evaluated over 12 weeks and 1 year through surveys and interviews for ePRO-based symptom management efficacy assessments. RESULTS: Herein, 355 participants comprised intervention (n = 182) and control groups (n = 173). At 12 weeks, the former had significantly lower symptoms threshold [0 (0-1) vs. 1 (0-3)], lower symptom scores [adjusted mean difference, -0.527 (95% CI: -0.788 to -0.266)], and higher QOL scores (emotional function: 2.908; 95% CI: 0.600-5.216, P = 0.014; global health: 6.775; 95% CI: 3.967-9.583). CONCLUSIONS: ePRO-based collaborative management effectively lessened postoperative burden and improved QOL beyond 6 months.This work was supported by the Project Assignment of Tangdu Hospital Discipline Innovation Development Plan (No: 2021LCYJ038), Air Force Medical University Clinical Research Project (No: 2022LC2233), and the Natural Science Foundation of China (82204151 and 82173627)
The autonomy of migration as travelling theory: Situated principles from Nepal
Get PDFThe autonomy of migration (AOM) theory views mobility as a fundamental force that shapes our world. This theory of migration challenges the state-centric view of migration as a problem to be solved. It emphasises the role of migrant agency in the transformation of social, political and economic structures. Whilst AOM has contributed to understanding migrant struggles in contexts where there are restrictions on the inflow of immigrants, it has also faced criticisms from migration scholars and activists, prompting ongoing engagement, refinement and transformation. In this article, I position AOM as a travelling theory, demonstrating how its core insights travel across geographical, political and academic contexts. I draw on three cases from Nepal, where citizens' outflow is restricted, to outline five situated principles of AOM that build on and expand the theory's original formulations relevant to the context of Nepal. These situated principles not only ground AOM contextually but also demonstrate how a travelling theory of migration evolves through its encounters with struggles, learns from situated practices and remains responsive to shifting regimes of mobility.Brunel University of London BRIEF AWARDS 2024/25; Gerda Henkel Foundation (grant number AZ 14/FM/23 - https://www.gerda-henkel-stiftung.de/en/forced_migration#123861)
The rise of fabricated majoritarianism: How nationalism based on ‘othering’ in democracies at times of scarcity is exacerbating existential threats to minorities
No full textWhile calls for system change ring loudly, the appetite for such change is defeated by vested interests. Set against the backdrop of climate crisis–induced scarcity, this chapter shows how fabricated majoritarianism driven by nationalism heightens existential risks to global minorities. It reflects how the last system reset (i.e. decolonisation) set in motion the inevitable consequences faced today, best reflected in the litmus test of minority treatment. Portraying decolonisation as akin to privatisation of an asset where hegemony is retained through majorities and preferential access, the chapter explains why the State, as currently configured, is unlikely to achieve the change needed. Drawing on older, pre-colonial histories, the chapter argues for a recalibration stemming from a sub-regional approach based on functionality rather than identity politics as a key element for securing a different future trajectory
Proteomic analysis reveals distinct cerebrospinal fluid signatures across genetic frontotemporal dementia subtypes
Get PDF‡ GENFI investigators are listed at the end of the paper (ORCiD https://orcid.org/0000-0002-9477-1812 ): GENFI authors: In addition to members of GENFI who are co-authors, the following members are collaborators who have contributed to the study design, the recruitment of participants, and the processing of samples at their sites, sending the samples and providing corresponding demographic data of their participants, data analysis, and interpretation: David L. Thomas, Thomas Cope, Timothy Rittman, Alberto Benussi, Enrico Premi, Roberto Gasparotti, Silvana Archetti, Stefano Gazzina, Valentina Cantoni, Andrea Arighi, Chiara Fenoglio, Elio Scarpini, Giorgio Fumagalli, Vittoria Borracci, Giacomina Rossi, Giorgio Giaccone, Giuseppe Di Fede, Paola Caroppo, Pietro Tiraboschi, Sara Prioni, Veronica Radaaelli, David Tang-Wai, Ekaterina Rogaeva, Michel Castelo-Branco, Morris Freedman, Ron Keren, Sandra Black, Sara Mitchell, Christen Shoesmith, Robart Bartha, Rosa Rademakers, Jackie Poos, Janne M. Papma, Lucia Giannini, Rick van Minkelen, Yolande Pijnenburg, Benedetta Nacmias, Camilla Ferrari, Cristina Polito, Gemma Lombardi, Valentina Bessi, Michele Veldsman, Christin Andersson, Hakan Thonberg, Linn Öijerstedt, Vesna Jelic, Paul Thompson, Tobias Langheinrich, Albert Lladó, Anna Antonell, Jaume Olives, Mircea Balasa, Nuria Bargalló, Sergi Borrego-Écija, Ana Verdelho, Carolina Maruta, Catarina B. Ferreira, Gabriel Miltenberger, Frederico Simões do Couto, Alazne Gabilondo, Jorge Villanua, Marta Cañada, Mikel Tainta, Miren Zulaica, Myriam Barandiaran, Patricia Alves, Benjamin Bender, Carlo Wilke, Lisa Graf, Annick Vogels, Mathieu Vandenbulcke, Philip van Damme, Rose Buffaerts, Koen Poesen, Pedro Rosa-Neto, Serge Gauthier, Agnès Camuzat, Alexis Brice, Anne Bertrand, Aurélie Funkiewiez, Daisy Rinaldi, Dario Saracino, Olivier Colliot, Sabrina Sayah, Catharina Prix, Elisabeth Wlasich, Olivia Wagemann, Sandra Loosli, Sonja Schönecker, Tobias Hoegen, Jolina Lombardi, Sarah Anderl-Straub, Adeline Rollin, Gregory Kuchcinski, Maxime Bertoux, Thibaud Lebouvier, Vincent Deramecourt, Beatriz Santiago, Diana Duro, Maria João Leitão, Maria Rosario Almeida, Miguel Tábuas-Pereira, Sónia Afonso.Editor’s summary:
Familial frontotemporal dementia (FTD) is caused by mutations in risk genes, most commonly C9orf72, MAPT, or GRN. Here, Sogorb-Esteve et al. used untargeted mass spectrometry of cerebrospinal fluid samples from presymptomatic and symptomatic carriers of these three risk genes to characterize distinct and shared proteomic alterations. Weighted gene coexpression network analysis allowed grouping FTD-dysregulated proteins into modules with high coexpression patterns, highlighting potentially dysregulated biological pathways, such as “core markers,” “synapse,” and “actin binding.” The expression of a subset of these modules was correlated with clinical scores. These results provide a useful resource for FTD research and disease marker development. —Daniela NeuhoferSupplementary Materials are available online at: https://www.science.org/doi/10.1126/scitranslmed.adm9654#supplementary-materials .We used an untargeted mass spectrometric approach, tandem mass tag proteomics, for the identification of proteomic signatures in genetic frontotemporal dementia (FTD). A total of 238 cerebrospinal fluid (CSF) samples from the Genetic FTD Initiative were analyzed, including samples from 107 presymptomatic (44 C9orf72, 38 GRN, and 25 MAPT) and 55 symptomatic (27 C9orf72, 17 GRN, and 11 MAPT) mutation carriers as well as 76 mutation-negative controls (“noncarriers”). We found shared and distinct proteomic alterations in each genetic form of FTD. Among the proteins significantly altered in symptomatic mutation carriers compared with noncarriers, we found that a set of proteins including neuronal pentraxin 2 and fatty acid binding protein 3 changed across all three genetic forms of FTD and patients with Alzheimer’s disease from previously published datasets. We observed differential changes in lysosomal proteins among symptomatic mutation carriers with marked abundance decreases in MAPT carriers but not other carriers. Further, we identified mutation-associated proteomic changes already evident in presymptomatic mutation carriers. Weighted gene coexpression network analysis combined with gene ontology annotation revealed clusters of proteins enriched in neurodegeneration and glial responses as well as synapse- or lysosome-related proteins indicating that these are the central biological processes affected in genetic FTD. These clusters correlated with measures of disease severity and were associated with cognitive decline. This study revealed distinct proteomic changes in the CSF of patients with genetic FTD, providing insights into the pathological processes involved in the disease. In addition, we identified proteins that warrant further exploration as diagnostic and prognostic biomarker candidates.Alzheimer's Association: ADSF-24-1284328-C;
Göteborgs Läkaresällskap: GLS-988641;
the Bluefield Project;
Race Against Dementia: ARUK-RADF2021A-003;
Swedish Research Council: 2023-00356;
European Union’s Horizon Europe research and innovation programme: 22HLT07;
Alzheimerfonden: AF-980746;
Stiftelsen för Gamla Tjänarinnor: 2022-01324.
This work was supported by a Race Against Dementia fellowship, supported by Alzheimer’s Research UK (ARUK-RADF2021A-003 to A.S.-E.) and the UK Dementia Research Institute, which receives its funding from DRI Ltd, funded by the UK Medical Research Council, Alzheimer’s Society and Alzheimer’s Research UK (to A.S.-E.). The Dementia Research Centre is supported by Alzheimer’s Research UK, Alzheimer's Society, Brain Research UK, and the Wolfson Foundation. Coauthors of the manuscript were supported by the Gothenburg Medical Society (Göteborgs Läkaresällskap, #GLS-988641 to J.S.). H.Z. is a Wallenberg scholar and a distinguished professor at the Swedish Research Council supported by grants from the Swedish Research Council (#2023-00356, #2022-01018, and #2019-02397); the European Union’s Horizon Europe research and innovation programme under grant agreement no. 101053962; Swedish State Support for Clinical Research (#ALFGBG-71320); the Alzheimer Drug Discovery Foundation (ADDF), USA (#201809-2016862); the AD Strategic Fund and the Alzheimer’s Association (#ADSF-21-831376-C, #ADSF-21-831381-C, #ADSF-21-831377-C, and #ADSF-24-1284328-C); the European Partnership on Metrology, cofinanced from the European Union’s Horizon Europe Research and Innovation Programme and by the participating states (NEuroBioStand, #22HLT07); the Bluefield Project; Cure Alzheimer’s Fund; the Olav Thon Foundation; the Erling-Persson Family Foundation; Familjen Rönströms Stiftelse; Stiftelsen för Gamla Tjänarinnor, Hjärnfonden, Sweden (#FO2022-0270); the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement no. 860197 (MIRIADE); the European Union Joint Programme—Neurodegenerative Disease Research (JPND2021-00694); the National Institute for Health and Care Research University College London Hospitals Biomedical Research Centre; and the UK Dementia Research Institute at UCL (UKDRI-1003). K.B. is supported by the Swedish Research Council (#2017-00915 and #2022-00732); the Swedish Alzheimer Foundation (#AF-930351, #AF-939721, and #AF-968270); Hjärnfonden, Sweden (#FO2017-0243 and #ALZ2022-0006); the Swedish state under the agreement between the Swedish government and the County Councils, the ALF-agreement (#ALFGBG-715986 and #ALFGBG-965240); the European Union Joint Program for Neurodegenerative Disorders (JPND2019-466-236); the Alzheimer’s Association 2021 Zenith Award (ZEN-21-848495); and the Alzheimer’s Association 2022-2025 grant (SG-23-1038904 QC). J.C.V.S. was supported by the Dioraphte Foundation grant 09-02-03-00, Association for Frontotemporal Dementias Research Grant 2009, Netherlands Organization for Scientific Research grant HCMI 056-13-018, ZonMw Memorabel (Deltaplan Dementie, project number 733 051 042), Alzheimer Nederland, and the Bluefield Project. F.M. received funding from the Tau Consortium and the Center for Networked Biomedical Research on Neurodegenerative Disease. R.S.-V. is supported by Alzheimer’s Research UK Clinical Research Training Fellowship (ARUK-CRF2017B-2) and has received funding from Fundació Marató de TV3, Spain (grant no. 20143810). D.G. received support from the EU Joint Programme–Neurodegenerative Disease Research and the Italian Ministry of Health (PreFrontALS) grant 733051042. C.G. received funding from EU Joint Programme–Neurodegenerative Disease Research-Prefrontals VR Dnr 529-2014-7504, VR 2015-02926, and 2018-02754; the Swedish FTD Inititative-Schörling Foundation; Alzheimer Foundation; Brain Foundation; and Stockholm County Council ALF. M.M. has received funding from a Canadian Institute of Health Research operating grant and the Weston Brain Institute and Ontario Brain Institute. J.B.R. has received funding from the Wellcome Trust (220258) and the Bluefield Project and is supported by the Cambridge University Centre for Frontotemporal Dementia, the Medical Research Council (MC_UU_00030/14; MR/T033371/1), and the National Institute for Health Research Cambridge Biomedical Research Centre (NIHR203312). E.F. has received funding from a Canadian Institute of Health Research grant #327387. RV has received funding from the Mady Browaeys Fund for Research into Frontotemporal Dementia. J.L. received funding for this work by the Deutsche Forschungsgemeinschaft German Research Foundation under Germany’s Excellence Strategy within the framework of the Munich Cluster for Systems Neurology (EXC 2145 SyNergy—ID 390857198). M.O. has received funding from Germany’s Federal Ministry of Education and Research (BMBF). J.D.R. is supported by the Bluefield Project and the National Institute for Health and Care Research University College London Hospitals Biomedical Research Centre and has received funding from an MRC Clinician Scientist Fellowship (MR/M008525/1) and a Miriam Marks Brain Research UK Senior Fellowship. J.G. is supported by Alzheimerfonden (AF-980746) and Stiftelsen för Gamla tjänarinnor (2022-01324). Several authors of this publication are members of the European Reference Network for Rare Neurological Diseases (ERN-RND) - Project ID no. 739510 to J.C.V.S., M.S., R.S.V., A.d.M., M.O., R.V., and J.D.R. This work was also supported by the EU Joint Programme—Neurodegenerative Disease Research GENFI-PROX grant (2019-02248, to J.D.R., M.O., B.B., C.G., J.C.V.S., and M.S.) and by the Clinician Scientist programme “PRECISE.net” funded by the Else Kröner-Fresenius-Stiftung (to M.S.)
Intelligent Resource Allocation via Hybrid Reinforcement Learning in 5G Network Slicing
Get PDFManufacturers are focusing on reconfigurable, resilient environments for Industry 5.0 paradigms. Applications like digital twins and mobile robots require communication networks to meet latency, bandwidth, and reliability requirements. Beyond 5G (B5G) networks provide unprecedented communications performance and flexibility through virtualization and network slicing, which generates various logical partitions for particular applications with specific requirements. RAN slicing is an essential section of 5G network slicing due to its vulnerability to errors, affecting its ability to meet stringent reliability requirements. This paper presents a novel framework for optimizing resource allocation in 5G network slicing by integrating Double Deep Q-Network with Prioritized Experience Replay (DDQN-PER) and Pointer Network-based Long Short-Term Memory (PtrNet-LSTM). The proposed framework dynamically adjusts the attention coefficient, balancing Service Satisfaction Level (SSL) and Quality of Experience (QoE), improving system efficiency, spectrum efficiency, and user connectivity across diverse user scenarios. The experiment illustrates that the combined PtrNet-LSTM framework within DDQN-PER outperforms the baseline methods in terms of spectrum efficiency and user connectivity, demonstrating scalability and the potential to address challenges in dynamic wireless networks.10.13039/501100006540-Department of Electronic and Electrical Engineering, Brunel University London, U.K
Biorefinery-Based Energy Recovery from Algae: Comparative Evaluation of Liquid and Gaseous Biofuels
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The original contributions presented in this study are included in the article. Further inquiries can be directed to the corresponding author.In recent years, biofuels and bioenergy derived from algae have gained increasing attention, fueled by the growing demand for renewable energy sources and the urgent need to lower CO2 emissions. This research examines the generation of bioethanol and biomethane using freshly harvested and sedimented algal biomass. Employing a factorial experimental design, various trials were conducted, with ethanol yield as the primary optimization target. The findings indicated that the sodium hydroxide concentration during pretreatment and the amylase dosage in enzymatic hydrolysis were key parameters influencing the ethanol production efficiency. Under optimized conditions—using 0.3 M NaOH, 25 μL/g starch, and 250 μL/g cellulose—fermentation yielded ethanol concentrations as high as 2.75 ± 0.18 g/L (45.13 ± 2.90%), underscoring the significance of both enzyme loading and alkali treatment. Biomethane potential tests on the residues of fermentation revealed reduced methane yields in comparison with the raw algal feedstock, with a peak value of 198.50 ± 25.57 mL/g volatile solids. The integrated process resulted in a total energy recovery of up to 809.58 kWh per tonne of algal biomass, with biomethane accounting for 87.16% of the total energy output. However, the energy recovered from unprocessed biomass alone was nearly double, indicating a trade-off between sequential valorization steps. A comparison between fresh and dried feedstocks also demonstrated marked differences, largely due to variations in moisture content and biomass composition. Overall, this study highlights the promise of integrated algal biomass utilization as a viable and energy-efficient route for sustainable biofuel production.This project has been funded by the European Union’s Horizon 2020 research and innovation program under grant agreement No. 101084405 (CRONUS)
Sativex (nabiximols) for the treatment of Agitation & Aggression in Alzheimer’s dementia in UK nursing homes: a randomised, double-blind, placebo-controlled feasibility trial
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A de-identified version of the dataset for meta-analyses or analyses will be available with investigator support from 1 year after the publication via [email protected]. Written proposals will be assessed by members of the King’s Clinical Trials Unit committee, and a decision about the appropriateness of the use of data will be made. A data sharing agreement would need to be put in place before any data is shared.Supplementary data are available online at: https://academic.oup.com/ageing/article/54/6/afaf149/8158002#supplementary-data .Background:
Alzheimer’s Disease (AD) patients often experience clinically significant agitation, leading to distress, increased healthcare costs and earlier institutionalisation. Current treatments have limited efficacy and significant side effects. Cannabinoid-based therapies, such as the nabiximols oral spray (Sativex®; 1:1 delta-9-tetrahydrocannabinol and cannabidiol), offer potential alternatives. We aimed to explore the feasibility and safety of nabiximols as a potential treatment for agitation in AD.
Methods:
The ‘Sativex® for Agitation & Aggression in Alzheimer’s Dementia’ (STAND) trial was a randomised, double-blind, placebo-controlled, feasibility study conducted in UK care homes. Participants with probable AD and predefined clinically significant agitation were randomised to receive placebo or nabiximols for 4 weeks on an up-titrated schedule, followed by a 4-week observation period. To be considered feasible, we prespecified the following thresholds that needed to be met: randomising 60 participants within 12 months, achieving a ≥ 75% follow-up rate at 4 weeks, maintaining ≥80% adherence to allocation and estimating a minimum effect size (Cohen’s d ≥ 0.3) on the Cohen–Mansfield Agitation Inventory. This trial is registered with ISRCTN 7163562.
Findings:
Between October 2021 and June 2022, 53 candidates were assessed; 29 met eligibility criteria and were randomised. No participants withdrew, and adherence was high (100%) and was generally feasible to deliver. The intervention was well tolerated (0 adverse reactions), with no safety concerns reported.
Interpretation:
Despite significant COVID-19 pandemic related challenges, administering nabiximols through oral mucosa to advanced AD patients with agitation demonstrated feasibility and safety. These findings support a larger confirmatory efficacy trial to evaluate the potential therapeutic efficacy of nabiximols for agitation in AD.This research is funded by Alzheimer’s Research UK [Registered Charity No: 207711 (England and Wales), SC041156 (Scotland)] and Global Clinical Trials Fund. Additional support is supplied from the Maudsley NIHR BRC, the NIHR Clinical Research Network and Ageing Research at King’s (www.kcl.ac.uk/ark)
An integrated numerical modelling framework for simulation of the multiphysics in sonoprocessing of materials
Get PDFSupplementary data are available online at: https://www.sciencedirect.com/science/article/pii/S135041772500207X#s0090 .This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.We have designed, developed, and integrated a comprehensive mathematical and numerical modelling framework for simulations of the complex physics and highly dynamic phenomena that occur across different length and time scale in the processes of sonochemistry and sonication of materials. The framework comprises three interconnected sub-models: (1) a bubble oscillation and implosion model, (2) a shock wave emission and propagation model, and (3) a wave–structure interaction (WSI) model. Firstly, we described in detail the governing equations, numerical schemes, boundary and initial conditions used in each sub-model with a particular emphasis on the data mapping methods for numerically linking the three sub-model together. Then, we present a number of simulation cases to demonstrate the power and usefulness of the model. We also did systematic model validation and calibration using the in-situ and real-time collected big X-ray image data. This is the first time such comprehensive and high-fidelity numerical models have been achieved for sonoprocessing of materials. Complementary to the most advanced in-situ and operando experiments, the integrated model is an indispensable modelling tool for computational studies and optimization of the ultrasound-assisted chemical synthesis and sonoprocessing of materials.The authors would like to acknowledge the financial support from the UK Engineering and Physical Sciences Research Council (Grant Nos. EP/R031819/1; EP/R031665/1; EP/R031401/1; EP/R031975/1)
Reputation-based Distributed Filtering Over Sensor Networks Subject to Stochastic Nonlinearity and Network-Induced Quantization
Get PDFIn sensor networks, due to inevitable sensor faults, malfunctions, or deliberate attacks, sensors may transmit erroneous, inaccurate, or misleading data, thereby degrading overall system performance. To address this issue, an effective approach is to assign reputation scores to sensors based on their trustworthiness, historical performance, or reliability. In this paper, the reputation-based distributed filtering (RBDF) problem is considered for a class of stochastic nonlinear systems over sensor networks with network-induced quantization. A reputation mechanism is employed to mitigate the adverse effects caused by noisy, faulty, or malicious sensors. Specifically, reputations are allocated by each sensor to the data received from its neighbors, ensuring that abnormal data are assigned smaller reputation values and may even be discarded. For the first time, a recursive RBDF algorithm is proposed, wherein an upper bound of the filtering error covariance (UBFEC) is derived by solving two matrix equations. Subsequently, the filter gain is determined by minimizing the trace of UBFEC at each step. Furthermore, a sufficient condition is presented to ensure the uniform boundedness of the filtering error dynamics. Finally, a simulation example is provided to verify the feasibility and validity of the developed RBDF algorithm.10.13039/501100001809-National Natural Science Foundation of China (Grant Number: 12301567, 12471416 and 61933007);
10.13039/501100005046-Natural Science Foundation of Heilongjiang Province (Grant Number: PL2024F015);
Fundamental Research Foundation for Universities of Heilongjiang Province of China (Grant Number: 2022-KYYWF-0141);
Royal Society of the U.K.;
Alexander von Humboldt Foundation of Germany
Effects of interventions on sedentary behaviour and cardiovascular disease biomarkers in individuals with spinal cord injury: a systematic review
No full textData availability statement:
All data associated with this review can be found within the included published articles.Supplemental material:is available online at: https://www.tandfonline.com/doi/full/10.1080/09638288.2025.2592500# .A preprint version of the article is available on Open Science Framework (OSF) at: https://osf.io/5dwm6_v1/ under a Creative Commons Attribution 4.0 International Public License. It has not been certified by peer review.Purpose:
Reducing sedentary behaviour may be an intervention target to improve cardiovascular health in individuals with spinal cord injury. The aim of this study was to systematically review the effects of interventions on sedentary behaviour and cardiovascular disease biomarkers in individuals with paraplegia.
Materials and methods:
Following prospective protocol registration (CRD42023420260), eleven sources were searched to identify articles, which were screened by two reviewers. Eligible articles included participants with paraplegia, interventions targeting physical activity and/or sedentary behaviour and studies that measured sedentary behaviour and cardiovascular disease biomarkers. Quality of evidence was assessed for each outcome.
Results:
Two interventions targeting sedentary behaviour and six targeting physical activity were included. One intervention targeting sedentary behaviour and one targeting physical activity reduced sedentary behaviour. Two interventions targeting sedentary behaviour and three targeting physical activity improved cardiovascular disease biomarkers. Quality of evidence was very low for sedentary behaviour and moderate for cardiovascular disease biomarker outcomes.
Conclusions:
Sedentary behaviour was not improved by physical activity interventions but these interventions may improve cardiovascular disease biomarkers in individuals with paraplegia. Interventions targeting sedentary behaviour, although limited, show potential effectiveness for improving cardiovascular disease biomarkers; such interventions require further investigation to inform public health and clinical care guidelines.
IMPLICATIONS FOR REHABILITATION:
• Physical activity interventions are not effective for reducing sedentary behaviour in individuals with paraplegia
• Evidence regarding interventions targeting sedentary behaviour is limited, but such interventions show some potential effectiveness
• Interventions targeting sedentary behaviour in paraplegia should be investigated further to inform their relevance for rehabilitationThe author(s) reported there is no funding associated with the work featured in this article
Data sources:
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