App-delivered self-management intervention trial selfBACK for people with low back pain: protocol for implementation and process evaluation

Background: Implementation and process evaluation is vital for understanding how interventions function in different settings, including if and why interventions have different effects or do not work at all. Objective: This paper presents the protocol for an implementation and process evaluation embedded in a multicenter randomized controlled trial conducted in Denmark and Norway (the selfBACK project). selfBACK is a data-driven decision support system that provides participants with weekly self-management plans for low back pain. These plans are delivered through a smartphone app and tailored to individual participants by using case-based reasoning methodology. In the trial, we compare selfBACK in addition to usual care with usual care alone. Methods: The aim of this study is to conduct a convergent mixed-methods implementation and process evaluation of the selfBACK app by following the reach, effectiveness, adoption, implementation, and maintenance framework. We will evaluate the process of implementing selfBACK and investigate how participants use the intervention in daily life. The evaluation will also cover the reach of the intervention, health care provider willingness to adopt it, and participant satisfaction with the intervention. We will gather quantitative measures by questionnaires and measures of data analytics on app use and perform a qualitative exploration of the implementation using semistructured interviews theoretically informed by normalization process theory. Data collection will be conducted between March 2019 and October 2020. Results: The trial opened for recruitment in February 2019. This mixed-methods implementation and evaluation study is embedded in the randomized controlled trial and will be collecting data from March 2019 to October 2020; dissemination of trial results is planned thereafter. The results from the process evaluation are expected 2021-2022. Conclusions: This study will provide a detailed understanding of how self-management of low back pain can be improved and how a digital health intervention can be used as an add-on to usual care to support patients to self-manage their low back pain. We will provide knowledge that can be used to explore the possibilities of extending the generic components of the selfBACK system and key drivers that could be of use in other conditions and diseases where self-management is an essential prevention or treatment strategy. Trial Registration: ClinicalTrials.gov NCT03798288; https://www.clinicaltrials.gov/ct2/show/NCT03798288 International Registered Report Identifier (IRRID): DERR1-10.2196/20308

An app-delivered self-management program for people with low back pain: protocol for the selfBACK randomized controlled trial.

Background: Low back pain (LBP) is prevalent across all social classes, in all age groups, and across industrialized and developing countries. From a global perspective, LBP is considered the leading cause of disability and negatively impacts everyday life and well-being. Self-management is a recommended first-line treatment, and mobile apps are a promising platform to support self-management of conditions like LBP. In the selfBACK project, we have developed a digital decision support system made available for the user via an app intended to support tailored self-management of nonspecific LBP. Objective: The trial aims to evaluate the effectiveness of using the selfBACK app to support self-management in addition to usual care (intervention group) versus usual care only (control group) in people with nonspecific LBP. Methods: This is a single-blinded, randomized controlled trial (RCT) with two parallel arms. The selfBACK app provides tailored self-management plans consisting of advice on physical activity, physical exercises, and educational content. Tailoring of plans is achieved by using case-based reasoning (CBR) methodology, which is a branch of artificial intelligence. The core of the CBR methodology is to use data about the current case (participant) along with knowledge about previous and similar cases to tailor the self-management plan to the current case. This enables a person-centered intervention based on what has and has not been successful in previous cases. Participants in the RCT are people with LBP who consulted a health care professional in primary care within the preceding 8 weeks. Participants are randomized to using the selfBACK app in addition to usual care versus usual care only. We aim to include a total of 350 participants (175 participants in each arm). Outcomes are collected at baseline, 6 weeks, and 3, 6, and 9 months. The primary end point is difference in pain-related disability between the intervention group and the control group assessed by the Roland-Morris Disability Questionnaire at 3 months. Results: The trial opened for recruitment in February 2019. Data collection is expected to be complete by fall 2020, and the results for the primary outcome are expected to be published in fall 2020. Conclusions: This RCT will provide insights regarding the benefits of supporting tailored self-management of LBP through an app available at times convenient for the user. If successful, the intervention has the potential to become a model for the provision of tailored self-management support to people with nonspecific LBP and inform future interventions for other painful musculoskeletal conditions

Effectiveness of app-delivered, tailored self-management support for adults with lower back pain–related disability

Importance: Lower back pain (LBP) is a prevalent and challenging condition in primary care. The effectiveness of an individually tailored self-management support tool delivered via a smartphone app has not been rigorously tested. Objective: To investigate the effectiveness of selfBACK, an evidence-based, individually tailored self-management support system delivered through an app as an adjunct to usual care for adults with LBP-related disability. Design, Setting, and Participants: This randomized clinical trial with an intention-to-treat data analysis enrolled eligible individuals who sought care for LBP in a primary care or an outpatient spine clinic in Denmark and Norway from March 8 to December 14, 2019. Participants were 18 years or older, had nonspecific LBP, scored 6 points or higher on the Roland-Morris Disability Questionnaire (RMDQ), and had a smartphone and access to email. Interventions: The selfBACK app provided weekly recommendations for physical activity, strength and flexibility exercises, and daily educational messages. Self-management recommendations were tailored to participant characteristics and symptoms. Usual care included advice or treatment offered to participants by their clinician. Main Outcomes and Measures: Primary outcome was the mean difference in RMDQ scores between the intervention group and control group at 3 months. Secondary outcomes included average and worst LBP intensity levels in the preceding week as measured on the numerical rating scale, ability to cope as assessed with the Pain Self-Efficacy Questionnaire, fear-avoidance belief as assessed by the Fear-Avoidance Beliefs Questionnaire, cognitive and emotional representations of illness as assessed by the Brief Illness Perception Questionnaire, health-related quality of life as assessed by the EuroQol-5 Dimension questionnaire, physical activity level as assessed by the Saltin-Grimby Physical Activity Level Scale, and overall improvement as assessed by the Global Perceived Effect scale. Outcomes were measured at baseline, 6 weeks, 3 months, 6 months, and 9 months. Results: A total of 461 participants were included in the analysis; the population had a mean [SD] age of 47.5 [14.7] years and included 255 women (55%). Of these participants, 232 were randomized to the intervention group and 229 to the control group. By the 3-month follow-up, 399 participants (87%) had completed the trial. The adjusted mean difference in RMDQ score between the 2 groups at 3 months was 0.79 (95% CI, 0.06-1.51; P = .03), favoring the selfBACK intervention. The percentage of participants who reported a score improvement of at least 4 points on the RMDQ was 52% in the intervention group vs 39% in the control group (adjusted odds ratio, 1.76; 95% CI, 1.15-2.70; P = .01). Conclusions and Relevance Among adults who sought care for LBP in a primary care or an outpatient spine clinic, those who used the selfBACK system as an adjunct to usual care had reduced pain-related disability at 3 months. The improvement in pain-related disability was small and of uncertain clinical significance. Process evaluation may provide insights into refining the selfBACK app to increase its effectiveness. Trial Registration ClinicalTrials.gov Identifier: NCT0379828

DataSheet_1_T-DNA characterization of genetically modified 3-R-gene late blight-resistant potato events with a novel procedure utilizing the Samplix Xdrop® enrichment technology.pdf

Before the commercialization of genetically modified crops, the events carrying the novel DNA must be thoroughly evaluated for agronomic, nutritional, and molecular characteristics. Over the years, polymerase chain reaction-based methods, Southern blot, and short-read sequencing techniques have been utilized for collecting molecular characterization data. Multiple genomic applications are necessary to determine the insert location, flanking sequence analysis, characterization of the inserted DNA, and determination of any interruption of native genes. These techniques are time-consuming and labor-intensive, making it difficult to characterize multiple events. Current advances in sequencing technologies are enabling whole-genomic sequencing of modified crops to obtain full molecular characterization. However, in polyploids, such as the tetraploid potato, it is a challenge to obtain whole-genomic sequencing coverage that meets the regulatory approval of the genetic modification. Here we describe an alternative to labor-intensive applications with a novel procedure using Samplix Xdrop® enrichment technology and next-generation Nanopore sequencing technology to more efficiently characterize the T-DNA insertions of four genetically modified potato events developed by the Feed the Future Global Biotech Potato Partnership: DIA_MSU_UB015, DIA_MSU_UB255, GRA_MSU_UG234, and GRA_MSU_UG265 (derived from regionally important varieties Diamant and Granola). Using the Xdrop® /Nanopore technique, we obtained a very high sequence read coverage within the T-DNA and junction regions. In three of the four events, we were able to use the data to confirm single T-DNA insertions, identify insert locations, identify flanking sequences, and characterize the inserted T-DNA. We further used the characterization data to identify native gene interruption and confirm the stability of the T-DNA across clonal cycles. These results demonstrate the functionality of using the Xdrop® /Nanopore technique for T-DNA characterization. This research will contribute to meeting regulatory safety and regulatory approval requirements for commercialization with small shareholder farmers in target countries within our partnership.</p

Verfahrensentwicklung zur fernerkundungsbasierten Erstellung des Waldverzeichnisses Thueringen

SIGLEAvailable from TIB Hannover: F03B1399 / FIZ - Fachinformationszzentrum Karlsruhe / TIB - Technische InformationsbibliothekDeutsche Gesellschaft fuer Luft- und Raumfahrt e.V., Bonn (Germany)DEGerman

Barriers and facilitators to patient uptake and utilisation of digital interventions for the self-management of low back pain: a systematic review of qualitative studies.

Objectives: Low back pain (LBP) is a leading contributor to disability globally. Self-management is a core component of LBP management. We aimed to synthesise published qualitative literature concerning digital health interventions (DHIs) to support LBP self-management to: (1) determine engagement strategies, (2) identify barriers and facilitators affecting patient uptake/utilisation and (3) develop a preliminary conceptual model of barriers and facilitators to uptake/utilisation. Design: Systematic review following PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. Data sources: MEDLINE, Embase, CINAHL, PsycINFO, Cochrane Library, DoPHER, TRoPHI, Web of Science and OT Seeker, from January 2000 to December 2018, using the concepts: LBP, DHI and self-management. Eligibility criteria: Peer-reviewed qualitative study (or component) examining engagement with, or barriers and/or facilitators to the uptake/utilisation of an interactive DHI for self-management of LBP in adults (community, primary or secondary care settings). Data extraction and synthesis: Standardised data extraction form was completed. COREQ (Consolidated criteria for Reporting Qualitative research) checklist was used to assess methodology. Data was synthesised narratively for engagement strategies, thematically for barriers/facilitators to uptake/utilisation and normalisation process theory was applied to produce a conceptual model. Results: We identified 14 191 citations, of which 105 full-text articles were screened, and five full-text articles from four studies included. These were from community and primary care contexts in Europe and the USA, and involved 56 adults with LBP and 19 healthcare professionals. There was a lack of consideration on how to sustain engagement with DHIs. Examination of barriers and facilitators for uptake/utilisation identified four major themes: IT (information technology) usability–accessibility; quality–quantity of content; tailoring–personalisation; and motivation–support. These themes informed the development of a preliminary conceptual model for uptake/utilisation of a DHI for LBP self-management. Conclusions: We highlight key barriers and facilitators that should be considered when designing DHIs for LBP self-management. Our findings are in keeping with reviews of DHIs for other long-term conditions, implying these findings may not be condition specific

App-Delivered Self-Management Intervention Trial selfBACK for People With Low Back Pain: Protocol for Implementation and Process Evaluation

Background: Implementation and process evaluation is vital for understanding how interventions function in different settings, including if and why interventions have different effects or do not work at all. Objective: This paper presents the protocol for an implementation and process evaluation embedded in a multicenter randomized controlled trial conducted in Denmark and Norway (the selfBACK project). selfBACK is a data-driven decision support system that provides participants with weekly self-management plans for low back pain. These plans are delivered through a smartphone app and tailored to individual participants by using case-based reasoning methodology. In the trial, we compare selfBACK in addition to usual care with usual care alone. Methods: The aim of this study is to conduct a convergent mixed-methods implementation and process evaluation of the selfBACK app by following the reach, effectiveness, adoption, implementation, and maintenance framework. We will evaluate the process of implementing selfBACK and investigate how participants use the intervention in daily life. The evaluation will also cover the reach of the intervention, health care provider willingness to adopt it, and participant satisfaction with the intervention. We will gather quantitative measures by questionnaires and measures of data analytics on app use and perform a qualitative exploration of the implementation using semistructured interviews theoretically informed by normalization process theory. Data collection will be conducted between March 2019 and October 2020. Results: The trial opened for recruitment in February 2019. This mixed-methods implementation and evaluation study is embedded in the randomized controlled trial and will be collecting data from March 2019 to October 2020; dissemination of trial results is planned thereafter. The results from the process evaluation are expected 2021-2022. Conclusions: This study will provide a detailed understanding of how self-management of low back pain can be improved and how a digital health intervention can be used as an add-on to usual care to support patients to self-manage their low back pain. We will provide knowledge that can be used to explore the possibilities of extending the generic components of the selfBACK system and key drivers that could be of use in other conditions and diseases where self-management is an essential prevention or treatment strategy