Evidence map›Paper›PMID 34807837›Full record

ReviewJMIR rehabilitation and assistive technologies2021

Digital Therapeutic Care and Decision Support Interventions for People With Low Back Pain: Systematic Review.

Daniel Lewkowicz, Tamara Slosarek, Sarah Wernicke, Antonia Winne, Attila M Wohlbrandt, Erwin Bottinger

Abstract readReview
In one paragraph

Review in JMIR rehabilitation and assistive technologies, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
24citing papers in PubMed, 2 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

24 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Trial
  4. Trial
  5. Trial
  6. Article
  7. Review
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. British journal of pain · 2024
    Article
  16. Article
  17. Review
  18. Article
  19. Article
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Daniel LewkowiczDigital Health Center, Hasso Plattner Institute, University of Potsdam, Potsdam, Germany.ORCID https://orcid.org/0000-0002-3167-8741
Tamara SlosarekDigital Health Center, Hasso Plattner Institute, University of Potsdam, Potsdam, Germany.ORCID https://orcid.org/0000-0003-1514-1706
Sarah WernickeDigital Health Center, Hasso Plattner Institute, University of Potsdam, Potsdam, Germany.ORCID https://orcid.org/0000-0001-8127-1969
Antonia WinneDigital Health Center, Hasso Plattner Institute, University of Potsdam, Potsdam, Germany.ORCID https://orcid.org/0000-0002-4515-0518
Attila M WohlbrandtDigital Health Center, Hasso Plattner Institute, University of Potsdam, Potsdam, Germany.ORCID https://orcid.org/0000-0001-6476-3451
Erwin BottingerDigital Health Center, Hasso Plattner Institute, University of Potsdam, Potsdam, Germany.ORCID https://orcid.org/0000-0001-6868-6676

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundLow back pain (LBP) is the leading cause of worldwide years lost because of disability, with a tremendous economic burden for health care systems. Digital therapeutic care (DTC) programs provide a scalable, universally accessible, and low-cost approach to the multidisciplinary treatment of LBP. Moreover, novel decision support interventions such as personalized feedback messages, push notifications, and data-driven activity recommendations amplify DTC by guiding the user through the program while aiming to increase overall engagement and sustainable behavior change.

objectiveThis systematic review aims to synthesize recent scientific literature on the impact of DTC apps for people with LBP and outline the implementation of add-on decision support interventions, including their effect on user retention and attrition rates.

methodsWe searched bibliographic databases, including MEDLINE, Cochrane Library, Web of Science, and the Physiotherapy Evidence Database, from March 1, 2016, to October 15, 2020, in accordance with the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines and conducted this review based on related previously published systematic reviews. Besides randomized controlled trials (RCTs), we also included study designs with the evidence level of at least a retrospective comparative study. This enables the consideration of real-world user-generated data and provides information regarding the adoption and effectiveness of DTC apps in a real-life setting. For the appraisal of the risk of bias, we used the Risk of Bias 2 Tool and the Risk of Bias in Non-Randomized Studies of Interventions Tool for the RCTs and nonrandomized trials, respectively. The included studies were narratively synthesized regarding primary and secondary outcome measures, DTC components, applied decision support interventions, user retention, and attrition rates.

resultsWe retrieved 1388 citations, of which 12 studies are included in this review. Of the 12 studies, 6 (50%) were RCTs and 6 (50%) were nonrandomized trials. In all included studies, lower pain levels and increased functionality compared with baseline values were observed in the DTC intervention group. A between-group comparison revealed significant improvements in pain and functionality levels in 67% (4/6) of the RCTs. The study population was mostly homogeneous, with predominantly female, young to middle-aged participants of normal to moderate weight. The methodological quality assessment revealed moderate to high risks of biases, especially in the nonrandomized trials.

conclusionsThis systematic review demonstrates the benefits of DTC for people with LBP. There is also evidence that decision support interventions benefit overall engagement with the app and increase participants' ability to self-manage their recovery process. Finally, including retrospective evaluation studies of real-world user-generated data in future systematic reviews of digital health intervention trials can reveal new insights into the benefits, challenges, and real-life adoption of DTC programs.

Indexed as

backbehavior change techniquesdecision supportdecision support interventionsdigital therapeutic caredigital therapylow back painmobile phoneorthopedicsystematic review

Identifiers

PMID34807837
PMCPMC8663573

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.