Evidence map›Paper›PMID 39136855›Full record

ArticleApplied psychophysiology and biofeedback2024

Brief Report: Baseline HRV Time Domain Parameters Predict Trauma and Depression Symptom Change in Veterans with PTSD Undergoing Biofeedback.

Donna L Schuman, Pavleta Ognyanova, J P Ginsberg, Debra K Moser

Abstract read
PubMed Publisher
In one paragraph

Article in Applied psychophysiology and biofeedback, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–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

2 citing papers in PubMed.

  1. Review
  2. 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

4 authors.

Donna L SchumanSchool of Social Work, University of Texas at Arlington, Box 19129, Arlington, TX, USA. donna.schuman@uta.edu.ORCID 0000-0001-9340-3121
Pavleta OgnyanovaPrivate Practice, Sofia, Bulgaria.
J P GinsbergSaybrook University, Oakland, USA.ORCID 0000-0002-8375-2288
Debra K MoserUniversity of Kentucky, Lexington, USA.ORCID 0000-0003-2727-5920

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Heart rate variability (HRV) is an index of cardiac autonomic function and an objective biomarker for stress and health. Improving HRV through biofeedback has proven effective in reducing symptoms of posttraumatic stress disorder (PTSD) and depression in veteran populations. Brief protocols involving fewer sessions can better maximize limited clinic resources; however, there is a dearth of knowledge on the number of clinical sessions needed to significantly reduce trauma and depression symptoms. We conducted a series of linear regression models using baseline, post-intervention, and follow-up data from intervention group participants (N = 18) who engaged in a pilot waitlist-controlled study testing the efficacy of a 3-session mobile app-adapted HRV biofeedback intervention for veterans with PTSD. Based on Nunan et al. (Pacing and Clinical Electrophysiology 33:1407-1417, 2010) short-term norms, we found that pre-intervention RMSSD in the normal range significantly predicted PTSD and depression symptom improvement. Findings suggest the utility of baseline RMSSD as a useful metric for predicting HRV biofeedback treatment outcomes for veterans with PTSD and comorbid depression. Those with below-normal baseline RMSSD may likely need additional sessions or an alternative treatment to show clinically meaningful symptom improvement.

Indexed as

Biofeedback, PsychologyDepressionHeart RateStress Disorders, Post-TraumaticVeteransAdultFemaleHumansMaleMiddle AgedPilot ProjectsBiofeedbackHeart rate variabilityPosttraumatic stressVeterans

Identifiers

PMID39136855

What OpenQuestion holds

Textmetadata
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.