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Skip search results from other journals and go to results- 4 Journal of Medical Internet Research
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Finally, we calculated Cohen d effect sizes (0.20=small, 0.50=medium, and 0.80=large) [64] to aid interpretation.
Across the daily assessments, a similar multilevel modeling approach was used to take advantage of the repeated-measures design. All multilevel models included random intercepts at the participant level and fixed effects of each predictor.
JMIR Form Res 2025;9:e68292
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In a previous single-arm ER pilot study involving mixed etiology chronic pain, a sample size of 57 participants was needed to detect a significant time effect on pain catastrophizing scores at 1 month post treatment (Cohen d=1.15, large effect) [46]. In addition, when conducting a repeated-measures ANOVA with a prior in-person randomized controlled trial (RCT) ER class data only [25], a sample size of 52 was needed to detect a significant time effect.
JMIR Res Protoc 2024;13:e53784
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Effect sizes for the Ease VRx vs sham VR between-group comparison used the standardized mean difference version of Cohen d [17].
For each outcome variable, the effect size of the change pretreatment to 6 months posttreatment was assessed by treatment group using a repeated measures variation of Cohen d as drm owing to the within-subject nature of the comparison [17]. We applied common effect size thresholds of 0.3 (small), 0.5 (medium), and 0.8 (large).
J Med Internet Res 2022;24(5):e37480
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Effect sizes for web-based interventions for chronic pain have been estimated to range from small to moderate (Cohen d range 0.04-1.23) [18]. In addition to CBT, existing web-based interventions for patients with pain include compassionate mind training [22], social media–based web-based community intervention [23], pain self-management [24], and hypnosis [25].
J Med Internet Res 2021;23(9):e29672
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While CBT has not shown efficacy for reducing pain intensity, it has small to moderate effects for reducing depressive symptoms [7], pain bothersomeness [6,7], and pain catastrophizing [6,7] (Darnall et al, unpublished data) in mixed etiology chronic pain as well as c LBP.
J Med Internet Res 2021;23(2):e26292
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In the originally published paper, the list of authors appeared as follows:
Laura Garcia, Beth Darnall, Parthasarathy Krishnamurthy, Ian Mackey, Josh Sackman, Robert Louis, Todd Maddox, Brandon Birckhead
The list has been corrected as follows:
Laura M Garcia, Beth D Darnall, Parthasarathy Krishnamurthy, Ian G Mackey, Josh Sackman, Robert G Louis, Todd Maddox, Brandon J Birckhead
The correction will appear in the online version of the paper on the JMIR Publications website on February 12, 2021, together with
JMIR Res Protoc 2021;10(2):e27652
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However, we note that people with c LBP often report having 2 or more comorbid pain conditions (Darnall et al, unpublished). As such, chronic back pain is not often experienced in isolation.
Digital behavioral health treatment studies typically report relatively low treatment engagement rates among participants with rates ranging between 20% and 60% [32,58-60].
JMIR Res Protoc 2021;10(1):e25291
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Posttreatment effect sizes (baseline to treatment completion at day 21) were computed by treatment group using an adaptation of Cohen d to suit the repeated measures design [49].
The four-item PCS and two-item PSEQ scales were analyzed in a mixed modeling framework, except that there were only 2 time points (baseline day 0 and day 22).
JMIR Form Res 2020;4(7):e17293
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