Comparison of video-assisted CPR using the LINE application and telephone-assisted CPR: a randomized controlled simulation trial.

Comparison of video-assisted CPR using the LINE application and telephone-assisted CPR: a randomized controlled simulation trial - PMC Skip to main content An official website of the United States government Here's how you know Here's how you know Search Log in Primary site navigation Search Log in Search PMC Full-Text Archive Search in PMC Journal List User Guide As a library, NLM provides access to scientific literature. Inclusion in an NLM database does not imply endorsement of, or agreement with, the contents by NLM or the National Institutes of Health. Learn more: PMC Disclaimer | PMC Copyright Notice BMC Emerg Med . 2026 Apr 21;26:163. doi: 10.1186/s12873-026-01591-y Comparison of video-assisted CPR using the LINE application and telephone-assisted CPR: a randomized controlled simulation trial Muthita Munsongthum 1 , Thanat Tangpaisarn 2 , Tai Luanghvisut 1 , Pinhatai Pakirana 1 , Ploypailin Wintasombut 1 , Konglar Saenpan 3 , Sumana Sriphrom 3 , Pariwat Phungoen 2, ✉ Author information Article notes Copyright and License information 1 Faculty of Medicine, Khon Kaen University, Khon Kaen, Thailand 2 Department of Emergency Medicine, Faculty of Medicine, Khon Kaen University, Khon Kaen, Thailand 3 CPR Training Unit, Faculty of Medicine, Khon Kaen University, Khon Kaen, Thailand ✉ Corresponding author. Received 2025 Sep 1; Accepted 2026 Apr 16; Collection date 2026. © The Author(s) 2026 Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/ . PMC Copyright notice PMCID: PMC13231593  PMID: 42015035 Abstract Background Dispatcher-assisted cardiopulmonary resuscitation (DA-CPR) is associated with improved bystander CPR performance and outcomes in out-of-hospital cardiac arrest (OHCA). However, the optimal method for delivering DA-CPR—telephone-assisted CPR (T-CPR) versus video-assisted CPR (V-CPR)—remains unclear. The LINE application, a widely used messaging platform in Thailand, offers a video call feature that could support real-time CPR guidance. Objective To compare CPR quality metrics—including chest compression depth, chest compression rate, correct hand positioning, and high-quality CPR fraction—between V-CPR delivered via the LINE application and T-CPR in a simulated OHCA scenario. Methods In this randomized controlled trial, undergraduate students aged ≥ 18 years from non–health science faculties without prior CPR training were enrolled and paired by sex. Participant pairs were randomly assigned to receive dispatcher guidance via telephone (T-CPR) or video call using the LINE application (V-CPR). Participants performed CPR in a simulated OHCA scenario under real-time dispatcher guidance. CPR quality metrics were measured using a training manikin. Results A total of 192 participants (48 pairs per group) were randomized to T-CPR or V-CPR. Baseline characteristics were comparable between groups, and all V-CPR pairs successfully initiated video calls using the LINE application. Compared with the T-CPR group, the V-CPR group achieved greater chest compression depth (3.82 ± 0.85 cm vs. 3.34 ± 0.97 cm; P = 0.011) and a higher high-quality CPR fraction (median 0.47% [IQR 0.00–19.55%] vs. 0.00% [IQR 0.00–2.02%]; P = 0.028). Other metrics, including compression rate and hand positioning accuracy, were comparable between groups. No-flow time was longer in the V-CPR group (median 9 s vs. 6 s; P < 0.001). Conclusion In this simulation-based trial, V-CPR using the LINE application improved chest compression depth compared with T-CPR but was associated with longer no-flow time. Trial registration Thai Clinical Trials Registry, TCTR20241022011. Registered on 19 October 2024. First posted publicly on 22 October 2024. https://www.thaiclinicaltrials.org/ . Supplementary Information The online version contains supplementary material available at 10.1186/s12873-026-01591-y. Keywords: Cardiopulmonary resuscitation (CPR), Bystander resuscitation, Video-assisted CPR, Telephone-assisted CPR, LINE application, CPR quality metrics Background Out-of-hospital cardiac arrest (OHCA) remains a major public health challenge and a leading cause of death worldwide [ 1 – 3 ]. Despite widespread implementation of standardized cardiopulmonary resuscitation (CPR) guidelines [ 4 , 5 ], survival rates remain low [ 6 – 8 ]. Early recognition and prompt initiation of high-quality bystander CPR are key determinants of survival, with effective chest compressions before emergency medical services (EMS) arrival linked to improved survival and neurological outcomes [ 9 – 11 ]. Dispatcher-assisted CPR (DA-CPR) is a widely used strategy to improve bystander CPR performance and patient outcomes [ 5 , 12 – 14 ]. Traditionally, DA-CPR has relied on telephone-assisted CPR (T-CPR), with dispatchers providing instructions via audio communication. Advances in communication technology now allow for video-assisted CPR (V-CPR) guidance. Simulation studies have shown that V-CPR allows dispatchers to visually assess and provide real-time feedback on key CPR metrics—such as hand position, compression depth, and recoil—potentially improving CPR effectiveness [ 15 – 17 ]. To date, evidence supporting the effectiveness of V-CPR in real-world OHCA settings has largely been derived from retrospective cohort studies [ 16 , 18 , 19 ]. Linderoth et al. demonstrated that the use of live video streaming from bystanders’ smartphones to medical dispatchers is feasible and may be associated with improved CPR performance [ 19 ]. A recent randomized controlled trial by Szöllősi et al. compared V-CPR, telephone-assisted CPR (T-CPR), and unassisted CPR, reporting that V-CPR had the potential to enhance overall CPR quality [ 17 ]. However, the study’s design limits its generalizability. It employed FaceTime on an iPhone with a stable Wi-Fi connection, evaluated only a single 2-minute CPR cycle using a manikin, and relied on a designated operator to handle both the smartphone and the emergency call. Furthermore, most previous studies have specifically utilized designated video call programs or applications, which further constrain external validity [ 15 , 16 , 18 , 20 ]. One major barrier to implementation is the lack of widespread access to standardized video call platforms across emergency systems. To address this gap, we sought to evaluate a widely used communication tool in Thailand as a feasible option for video-assisted dispatch. In Thailand, the LINE application is the most widely used messaging platform, with over 50 million of the country’s 70 million residents (approximately 70%) actively using the app [ 21 ]. Its video call functionality offers a scalable, practical option for V-CPR, enabling real-time CPR guidance without the need for specialized applications [ 22 ]. The aim of this study was to compare CPR quality metrics—including chest compression depth, chest compression rate, correct hand positioning, and high-quality CPR fraction—between video-assisted CPR (V-CPR) delivered via the LINE application and telephone-assisted CPR (T-CPR) in a simulated out-of-hospital cardiac arrest (OHCA) scenario. We hypothesized that V-CPR via LINE would result in superior CPR quality. In addition, we evaluated time-related CPR performance metrics and the feasibility of using the LINE platform to provide real-time dispatcher-assisted CPR. Methods Study design This randomized controlled simulation trial was conducted at the CPR Training Unit between September 26, 2024, and November 2, 2024. The study included both objective CPR performance assessment using a manikin and participant questionnaire data evaluating CPR confidence and feasibility of video-assisted CPR. The study followed the Consolidated Standards of Reporting Trials (CONSORT) guidelines. The CONSORT-EHEALTH checklist is provided in Supplementary Material 1 . Participants and ethical consideration Participants were undergraduate students aged 18 years or older from non–health science faculties at Khon Kaen University. Eligible participants had no prior practical CPR training, including chest compressions or ventilation with mannequins, and no real-life CPR experience. Exclusion criteria included physical conditions or injuries that could affect CPR performance, inability to perform moderate-intensity exercise, lack of a smartphone with video call and internet capabilities, and absence of the LINE application on their device. Written informed consent was obtained from all participants before enrollment. Participants received compensation of 400 Thai Baht and were provided CPR training after completion of the study, as approved by the Ethics Committee. The study was conducted in accordance with the Declaration of Helsinki and Good Clinical Practice guidelines. Ethical approval was granted by the Khon Kaen University Ethics Committee for Human Research ( HE671055 ; IRB No. IRB00001189) on 4 September 2024. The trial was retrospectively registered with the Thai Clinical Trials Registry (TCTR20241022011) on 19 October 2024 and was first posted publicly on 22 October 2024. Sample size calculation Sample size was calculated using a two-sided hypothesis test. Based on data from a previous study [ 20 ], we hypothesized a 30% difference in the proportion of correct hand positioning between study groups. With a significance level (α) of 0.05, a power of 90%, and allowing for a 10% dropout rate, 48 participant pairs per group were required. As participants were enrolled and analyzed in pairs (see Participant Recruitment, Randomization, and Group Allocation section), this corresponded to 96 participant pairs across both groups, resulting in a total sample size of 192 participants. Participant recruitment, randomization and group allocation Participants were recruited through poster advertisements placed in public areas on campus and through posts on the university’s official Facebook page. After all eligible participants had been enrolled (see Results for exclusion details), they were paired by sex in the order of recruitment. Pairing by sex was performed to minimize potential confounding, as rescuer physical characteristics may influence CPR performance [ 23 ]. For example, if Participant No. 1 was female, No. 2 male, and No. 3 female, then Participants No. 1 and No. 3 were assigned to the same pair. This process yielded 36 male pairs and 60 female pairs, totaling 96 participant pairs. To ensure balanced sex distribution across the study arms, separate block randomization was performed within each sex group using a fixed block size of four. Randomization was conducted using a computerized tool ( https://www.sealedenvelope.com/ ). The final allocation assigned 48 participant pairs to each study arm (T-CPR and V-CPR), with 18 male pairs and 30 female pairs per group. An independent researcher (TT), who was not involved in participant recruitment or data collection, generated the randomization sequence to ensure allocation concealment. Group assignments were stored in a secure computerized system linked to sequentially numbered participant codes. Study staff accessed assignment details only on the day of the intervention, immediately before the simulation, to inform participants of their assigned group. LINE application and participant smartphone requirements Eligible participants were required to own a smartphone with internet access and have the LINE application (LY Corporation, Tokyo, Japan) installed on their device. Although the version of the LINE application varied by participant, all were encouraged to update to the latest version prior to the study. LINE is a free communication application available on both iOS and Android platforms, as well as desktop versions through the Windows Store. Its core functionalities include text messaging, voice and video calls, open chat, digital wallet services, and corporate solutions. Further details are available at https://www.line.me/en/ . Study protocol A simulated out-of-hospital cardiac arrest scenario was conducted using a Resusci Anne ® QCPR manikin (Laerdal, Norway) in a controlled simulation room. Two staff members—a timekeeper and a video recorder—were present to document time-related outcomes. Blinding of participants and on-site investigators was not feasible due to the nature of the simulation study. However, the trained dispatcher who provided CPR instructions was blinded to both the simulation environment and group assignment. The dispatcher was located in a separate room and delivered instructions via telephone or video call, without any direct visual access to the participants or the simulation setup. To ensure consistency and minimize variability in instruction delivery, all CPR guidance for every participant pair was provided by a single dispatcher throughout the study. This dispatcher was certified by the National Institute for Emergency Medicine (NIEM), Thailand, and had completed formal emergency medical dispatcher training in accordance with national EMS standards. Before the session, participants received standardized instructions on the study protocol and were assigned predefined roles as Participant A (first bystander) or Participant B (second bystander). At the start of the scenario, in both study groups, Participant A initiated the emergency call and began chest compressions under dispatcher guidance. The dispatcher provided step-by-step instructions, including activating the speakerphone and delivering high-quality chest compressions, with emphasis on proper hand placement and a compression depth of 5–6 cm. Chest compression rate was standardized using a metronome function provided by the CPR Tempo application (Frozen Ape Pte. Ltd., Singapore), set at 110 compressions per minute (within the recommended range of 100–120 compressions per minute). In the T-CPR group (Fig. 1 ), Participant B initially remained inactive and observed while Participant A performed chest compressions under dispatcher guidance. After 2 min, Participant B took over chest compressions as instructed by the dispatcher. Thereafter, the dispatcher continued to provide telephone-assisted CPR instructions, directing participants to switch compressors at fixed 2-minute intervals and reinforcing adherence to CPR quality standards throughout the session. Detailed dispatcher instructions and protocol are provided in Supplement Material 2 . Fig. 1. Open in a new tab Simulated out-of-hospital cardiac arrest (OHCA) scenario in the telephone-assisted CPR group In the V-CPR group (Fig. 2 ), Participant B used a separate smartphone to set up and initiate a video call via the LINE application following the dispatcher’s instructions (Supplementary Material 2 ). After successful video call establishment, Participant B managed the video call, including positioning the camera to enable real-time visualization of the CPR procedure. This setup allowed the dispatcher to remotely observe CPR performance and provide immediate feedback. Participant A performed chest compressions while Participant B maintained the video connection. As in the T-CPR group, participants were instructed to switch compressors every 2 min, and the dispatcher reinforced CPR quality throughout the session. A demonstration video outlining participant roles and detailed procedures is available in Supplementary Material 3 . Fig. 2. Open in a new tab Simulated out-of-hospital cardiac arrest (OHCA) scenario in the video-assisted CPR group After completion of the simulation scenario, all participants completed a structured questionnaire assessing CPR confidence, smartphone and LINE application experience, and perceptions of video-assisted CPR. Outcomes The 2020 International Resuscitation Guidelines [ 5 ] define high-quality CPR using several key performance metrics. The primary outcome examined in this study was chest compression depth, measured as both the mean depth (cm) and the proportion of compressions within the recommended 5 to 6 cm range. Secondary outcomes included chest compression rate (compressions per minute and percentage within 100 to 120), correct hand positioning (percentage of compressions with proper placement), and full chest recoil (percentage allowing complete recoil). In addition, we evaluated a composite performance metric termed the “high-quality CPR fraction,” developed for this study and defined as the percentage of total compressions that simultaneously met all four quality criteria: correct hand placement, adequate compression depth, appropriate compression rate, and complete chest recoil. Other secondary outcomes included time-related CPR quality metrics, the feasibility of using LINE video calls for real-time CPR guidance, and participants’ pre- and post-session CPR confidence. Time-related metrics included total session duration, total CPR duration, time to first chest compression, time to initiate the video call, video call setup time, and no-flow time. The simulation sequence and outcome measurement timeline are shown in Fig. 3 . Definitions of these metrics are provided in Supplement Material 4 . Fig. 3. Open in a new tab The sequence of the simulation scenario and timing for outcome measurement LINE’s feasibility as a tool for real-time CPR guidance was assessed based on the percentage of participants who successfully completed a video call. Participants’ pre- and post-session CPR confidence was evaluated using a simple numeric rating scale questionnaire developed specifically for this simulation-based study. Participants were asked to rate their confidence based on their perceived ability to perform CPR effectively in the simulated OHCA scenario. The questionnaire also collected data on smartphone usage habits and perceptions regarding the feasibility of using LINE video calls in emergency situations. An English translation of the original Thai questionnaire is provided in Supplement Material 5 . All CPR performance data were collected using the Resusci Anne ® QCPR manikin and analyzed with SimPad ® PLUS and SkillReporter™ software (Laerdal, Norway). Time-related outcomes were recorded using both the QCPR system and manual stopwatch measurements by designated timekeeping staff. A representative SkillReporter™ output is shown in Supplement Material 6 . Video recordings were systematically reviewed by study staff to verify the accuracy and consistency of time metrics across all sessions. Statistical analysis All statistical analyses were conducted using Stata version 10 (StataCorp, College Station, TX, USA). Normality of continuous variables was assessed using the Shapiro-Wilk test. Normally distributed variables were reported as mean ± standard deviation (SD) and compared using independent samples t-tests. Non-normally distributed variables were presented as median with interquartile range (IQR) and compared using the Mann–Whitney U test. Categorical variables were summarized as frequencies and percentages and compared using Pearson’s chi-squared test or Fisher’s exact test, as appropriate. For CPR performance outcomes, analyses were conducted at the participant pair level, consistent with the study design and randomization. For questionnaire-based outcomes, analyses were conducted at the individual participant level. Post-session confidence scores were analyzed using ANCOVA adjusted for baseline CPR confidence, with standard errors clustered by participant pair. Effect estimates with corresponding 95% CIs were reported when estimable. All analyses were conducted according to the intention-to-treat principle. A two-sided p-value < 0.05 was considered statistically significant. Results A total of 194 participants were enrolled. Two participants were excluded—one due to inability to perform moderate-intensity physical activity (related to sleep-related fatigue), and one because the LINE application was not installed on their smartphone. The remaining 192 participants were randomized into two groups: T-CPR (48 participant pairs; 96 participants) and V-CPR (48 participant pairs; 96 participants). All participants completed the simulation and were included in the final analysis. Baseline characteristics are summarized in Table 1 and were similar between groups. The mean age was 20.28 ± 1.37 years in the T-CPR group and 20.15 ± 1.06 years in the V-CPR group ( p = 0.589). The proportion of male participants was identical in both groups (37.5%, p > 0.999). BMI was comparable (median [IQR]: T-CPR 21.21 [19.82–24.37], V-CPR 21.33 [19.18–23.61], p = 0.908). Pre-session CPR confidence, measured on a 1–10 scale (higher scores indicating greater confidence), did not differ significantly between groups (median [IQR]: 4 [2–5], p = 0.913). Table 1. Baseline characteristics of study participants Characteristic T-CPR group ( n = 96 participants) V-CPR group ( n = 96 participants) P value Age, years (mean ± SD) 20.28 ± 1.37 20.15 ± 1.06 0.589 Male, n (%) 36 (37.5) 36 (37.5) > 0.999 Body mass index, kg/m² (median, IQR) 21.21 (19.82–24.37) 21.33 (19.18–23.61) 0.908 Pre-session CPR confidence (median, IQR) 4 (2–5) 4 (2–5) 0.913 Open in a new tab Values are presented as mean ± standard deviation (SD), median (interquartile range, IQR), or n (%), as appropriate Baseline characteristics were summarized at the participant level CPR quality metrics All participants in the V-CPR group successfully established video calls using the LINE application. Compared with the T-CPR group, the V-CPR group achieved significantly greater mean chest compression depth (3.82 ± 0.85 cm vs. 3.34 ± 0.97 cm; P = 0.011) and a higher median high-quality CPR fraction (0.47% [IQR 0.00–19.55%] vs. 0.00% [IQR 0.00–2.02%]; P = 0.028). Other CPR metrics—including the percentage of correct chest compression depth (0% vs. 1.5%; P = 0.175), chest compression rate (111 vs. 111 compressions per minute; P = 0.776), correct hand positioning (100% in both groups), and full chest recoil (73% vs. 75.5%; P = 0.162)–were similar between groups (Table 2 ). Table 2. Comparison of chest compression performance between telephone-assisted CPR (T-CPR) and video-assisted CPR (V-CPR) groups ( n = 48 pairs per group) Outcome T-CPR group ( n = 48 pairs) V-CPR group ( n = 48 pairs) Difference (95% CI) P value Chest compression depth (cm) 3.34 ± 0.97 3.82 ± 0.85 0.48 (0.11 to 0.85) 0.011 Correct compression depth (%) 0 (0–9) 1.5 (0–26.5) 0 (0 to 2) 0.175 Compression rate (per min) 111 (109–113) 111 (109–113) 0 (–2 to 1) 0.776 % Correct compression rate 89 (74.5–95.5) 90 (75–94) –1 (–5 to 4) 0.689 % Correct hand positioning 100 (98.5–100) 100 (94.5–100) 0 (0 to 0) 0.788 % Correct full chest recoil 73.0 (39–94.5) 75.5 (56.5–91.5) 8 (–2 to 20) 0.162 High-quality CPR fraction (%) 0.00 (0–2.02) 0.47 (0–19.55) — 0.028 Total session time (sec) 581.5 (574.5–588) 580 (574–584.5) –1 (–5 to 3) 0.524 Total CPR time (sec) 480 (479–481) 481 (480–482) 1 (0 to 1) 0.020 Time to first compression (sec) 103 (94.5–107) 100 (91.5–105) –3 (–7 to 1) 0.139 Time to start video call (sec) — 167 (154–179.5) — — LINE video call setup time (sec) — 43 (38–52.5) — — No-flow time (sec) 6 (3–9) 9 (7.5–12) 3 (3 to 6) < 0.001 Open in a new tab Values are presented as mean ± standard deviation (SD) or median (interquartile range, IQR), as appropriate. Mean differences with 95% confidence intervals (CI) are presented for normally distributed data. For non-normally distributed data, differences between groups were assessed using the Mann–Whitney U test, and corresponding 95% CIs were reported when estimable. Comparisons between groups were performed using Student’s t-test or Mann–Whitney U test, as appropriate Abbreviations: T-CPR, telephone-assisted cardiopulmonary resuscitation; V-CPR, video-assisted cardiopulmonary resuscitation; CI, confidence interval Time-related CPR quality metrics Total session duration and median time to initiate CPR were similar between groups. Total CPR time was slightly longer in the V-CPR group (481 s [IQR, 480–482]) compared with the T-CPR group (480 s [IQR, 479–481]; P = 0.02). In the V-CPR group, the median time to establish a video call was 167 s (IQR, 154–179.5), and the median LINE video call setup time was 43 s (IQR, 38–52.5). No-flow time was significantly longer in the V-CPR group compared with the T-CPR group (9 s [IQR, 7.5–12] vs. 6 s [IQR, 3–9]; P < 0.001) (Table 2 ). Participants’ attitudes and perceptions Table 3 presents participants’ attitudes and perceptions regarding smartphone and LINE use. Post-session CPR confidence was similar between the T-CPR and V-CPR groups (mean ± SD, 7.53 ± 1.59 vs. 7.60 ± 1.70; adjusted mean difference, 0.05; 95% CI, − 0.37 to 0.48; P = 0.80). Median confidence scores were also identical between groups (median [IQR], 8 [7–9] vs. 8 [7–9]). Table 3. Participants’ attitudes and perceptions toward smartphone and LINE experience Outcome T-CPR group ( n = 96 participants) V-CPR group ( n = 96 participants) Difference (95% CI) P value Post-session CPR confidence rating mean ± SD 7.53 ± 1.59 7.60 ± 1.70 median (IQR) 8 (7–9) 8 (7–9) Adjusted mean difference¹ 0.05 (–0.37, 0.48) 0.803 Owning a smartphone, n (%) 96 (100%) 96 (100%) > 0.999 LINE application installed on smartphone, n (%) 96 (100%) 96 (100%) > 0.999 Prior experience with LINE application video calls, n (%) 94 (97.92%) 95 (98.96%) > 0.999 LINE application use frequency per day, n (%) 0.657 < 1 h/day 47 (48.96%) 46 (47.92%) 1–2 h/day 28 (29.17%) 33 (34.38%) > 2 h/day 21 (21.88%) 17 (17.71%) Feasibility of using LINE video calls in real-world scenarios (median, IQR) 8 (7–9) 8 (7–10) 0 (0–1) 0.355 Open in a new tab 1 The adjusted mean difference in post-session confidence was estimated using ANCOVA adjusted for baseline CPR confidence, with standard errors clustered at the participant-pair level Values are presented as mean ± standard deviation (SD), median (interquartile range, IQR), or n (%), as appropriate All participants owned a smartphone and had the LINE application installed. Nearly all participants had prior experience with LINE video calls, and the frequency of LINE use was comparable between groups. The perceived feasibility of using LINE video calls in real-world scenarios was high and similar between groups (median score, 8 [7–9] vs. 8 [7–10]; P = 0.36), with no statistically significant differences observed (Table 3 ). Discussion This study compared CPR quality across key metrics between V-CPR via the LINE application and T-CPR. The V-CPR group achieved significantly greater chest compression depth and a higher high-quality CPR fraction, though they also experienced longer no-flow time. All participants in the V-CPR group successfully initiated video calls using the LINE app, with a median setup time of 43 s. These findings support the feasibility of using LINE as a video dispatch tool in populations where usage of the app is prevalent, with potential to enhance real-time CPR guidance. Theoretically, video-based dispatch through V-CPR should improve lay-rescuer CPR quality by enabling real-time feedback on performance and positioning. However, findings from simulation studies and clinical trials have been inconsistent across different CPR quality metrics. In line with recent meta-analyses, our study found a statistically significant increase in chest compression depth in the V-CPR group [ 24 ]. In contrast, we observed no significant difference in chest compression rate between groups, contradicting results from two recent meta-analyses that reported improvements with video-assisted instruction [ 24 , 25 ]. This discrepancy is likely due to the use of a standardized metronome set at 110 compressions per minute in both groups, which may have minimized differences attributable to instructional modality. Both the T-CPR and V-CPR groups demonstrated shallow chest compressions, with a low proportion reaching the recommended depth and values generally falling below those reported in previous studies (4.18–5.54 cm.) [ 15 , 17 , 20 ]. This discrepancy may reflect demographic differences in our study population, which was predominantly female with lower average BMI and weight compared to populations in prior studies (BMI ~ 24–26) [ 17 , 20 ]. Previous research by Krikscionaitiene et al. [ 23 ] demonstrated that lightweight rescuers were significantly more likely to produce insufficient compression depth, likely due to reduced ability to generate adequate compression force. This may partly explain the shallower compression depth observed in our study population. These findings highlight the importance of targeted CPR training and dispatcher guidance to optimize compression quality, particularly among lightweight lay rescuers. Notably, this finding aligns with those of a recent randomized controlled trial, underscoring the importance of tailored CPR training for both laypersons and dispatchers to optimize compression quality [ 17 ]. This study also evaluated the “high-quality CPR fraction,” a composite performance metric defined as the percentage of total compressions that simultaneously met all four CPR quality criteria. We hypothesized that V-CPR could improve overall CPR quality through real-time dispatcher feedback; however, our findings only partially supported this hypothesis. Although V-CPR showed a statistically significant improvement compared with T-CPR, the overall high-quality CPR fraction remained very low in both groups. This likely reflects the persistently insufficient compression depth observed across participants. Rapid initiation of CPR following cardiac arrest is critical to improving survival. Studies comparing time to first chest compression between telephone-assisted CPR (T-CPR) and video-assisted CPR (V-CPR) have reported conflicting results, with initiation times in V-CPR groups ranging from 77.5 to 146 s [ 17 , 20 , 24 ]. To address this variability, our study employed a two-bystander protocol in which the video call was initiated only after conventional CPR had begun. This approach resulted in comparable times to first compression between groups, with no significant difference. While this strategy effectively minimized delays in starting CPR, the V-CPR group experienced significantly longer no-flow intervals between compression cycles. These extended pauses were likely due to interruptions caused by passing the phone during compressions. Refining video-assisted dispatch protocols to reduce such interruptions is essential to improving the clinical utility of V-CPR. The implementation of T-CPR in real-world settings presents several challenges [ 18 ]. Most simulation studies have relied on in-house or proprietary video call systems, limiting the generalizability of their findings. A real-world study in Korea evaluated video-instructed dispatcher-assisted CPR using a structured video dispatch system and demonstrated its feasibility in an emergency medical service setting [ 16 ]. Dedicated video-assisted dispatch systems have also been implemented in some countries, highlighting the importance of system-level integration within emergency medical services. Our study was unique in that it evaluated the LINE application—the most widely used communication platform in our country—as a practical tool for video-assisted CPR guidance in a simulation setting. We demonstrated excellent feasibility, with a 100% success rate in video call initiation. Future research should explore the implementation and effectiveness of this approach in real-world scenarios. However, using a consumer communication application such as the LINE application in real-world emergency settings raises important considerations regarding regulatory approval, data security, and system integration. In many jurisdictions, such systems may require medical device certification or compliance with healthcare-specific regulations prior to widespread implementation. Limitations First, the sample size calculation was based on the expected difference in correct hand positioning, whereas the primary analysis focused on chest compression depth. This inconsistency between the calculated and emphasized primary outcomes may have introduced bias and should be considered when interpreting the findings. Second, the study population primarily consisted of young female participants with a mean BMI of 21, which may limit the generalizability of the findings. In addition, all participants were Generation Z students with high familiarity with smartphones and digital communication, which may have influenced the feasibility and effectiveness of V-CPR. Results may differ in populations with lower smartphone literacy or in real-world emergency settings, where additional stressors and environmental factors could affect performance. Third, although V-CPR improved overall performance, the percentage of compressions reaching adequate depth remained low. This may reflect participant characteristics as well as the quality of dispatcher guidance. These findings highlight the importance of regular, effective CPR training to improve compression quality—even when real-time video assistance is available. Fourth, another limitation was that the study protocol required two bystanders to minimize confounding and avoid delays in CPR initiation during video call setup. However, real-life cardiac arrest scenarios often involve only a single bystander, which may significantly affect the practicality and effectiveness of video-assisted CPR. Further research is needed to assess the feasibility and performance of video-dispatch systems in single-bystander situations. Fifth, although the difference in mean chest compression depth between groups (mean difference, 0.48 cm; 95% CI, 0.11 to 0.85) was statistically significant, its clinical relevance is uncertain. Although greater compression depth is generally associated with improved outcomes, the minimum magnitude of change required for meaningful improvement is not well established. Sixth, CPR instructions were standardized and delivered by a single trained dispatcher to minimize inter-dispatcher variability. However, this may limit the generalizability of our findings to real-world settings, where dispatcher experience, communication style, and protocols may differ. Finally, due to privacy and security policies within the LINE application, initiating a video call required preliminary steps, such as adding the dispatcher as a contact, resulting in an average setup time of approximately 43 s. This process could potentially be streamlined by implementing an emergency video call function. In addition, the LINE application is a consumer communication platform rather than a certified medical device. Although no patient data were involved in this simulation, its use in real clinical settings would require careful consideration of data security, encryption, privacy protection, and medicolegal implications. Conclusion In this simulation-based trial, video-assisted CPR via the LINE application improved chest compression depth and high-quality CPR fraction compared with telephone-assisted CPR, suggesting improved CPR quality in selected parameters. Other CPR performance metrics showed no significant differences between groups. However, video-assisted CPR was also associated with longer no-flow time, likely due to the additional steps required to initiate the video call. The successful initiation of video calls among all V-CPR participants suggests that using the LINE application for dispatcher-assisted CPR is feasible in a controlled setting. Further research is needed to evaluate its effectiveness and practicality in real-world out-of-hospital cardiac arrest scenarios. As the LINE application is a commercially developed platform rather than a purpose-built medical system, its use in emergency care requires consideration of regulatory, security, and privacy aspects. Supplementary Information Below is the link to the electronic supplementary material. Supplementary Material 1 (702.9KB, pdf) Supplementary Material 2 (132KB, docx) Supplementary Material 3 (15.4KB, docx) Supplementary Material 4 (16KB, docx) Supplementary Material 5 (27.6KB, docx) Supplementary Material 6 (260.4KB, docx) Acknowledgements We would like to thank Dr. Dylan Southard for his assistance with English-language editing of this manuscript. We also used generative artificial intelligence tools, including Grammarly, to improve the grammar, style, and clarity. All content was subsequently reviewed and revised by our research team and Dr. Southard, who provided additional proofreading. Abbreviations BMI Body Mass Index CONSORT Consolidated Standards of Reporting Trials CPR Cardiopulmonary Resuscitation DA-CPR Dispatcher-Assisted CPR OHCA Out-of-Hospital Cardiac Arrest T-CPR Telephone-Assisted CPR V-CPR CPR guided by live video instructions Author contributions MM, TL, PP, and PW contributed to the conception and design of the study, participant recruitment, data acquisition and management, and drafting of the manuscript. TT contributed to the conception of the study, methodology, formal analysis and manuscript drafting. KS and SS assisted with participant recruitment. PH conceived the study, secured research funding, and takes overall responsibility for the integrity of the work. All authors were involved in data interpretation, critically revised the manuscript for important intellectual content, approved the final version for submission, and agree to be accountable for all aspects of the work. Funding This work (Grant No. IN67087) was supported by Khon Kaen University Faculty of Medicine. Data availability The datasets generated or analyzed during this study are available from the corresponding author on reasonable request. Declarations Ethics approval and consent to participate Ethical approval for this study was obtained from the Khon Kaen University Ethics Committee for Human Research ( HE671055 ; IRB No. IRB00001189) on 4 September 2024. Written informed consent was obtained from all participants before enrollment. The trial was retrospectively registered with the Thai Clinical Trials Registry (TCTR20241022011) on 19 October 2024 and was first posted publicly on 22 October 2024. Presentation This study was presented as a poster at the International Conference on Emergency Medicine (ICEM 2025), May 24–28, 2025, Montreal, QC, Canada. Competing interests The authors declare no competing interests. Footnotes Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. References 1. Zive DM, Schmicker R, Daya M, Kudenchuk P, Nichol G, Rittenberger JC, et al. Survival and variability over time from out of hospital cardiac arrest across large geographically diverse communities participating in the Resuscitation Outcomes Consortium. Resuscitation. 2018;131:74–82. 10.1016/j.resuscitation.2018.07.023. [ DOI ] [ PubMed ] [ Google Scholar ] 2. Amacher SA, Bohren C, Blatter R, Becker C, Beck K, Mueller J, et al. Long-term Survival After Out-of-Hospital Cardiac Arrest: A Systematic Review and Meta-analysis. JAMA Cardiol. 2022;7:633–43. 10.1001/jamacardio.2022.0795. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 3. Garcia RA, Girotra S, Jones PG, McNally B, Spertus JA, Chan PS. Variation in Out-of-Hospital Cardiac Arrest Survival Across Emergency Medical Service Agencies. Circ Cardiovasc Qual Outcomes. 2022;15:e008755. 10.1161/CIRCOUTCOMES.121.008755. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 4. Soar J, Böttiger BW, Carli P, Couper K, Deakin CD, Djärv T, et al. European resuscitation council guidelines. 2021: Adult advanced life support. Resuscitation. 2021;161:115–51. 10.1016/j.resuscitation.2021.02.010 [ DOI ] [ PubMed ] 5. Panchal AR, Bartos JA, Cabañas JG, Donnino MW, Drennan IR, Hirsch KG, et al. Part 3: Adult Basic and Advanced Life Support: 2020 American Heart Association Guidelines for Cardiopulmonary Resuscitation and Emergency Cardiovascular Care. Circulation. 2020;142 16suppl2:S366–468. 10.1161/CIR.0000000000000916. [ DOI ] [ PubMed ] [ Google Scholar ] 6. Gräsner J-T, Herlitz J, Tjelmeland IBM, Wnent J, Masterson S, Lilja G, et al. European Resuscitation Council Guidelines 2021: Epidemiology of cardiac arrest in Europe. Resuscitation. 2021;161:61–79. 10.1016/j.resuscitation.2021.02.007. [ DOI ] [ PubMed ] [ Google Scholar ] 7. Okada Y, Shahidah N, Ng YY, Chia MYC, Gan HN, Leong BSH, et al. Outcome assessment for out-of-hospital cardiac arrest patients in Singapore and Japan with initial shockable rhythm. Crit Care. 2023;27:351. 10.1186/s13054-023-04636-x. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 8. Ahn JY, Ryoo HW, Moon S, Jung H, Park J, Lee WK, et al. Prehospital factors associated with out-of-hospital cardiac arrest outcomes in a metropolitan city: a 4-year multicenter study. BMC Emerg Med. 2023;23:125. 10.1186/s12873-023-00899-3. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 9. Horriar L, Rott N, Böttiger BW. Improving survival after cardiac arrest in Europe: The synergetic effect of rescue chain strategies. Resusc Plus. 2024;17:100533. 10.1016/j.resplu.2023.100533. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 10. Nguyen DD, Spertus JA, Kennedy KF, Gupta K, Uzendu AI, McNally BF, et al. Association Between Delays in Time to Bystander CPR and Survival for Witnessed Cardiac Arrest in the United States. Circ Cardiovasc Qual Outcomes. 2024;17:e010116. 10.1161/CIRCOUTCOMES.123.010116. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 11. Riyapan S, Sanyanuban P, Chantanakomes J, Roongsaenthong P, Somboonkul B, Rangabpai W, et al. Enhancing survival outcomes in developing emergency medical service system: Continuous quality improvement for out-of-hospital cardiac arrest. Resusc Plus. 2024;19:100683. 10.1016/j.resplu.2024.100683. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 12. Nikolaou N, Dainty KN, Couper K, Morley P, Tijssen J, Vaillancourt C, et al. A systematic review and meta-analysis of the effect of dispatcher-assisted CPR on outcomes from sudden cardiac arrest in adults and children. Resuscitation. 2019;138:82–105. 10.1016/j.resuscitation.2019.02.035. [ DOI ] [ PubMed ] [ Google Scholar ] 13. Wyckoff MH, Singletary EM, Soar J, Olasveengen TM, Greif R, Liley HG, et al. Education, Implementation, and Teams; First Aid Task Forces; and the COVID-19 Working Group. Resuscitation. 2021;169:229–311. 10.1016/j.resuscitation.2021.10.040. 2021 International Consensus on Cardiopulmonary Resuscitation and Emergency Cardiovascular Care Science With Treatment Recommendations: Summary From the Basic Life Support; Advanced Life Support; Neonatal Life Support. [ DOI ] [ PMC free article ] [ PubMed ] 14. Ahmed F, Khan UR, Soomar SM, Raheem A, Naeem R, Naveed A, et al. Acceptability of telephone-cardiopulmonary resuscitation (T-CPR) practice in a resource-limited country- a cross-sectional study. BMC Emerg Med. 2022;22:139. 10.1186/s12873-022-00690-w. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 15. Ecker H, Lindacher F, Adams N, Hamacher S, Wingen S, Schier R, et al. Video-assisted cardiopulmonary resuscitation via smartphone improves quality of resuscitation: A randomised controlled simulation trial. Eur J Anaesthesiol. 2020;37:294–302. 10.1097/EJA.0000000000001177. [ DOI ] [ PubMed ] [ Google Scholar ] 16. Lee HS, You K, Jeon JP, Kim C, Kim S. The effect of video-instructed versus audio-instructed dispatcher-assisted cardiopulmonary resuscitation on patient outcomes following out of hospital cardiac arrest in Seoul. Sci Rep. 2021;11:15555. 10.1038/s41598-021-95077-5. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 17. Szöllősi V, Horváth B, Németh D, Bánfai-Csonka H, Betlehem J, Bánfai B. A randomized controlled simulation trial comparing video-assisted with telephone-assisted and unassisted cardiopulmonary resuscitation performed by non-healthcare university students. Sci Rep. 2023;13:14925. 10.1038/s41598-023-42131-z. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 18. Magnusson C, Ollis L, Munro S, Maben J, Coe A, Fitzgerald O, et al. Video livestreaming from medical emergency callers’ smartphones to emergency medical dispatch centres: a scoping review of current uses, opportunities, and challenges. BMC Emerg Med. 2024;24:99. 10.1186/s12873-024-01015-9. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 19. Linderoth G, Rosenkrantz O, Lippert F, Østergaard D, Ersbøll AK, Meyhoff CS, et al. Live video from bystanders’ smartphones to improve cardiopulmonary resuscitation. Resuscitation. 2021;168:35–43. 10.1016/j.resuscitation.2021.08.048. [ DOI ] [ PubMed ] [ Google Scholar ] 20. Stipulante S, Delfosse A-S, Donneau A-F, Hartsein G, Haus S, D’Orio V, et al. Interactive videoconferencing versus audio telephone calls for dispatcher-assisted cardiopulmonary resuscitation using the ALERT algorithm: a randomized trial. Eur J Emerg Med. 2016;23:418–24. 10.1097/MEJ.0000000000000338. [ DOI ] [ PubMed ] [ Google Scholar ] 21. Kittipimpanon K, Noyudom A, Panjatharakul P, Visudtibhan PJ. Use of and Satisfaction With Mobile Health Education During the COVID-19 Pandemic in Thailand: Cross-sectional Study. JMIR Form Res. 2023;7:e43639. 10.2196/43639. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 22. LINE always at your side. https://www.line.me/en/ . Accessed 22 Mar 2025. 23. Krikscionaitiene A, Stasaitis K, Dambrauskiene M, Dambrauskas Z, Vaitkaitiene E, Dobozinskas P, et al. Can lightweight rescuers adequately perform CPR according to 2010 resuscitation guideline requirements? Emerg Med J. 2013;30:159–60. 10.1136/emermed-2011-200634. [ DOI ] [ PubMed ] [ Google Scholar ] 24. Bielski K, Böttiger BW, Pruc M, Gasecka A, Sieminski M, Jaguszewski MJ, et al. Outcomes of audio-instructed and video-instructed dispatcher-assisted cardiopulmonary resuscitation: a systematic review and meta-analysis. Ann Med. 2022;54:464–71. 10.1080/07853890.2022.2032314. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 25. Lin Y-Y, Chiang W-C, Hsieh M-J, Sun J-T, Chang Y-C, Ma MH-M. Quality of audio-assisted versus video-assisted dispatcher-instructed bystander cardiopulmonary resuscitation: a systematic review and meta-analysis. Resuscitation. 2018;123:77–85. 10.1016/j.resuscitation.2017.12.010. [ DOI ] [ PubMed ] [ Google Scholar ] Associated Data This section collects any data citations, data availability statements, or supplementary materials included in this article. Data Citations Wyckoff MH, Singletary EM, Soar J, Olasveengen TM, Greif R, Liley HG, et al. Education, Implementation, and Teams; First Aid Task Forces; and the COVID-19 Working Group. Resuscitation. 2021;169:229–311. 10.1016/j.resuscitation.2021.10.040. 2021 International Consensus on Cardiopulmonary Resuscitation and Emergency Cardiovascular Care Science With Treatment Recommendations: Summary From the Basic Life Support; Advanced Life Support; Neonatal Life Support. [ DOI ] [ PMC free article ] [ PubMed ] Supplementary Materials Supplementary Material 1 (702.9KB, pdf) Supplementary Material 2 (132KB, docx) Supplementary Material 3 (15.4KB, docx) Supplementary Material 4 (16KB, docx) Supplementary Material 5 (27.6KB, docx) Supplementary Material 6 (260.4KB, docx) Data Availability Statement The datasets generated or analyzed during this study are available from the corresponding author on reasonable request. Articles from BMC Emergency Medicine are provided here courtesy of BMC ACTIONS View on publisher site PDF (1.4 MB) Cite Collections Permalink RESOURCES Similar articles Cited by other articles Links to NCBI Databases Follow NCBI NCBI on X (formerly known as Twitter) NCBI on Facebook NCBI on LinkedIn NCBI on GitHub NCBI RSS feed Connect with NLM NLM on X (formerly known as Twitter) NLM on Facebook NLM on YouTube National Library of Medicine 8600 Rockville Pike Bethesda, MD 20894 Web Policies FOIA HHS Vulnerability Disclosure Help Accessibility Careers NLM NIH HHS USA.gov Back to Top

Related documents

• Automated Real-time Feedback on CPR Study#884629
• Multifaceted Intervention for Increasing Performance of CPR by Laypersons in Out-of-hospital Cardiac Arrest#841257
• Conduction System Pacing International Registry (CONSPIRE)#682991
• Pediatric Resuscitation With Feedback Devices#802101
• Automatic External Defibrillation Monitoring in Cardiac Arrest#1009224