Heart rate variability biofeedback intervention programme to improve attention in primary schools

Heart rate variability biofeedback intervention programme to improve attention in primary schools | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Heart rate variability biofeedback intervention programme to improve attention in primary schools Ainara Aranberri Ruiz, Malen Migueles Seco This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4654519/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 23 Aug, 2024 Read the published version in Applied Psychophysiology and Biofeedback → Version 1 posted 9 You are reading this latest preprint version Abstract The importance of attentional capacity for academic performance is highlighted by the increasing demands placed on students during primary school. Between the ages of 6 and 12, there is an evolutionary improvement in attentional capacity and the school environment is shown to be an appropriate setting in which to develop programmes to improve attention. Heart rate variability is an appropriate indicator of attentional capacity. For all these reasons, a heart rate variability biofeedback intervention focused on breathing was developed and implemented to improve attention. The intervention consists of two phases. In the first phase, the teachers of the school are trained to develop the intervention. In the second phase, the students receive 5 individual sessions from their teachers. In each individual session, they learn to breathe in a way that increases their heart rate variability. A total of 272 girls and 314 boys (N=586) aged 6-12 years participated in the programme. In order to study the impact on the three cycles of primary school, the attention of the control and experimental groups was assessed before and after the implementation of the programme. According to the data obtained, despite developmental improvements, the students who participated in the programme showed an increase in heart rate variability and an improvement in attentional capacity, with a greater impact on the first cycle of primary school. Our conclusion is to discuss the usefulness of heart rate variability biofeedback interventions in improving attention in primary school children and to present arguments for their use. attention intervention primary school biofeedback heart rate variability breathing Introduction During the school years, the child's attentional demands increase and expand to include more symbolic stimuli (Ristic and Enns, 2015 ; Santa-Cruz and Rosas, 2017 ). Specifically, in the primary school cycle, new school demands require students to develop learning skills related to letter and number identification in order to perform higher cognitive tasks (Mikhailova, 2017 ; Schachner, 2019 ), such as reading and mathematical problem-solving (Kim et al., 2018 ). Such tasks are strongly related to attentional capacity, which is crucial for learning (Duarte et al., 2020 ; Fisher et al., 2013 ; Rabiner et al., 2016 ). Attention is the activity of three brain networks (vigilance, orientation and executive control networks) that influence how information is processed (Posner, 2012 ; Posner et al., 2020 ). The vigilance network is responsible for the state of alertness. The orientation network focuses on locating specific sources of stimulation. Finally, the executive control network is related to all the processes that help us to voluntarily regulate our behaviour and cognition through the control of attention. All three attentional networks interact with each other to influence attentional performance (Spagna et al., 2014 ; Xuan et al., 2016 ) and are necessary for proper academic performance (Posner et al., 2020 ; Posner, 2023 ). Such networks are present in the infant brain, but with a lower degree of functional integration than in the adult brain (De Bie et al., 2012 ; Johansen et al., 2023; Kaufmann et al., 2017 ; ). And greater integration occurs during infant development (De Bie et al., 2012 ), enabling better attentional performance (Posner et al., 2020 ; Rohr et al., 2018 ). In a normative study by Jiménez et al. ( 2012 ), it was observed that in primary school, aged 6–12 years, there is an improvement in attentional ability as measured by the D2 attention test (Brickenkamp, 2002 ) as development progresses. A later normative study by Rivera et al. ( 2017 ) also confirmed this trend. Given that the D2 test integrates in its measurement the functions corresponding to the functioning of the three brain networks mentioned above, and that attention is in a developmental process during this period, the development of interventions aimed at improving attentional skills may be particularly appropriate, given the potential for improvement in school programmes (Lee et al., 2019 ; Zhang and Bray, 2020 ). Heart rate variability (hereafter HRV) refers to changes in the time interval that occurs between consecutive heartbeats (Shaffer and Ginsberg, 2017 ; Task Force, 2016) and is related to the functioning of the autonomic nervous system (Aranberri-Ruiz, 2023 ). HRV is an appropriate indicator of the stress response (Aranberri, 2023; Aranberri et al., 2022; Alitzeta et al., 2022; Alitzeta et al., 2017; Immanuel et al., 2023) and the level of cognitive function (Thayer et al., 2009 ; Winkelmann et al., 2017 ). Furthermore, HRV has been shown to be an appropriate measure of attentional capacity (Forte et al., 2019 ; Jennings et al., 2016 ; Park and Thayer, 2014 ; Porges and Raskins, 1969; Sakaki et al., 2016 ; Thayer and Lane, 2009 ; Ning and Wang, 2021 ; Tinello et al., 2022 ). Through biofeedback techniques we obtain real-time information about variations in HRV (Schwartz and Andrasik, 2003 ) and we can learn to modulate our HRV by practising slow and prolonged breathing (Goessl et al., 2017 ). The Polyvagal Theory (Porges, 1995 , 2011 , 2022 ) justifies the impact of slow and prolonged breathing on the ventral vagus nerve and its parasympathetic influence, reducing the heart rate and increasing HRV itself by reducing the activity of the adrenal sympathetic system and the consequent stress response (Aranberri-Ruiz, 2023 ), thus making it possible to improve attentional capacity (Kredlow, et al., 2022 ). HRV biofeedback programmes focused on learning a breathing pattern of approximately 6 breaths per minute - a measure also validated through studies of the impact of the breathing pattern on evoked action potentials of different brain areas (Herrero et al., 2017 ) - have been shown to be effective in improving academic-cognitive performance and attentional capacity (Aritzeta et al., 2017 ; Park et al., 2013 ; Rush et al., 2017 ). In the school context we have only found two HRV biofeedback interventions implemented to improve attentional capacity in Primary Education (Crevenna et al., 2016 ; Rush et al., 2017 ). The intervention developed by Crevena et al. (2016) was aimed at 15 pupils in the 4th year of Primary School, while the intervention by Rush et al. ( 2017 ) was aimed at 27 pupils aged 8 to 12 years. In both studies, the participating students improved their attentional capacity after the training. However, these are very small samples and do not allow a comparison of the differential effectiveness of the treatment in the three cycles that make up Primary Education to be made in a single study. Thus, given the effectiveness and scarcity of HRV biofeedback interventions in school settings, a HRV biofeedback programme focused on breathing was designed to improve the attentional capacity of primary school students. We expect that, as in previous studies and independently of the educational cycle, the training will improve performance on the d2 attention test (Brickenkamp, 2002 ). Further aims of the study are to examine the interactions of training with educational level on different measures of attention. Material and methods This study included 585 elementary school students (46.4% were girls and 53.5% were boys) aged between 7 and 12 years (M = 8.51; SD = 1.26). This sample was divided according to the cycles of primary schooling, with 21.4% belonging to the first cycle, 64.6% to the second cycle and the remaining 14% to the third cycle. In order to carry out the study, the sample was divided into an experimental group and a control group. Regarding the composition of the experimental group, it was decided, at the suggestion of the school management, to assign students with different difficulties (emotional, academic, etc.) to the experimental group. The selection process involved the tutors, the teaching staff, the head of therapeutic education and the management team. The rest of the students were randomly assigned. Thus, in the first cycle we had 83 participants in the experimental group and 42 in the control group, in the second cycle 257 participants in the experimental group and 121 in the control group, and finally in the third cycle 49 participants in the experimental group and 33 in the control group. The participation of the students was voluntary and consented to by the school council, parents and guardians. The study had the favourable report of the ethics committee for research with human beings, their samples and data (CEISH/269 1-2-3-4-/2014) of the University of the Basque Country/Euskal Herriko Unibertsitatea with DSI file INA0079. The ethical aspects required for research with human subjects (informed consent, right to information, protection of personal data, guarantees of confidentiality, non-discrimination, free of charge and the possibility of abandoning the study at any stage) were scrupulously respected. Design The biofeedback treatment to teach girls and boys to breathe consists of 5 sessions - individual sessions - that make up the programme: the first measure being the baseline measure, and the last measure being the final treatment or post-treatment measure. To assess the impact of the training on the students' attentional capacity, a mixed design 2 (Group: control, experimental) x 2 (Assessment: pre- and post-training) x 3 (Educational cycle: first, second and third) was used, with the factors Group and Educational cycles being independent or inter-participant measures and the factor Assessment being intra-participant or repeated measures. The dependent variable was performance on the d2 attention test (Brickenkamp, 2002 ). Procedure and Instruments The HeartMath Emwave software (Institute of HeartMath, 2012 ) was chosen in this study to investigate the effects of an HRV biofeedback programme on attention tasks and to teach prolonged and paused breathing. This software has been shown to be effective in several studies (Aranberri et al., 2022; Aritzeta et al., 2022 ; Aritzeta et al., 2017 ; Rush, et al., 2017 ). In this software, HRV is measured in real time by means of the application's own sensor, which is placed on the participant's earlobe. In this way, the computer, through the images on the screen, offers the HRV values in real time, thus allowing the subject to observe the impact that the breathing pattern itself has on HRV. By means of different software applications, the children learn, through trial, error and success, to breathe in a prolonged and paused manner (approximately 6 breaths per minute), thus increasing their own HRV. Based on the HeartMath Emwave software (Institute of HeartMath, 2012 ), an HRV biofeedback programme for attentional improvement was developed in two implementation phases. Phase 1 or pre-intervention. It consists of theoretical and practical training in the aforementioned computer application - HeartMath Emwave software (Institute of HeartMath, 2012 ) - for the school's teaching staff, thus providing the necessary training for teachers to be able to carry out the training programme developed for each individual pupil, which will be described in phase 2 below. Phase 2 or intervention programme. It consists of 6 weekly sessions: the first one in a group and the remaining 5 individual sessions. In the first session in each classroom participating in the programme, the tutor, together with a member of the research team, explains the intervention to all the students in a pleasant way. After one week, individual biofeedback training in HRV biofeedback begins for each student. The 5 individual sessions will be carried out with the tutor of each student in a relaxed and suitable place to develop the intervention. There will be two chairs - one for the tutor and one for each student - a table with a computer and the HeartMath Emwave software (Institute of HeartMath, 2012 ) installed, and the computer application's own earlobe sensor to detect HRV. The duration of the individual sessions is 20 minutes and after each session the tutors record the HRV values obtained by each participant on each student's individual record sheet. Throughout the 5 sessions and through the applications Coherence Coach and Baloom Game -which resemble animations and cartoons, from the HeartMath Emwave software (Institute of HeartMath, 2012 )- the children learn to breathe slowly and slowly through trial, error and success by performing different actions, all with the common objective of teaching them to breathe slowly and slowly (approximately 6 pairs of breaths per minute), gradually, session by session. In the third session, in order to be able to generalise what they have learnt, each pupil is given a "target" image - specific to the programme - laminated in 6x4cm so that they can carry it in their school bag and use it when the teachers recommend it and when they feel nervous. In this way, the image helps them to breathe in a slow and prolonged way without the need for the computer programme. In the remaining sessions, 4 and 5, they continue practising the breathing they have learnt together with the aforementioned image. In the last session, the intervention ends by congratulating each participating pupil, placing special emphasis on the importance of the breathing practice learnt and the use of the image mentioned. To assess the attentional capacity before and after training, both the control group and the experimental group used the d2 attention test (Brickenkamp, 2002 ). This is a test that measures attention designed for people between 6 and 60 years of age. It is a test composed of 14 lines, each with 47 characters. Participants must identify any letter "d" that has two dashes (one at the top and one at the bottom, both at the top and both at the bottom). These are known as relevant or target items, and items that do not have these characteristics are known as irrelevant or distractors. The participants have 20 seconds for each line, and it is the instructor who tells them when to start and finish. The dimensions considered in this study were: Total correctly processed (TN-E); omissions (O) -total number of relevant items not marked-; as well as the TOTR count -which is calculated by subtracting the sum of omissions (O) and errors (E)- from the Total correctly processed (TN-E) and measures the total effectiveness of the test; and concentration (CON) -which is calculated by subtracting errors (E) from the total number of answers (TA). The psychometric properties of the d2 are adequate (average reliability coefficient of 0.95). Analysis and results First, a normality analysis was performed using the Kolmogorov-Smirnov test. The results showed that there was normality of the data distribution. The results on the effectiveness of biofeedback training show that, from the HRV measurement at the beginning of the training to the final assessment, all participants in the experimental group learned to breathe in a prolonged and slow manner, F(1.97) = 176.26, p = 000; \({\eta }_{p}^{2}\) = 0.372. This learning occurred in all educational cycles F(2, 297)=11.10, p=.000, \({\eta }_{p}^{2}=\) .070 but as the interaction shows F(2,297)=21.05; p=.000; \({\eta }_{p}^{2}=0.124\) it was the students in the second cycle (Cycle 2=HRV session 1: M=23.78;HRV session 5: M= 94.99) who showed a greater improvement from the first HRV measurement to the last measurement after the end of the programme (Cycle 1=HRV session 1: M = 26.61;HRV session 5: M= 49.77; Cycle 3=HRV session 1: M=13.16;HRV session 5: M= 54.84). Performance in the attention test was assessed by scoring one point for each mark made, whether correct or incorrect. In addition, omissions or unmarked stimuli were also scored. Thus, to examine the impact of HRV biofeedback training on the attentional performance of girls and boys in the d2 test, we analysed the hit rate, omissions, task concentration and total test effectiveness (see Table 1 ). Results were analysed with ANOVAS for mixed designs, 2 (Group: control, experimental), x 2 (Assessment: pre- and post-training), x 3 (Educational cycle: first, second and third) with the variables Group and Educational cycle as independent measures and Assessment as repeated measures. Post-hoc comparisons were performed with the Bonferroni test and pairwise comparisons with Student's t-test. Table 1 Means and standard deviations in brackets of the experimental and control groups in the pretest and posttest for the 3 cycles of primary education. Experimental Control Cycle 1 Cycle 2 Cycle 3 Cycle 1 Cycle 2 Cycle 3 M(DT) M(DT) M(DT) M(DT) M(DT) M(DT) TN-E pre 57.13 (26.13) 96.76(41.13) 136.79(44.96) 73(27.00) 103.14(32.16) 153.85(33.73) post 85.32(27.06) 120.02(38.39) 165.68(42.41) 68.87(30.29) 118.92(41.23) 154.35(54.39) CON pre 43.23(28.50) 89.56(48.20) 132.75(47.36) 42.78(37.28) 95.92(35.04) 148.36(45.41) post 76.57(30.28) 116.04(39.87) 163.51(44.75) 51.72(50.75) 121.09(37.07) 163.67(37.75) TO pre 243.11(27.89) 201.90(41.49) 162.21(44.95) 225.22(26.66) 195.86(31.94) 145.09(33.82) post 213.22(27.46) 167.40(56.43) 127.86(49.23) 229.97(30.31) 152.42(69.10) 116(55.81) TOTR pre 57.13(26.13) 96.76(41.13) 136.79(44.96) 73(27.00) 103.14(32.16) 153.85(33.73) post 85.32(27.06) 120.55(37.64) 165.68(42.41) 68.87(30.29) 123.59(34.42) 165.78(34.89) * Total correctly processed (TN-E), CON concentration (total hits-errors), TO total omissions and TOTR total responses - (omissions + errors). Total correctly processed The Total correctly processed (TN-E) measure refers to the number of relevant characters marked correctly. The number of Total Answers was higher in the post evaluation than in the pre evaluation (119.17 vs. 98.27), F(1, 490) = 89.08, p = 0.001, \({\eta }_{p}^{2}\) =0.154. Although the Group factor was not significant, it interacted with the Evaluation factor, F(1, 490)=45.53, p=0.991, \({\eta }_{p}^{2}\) = 0.083. Thus, although in the initial evaluation, the control group obtained more correct scores in the attention test than the experimental group (105.48 vs 94.01), t(552)=-2.97, p = 0.004, d=0.268) after training, in the final evaluation there were no significant differences between the control and experimental groups (113.61 vs 118.62), t(523)=1.86, p=0.236, d=0.18. However, each of the groups improved in the total number of correct scores from the initial assessment to the final assessment, showing a greater impact of training on the experimental group compared to the control group (control t(164)=-3.58, p = 0.000, d=-0.220; experimental t(330)=-15.81, p = 0.000, d=-0.580). In addition, the educational cycle factor was significant, F(2,490)=120, p = 0.000, \({\eta }_{p}^{2}\) =Post hoc comparisons with the Bonferroni test showed that as the age of the students increases, the performance in the number of correct answers increases in the attention test. Thus, students in cycle 1 performed worse (M=71.31) than students in cycle 2 (M=111.40) and cycle 3 (M=152.81). Moreover, students in cycle 3 also outperformed students in cycle 2 (p=0.000). Finally, the interaction Group x Educational Cycle x Assessment was significant, F(2,490)=10.33, p=0.000, \({\eta }_{p}^{2}\) =An important aspect to highlight is the special positive impact shown by the intervention on Cycle 1 in relation to the improvement in the total number of correct scores obtained. On the one hand, and recalling that the experimental group obtained worse scores in total hits than the control group in the pretest, it should be noted that cycle 1 is the only cycle of the experimental group that shows an improvement in the scores in relation to the control group (85.32 vs. 68.87), t(113)=2.86, p = 0.006, d=0.574). Moreover, in cycle 1 the experimental group obtains a statistically significant improvement from the first assessment to the last assessment with a large effect size (t(66)=-8.135, p = 0.000, d=-1.204) higher than the rest of the educational cycles which obtain moderate effect sizes (cycle 2: t(216)=-11.82, p = 0.000, d=-0.610; cycle 3: t(44)=-6.95, p = 0.000, d=-0.689). Omissions The Omission measure refers to the total number of relevant items not checked. The number of Omissions was lower in the post evaluation than in the pre evaluation (165.949 vs. 201.002), F(1,521) = 99.89, p = 0.001, \({\eta }_{p}^{2}\) =0.161. The Group x Evaluation interaction was also significant F(1,521)=5.43, p=0.002, \({\eta }_{p}^{2}\) =0.020. Thus, in the initial evaluation the control group committed a lower number of omissions than the experimental group (193.94 vs. 205.02), t(552)=2.96, p = 0.003, d=0.272, while in the final evaluation no statistically significant differences between the control group and the experimental group (162.51 vs. 171.61), t(553)=1.64, p = 0.101, d = 0.143. Although both the control and experimental groups improve performance from the initial assessment to the final assessment, the improvement is more relevant in the experimental group (control: t(179)=6.98, p = 0.000, d = 0.606; experimental: t(346) = 13.28, p = 0.000, d = 0.775). The factor educational cycle was significant, F(2,521)=123.91, p = 0.000, \({\eta }_{p}^{2}\) =Post hoc comparisons with the Bonferroni test showed that as the age of the students increased, performance in the omissions dimension improved and the number of omissions decreased. Thus, students in cycle 1 performed worse (M=227.586) than students in cycle 2 (M=180.1664) and cycle 3 (M=139.203). Moreover, students in cycle 3 also outperformed students in cycle 2 (p=0.000). We observed significant interactions between Assessment time x Educational cycle F(2,521)=9.82, p = 0.000, \({\eta }_{p}^{2}\) =.036 and between Assessment time x Group x Educational cycle F(2,521)=7.94, p = 0.000, \({\eta }_{p}^{2}\) =0.030. Recalling that the experimental group obtained worse scores than the experimental group in the pretest, in the posttest the experimental group in cycle 1 obtained better scores (213.22 vs. 229.97), t(113)=-2.89, p = 0.005, d= -0.580). Moreover, the experimental group of cycle 1 obtains better scores in the posttest than in the pretest with a large effect size (t(66)=7.97, p = 0.000, d=1,230) higher than in the rest of the educational cycles (cycle 2: t(230)=9,916, p = 0.000, d= 0.746; cycle 3: t(46)=6.49, p = 0.000; d=0.753). Concentration The Concentration measure is a measure of accuracy calculated by subtracting errors from the total number of hits. Analyses showed that there was a higher Concentration in the final evaluation than in the initial evaluation (115.646 vs. 89.886), F(1,485) = 162.090, p = 0.000, \({\eta }_{p}^{2}\) =0.250. The factor Group was not significant but interacted with the factor Evaluation, F(1,485)=10.04, p=0.000, \({\eta }_{p}^{2}\) =0.028. Thus, it is observed that there were significant differences (p<.05) between the control and experimental groups in the initial evaluation (85.86 vs 93.52) but not in the final evaluation (113.84 vs 111.88). The variable Educational cycle was also significant, F(2,485)=149.89, p = 0.000, \({\eta }_{p}^{2}\) =Post hoc comparisons with the Bonferroni test showed that as the age of the students increases, performance in the concentration dimension increases. Thus, as in the rest of the dimensions analysed, there was a significant improvement (p=0.000) as the participants progressed through the educational cycle (first cycle M=53.63; second cycle M= 08.25; third cycle M=152.10). The interaction Group x Educational level was also significant, F(2,485)=3.56, p= 0.029, \({\eta }_{p}^{2}\) =0.1 and the interaction Evaluation x Group x Educational Level F(2, 485)=5.46, p=0.05, \({\eta }_{p}^{2}\) =0.22. Thus, as with the rest of the dimensions analysed, it can be seen that in the first cycle biofeedback training is more effective than in the rest of the educational cycles. It is also observed that taking into account that the experimental group obtained worse scores than the control group in the pre-test, in the post-test cycle 1 obtains better scores in Concentration than the control group (76.56 vs. 51.71). Also in cycle 1 there is a statistically significant improvement in the Concentration measure in the posttest with respect to the pretest and with a large effect size (t(66)=-9.44, p=0.000, d=-1.213) higher than in the rest of the cycles (cycle 2: t(216)=-11.09, p=0.000, d=-0.621; cycle 3: t(44)=-8.07, p = 0.000, d=-0.741). Total Test Rate Effectiveness (TOTR) This measure measures the overall effectiveness of the test by subtracting the sum of omissions and errors from the total number of responses. The TOTR measure was higher in the post than in the pre assessment (120.63 vs. 98.03), F(1, 484) = 150.286, p = 0.000, \({\eta }_{p}^{2}\) =0.237. Although the Group factor was not significant, it interacted with the Evaluation factor, F(1,484)=35.51, p=0.000, \({\eta }_{p}^{2}\) =Thus, although in the initial evaluation the control group scored better in the TOTR variable than the experimental group (105.48 vs 94.01), t(552)=-2.927, p = 0.004, d=0.268) after training, in the final evaluation there were no significant differences between the control and experimental groups (117.67 vs 118.96), t(516)=0.314, p=0.753, d=0.029. However, each of the groups improved their performance in this dimension from the initial assessment to the final assessment, showing a greater impact of training on the experimental group compared to the control group (control t(159)=-6.69, p = 0.000, d=-0.324; experimental t(329)=-16.49, p=.000, d=-0.588). The factor Educational cycle was also significant, F(2,484)=130.83, p = .000, \({\eta }_{p}^{2}\) =0.351. Post hoc comparisons with the Bonferroni test showed that as the age of the participants increases, the performance in the total effectiveness of the test increases. Thus, students in cycle 1 performed worse (M=71.55) than students in cycle 2 (M=111.48) and cycle 3 (M=154.45). Moreover, students in cycle 3 also outperformed students in cycle 2 (p=.000). Finally, the interaction Group x Educational Cycle x Assessment was significant, F(2,484)=10.07, p=0.000, \({\eta }_{p}^{2}\) =0.051. Thus, as with the rest of the variables analysed, it can be seen that biofeedback training is more effective in cycle 1. Remembering that the experimental group also obtained worse scores in the total effectiveness of the test, cycle 1 in the post-test obtained better results than the control group (85.32 vs 68.87), t(113)=2.86, p=0.006, d=0.574). And in relation to the improvement of the total test effectiveness scores of the experimental group in the posttest compared to the pretest, cycle 1 also obtains a very large effect size (t(66)=-8.13, p=0.000, d=-1.204) higher than the rest of the cycles (cycle 2: t(215)=-12.63, p = 0.000, d=-0.631; cycle 3: t(44)=-6.95, p = 0.000, d=-0.689). Discussion and conclusions The aim of the HRV biofeedback intervention is to improve attention in primary school children. The results of the study show that the intervention developed on the HeartMath Enwave software (Institute of HeartMath, 2012 ) is a simple and effective strategy to modify the way children breathe and influence their HRV and improve their attentional capacity. In contrast to previous studies that have analysed the effects of biofeedback based on prolonged and paused breathing in primary education with very small samples (Crevenna et al., 2016 ) or with inhomogeneous age groups (Rush et al., 2017 ), this study distinguished the effects in three cycles of primary education and with a large number of participants. In order to understand the results obtained, it is necessary to understand the composition of the experimental group. The participating school recommended that part of the experimental group should be made up of pupils who, because of their personal situation, needed to improve their attention and academic performance. We considered that, as in previous studies (Lynch and Chen, 2015 ; Rukmani, et al., 2016 ; Rush et al., 2017 ; Wade et al., 2017 ), the non-randomisation of students in need of attentional improvement and academic performance corresponded to an educational and personal adjustment criterion that we prioritised in this intervention. This acceptance found its empirical foundation in the positive results observed in different biofeedback interventions. Such as those developed on academic performance and well-being with children with traumatic stress in residential care (Schuurmans, et al., 2020 ); with premature alcohol exposure (Reid and Petrenko, 2018 ); with different types of intellectual disability (Laborde et al., 2017 ); or with a population diagnosed with ADHD (Groeneveld et al., 2019 ; Lloyd et al., 2010 ; Price et al., 2017 ; Rukmani et al., 2016 ; Wade et al., 2017 ). Therefore, part of the experimental group was selected according to the school's criteria. The rest of the experimental group was selected randomly, as was the control group. An advantage of the design is that it allows the effect of biofeedback to be studied in all three cycles of primary school. This distinction made it possible to determine whether the age and developmental stage of the students influenced the effectiveness of the treatment. Attentional processes are thought to improve with age (Jiménez et al., 2012 ; Rivera et al., 2017 ). For example, Jiménez et al. ( 2012 ) tested 1,032 primary school students with the d2 attention test (Brickenkamp, 2002 ) and found that performance improved significantly as a function of age. Consistent with these, the present study found that attentional ability and performance on the attention test improved with age across all dimensions. Although these age and developmental improvements were significant, it can be seen that the initially disadvantaged experimental group at the end of the treatment resembled the performance of the control groups in all cycles. In other words, both groups, experimental and control, improved significantly from pre-test to post-test, but more significantly in the experimental group. It should be noted that the treatment had a greater impact and effect size on students in the first cycle. In this cycle, the participants in the experimental group improved their correct scores, reduced their omissions and improved their concentration and efficiency in the test compared to the control group. With regard to the effectiveness of HRV biofeedback interventions for improving attention in the school setting, as mentioned above, only two studies have been conducted with primary school students. The first is the study by Crevenna et al. ( 2016 ), who conducted a 6-week HRV biofeedback programme with 15 fourth-year primary school students aged 10 years, which also aimed to improve attentional capacity as measured by the d2 (Brickenkamp, 2002 ). After the intervention, the experimental group showed significant improvements from baseline to the end of the intervention. Furthermore, this improvement was maintained until the end of the school year, showing that the benefits of the training were maintained over time. The second HRV biofeedback intervention was proposed by Rush et al. ( 2017 ) with 27 boys and girls aged 8–12 years. They focused on intervening with students with special needs characterised by poor academic performance and difficulties with social skills.They designed a 12-week training with the aim of improving persistence or maintenance in performing a task, as measured by the 'Behavioural Observation of Students in Schools' (BOOS) (Shapiro, 2011 ). After the intervention, students in the treatment group spent significantly less time off-task than students in the control group. Therefore, we believe that the results obtained in this study are consistent with those observed in previous studies. Thus, our research shows that by using the breathing pattern learned through HRV biofeedback (approximately 6 breaths per minute), participating students improve their attentional capacity. And this improvement seems to have a particular effect on the earliest ages of primary school. As far as the limitations of this study are concerned, the main one is the composition of the experimental group itself. The inclusion of students with a greater need for improvement creates a certain imbalance in the sample composition. At the same time, it also confirms the suitability of carrying out HRV biofeedback interventions with students with difficulties. Another limitation of our study stems from one of the main aims of the study; as one of the aims of the research was to analyse the effectiveness of the intervention in a cross-sectional manner, the study of the longitudinal effects of the intervention and the possible influence of other variables, for example, was left aside. Future research should therefore examine the long-term effects of such programmes and the role of other possible mediating variables. For example, given that maternal attachment seems to play a mediating role on HRV (Sichko et al., 2018 ), it seems of great interest to analyse the influence of maternal-father-child relationships on HRV and attentional capacity at this age (6–12 years). It is also worth analysing whether the improvement of attentional capacity has an impact on school performance, school climate and other realities of the learning process that takes place in school. In this way, more knowledge will be gained about the dynamics of biofeedback interventions for HRV, which will allow us to adapt and improve future HRV biofeedback programmes for improving attention in primary education, always based on their effectiveness. Declarations Author Contribution Ainara Aranberri wrote the main manuscript and Malen Migueles reviewed these. References Aranberri-Ruiz, A., Aritzeta, A., Olarza, A., Soroa, G., y Mindeguia, R. (2022). Reducing anxiety and social stress in primary education: A breath-focused heart rate variability biofeedback intervention. International Journal of Environmental Research and Public Health , 19(16), 10181. 10.3390/ijerph191610181 Aranberri-Ruiz, A. (2023). Emotional experience and its biological underpinnings: improving emotional well-being through vagal tone. Papeles del Psicólogo , 44(2), 95-101. 10.23923/pap.psicol.3016 Aritzeta, A., Soroa, G., Balluerka, N., Muela, A., Gorostiaga, A., y Alieri. J. (2017). Reducing Anxiety and improving academic performance through a biofeedback relaxation training program. Applied Psychophysiol Biofeedback , 42, 193-202. https://doi.org/10.1007/s10484-017-9367-z Aritzeta, A., Aranberri-Ruiz, A., Soroa, G., Mindeguia, R., y Olarza, A. (2022). Emotional self-regulation in primary education: A heart rate-variability biofeedback intervention programme. International journal of environmental research and public health , 19(9), 5475. 10.3390/ijerph19095475 Brickenkamp, R. (2002). D2, Test de atención. Madrid: TEA Ediciones. Crevenna, R., Krammer, C., y Keilani, M. (2016). Feasibility and acceptance of biofeedback-assisted mental training in an Austrian elementary school: a pilot study. Wiener Medizinische Wochenschrift , 166, 179-181. https://doi.org/10.1007/s10354-015-0397-y De Bie, H.M., Boersm, M., Adriaanse, S., Veltman, D.., Wink, A.M., Roosendaal, S.D., y Sanz‐Arigita, E.J. (2012). Resting‐state networks in awake five‐to eight‐year old children. Human Brain Mapping , 33, 1189-1201. https://doi.org/10.1002/hbm.21280 Duarte, L., Gonçalves, M., Mendes, P., Matos, L. C., Greten, H. J., y Machado, J. (2020). Can qigong improve attention in adolescents? a prospective randomised controlled trial. Journal of Bodywork & Movement Therapies , 24(1), 175–181. https://doi.org/10.1016/j.jbmt.2019.05.005 Fisher, A., Thiessen, E., Godwin, K., Kloos, H., y Dickerson, J. (2013). Assessing selective sustained attention in 3- to 5-year-old children: Evidence from a new paradigm. Journal of Experimental Child Psychology, 114, 275-294. https://doi.org/10.1016/j.jecp.2012.07.006 Forte, G., Favieri, F., y Casagrande, M. (2019). Heart Rate Variability and Cognitive Function: A Systematic Review. Frontiers in Neuroscience , 13, 2710. https://doi.org/10.3389/fnins.2019.00710 Goessl, V.C., Curtiss, J.E., y Hofmann, S.G. (2017). The effect of heart rate variability biofeedback training on stress and anxiety: a meta-analysis. Psychological Medicine , 47, 2578-2586. https://doi.org/10.1017/S0033291717001003 Groeneveld, K. M., Mennenga, A. M., Heidelberg, R. C., Martin, R. E., Tittle, R. K., Meeuwsen, K. D., Walker, L. A., y White, E. K. (2019). Z-score neurofeedback and heart rate variability training for adults and children with symptoms of attention-deficit/hyperactivity disorder: a retrospective study. Applied Psychophysiology and Biofeedback , 44 (4), 291–308. https://doi.org/10.1007/s10484-019-09439-x Herrero, J.L., Khuvis, S., Yeagle, E., Cerf, M., y Mehta, A.D. (2017). Breathing above the brain stem: volitional control and attentional modulation in humans. Journal of Neurophysiology , 119, 145-159. https://doi.org/10.1152/jn.00551.2017 Institute of HeartMath (2012). EmWave Desktop©.California: HeartMath. Jennings, J. R., Sheu, L. K., Kuan, D. C.-H., Manuck, S. B., y Gianaros, P. J. (2016). Resting state connectivity of the medial prefrontal cortex covaries with individual differences in high-frequency heart rate variability. Psychophysiology , 53 (4), 444–454. https://doi.org/10.1111/psyp.12586 Jiménez, J. E., Hernández, S., García, E., Díaz, A., Rodríguez, C., y Martín, R. (2012). Test de atención D2: Datos normativos y desarrollo evolutivo de la atención en educación primaria [Attention test D2: Normative data and attention development in elementary grades]. European Journal of Education and Psychology, 5 (1), 93–106. https://doi.org/10.30552/ejep.v5i1.79 Kaufmann, T., Alnæs, D., Doan, N., Brandt. C.L., Andreassem, O.A., y Wrtlye, L.T. (2017). Delayed stabilization and individualization in connectome development are related to psychiatric disorders. Nature Neuroscience , 20, 513–515. https://doi.org/10.1038/nn.4511 Kim, H., Duran, C. A. K., Cameron, C. E., y Grissmer, D. (2018). Developmental relations among motor and cognitive processes and mathematics skills. Child Development , 89 (2), 476–494. https://doi.org/10.1111/cdev.12752 Kredlow, M. A., de Voogd, L. D., y Phelps, E. A. (2022). A case for translation from the clinic to the laboratory. Perspectives on Psychological Science , 17(4), 1120-1149. 10.1177/17456916211039852 Laborde, S., Allen, M. S., Göhring N, y Dosseville, F. (2017). The effect of slow-paced breathing on stress management in adolescents with intellectual disability. Journal of Intellectual Disability Research , 61(6), 560–567. https://doi.org/10.1111/jir.12350 Lee, A., Lo, A. S. C., Keung, M. W., Kwong, C. M. A., y Wong, K. K. (2019). Effective health promoting school for better health of children and adolescents: indicators for success. Bmc Public Health , 19(1), 1–12. https://doi.org/10.1186/s12889-019-7425-6 Lloyd, A., Brett, D., y Wesnes, K. (2010). Coherence training in children with attention-deficit hyperactivity disorder: cognitive functions and behavioral changes. Alternative Therapies in Health & Medicine , 16(4). Lynch, M. D., y Chen, L. (2015). A mixed method analysis of an Early Intervention Program for students with behavioural and concentration difficulties in two schools in Malmö, Sweden (Doctoral dissertation, University of Sussex). Mikhailova, O. B. (2017). Characteristics of creativity and innovativeness manifestations in students of middle AHD high school. Journal of Psychology and Pedagogics , 14, 76–87. https://doi.org/10.22363/2313-1683-2017-14-1-76-87 Ning, K., y Wang, T. (2021). Multimodal Interventions Are More Effective in Improving Core Symptoms in Children With ADHD. Frontiers in psychiatry , 12,759315. https://doi.org/10.3389/fpsyt.2021.759315 Park, G., y Thayer, J.F. (2014). From the heart to the mind: cardiac vagal tone modulates top-down and bottom-up visual perception and attention to emotional stimuli . Frontiers in Psychology , 5, e278. https://doi.org/10.3389/fpsyg.2014.00278 Park, G., Vasey, M.W., Van Bavel, J.J., y Thayer, J.F. (2013). Cardiac vagal tone is correlated with selective attention to neutral distractors under load. Psychophysiology , 50, 398-406. https://doi.org/10.1111/psyp.12029 Porges S.W., y Raskin, D.C. (1969). Respiratory and heart rate components of attention. Journal of Experimental Psychology, 81, 497-503. https://doi.org/10.1037/h0027921 Porges, S.W. (1995). Orienting in a defensive world: Mammalian modifications of our evolutionary heritage. A polyvagal theory. Psychophysiology , 32, 301-318. https://doi.org/10.1111/j.1469-8986.1995.tb01213.x Porges, S.W. (2011). The polyvagal theory: neurophysiological foundations of emotions, attachment, communication, and self-regulation (Norton Series on Interpersonal Neurobiology). WW Norton & Company. Posner, M. I. (2012). Imaging attention networks. Neuroimage , 61, 450-456. https://doi.org/10.1016/j.neuroimage.2011.12.040 Posner, M. I., Rothbart, M. K., y Ghassemzadeh, H. (2020). Developing attention in typical children related to disabilities. In Handbook of clinical neurology (Vol. 173, pp. 215-223). Elsevier. https://doi.org/10.1016/B978-0-444-64150-2.00019-8 Porges, S. W. (2022). Polyvagal theory: a science of safety. Frontiers in Integrative Neuroscience , 16, 871227–871227. https://doi.org/10.3389/fnint.2022.871227 Posner, M. I. (2023). The evolution and future development of attention networks. Journal of Intelligence , 11(6). https://doi.org/10.3390/jintelligence11060098 Price, A., Collins, H., Martin, A., y Wade, M. (2017). The Effect of Emotional Self-Regulation Training Using Heart Rate Variability Biofeedback on Symptoms of ADHD in Elementary Age Children: A Pilot Study (Doctoral dissertation, Brenau University). Rabiner, D. L., Godwin, J., y Dodge, K. A. (2016). Predicting academic achievement and attainment: the contribution of early academic skills, attention difficulties, and social competence . School Psychology Review , 45(2), 250–267. 10.17105/SPR45-2.250-267 Reid, N., y Petrenko, C. L. M. (2018). Applying a developmental framework to the self-regulatory difficulties of young children with prenatal alcohol exposure: a review. Alcoholism: Clinical and Experimental Research , 42(6), 987–1005. https://doi.org/10.1111/acer.13756 Ristic, J., y Enns, J.T., (2015). The changing face of attentional development. Current Directions in Psychology Science , 24, 24–31. https://doi.org/10.1177/0963721414551165 Rivera, D., Salinas, C., Ramos-Usuga, D., Delgado-Mejía I.D, Vasallo Key, Y., Hernández Agurcia G.P, Valencia Vásquez J, García-Guerrero C.E, García de la Cadena C, Rabago Barajas, B. V., Romero-García I, Campos Varillas, A. I., Sánchez-SanSegundo M, Galvao-Carmona, A., Lara, L., Granja Gilbert, E. J., Martín-Lobo P, Velázquez-Cardoso J, y Caracuel, A. (2017). Concentration endurance test (d2): normative data for spanish-speaking pediatric population. Neurorehabilitation , 41(3), 661–671. https://doi.org/10.3233/NRE-172248 Rohr, C.S., Arora, A., Cho, I.Y., Katlariwala, P., Dimond, D., Dewey, D., y Bray, S. (2018). Functional network integration and attention skills in young children. Developmental Cognitive Neuroscience , 30, 200-211. https://doi.org/10.1016/j.dcn.2018.03.007 Rukmani, M. R., Seshadri, S. P., Thennarasu, K., Raju, T. R., y Sathyaprabha, T. N. (2016). Heart rate variability in children with attention-deficit/hyperactivity disorder: a pilot study. Annals of neurosciences , 23(2), 81-88. https://doi.org/10.1159/000443574 Rush, K.S., Golden, M., Mortenson, B.P., Albohn, D., y Horger, M. (2017). The effects of a mindfulness and biofeedback program on the on- and off-task behaviors of students with emotional behavioral disorders. Contemporary School Psychology , 21,347–357. https://doi.org/10.1007/s40688-017-0140-3 Sakaki, M., Yoo, H.J., Nga, L., Lee, L., Thayer, J.F., y Mather, M. (2016). Heart rate variability is associated with amygdala functional connectivity with MPFC across younger and older adults. NeuroImage , 139, 44-52. https://doi.org/10.1016/j.neuroimage.2016.05.076 Santa-Cruz, C., y Rosas, R. (2017). Mapping of executive functions/Cartografía de las funciones ejecutivas. Studies in Psychology , 38(2), 284-310. 10.1080/02109395.2017.1311459 Schachner, M.K. (2019). From equality and inclusion to cultural pluralism: Evolution and effects of cultural diversity perspectives in schools. European Journal of Developmental Psychology , 16, 1-17. https://doi.org/10.1080/17405629.2017.1326378 Schuurmans, A. A. T., Nijhof, K. S., Scholte, R., Popma, A., y Otten, R. (2020). A novel approach to improve stress regulation among traumatized youth in residential care: feasibility study testing three game-based meditation interventions. Early Intervention in Psychiatry , 14(4), 476–485. https://doi.org/10.1111/eip.12874 Schwartz, M.S., y Andrasik, F. (2003). Definitions of biofeedback and applied psychophysiology biofeedback: A practitioner’s guide . Nueva York: Guilford Press. Shaffer, F., y Ginsberg, J. P. (2017). An overview of heart rate variability metrics and norms. Frontiers in Public Health, 5 , 258. https://doi.org/10.3389/fpubh.2017.00258 Shaffer, C., Barrett, L. F., y Quigley, K. S. (2023). Signal processing in the vagus nerve: hypotheses based on new genetic and anatomical evidence. Biological Psychology , 182, 108626–108626. https://doi.org/10.1016/j.biopsycho.2023.108626 Shapiro, E. S. (2011). The Behavioral Observation of Students in Schools (BOSS). Nueva York: Pearson. Sichko, S., Borelli, J. L., Smiley, P. A., Goldstein, A., y Rasmussen, H. F. (2018). Child and maternal attachment predict school-aged children’s psychobiological convergence. Developmental Psychobiology , 60(8), 913–926. https://doi.org/10.1002/dev.21748 Spagna, A., Martella, D., Sebastiani, M., Maccari, L., Marotta, A., y Casagrande, M. (2014). Efficiency and interactions of alerting, orienting and executive networks: The impact of imperative stimulus type. Acta psychologica , 148, 209-215. https://doi.org/10.1016/j.actpsy.2014.02.007 Task Force of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology. (1996). Heart rate variability. Standards of measurement, physiological interpretation, and clinical use. Circulation , 93, 1043–1065. https://doi.org/10.1161/01.CIR.93.5.1043 Thayer, J.F., y Lane, R.D. (2009). Claude Bernard and the heart–brain connection: Further elaboration of a model of neurovisceral integration. Neuroscience & Biobehavioral Reviews , 33, 81-88. https://doi.org/10.1016/j.neubiorev.2008.08.004 Thayer, J. F., Hansen, A. L., Saus-Rose, E., & Johnsen, B. H. (2009). Heart rate variability, prefrontal neural function, and cognitive performance: The neurovisceral integration perspective on self-regulation, adaptation, and health. Annals of Behavioral Medicine, 37 (2), 141–153. https://doi.org/10.1007/s12160-009-9101-z Tinello, D., Kliegel, M., & Zuber, S. (2022). Does heart rate variability biofeedback enhance executive functions across the lifespan? A systematic review. Journal of Cognitive Enhancement , 6 (1), 126-142. https://doi.org/10.1007/s41465-021-00218-3 Wade, M., Collins, H., Martin, A., y Price, A. (2017). The Effect of Emotional Self-Regulation Training Using Heart Rate Variability Biofeedback on Symptoms of ADHD in Elementary Age Children: A Pilot Study . Tesis Doctoral de Brenau University. https://search.proquest.com/docview/1910063652?pq-origsite=gscholar&fromopenview=true Winkelmann, T., Thayer, J. F., Pohlack, S., Nees, F., Grimm, O., & Flor, H. (2017). Structural brain correlates of heart rate variability in a healthy young adult population. Brain Structure and Function, 222 (2), 1061–1068. https://doi.org/10.1007/s00429-016-1185-1 Xuan, B., Mackie, M.A., Spagna, A., Wu, T., Tian, Y., Hof, P.R., y Fan, J. (2016). The activation of interactive attentional networks. Neuroimage , 129, 308-319. https://doi.org/10.1016/j.neuroimage.2016.01.017 Zhang, W., y Bray, M. (2020). Comparative research on shadow education: achievements, challenges, and the agenda ahead. European Journal of Education , 55(3), 322–341. https://doi.org/10.1111/ejed.12413 Additional Declarations No competing interests reported. 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Specifically, in the primary school cycle, new school demands require students to develop learning skills related to letter and number identification in order to perform higher cognitive tasks (Mikhailova, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Schachner, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), such as reading and mathematical problem-solving (Kim et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Such tasks are strongly related to attentional capacity, which is crucial for learning (Duarte et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Fisher et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Rabiner et al., \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2016\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAttention is the activity of three brain networks (vigilance, orientation and executive control networks) that influence how information is processed (Posner, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Posner et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). The \u003cem\u003evigilance network\u003c/em\u003e is responsible for the state of alertness. The \u003cem\u003eorientation network\u003c/em\u003e focuses on locating specific sources of stimulation. Finally, the \u003cem\u003eexecutive control network\u003c/em\u003e is related to all the processes that help us to voluntarily regulate our behaviour and cognition through the control of attention. All three attentional networks interact with each other to influence attentional performance (Spagna et al., \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Xuan et al., \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2016\u003c/span\u003e) and are necessary for proper academic performance (Posner et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Posner, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Such networks are present in the infant brain, but with a lower degree of functional integration than in the adult brain (De Bie et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Johansen et al., 2023; Kaufmann et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; ). And greater integration occurs during infant development (De Bie et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2012\u003c/span\u003e), enabling better attentional performance (Posner et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Rohr et al., \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). In a normative study by Jim\u0026eacute;nez et al. (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2012\u003c/span\u003e), it was observed that in primary school, aged 6\u0026ndash;12 years, there is an improvement in attentional ability as measured by the D2 attention test (Brickenkamp, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2002\u003c/span\u003e) as development progresses. A later normative study by Rivera et al. (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) also confirmed this trend. Given that the D2 test integrates in its measurement the functions corresponding to the functioning of the three brain networks mentioned above, and that attention is in a developmental process during this period, the development of interventions aimed at improving attentional skills may be particularly appropriate, given the potential for improvement in school programmes (Lee et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Zhang and Bray, \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eHeart rate variability (hereafter HRV) refers to changes in the time interval that occurs between consecutive heartbeats (Shaffer and Ginsberg, \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Task Force, 2016) and is related to the functioning of the autonomic nervous system (Aranberri-Ruiz, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). HRV is an appropriate indicator of the stress response (Aranberri, 2023; Aranberri et al., 2022; Alitzeta et al., 2022; Alitzeta et al., 2017; Immanuel et al., 2023) and the level of cognitive function (Thayer et al., \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Winkelmann et al., \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Furthermore, HRV has been shown to be an appropriate measure of attentional capacity (Forte et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Jennings et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Park and Thayer, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Porges and Raskins, 1969; Sakaki et al., \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Thayer and Lane, \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Ning and Wang, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Tinello et al., \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Through biofeedback techniques we obtain real-time information about variations in HRV (Schwartz and Andrasik, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2003\u003c/span\u003e) and we can learn to modulate our HRV by practising slow and prolonged breathing (Goessl et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). The Polyvagal Theory (Porges, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e1995\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2011\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) justifies the impact of slow and prolonged breathing on the ventral vagus nerve and its parasympathetic influence, reducing the heart rate and increasing HRV itself by reducing the activity of the adrenal sympathetic system and the consequent stress response (Aranberri-Ruiz, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), thus making it possible to improve attentional capacity (Kredlow, et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eHRV biofeedback programmes focused on learning a breathing pattern of approximately 6 breaths per minute - a measure also validated through studies of the impact of the breathing pattern on evoked action potentials of different brain areas (Herrero et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) - have been shown to be effective in improving academic-cognitive performance and attentional capacity (Aritzeta et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Park et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Rush et al., \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). In the school context we have only found two HRV biofeedback interventions implemented to improve attentional capacity in Primary Education (Crevenna et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Rush et al., \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). The intervention developed by Crevena et al. (2016) was aimed at 15 pupils in the 4th year of Primary School, while the intervention by Rush et al. (\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) was aimed at 27 pupils aged 8 to 12 years. In both studies, the participating students improved their attentional capacity after the training. However, these are very small samples and do not allow a comparison of the differential effectiveness of the treatment in the three cycles that make up Primary Education to be made in a single study.\u003c/p\u003e \u003cp\u003eThus, given the effectiveness and scarcity of HRV biofeedback interventions in school settings, a HRV biofeedback programme focused on breathing was designed to improve the attentional capacity of primary school students. We expect that, as in previous studies and independently of the educational cycle, the training will improve performance on the d2 attention test (Brickenkamp, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2002\u003c/span\u003e). Further aims of the study are to examine the interactions of training with educational level on different measures of attention.\u003c/p\u003e"},{"header":"Material and methods","content":"\u003cp\u003eThis study included 585 elementary school students (46.4% were girls and 53.5% were boys) aged between 7 and 12 years (M = 8.51; SD = 1.26). This sample was divided according to the cycles of primary schooling, with 21.4% belonging to the first cycle, 64.6% to the second cycle and the remaining 14% to the third cycle.\u003c/p\u003e \u003cp\u003eIn order to carry out the study, the sample was divided into an experimental group and a control group. Regarding the composition of the experimental group, it was decided, at the suggestion of the school management, to assign students with different difficulties (emotional, academic, etc.) to the experimental group. The selection process involved the tutors, the teaching staff, the head of therapeutic education and the management team. The rest of the students were randomly assigned. Thus, in the first cycle we had 83 participants in the experimental group and 42 in the control group, in the second cycle 257 participants in the experimental group and 121 in the control group, and finally in the third cycle 49 participants in the experimental group and 33 in the control group.\u003c/p\u003e \u003cp\u003eThe participation of the students was voluntary and consented to by the school council, parents and guardians. The study had the favourable report of the ethics committee for research with human beings, their samples and data (CEISH/269 1-2-3-4-/2014) of the University of the Basque Country/Euskal Herriko Unibertsitatea with DSI file INA0079. The ethical aspects required for research with human subjects (informed consent, right to information, protection of personal data, guarantees of confidentiality, non-discrimination, free of charge and the possibility of abandoning the study at any stage) were scrupulously respected.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eDesign\u003c/h2\u003e \u003cp\u003eThe biofeedback treatment to teach girls and boys to breathe consists of 5 sessions - individual sessions - that make up the programme: the first measure being the baseline measure, and the last measure being the final treatment or post-treatment measure. To assess the impact of the training on the students' attentional capacity, a mixed design 2 (Group: control, experimental) x 2 (Assessment: pre- and post-training) x 3 (Educational cycle: first, second and third) was used, with the factors Group and Educational cycles being independent or inter-participant measures and the factor Assessment being intra-participant or repeated measures. The dependent variable was performance on the d2 attention test (Brickenkamp, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2002\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eProcedure and Instruments\u003c/h2\u003e \u003cp\u003eThe HeartMath Emwave software (Institute of HeartMath, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2012\u003c/span\u003e) was chosen in this study to investigate the effects of an HRV biofeedback programme on attention tasks and to teach prolonged and paused breathing. This software has been shown to be effective in several studies (Aranberri et al., 2022; Aritzeta et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Aritzeta et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Rush, et al., \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). In this software, HRV is measured in real time by means of the application's own sensor, which is placed on the participant's earlobe. In this way, the computer, through the images on the screen, offers the HRV values in real time, thus allowing the subject to observe the impact that the breathing pattern itself has on HRV. By means of different software applications, the children learn, through trial, error and success, to breathe in a prolonged and paused manner (approximately 6 breaths per minute), thus increasing their own HRV. Based on the HeartMath Emwave software (Institute of HeartMath, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2012\u003c/span\u003e), an HRV biofeedback programme for attentional improvement was developed in two implementation phases.\u003c/p\u003e \u003cp\u003ePhase 1 or pre-intervention. It consists of theoretical and practical training in the aforementioned computer application - HeartMath Emwave software (Institute of HeartMath, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2012\u003c/span\u003e) - for the school's teaching staff, thus providing the necessary training for teachers to be able to carry out the training programme developed for each individual pupil, which will be described in phase 2 below.\u003c/p\u003e \u003cp\u003ePhase 2 or intervention programme. It consists of 6 weekly sessions: the first one in a group and the remaining 5 individual sessions. In the first session in each classroom participating in the programme, the tutor, together with a member of the research team, explains the intervention to all the students in a pleasant way. After one week, individual biofeedback training in HRV biofeedback begins for each student. The 5 individual sessions will be carried out with the tutor of each student in a relaxed and suitable place to develop the intervention. There will be two chairs - one for the tutor and one for each student - a table with a computer and the HeartMath Emwave software (Institute of HeartMath, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2012\u003c/span\u003e) installed, and the computer application's own earlobe sensor to detect HRV. The duration of the individual sessions is 20 minutes and after each session the tutors record the HRV values obtained by each participant on each student's individual record sheet. Throughout the 5 sessions and through the applications Coherence Coach and Baloom Game -which resemble animations and cartoons, from the HeartMath Emwave software (Institute of HeartMath, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2012\u003c/span\u003e)- the children learn to breathe slowly and slowly through trial, error and success by performing different actions, all with the common objective of teaching them to breathe slowly and slowly (approximately 6 pairs of breaths per minute), gradually, session by session. In the third session, in order to be able to generalise what they have learnt, each pupil is given a \"target\" image - specific to the programme - laminated in 6x4cm so that they can carry it in their school bag and use it when the teachers recommend it and when they feel nervous. In this way, the image helps them to breathe in a slow and prolonged way without the need for the computer programme. In the remaining sessions, 4 and 5, they continue practising the breathing they have learnt together with the aforementioned image. In the last session, the intervention ends by congratulating each participating pupil, placing special emphasis on the importance of the breathing practice learnt and the use of the image mentioned.\u003c/p\u003e \u003cp\u003eTo assess the attentional capacity before and after training, both the control group and the experimental group used the d2 attention test (Brickenkamp, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2002\u003c/span\u003e). This is a test that measures attention designed for people between 6 and 60 years of age. It is a test composed of 14 lines, each with 47 characters. Participants must identify any letter \"d\" that has two dashes (one at the top and one at the bottom, both at the top and both at the bottom). These are known as relevant or target items, and items that do not have these characteristics are known as irrelevant or distractors. The participants have 20 seconds for each line, and it is the instructor who tells them when to start and finish. The dimensions considered in this study were: Total correctly processed (TN-E); omissions (O) -total number of relevant items not marked-; as well as the TOTR count -which is calculated by subtracting the sum of omissions (O) and errors (E)- from the Total correctly processed (TN-E) and measures the total effectiveness of the test; and concentration (CON) -which is calculated by subtracting errors (E) from the total number of answers (TA). The psychometric properties of the d2 are adequate (average reliability coefficient of 0.95).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e\u003c/p\u003e \u003c/div\u003e"},{"header":"Analysis and results","content":"\u003cp\u003eFirst, a normality analysis was performed using the Kolmogorov-Smirnov test. The results showed that there was normality of the data distribution.\u003c/p\u003e\u003cp\u003eThe results on the effectiveness of biofeedback training show that, from the HRV measurement at the beginning of the training to the final assessment, all participants in the experimental group learned to breathe in a prolonged and slow manner, F(1.97) = 176.26, p = 000; \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\eta }_{p}^{2}\\)\u003c/span\u003e\u003c/span\u003e= 0.372. This learning occurred in all educational cycles F(2, 297)=11.10, p=.000,\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\eta }_{p}^{2}=\\)\u003c/span\u003e\u003c/span\u003e.070 but as the interaction shows F(2,297)=21.05; p=.000; \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\eta }_{p}^{2}=0.124\\)\u003c/span\u003e\u003c/span\u003e it was the students in the second cycle (Cycle 2=HRV session 1: M=23.78;HRV session 5: M= 94.99) who showed a greater improvement from the first HRV measurement to the last measurement after the end of the programme (Cycle 1=HRV session 1: M = 26.61;HRV session 5: M= 49.77; Cycle 3=HRV session 1: M=13.16;HRV session 5: M= 54.84).\u003c/p\u003e\u003cp\u003ePerformance in the attention test was assessed by scoring one point for each mark made, whether correct or incorrect. In addition, omissions or unmarked stimuli were also scored. Thus, to examine the impact of HRV biofeedback training on the attentional performance of girls and boys in the d2 test, we analysed the hit rate, omissions, task concentration and total test effectiveness (see Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Results were analysed with ANOVAS for mixed designs, 2 (Group: control, experimental), x 2 (Assessment: pre- and post-training), x 3 (Educational cycle: first, second and third) with the variables Group and Educational cycle as independent measures and Assessment as repeated measures. Post-hoc comparisons were performed with the Bonferroni test and pairwise comparisons with Student's t-test.\u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u003cem\u003eMeans and standard deviations in brackets of the experimental and control groups in the pretest and posttest for the 3 cycles of primary education.\u003c/em\u003e\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e\u003ccolgroup cols=\"8\"\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e \u003cp\u003eExperimental\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colspan=\"3\" nameend=\"c8\" namest=\"c6\"\u003e \u003cp\u003eControl\u003c/p\u003e \u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCycle 1\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCycle 2\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCycle 3\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCycle 1\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eCycle 2\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eCycle 3\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eM(DT)\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eM(DT)\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eM(DT)\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eM(DT)\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003eM(DT)\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cem\u003eM(DT)\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cem\u003eTN-E\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003epre\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e57.13 (26.13)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e96.76(41.13)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e136.79(44.96)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e73(27.00)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e103.14(32.16)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e153.85(33.73)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003epost\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e85.32(27.06)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e120.02(38.39)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e165.68(42.41)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e68.87(30.29)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e118.92(41.23)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e154.35(54.39)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cem\u003eCON\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003epre\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e43.23(28.50)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e89.56(48.20)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e132.75(47.36)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e42.78(37.28)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e95.92(35.04)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e148.36(45.41)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003epost\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e76.57(30.28)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e116.04(39.87)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e163.51(44.75)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e51.72(50.75)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e121.09(37.07)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e163.67(37.75)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cem\u003eTO\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003epre\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e243.11(27.89)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e201.90(41.49)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e162.21(44.95)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e225.22(26.66)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e195.86(31.94)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e145.09(33.82)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003epost\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e213.22(27.46)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e167.40(56.43)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e127.86(49.23)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e229.97(30.31)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e152.42(69.10)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e116(55.81)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cem\u003eTOTR\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003epre\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e57.13(26.13)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e96.76(41.13)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e136.79(44.96)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e73(27.00)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e103.14(32.16)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e153.85(33.73)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003epost\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e85.32(27.06)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e120.55(37.64)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e165.68(42.41)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e68.87(30.29)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e123.59(34.42)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e165.78(34.89)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/table\u003e\u003c/div\u003e\u003cp\u003e \u003cem\u003e* Total correctly processed (TN-E), CON concentration (total hits-errors), TO total omissions and TOTR total responses - (omissions + errors).\u003c/em\u003e \u003c/p\u003e\u003cp\u003eTotal correctly processed\u003c/p\u003e\u003cp\u003eThe Total correctly processed (TN-E) measure refers to the number of relevant characters marked correctly. The number of Total Answers was higher in the post evaluation than in the pre evaluation (119.17 vs. 98.27), F(1, 490) = 89.08, p = 0.001, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\eta }_{p}^{2}\\)\u003c/span\u003e\u003c/span\u003e=0.154. Although the Group factor was not significant, it interacted with the Evaluation factor, F(1, 490)=45.53, p=0.991, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\eta }_{p}^{2}\\)\u003c/span\u003e\u003c/span\u003e= 0.083. Thus, although in the initial evaluation, the control group obtained more correct scores in the attention test than the experimental group (105.48 vs 94.01), t(552)=-2.97, p = 0.004, d=0.268) after training, in the final evaluation there were no significant differences between the control and experimental groups (113.61 vs 118.62), t(523)=1.86, p=0.236, d=0.18. However, each of the groups improved in the total number of correct scores from the initial assessment to the final assessment, showing a greater impact of training on the experimental group compared to the control group (control t(164)=-3.58, p = 0.000, d=-0.220; experimental t(330)=-15.81, p = 0.000, d=-0.580). In addition, the educational cycle factor was significant, F(2,490)=120, p = 0.000, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\eta }_{p}^{2}\\)\u003c/span\u003e\u003c/span\u003e=Post hoc comparisons with the Bonferroni test showed that as the age of the students increases, the performance in the number of correct answers increases in the attention test. Thus, students in cycle 1 performed worse (M=71.31) than students in cycle 2 (M=111.40) and cycle 3 (M=152.81). Moreover, students in cycle 3 also outperformed students in cycle 2 (p=0.000). Finally, the interaction Group x Educational Cycle x Assessment was significant, F(2,490)=10.33, p=0.000, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\eta }_{p}^{2}\\)\u003c/span\u003e\u003c/span\u003e=An important aspect to highlight is the special positive impact shown by the intervention on Cycle 1 in relation to the improvement in the total number of correct scores obtained. On the one hand, and recalling that the experimental group obtained worse scores in total hits than the control group in the pretest, it should be noted that cycle 1 is the only cycle of the experimental group that shows an improvement in the scores in relation to the control group (85.32 vs. 68.87), t(113)=2.86, p = 0.006, d=0.574). Moreover, in cycle 1 the experimental group obtains a statistically significant improvement from the first assessment to the last assessment with a large effect size (t(66)=-8.135, p = 0.000, d=-1.204) higher than the rest of the educational cycles which obtain moderate effect sizes (cycle 2: t(216)=-11.82, p = 0.000, d=-0.610; cycle 3: t(44)=-6.95, p = 0.000, d=-0.689).\u003c/p\u003e\u003cp\u003eOmissions\u003c/p\u003e\u003cp\u003eThe Omission measure refers to the total number of relevant items not checked. The number of Omissions was lower in the post evaluation than in the pre evaluation (165.949 vs. 201.002), F(1,521) = 99.89, p = 0.001, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\eta }_{p}^{2}\\)\u003c/span\u003e\u003c/span\u003e=0.161. The Group x Evaluation interaction was also significant F(1,521)=5.43, p=0.002, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\eta }_{p}^{2}\\)\u003c/span\u003e\u003c/span\u003e=0.020. Thus, in the initial evaluation the control group committed a lower number of omissions than the experimental group (193.94 vs. 205.02), t(552)=2.96, p = 0.003, d=0.272, while in the final evaluation no statistically significant differences between the control group and the experimental group (162.51 vs. 171.61), t(553)=1.64, p = 0.101, d = 0.143. Although both the control and experimental groups improve performance from the initial assessment to the final assessment, the improvement is more relevant in the experimental group (control: t(179)=6.98, p = 0.000, d = 0.606; experimental: t(346) = 13.28, p = 0.000, d = 0.775). The factor educational cycle was significant, F(2,521)=123.91, p = 0.000, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\eta }_{p}^{2}\\)\u003c/span\u003e\u003c/span\u003e=Post hoc comparisons with the Bonferroni test showed that as the age of the students increased, performance in the omissions dimension improved and the number of omissions decreased. Thus, students in cycle 1 performed worse (M=227.586) than students in cycle 2 (M=180.1664) and cycle 3 (M=139.203). Moreover, students in cycle 3 also outperformed students in cycle 2 (p=0.000). We observed significant interactions between Assessment time x Educational cycle F(2,521)=9.82, p = 0.000, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\eta }_{p}^{2}\\)\u003c/span\u003e\u003c/span\u003e=.036 and between Assessment time x Group x Educational cycle F(2,521)=7.94, p = 0.000, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\eta }_{p}^{2}\\)\u003c/span\u003e\u003c/span\u003e=0.030. Recalling that the experimental group obtained worse scores than the experimental group in the pretest, in the posttest the experimental group in cycle 1 obtained better scores (213.22 vs. 229.97), t(113)=-2.89, p = 0.005, d= -0.580). Moreover, the experimental group of cycle 1 obtains better scores in the posttest than in the pretest with a large effect size (t(66)=7.97, p = 0.000, d=1,230) higher than in the rest of the educational cycles (cycle 2: t(230)=9,916, p = 0.000, d= 0.746; cycle 3: t(46)=6.49, p = 0.000; d=0.753).\u003c/p\u003e\u003cp\u003eConcentration\u003c/p\u003e\u003cp\u003eThe Concentration measure is a measure of accuracy calculated by subtracting errors from the total number of hits. Analyses showed that there was a higher Concentration in the final evaluation than in the initial evaluation (115.646 vs. 89.886), F(1,485) = 162.090, p = 0.000, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\eta }_{p}^{2}\\)\u003c/span\u003e\u003c/span\u003e=0.250. The factor Group was not significant but interacted with the factor Evaluation, F(1,485)=10.04, p=0.000, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\eta }_{p}^{2}\\)\u003c/span\u003e\u003c/span\u003e=0.028. Thus, it is observed that there were significant differences (p\u0026lt;.05) between the control and experimental groups in the initial evaluation (85.86 vs 93.52) but not in the final evaluation (113.84 vs 111.88). The variable Educational cycle was also significant, F(2,485)=149.89, p = 0.000, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\eta }_{p}^{2}\\)\u003c/span\u003e\u003c/span\u003e=Post hoc comparisons with the Bonferroni test showed that as the age of the students increases, performance in the concentration dimension increases. Thus, as in the rest of the dimensions analysed, there was a significant improvement (p=0.000) as the participants progressed through the educational cycle (first cycle M=53.63; second cycle M= 08.25; third cycle M=152.10). The interaction Group x Educational level was also significant, F(2,485)=3.56, p= 0.029, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\eta }_{p}^{2}\\)\u003c/span\u003e\u003c/span\u003e=0.1 and the interaction Evaluation x Group x Educational Level F(2, 485)=5.46, p=0.05,\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\eta }_{p}^{2}\\)\u003c/span\u003e\u003c/span\u003e=0.22. Thus, as with the rest of the dimensions analysed, it can be seen that in the first cycle biofeedback training is more effective than in the rest of the educational cycles. It is also observed that taking into account that the experimental group obtained worse scores than the control group in the pre-test, in the post-test cycle 1 obtains better scores in Concentration than the control group (76.56 vs. 51.71). Also in cycle 1 there is a statistically significant improvement in the Concentration measure in the posttest with respect to the pretest and with a large effect size (t(66)=-9.44, p=0.000, d=-1.213) higher than in the rest of the cycles (cycle 2: t(216)=-11.09, p=0.000, d=-0.621; cycle 3: t(44)=-8.07, p = 0.000, d=-0.741).\u003c/p\u003e\u003cp\u003eTotal Test Rate Effectiveness (TOTR)\u003c/p\u003e\u003cp\u003eThis measure measures the overall effectiveness of the test by subtracting the sum of omissions and errors from the total number of responses. The TOTR measure was higher in the post than in the pre assessment (120.63 vs. 98.03), F(1, 484) = 150.286, p = 0.000, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\eta }_{p}^{2}\\)\u003c/span\u003e\u003c/span\u003e=0.237. Although the Group factor was not significant, it interacted with the Evaluation factor, F(1,484)=35.51, p=0.000, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\eta }_{p}^{2}\\)\u003c/span\u003e\u003c/span\u003e=Thus, although in the initial evaluation the control group scored better in the TOTR variable than the experimental group (105.48 vs 94.01), t(552)=-2.927, p = 0.004, d=0.268) after training, in the final evaluation there were no significant differences between the control and experimental groups (117.67 vs 118.96), t(516)=0.314, p=0.753, d=0.029. However, each of the groups improved their performance in this dimension from the initial assessment to the final assessment, showing a greater impact of training on the experimental group compared to the control group (control t(159)=-6.69, p = 0.000, d=-0.324; experimental t(329)=-16.49, p=.000, d=-0.588). The factor Educational cycle was also significant, F(2,484)=130.83, p = .000, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\eta }_{p}^{2}\\)\u003c/span\u003e\u003c/span\u003e=0.351. Post hoc comparisons with the Bonferroni test showed that as the age of the participants increases, the performance in the total effectiveness of the test increases. Thus, students in cycle 1 performed worse (M=71.55) than students in cycle 2 (M=111.48) and cycle 3 (M=154.45). Moreover, students in cycle 3 also outperformed students in cycle 2 (p=.000). Finally, the interaction Group x Educational Cycle x Assessment was significant, F(2,484)=10.07, p=0.000, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({\\eta }_{p}^{2}\\)\u003c/span\u003e\u003c/span\u003e=0.051. Thus, as with the rest of the variables analysed, it can be seen that biofeedback training is more effective in cycle 1. Remembering that the experimental group also obtained worse scores in the total effectiveness of the test, cycle 1 in the post-test obtained better results than the control group (85.32 vs 68.87), t(113)=2.86, p=0.006, d=0.574). And in relation to the improvement of the total test effectiveness scores of the experimental group in the posttest compared to the pretest, cycle 1 also obtains a very large effect size (t(66)=-8.13, p=0.000, d=-1.204) higher than the rest of the cycles (cycle 2: t(215)=-12.63, p = 0.000, d=-0.631; cycle 3: t(44)=-6.95, p = 0.000, d=-0.689).\u003c/p\u003e"},{"header":"Discussion and conclusions","content":"\u003cp\u003eThe aim of the HRV biofeedback intervention is to improve attention in primary school children. The results of the study show that the intervention developed on the HeartMath Enwave software (Institute of HeartMath, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2012\u003c/span\u003e) is a simple and effective strategy to modify the way children breathe and influence their HRV and improve their attentional capacity. In contrast to previous studies that have analysed the effects of biofeedback based on prolonged and paused breathing in primary education with very small samples (Crevenna et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2016\u003c/span\u003e) or with inhomogeneous age groups (Rush et al., \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), this study distinguished the effects in three cycles of primary education and with a large number of participants.\u003c/p\u003e \u003cp\u003eIn order to understand the results obtained, it is necessary to understand the composition of the experimental group. The participating school recommended that part of the experimental group should be made up of pupils who, because of their personal situation, needed to improve their attention and academic performance. We considered that, as in previous studies (Lynch and Chen, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Rukmani, et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Rush et al., \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Wade et al., \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), the non-randomisation of students in need of attentional improvement and academic performance corresponded to an educational and personal adjustment criterion that we prioritised in this intervention. This acceptance found its empirical foundation in the positive results observed in different biofeedback interventions. Such as those developed on academic performance and well-being with children with traumatic stress in residential care (Schuurmans, et al., \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2020\u003c/span\u003e); with premature alcohol exposure (Reid and Petrenko, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2018\u003c/span\u003e); with different types of intellectual disability (Laborde et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2017\u003c/span\u003e); or with a population diagnosed with ADHD (Groeneveld et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Lloyd et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Price et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Rukmani et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Wade et al., \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Therefore, part of the experimental group was selected according to the school's criteria. The rest of the experimental group was selected randomly, as was the control group.\u003c/p\u003e \u003cp\u003eAn advantage of the design is that it allows the effect of biofeedback to be studied in all three cycles of primary school. This distinction made it possible to determine whether the age and developmental stage of the students influenced the effectiveness of the treatment. Attentional processes are thought to improve with age (Jim\u0026eacute;nez et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Rivera et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). For example, Jim\u0026eacute;nez et al. (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2012\u003c/span\u003e) tested 1,032 primary school students with the d2 attention test (Brickenkamp, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2002\u003c/span\u003e) and found that performance improved significantly as a function of age. Consistent with these, the present study found that attentional ability and performance on the attention test improved with age across all dimensions. Although these age and developmental improvements were significant, it can be seen that the initially disadvantaged experimental group at the end of the treatment resembled the performance of the control groups in all cycles. In other words, both groups, experimental and control, improved significantly from pre-test to post-test, but more significantly in the experimental group. It should be noted that the treatment had a greater impact and effect size on students in the first cycle. In this cycle, the participants in the experimental group improved their correct scores, reduced their omissions and improved their concentration and efficiency in the test compared to the control group.\u003c/p\u003e \u003cp\u003eWith regard to the effectiveness of HRV biofeedback interventions for improving attention in the school setting, as mentioned above, only two studies have been conducted with primary school students. The first is the study by Crevenna et al. (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2016\u003c/span\u003e), who conducted a 6-week HRV biofeedback programme with 15 fourth-year primary school students aged 10 years, which also aimed to improve attentional capacity as measured by the d2 (Brickenkamp, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2002\u003c/span\u003e). After the intervention, the experimental group showed significant improvements from baseline to the end of the intervention. Furthermore, this improvement was maintained until the end of the school year, showing that the benefits of the training were maintained over time. The second HRV biofeedback intervention was proposed by Rush et al. (\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) with 27 boys and girls aged 8\u0026ndash;12 years. They focused on intervening with students with special needs characterised by poor academic performance and difficulties with social skills.They designed a 12-week training with the aim of improving persistence or maintenance in performing a task, as measured by the 'Behavioural Observation of Students in Schools' (BOOS) (Shapiro, \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). After the intervention, students in the treatment group spent significantly less time off-task than students in the control group. Therefore, we believe that the results obtained in this study are consistent with those observed in previous studies. Thus, our research shows that by using the breathing pattern learned through HRV biofeedback (approximately 6 breaths per minute), participating students improve their attentional capacity. And this improvement seems to have a particular effect on the earliest ages of primary school.\u003c/p\u003e \u003cp\u003eAs far as the limitations of this study are concerned, the main one is the composition of the experimental group itself. The inclusion of students with a greater need for improvement creates a certain imbalance in the sample composition. At the same time, it also confirms the suitability of carrying out HRV biofeedback interventions with students with difficulties. Another limitation of our study stems from one of the main aims of the study; as one of the aims of the research was to analyse the effectiveness of the intervention in a cross-sectional manner, the study of the longitudinal effects of the intervention and the possible influence of other variables, for example, was left aside.\u003c/p\u003e \u003cp\u003eFuture research should therefore examine the long-term effects of such programmes and the role of other possible mediating variables. For example, given that maternal attachment seems to play a mediating role on HRV (Sichko et al., \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), it seems of great interest to analyse the influence of maternal-father-child relationships on HRV and attentional capacity at this age (6\u0026ndash;12 years). It is also worth analysing whether the improvement of attentional capacity has an impact on school performance, school climate and other realities of the learning process that takes place in school. In this way, more knowledge will be gained about the dynamics of biofeedback interventions for HRV, which will allow us to adapt and improve future HRV biofeedback programmes for improving attention in primary education, always based on their effectiveness.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eAinara Aranberri wrote the main manuscript and Malen Migueles reviewed these.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAranberri-Ruiz, A., Aritzeta, A., Olarza, A., Soroa, G., y Mindeguia, R. (2022). Reducing anxiety and social stress in primary education: A breath-focused heart rate variability biofeedback intervention. \u003cem\u003eInternational Journal of Environmental Research and Public Health\u003c/em\u003e, 19(16), 10181. 10.3390/ijerph191610181\u003c/li\u003e\n\u003cli\u003eAranberri-Ruiz, A. (2023). Emotional experience and its biological underpinnings: improving emotional well-being through vagal tone. \u003cem\u003ePapeles del Psic\u0026oacute;logo\u003c/em\u003e, 44(2), 95-101. 10.23923/pap.psicol.3016\u003c/li\u003e\n\u003cli\u003eAritzeta, A., Soroa, G., Balluerka, N., Muela, A., Gorostiaga, A., y Alieri. J. (2017). Reducing Anxiety and improving academic performance through a biofeedback relaxation training program. \u003cem\u003eApplied Psychophysiol Biofeedback\u003c/em\u003e, 42, 193-202. https://doi.org/10.1007/s10484-017-9367-z\u003c/li\u003e\n\u003cli\u003eAritzeta, A., Aranberri-Ruiz, A., Soroa, G., Mindeguia, R., y Olarza, A. (2022). Emotional self-regulation in primary education: A heart rate-variability biofeedback intervention programme.\u003cem\u003e International journal of environmental research and public health\u003c/em\u003e, 19(9), 5475. 10.3390/ijerph19095475\u003c/li\u003e\n\u003cli\u003eBrickenkamp, R. (2002). D2, Test de atenci\u0026oacute;n. Madrid: TEA Ediciones.\u003c/li\u003e\n\u003cli\u003eCrevenna, R., Krammer, C., y Keilani, M. (2016). Feasibility and acceptance of biofeedback-assisted mental training in an Austrian elementary school: a pilot study. \u003cem\u003eWiener Medizinische Wochenschrift\u003c/em\u003e, 166, 179-181. https://doi.org/10.1007/s10354-015-0397-y\u003c/li\u003e\n\u003cli\u003eDe Bie, H.M., Boersm, M., Adriaanse, S., Veltman, D.., Wink, A.M., Roosendaal, S.D., y Sanz‐Arigita, E.J. (2012). Resting‐state networks in awake five‐to eight‐year old children. \u003cem\u003eHuman Brain Mapping\u003c/em\u003e, 33, 1189-1201. https://doi.org/10.1002/hbm.21280\u003c/li\u003e\n\u003cli\u003eDuarte, L., Gon\u0026ccedil;alves, M., Mendes, P., Matos, L. C., Greten, H. J., y Machado, J. (2020). Can qigong improve attention in adolescents? a prospective randomised controlled trial. \u003cem\u003eJournal of Bodywork \u0026amp; Movement Therapies\u003c/em\u003e, 24(1), 175\u0026ndash;181. https://doi.org/10.1016/j.jbmt.2019.05.005\u003c/li\u003e\n\u003cli\u003eFisher, A., Thiessen, E., Godwin, K., Kloos, H., y Dickerson, J. (2013). Assessing selective sustained attention in 3- to 5-year-old children: Evidence from a new paradigm. \u003cem\u003eJournal of Experimental Child Psychology,\u003c/em\u003e 114, 275-294. https://doi.org/10.1016/j.jecp.2012.07.006\u003c/li\u003e\n\u003cli\u003eForte, G., Favieri, F., y Casagrande, M. (2019). Heart Rate Variability and Cognitive Function: A Systematic Review. \u003cem\u003eFrontiers in Neuroscience\u003c/em\u003e, 13, 2710. https://doi.org/10.3389/fnins.2019.00710\u003c/li\u003e\n\u003cli\u003eGoessl, V.C., Curtiss, J.E., y Hofmann, S.G. (2017). The effect of heart rate variability biofeedback training on stress and anxiety: a meta-analysis. \u003cem\u003ePsychological Medicine\u003c/em\u003e, 47, 2578-2586. https://doi.org/10.1017/S0033291717001003\u003c/li\u003e\n\u003cli\u003eGroeneveld, K. M., Mennenga, A. M., Heidelberg, R. C., Martin, R. E., Tittle, R. K., Meeuwsen, K. D., Walker, L. A., y White, E. K. (2019). Z-score neurofeedback and heart rate variability training for adults and children with symptoms of attention-deficit/hyperactivity disorder: a retrospective study. \u003cem\u003eApplied Psychophysiology and Biofeedback\u003c/em\u003e, \u003cem\u003e44\u003c/em\u003e(4), 291\u0026ndash;308. https://doi.org/10.1007/s10484-019-09439-x\u003c/li\u003e\n\u003cli\u003eHerrero, J.L., Khuvis, S., Yeagle, E., Cerf, M., y Mehta, A.D. (2017). Breathing above the brain stem: volitional control and attentional modulation in humans. \u003cem\u003eJournal of Neurophysiology\u003c/em\u003e, 119, 145-159. https://doi.org/10.1152/jn.00551.2017\u003c/li\u003e\n\u003cli\u003eInstitute of HeartMath (2012). EmWave Desktop\u0026copy;.California: HeartMath.\u003c/li\u003e\n\u003cli\u003eJennings, J. R., Sheu, L. K., Kuan, D. C.-H., Manuck, S. B., y Gianaros, P. J. (2016). Resting state connectivity of the medial prefrontal cortex covaries with individual differences in high-frequency heart rate variability. \u003cem\u003ePsychophysiology\u003c/em\u003e, \u003cem\u003e53\u003c/em\u003e(4), 444\u0026ndash;454. https://doi.org/10.1111/psyp.12586\u003c/li\u003e\n\u003cli\u003eJim\u0026eacute;nez, J. E., Hern\u0026aacute;ndez, S., Garc\u0026iacute;a, E., D\u0026iacute;az, A., Rodr\u0026iacute;guez, C., y Mart\u0026iacute;n, R. (2012). Test de atenci\u0026oacute;n D2: Datos normativos y desarrollo evolutivo de la atenci\u0026oacute;n en educaci\u0026oacute;n primaria [Attention test D2: Normative data and attention development in elementary grades]. \u003cem\u003eEuropean Journal of Education and Psychology, 5\u003c/em\u003e(1), 93\u0026ndash;106. https://doi.org/10.30552/ejep.v5i1.79\u003c/li\u003e\n\u003cli\u003eKaufmann, T., Aln\u0026aelig;s, D., Doan, N., Brandt. C.L., Andreassem, O.A., y Wrtlye, L.T. (2017). Delayed stabilization and individualization in connectome development are related to psychiatric disorders. \u003cem\u003eNature Neuroscience\u003c/em\u003e, 20, 513\u0026ndash;515. https://doi.org/10.1038/nn.4511\u003c/li\u003e\n\u003cli\u003eKim, H., Duran, C. A. K., Cameron, C. E., y Grissmer, D. (2018). Developmental relations among motor and cognitive processes and mathematics skills. \u003cem\u003eChild Development\u003c/em\u003e, \u003cem\u003e89\u003c/em\u003e(2), 476\u0026ndash;494. https://doi.org/10.1111/cdev.12752 \u003c/li\u003e\n\u003cli\u003eKredlow, M. A., de Voogd, L. D., y Phelps, E. A. (2022). A case for translation from the clinic to the laboratory. \u003cem\u003ePerspectives on Psychological Science\u003c/em\u003e, 17(4), 1120-1149. 10.1177/17456916211039852\u003c/li\u003e\n\u003cli\u003eLaborde, S., Allen, M. S., Göhring N, y Dosseville, F. (2017). The effect of slow-paced breathing on stress management in adolescents with intellectual disability. \u003cem\u003eJournal of Intellectual Disability Research\u003c/em\u003e, 61(6), 560\u0026ndash;567. https://doi.org/10.1111/jir.12350\u003c/li\u003e\n\u003cli\u003eLee, A., Lo, A. S. C., Keung, M. W., Kwong, C. M. A., y Wong, K. K. (2019). Effective health promoting school for better health of children and adolescents: indicators for success. \u003cem\u003eBmc Public Health\u003c/em\u003e, 19(1), 1\u0026ndash;12. https://doi.org/10.1186/s12889-019-7425-6\u003c/li\u003e\n\u003cli\u003eLloyd, A., Brett, D., y Wesnes, K. (2010). Coherence training in children with attention-deficit hyperactivity disorder: cognitive functions and behavioral changes. \u003cem\u003eAlternative Therapies in Health \u0026amp; Medicine\u003c/em\u003e, 16(4).\u003c/li\u003e\n\u003cli\u003eLynch, M. D., y Chen, L. (2015). \u003cem\u003eA mixed method analysis of an Early Intervention Program for students with behavioural and concentration difficulties in two schools in Malm\u0026ouml;, Sweden\u003c/em\u003e (Doctoral dissertation, University of Sussex). \u003c/li\u003e\n\u003cli\u003eMikhailova, O. B. (2017). Characteristics of creativity and innovativeness manifestations in students of middle AHD high school. \u003cem\u003eJournal of Psychology and Pedagogics\u003c/em\u003e, 14, 76\u0026ndash;87. https://doi.org/10.22363/2313-1683-2017-14-1-76-87\u003c/li\u003e\n\u003cli\u003eNing, K., y Wang, T. (2021). Multimodal Interventions Are More Effective in Improving Core Symptoms in Children With ADHD. \u003cem\u003eFrontiers in psychiatry\u003c/em\u003e, 12,759315. https://doi.org/10.3389/fpsyt.2021.759315\u003c/li\u003e\n\u003cli\u003ePark, G., y Thayer, J.F. (2014). From the heart to the mind: cardiac vagal tone modulates top-down and bottom-up visual perception and attention to emotional stimuli\u003cem\u003e. Frontiers in Psychology\u003c/em\u003e, 5, e278. https://doi.org/10.3389/fpsyg.2014.00278\u003c/li\u003e\n\u003cli\u003ePark, G., Vasey, M.W., Van Bavel, J.J., y Thayer, J.F. (2013). Cardiac vagal tone is correlated with selective attention to neutral distractors under load. \u003cem\u003ePsychophysiology\u003c/em\u003e, 50, 398-406. https://doi.org/10.1111/psyp.12029\u003c/li\u003e\n\u003cli\u003ePorges S.W., y Raskin, D.C. (1969). Respiratory and heart rate components of attention. \u003cem\u003eJournal of Experimental Psychology,\u003c/em\u003e 81, 497-503. https://doi.org/10.1037/h0027921\u003c/li\u003e\n\u003cli\u003ePorges, S.W. (1995). Orienting in a defensive world: Mammalian modifications of our evolutionary heritage. A polyvagal theory. \u003cem\u003ePsychophysiology\u003c/em\u003e, 32, 301-318. https://doi.org/10.1111/j.1469-8986.1995.tb01213.x\u003c/li\u003e\n\u003cli\u003ePorges, S.W. (2011). \u003cem\u003eThe polyvagal theory: neurophysiological foundations of emotions, attachment, communication, and self-regulation\u003c/em\u003e (Norton Series on Interpersonal Neurobiology). WW Norton \u0026amp; Company.\u003c/li\u003e\n\u003cli\u003ePosner, M. I. (2012). Imaging attention networks. \u003cem\u003eNeuroimage\u003c/em\u003e, 61, 450-456. https://doi.org/10.1016/j.neuroimage.2011.12.040\u003c/li\u003e\n\u003cli\u003ePosner, M. I., Rothbart, M. K., y Ghassemzadeh, H. (2020). Developing attention in typical children related to disabilities. In \u003cem\u003eHandbook of clinical neurology\u003c/em\u003e (Vol. 173, pp. 215-223). Elsevier. https://doi.org/10.1016/B978-0-444-64150-2.00019-8\u003c/li\u003e\n\u003cli\u003ePorges, S. W. (2022). Polyvagal theory: a science of safety. \u003cem\u003eFrontiers in Integrative Neuroscience\u003c/em\u003e, 16, 871227\u0026ndash;871227. https://doi.org/10.3389/fnint.2022.871227\u003c/li\u003e\n\u003cli\u003ePosner, M. I. (2023). The evolution and future development of attention networks. \u003cem\u003eJournal of Intelligence\u003c/em\u003e, 11(6). https://doi.org/10.3390/jintelligence11060098\u003c/li\u003e\n\u003cli\u003ePrice, A., Collins, H., Martin, A., y Wade, M. (2017). \u003cem\u003eThe Effect of Emotional Self-Regulation Training Using Heart Rate Variability Biofeedback on Symptoms of ADHD in Elementary Age Children: A Pilot Study\u003c/em\u003e (Doctoral dissertation, Brenau University).\u003c/li\u003e\n\u003cli\u003eRabiner, D. L., Godwin, J., y Dodge, K. A. (2016). Predicting academic achievement and attainment: the contribution of early academic skills, attention difficulties, and social competence\u003cem\u003e. School Psychology Review\u003c/em\u003e, 45(2), 250\u0026ndash;267. 10.17105/SPR45-2.250-267\u003c/li\u003e\n\u003cli\u003eReid, N., y Petrenko, C. L. M. (2018). Applying a developmental framework to the self-regulatory difficulties of young children with prenatal alcohol exposure: a review. \u003cem\u003eAlcoholism: Clinical and Experimental Research\u003c/em\u003e, 42(6), 987\u0026ndash;1005. https://doi.org/10.1111/acer.13756\u003c/li\u003e\n\u003cli\u003eRistic, J., y Enns, J.T., (2015). The changing face of attentional development. \u003cem\u003eCurrent Directions in Psychology Science\u003c/em\u003e, 24, 24\u0026ndash;31. https://doi.org/10.1177/0963721414551165\u003c/li\u003e\n\u003cli\u003eRivera, D., Salinas, C., Ramos-Usuga, D., Delgado-Mejía I.D, Vasallo Key, Y., Hernández Agurcia G.P, Valencia Vásquez J, García-Guerrero C.E, García de la Cadena C, Rabago Barajas, B. V., Romero-García I, Campos Varillas, A. I., Sánchez-SanSegundo M, Galvao-Carmona, A., Lara, L., Granja Gilbert, E. J., Martín-Lobo P, Velázquez-Cardoso J, y Caracuel, A. (2017). Concentration endurance test (d2): normative data for spanish-speaking pediatric population. \u003cem\u003eNeurorehabilitation\u003c/em\u003e, 41(3), 661\u0026ndash;671. https://doi.org/10.3233/NRE-172248\u003c/li\u003e\n\u003cli\u003eRohr, C.S., Arora, A., Cho, I.Y., Katlariwala, P., Dimond, D., Dewey, D., y Bray, S. (2018). Functional network integration and attention skills in young children. Developmental Cognitive \u003cem\u003eNeuroscience\u003c/em\u003e, 30, 200-211. https://doi.org/10.1016/j.dcn.2018.03.007\u003c/li\u003e\n\u003cli\u003eRukmani, M. R., Seshadri, S. P., Thennarasu, K., Raju, T. R., y Sathyaprabha, T. N. (2016). Heart rate variability in children with attention-deficit/hyperactivity disorder: a pilot study. \u003cem\u003eAnnals of neurosciences\u003c/em\u003e, 23(2), 81-88. https://doi.org/10.1159/000443574 \u003c/li\u003e\n\u003cli\u003eRush, K.S., Golden, M., Mortenson, B.P., Albohn, D., y Horger, M. (2017). The effects of a mindfulness and biofeedback program on the on- and off-task behaviors of students with emotional behavioral disorders. \u003cem\u003eContemporary School Psychology\u003c/em\u003e, 21,347\u0026ndash;357. https://doi.org/10.1007/s40688-017-0140-3\u003c/li\u003e\n\u003cli\u003eSakaki, M., Yoo, H.J., Nga, L., Lee, L., Thayer, J.F., y Mather, M. (2016). Heart rate variability is associated with amygdala functional connectivity with MPFC across younger and older adults. \u003cem\u003eNeuroImage\u003c/em\u003e, 139, 44-52. https://doi.org/10.1016/j.neuroimage.2016.05.076\u003c/li\u003e\n\u003cli\u003eSanta-Cruz, C., y Rosas, R. (2017). Mapping of executive functions/Cartograf\u0026iacute;a de las funciones ejecutivas. \u003cem\u003eStudies in Psychology\u003c/em\u003e, 38(2), 284-310. 10.1080/02109395.2017.1311459\u003c/li\u003e\n\u003cli\u003eSchachner, M.K. (2019). From equality and inclusion to cultural pluralism: Evolution and effects of cultural diversity perspectives in schools. \u003cem\u003eEuropean Journal of Developmental Psychology\u003c/em\u003e, 16, 1-17. https://doi.org/10.1080/17405629.2017.1326378\u003c/li\u003e\n\u003cli\u003eSchuurmans, A. A. T., Nijhof, K. S., Scholte, R., Popma, A., y Otten, R. (2020). A novel approach to improve stress regulation among traumatized youth in residential care: feasibility study testing three game-based meditation interventions. \u003cem\u003eEarly Intervention in Psychiatry\u003c/em\u003e, 14(4), 476\u0026ndash;485. https://doi.org/10.1111/eip.12874\u003c/li\u003e\n\u003cli\u003eSchwartz, M.S., y Andrasik, F. (2003). \u003cem\u003eDefinitions of biofeedback and applied psychophysiology biofeedback: A practitioner\u0026rsquo;s guide\u003c/em\u003e. Nueva York: Guilford Press.\u003c/li\u003e\n\u003cli\u003eShaffer, F., y Ginsberg, J. P. (2017). An overview of heart rate variability metrics and norms. \u003cem\u003eFrontiers in Public Health,\u003c/em\u003e \u003cem\u003e5\u003c/em\u003e, 258. https://doi.org/10.3389/fpubh.2017.00258\u003c/li\u003e\n\u003cli\u003eShaffer, C., Barrett, L. F., y Quigley, K. S. (2023). Signal processing in the vagus nerve: hypotheses based on new genetic and anatomical evidence. \u003cem\u003eBiological Psychology\u003c/em\u003e, 182, 108626\u0026ndash;108626. https://doi.org/10.1016/j.biopsycho.2023.108626\u003c/li\u003e\n\u003cli\u003eShapiro, E. S. (2011). \u003cem\u003eThe Behavioral Observation of Students in Schools (BOSS).\u003c/em\u003e Nueva York: Pearson. \u003c/li\u003e\n\u003cli\u003eSichko, S., Borelli, J. L., Smiley, P. A., Goldstein, A., y Rasmussen, H. F. (2018). Child and maternal attachment predict school-aged children\u0026rsquo;s psychobiological convergence. \u003cem\u003eDevelopmental Psychobiology\u003c/em\u003e, 60(8), 913\u0026ndash;926. https://doi.org/10.1002/dev.21748\u003c/li\u003e\n\u003cli\u003eSpagna, A., Martella, D., Sebastiani, M., Maccari, L., Marotta, A., y Casagrande, M. (2014). Efficiency and interactions of alerting, orienting and executive networks: The impact of imperative stimulus type. \u003cem\u003eActa psychologica\u003c/em\u003e, 148, 209-215. https://doi.org/10.1016/j.actpsy.2014.02.007\u003c/li\u003e\n\u003cli\u003eTask Force of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology. (1996). Heart rate variability. Standards of measurement, physiological interpretation, and clinical use. \u003cem\u003eCirculation\u003c/em\u003e, 93, 1043\u0026ndash;1065. https://doi.org/10.1161/01.CIR.93.5.1043\u003c/li\u003e\n\u003cli\u003eThayer, J.F., y Lane, R.D. (2009). Claude Bernard and the heart\u0026ndash;brain connection: Further elaboration of a model of neurovisceral integration. \u003cem\u003eNeuroscience \u0026amp; Biobehavioral Reviews\u003c/em\u003e, 33, 81-88. https://doi.org/10.1016/j.neubiorev.2008.08.004\u003c/li\u003e\n\u003cli\u003eThayer, J. F., Hansen, A. L., Saus-Rose, E., \u0026amp; Johnsen, B. H. (2009). Heart rate variability, prefrontal neural function, and cognitive performance: The neurovisceral integration perspective on self-regulation, adaptation, and health. \u003cem\u003eAnnals of Behavioral Medicine,\u003c/em\u003e \u003cem\u003e37\u003c/em\u003e(2), 141\u0026ndash;153. https://doi.org/10.1007/s12160-009-9101-z\u003c/li\u003e\n\u003cli\u003eTinello, D., Kliegel, M., \u0026amp; Zuber, S. (2022). Does heart rate variability biofeedback enhance executive functions across the lifespan? A systematic review. \u003cem\u003eJournal of Cognitive Enhancement\u003c/em\u003e, \u003cem\u003e6\u003c/em\u003e(1), 126-142. https://doi.org/10.1007/s41465-021-00218-3\u003c/li\u003e\n\u003cli\u003eWade, M., Collins, H., Martin, A., y Price, A. (2017). \u003cem\u003eThe Effect of Emotional Self-Regulation Training Using Heart Rate Variability Biofeedback on Symptoms of ADHD in Elementary Age Children: A Pilot Study\u003c/em\u003e. Tesis Doctoral de Brenau University. https://search.proquest.com/docview/1910063652?pq-origsite=gscholar\u0026amp;fromopenview=true\u003c/li\u003e\n\u003cli\u003eWinkelmann, T., Thayer, J. F., Pohlack, S., Nees, F., Grimm, O., \u0026amp; Flor, H. (2017). Structural brain correlates of heart rate variability in a healthy young adult population. \u003cem\u003eBrain Structure and Function,\u003c/em\u003e \u003cem\u003e222\u003c/em\u003e(2), 1061\u0026ndash;1068. https://doi.org/10.1007/s00429-016-1185-1\u003c/li\u003e\n\u003cli\u003eXuan, B., Mackie, M.A., Spagna, A., Wu, T., Tian, Y., Hof, P.R., y Fan, J. (2016). The activation of interactive attentional networks. \u003cem\u003eNeuroimage\u003c/em\u003e, 129, 308-319. https://doi.org/10.1016/j.neuroimage.2016.01.017\u003c/li\u003e\n\u003cli\u003eZhang, W., y Bray, M. (2020). Comparative research on shadow education: achievements, challenges, and the agenda ahead. \u003cem\u003eEuropean Journal of Education\u003c/em\u003e, 55(3), 322\u0026ndash;341. https://doi.org/10.1111/ejed.12413\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"applied-psychophysiology-and-biofeedback","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"apbi","sideBox":"Learn more about [Applied Psychophysiology and Biofeedback](http://link.springer.com/journal/10484)","snPcode":"10484","submissionUrl":"https://submission.nature.com/new-submission/10484/3","title":"Applied Psychophysiology and Biofeedback","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"attention, intervention, primary school, biofeedback, heart rate variability, breathing","lastPublishedDoi":"10.21203/rs.3.rs-4654519/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4654519/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe importance of attentional capacity for academic performance is highlighted by the increasing demands placed on students during primary school. Between the ages of 6 and 12, there is an evolutionary improvement in attentional capacity and the school environment is shown to be an appropriate setting in which to develop programmes to improve attention. Heart rate variability is an appropriate indicator of attentional capacity. For all these reasons, a heart rate variability biofeedback intervention focused on breathing was developed and implemented to improve attention. The intervention consists of two phases. In the first phase, the teachers of the school are trained to develop the intervention. In the second phase, the students receive 5 individual sessions from their teachers. In each individual session, they learn to breathe in a way that increases their heart rate variability. A total of 272 girls and 314 boys (N=586) aged 6-12 years participated in the programme. In order to study the impact on the three cycles of primary school, the attention of the control and experimental groups was assessed before and after the implementation of the programme. According to the data obtained, despite developmental improvements, the students who participated in the programme showed an increase in heart rate variability and an improvement in attentional capacity, with a greater impact on the first cycle of primary school. Our conclusion is to discuss the usefulness of heart rate variability biofeedback interventions in improving attention in primary school children and to present arguments for their use.\u003c/p\u003e","manuscriptTitle":"Heart rate variability biofeedback intervention programme to improve attention in primary schools","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-07-22 04:06:42","doi":"10.21203/rs.3.rs-4654519/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-07-08T17:26:34+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-07-08T13:36:36+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"45484951269909828360977664488224454016","date":"2024-07-06T10:52:13+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-07-05T18:27:19+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"17396374512343431152532296830651620779","date":"2024-07-05T18:03:12+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-07-05T17:50:21+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-06-28T14:34:34+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-06-28T14:33:47+00:00","index":"","fulltext":""},{"type":"submitted","content":"Applied Psychophysiology and Biofeedback","date":"2024-06-28T11:38:01+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"applied-psychophysiology-and-biofeedback","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"apbi","sideBox":"Learn more about [Applied Psychophysiology and Biofeedback](http://link.springer.com/journal/10484)","snPcode":"10484","submissionUrl":"https://submission.nature.com/new-submission/10484/3","title":"Applied Psychophysiology and Biofeedback","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"18be8785-89f8-420f-b61c-f3c5e5c8f04f","owner":[],"postedDate":"July 22nd, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-08-26T16:10:17+00:00","versionOfRecord":{"articleIdentity":"rs-4654519","link":"https://doi.org/10.1007/s10484-024-09659-w","journal":{"identity":"applied-psychophysiology-and-biofeedback","isVorOnly":false,"title":"Applied Psychophysiology and Biofeedback"},"publishedOn":"2024-08-23 15:58:02","publishedOnDateReadable":"August 23rd, 2024"},"versionCreatedAt":"2024-07-22 04:06:42","video":"","vorDoi":"10.1007/s10484-024-09659-w","vorDoiUrl":"https://doi.org/10.1007/s10484-024-09659-w","workflowStages":[]},"version":"v1","identity":"rs-4654519","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4654519","identity":"rs-4654519","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}