Article, Cardiology

Muscular fitness as a mediator of quality cardiopulmonary resuscitation

a b s t r a c t

Background: It has been hypothesized that body mass index (BMI) and muscle strength (MS) of the rescuers are predictors of adequate external chest compressions (ECC). The aims of this study were: (a) to analyze, in college students, the relationship between BMI and MS with adequate ECC parameters; and (b) to examine whether the association between BMI and adequate ECC parameters is mediated by MS.

Methods: A cross-sectional analysis of the evaluation of a CPR performance test involving students (n = 63). We determined BMI and MS. After previous training, participants performed cardiopulmonary resuscitation on a mannequin for 20 minutes. PROCESS macro developed by Preacher and Hayes was used to assess whether the association between BMI and ECC was mediated by MS.

Results: Underweight subjects achieved lower results than those with normal weight and overweight/obese in several dependent variables including: correct compression depth (P b .001) and adequate ECC (P b .001). This differences remained after adjusting for muscle strength except for the compression rate (P = .053). Moreover, participants in the low MS quartile were lower in both correct compression depth (P = .001) and adequate ECC (P b .001) than participants in the medium/high quartile after adjusting for confounding variables. The effect of BMI on adequate ECC was partially mediated by MS. Similar results were obtained in the analysis of the mediator role of MS in the relationship between BMI and correct compression depth.

Conclusions: The ability to provide adequate ECC is influenced by the rescuer’s MS. Rescuers should be advised to exercise arm strength to improve the Quality of CPR.

(C) 2016

  1. Introduction

The out-of-hospital cardiac arrest poses a challenge to the health system. Survival rates after these events mainly depend only on effec- tive chest compressions, Early defibrillation, and advanced life support [1]. There is consensus that high quality cardiopulmonary resuscitation (CPR) is associated with a higher survival rate and remains essential to improving outcomes [2]. The technique for effective external chest

? Author’s contribution: All authors have made substantial contributions to all of the fol- lowing: (1) the conception and design of the study, or acquisition of data, or analysis and interpretation of data; (2) drafting the article or revising it critically for important intellec- tual content; (3) final approval of the version to be submitted.

* Corresponding author at: School of Nursing, University of Castilla-La Mancha, Edificio

Benjamin Palencia, 02071 Albacete, Spain. Tel.: +34 969 599200×2717; fax: +34 967

599267.

E-mail addresses: [email protected] (A. Lopez-Gonzalez), [email protected] (M. Sanchez-Lopez), [email protected] (A. Garcia-Hermoso), [email protected] (J. Lopez-Tendero), [email protected] (J. Rabanales-Sotos), [email protected] (V. Martinez-Vizcaino).

compression (ECC) and positive pressure ventilation is periodically reviewed by international organizations [1,2].

Authors indicate that the rescuer’s physical fatigue decreases the quality of ECC a few minutes after the start of the CPR [3-8]. Weight sta- tus has been also associated with the quality of ECC, such that those who are underweight perform CPR worse than those with normal weight or excess weight [4,5,9,10]. High levels of muscle strength are positively correlated with the number of adequate ECCs performed [5,10,11]. On the other hand, weight status has been related to muscle strength. In- creases in body mass index (BMI) are associated with improved perfor- mance in physical fitness tests that do not involve lifting the body, such as dynamometry [12-14]. In this way, muscle strength might be a po- tential mediator or play a confounding role in the analysis of the rela- tionship between weight status and adequate quality of the ECC.

Mediation analyses are the statistical procedures usually employed in order to clarify the relationship between two variables and how this relationship can be modified, mediated or confounded by a third variable. When the third variable (the mediator) carries the influence of a given independent variable on a given dependent variable, the ef- fect of mediation occurs [15].

http://dx.doi.org/10.1016/j.ajem.2016.06.058

0735-6757/(C) 2016

To our knowledge, no study has examined the mediator role of mus- cle strength on the relationship between BMI and adequate ECC param- eters by mediation analysis. The objectives of this study were 2-fold:

(1) to analyze, in college students, the relationship between BMI and muscle strength with adequate ECC parameters; and (2) to examine whether the association between BMI and adequate ECC parameters is mediated by muscle strength.

  1. Methods
    1. Study design and participants

A cross-sectional analysis of the evaluation of a CPR performance test was conducted from September 2011 to April 2012, which included sixty-three university students (19 men, 44 women), aged 19 to 43 years, from the Nursing Faculty of the Albacete Campus in the Uni- versity of Castilla-La Mancha, Spain (Table 1). All of them had been pre- viously trained in CPR based on European Resuscitation Council Guidelines [16]. All the participants were required to be able to achieve a maximal voluntary cardiopulmonary exercise test.

All the participants were informed in detail about the nature and risks of this study, and were provided with written informed consent. The study protocol was approved according to the Helsinki declaration by the Clinical Research Ethics Committee of the University Hospital from Albacete, Spain. Participants suffering from any cardiovascular and/or orthopedic injury/dysfunction were excluded.

Training program

The participants (in groups of 15) received, 48 hours before the mea- surement of the Anthropometric variables and physical fitness, a 30′ ses- sion of standardized training in basic CPR. This training, supervised by an instructor who followed the CPR Personal Anytime Learning Pro- grams method, allows each student to practice with a mannequin fol- lowing the instructions of a DVD, and the amendments of the instructor [17].

Measurements

Sociodemographic variables (age, sex, education and residence) were collected and the following were also measured in all subjects.

Anthropometry

Weight was measured to the nearest 100 g with a calibrated digital scale (SECA model 861; Vogel & Halke, Hamburg, Germany), with the participant barefoot and in light clothes. Height was measured to the

Table 1

Demographic, anthropometric and physical fitness variables of study population, by sex

Total

Men

Women

P

(n = 63)

(n = 19)

(n = 44)

Age (y)

22.7 (5.2)

23.3 (5.5)

22.4 (5.0)

.516

Weight (kg)

63.68

73.68

59.36 (8.28)

b.001

(10.32)

(7.20)

Height (m)

1.67

1.74

1.63 (0.06)

b.001

(0.80)

(0.05)

Body mass index (kg/m2)

19.02

21.11

18.11 (2.31)

b.001

(2.63)

(2.11)

Weight status (%)

Underweight

43.5

0

62.8

b.001

Normal weight

51.6

89.5

34.9

b.001

Overweight/obesity

4.8

10.5

2.3

b.001

Handgrip/weight0.67

1.85

2.41

1.60 (0.28)

b.001

(0.50)

(0.46)

Cardiorespiratory fitness (VO2max;

40.7 (7.4)

49.1 (6.0)

37.1 (4.3)

b.001

mL kg-1 min-1)

Values are means +- SD except when indicated.

nearest millimeter with a wall-mounted stadiometer (SECA model 220; Vogel & Halke, Hamburg, Germany), with the students standing straight against the wall without shoes to align the spine with the stadiometer. The head was positioned with the chin parallel to the floor. Finally, the mean of the two measurements of weight and height was used to calculate BMI (kg/m2). BMI was categorized according to the age and gender cut-off points defined by the World Health Organi- zation in underweight (b 18.5 kg/m2), normal weight (18.5-24.9 kg/ m2) and overweight/obesity (>= 25 kg/m2) [18].

Physical fitness tests

Muscle strength: the maximum strength of the upper body (capacity to produce the maximum muscular tension with a muscle contraction) was evaluated using digital handgrip dynamometer Takei TKK 5101 (rank, 5 to 100 kg, accuracy, 0.1 kg), which measured the force of max- imum grip strength in both hands alternately (with previous grip ad- justment of the dynamometer based on the hand size), making 2 attempts with each hand, with the subject standing up and leaving the arms relaxed and parallel to the body [19]. The final score was the mean of the four measures (kg). Various factors may confound strength performance tests. In addition to sex, age, level of physical activity, and skill, body size is a well-recognized factor affecting muscle strength. Thus, to avoid the potential biasing effect of body weight on the estima- tion of muscular fitness, handgrip was adjusted for body weight (in kg)0.67 in line with standard assumptions about morphologic effects as some authors have suggested [20,21].

Cardiorespiratory fitness (CRF) was estimated through peak or max- imum oxygen uptake determined by the maximum effort test according to the Bruce ramp protocol on a treadmill ergometer (HP-Cosmos, model Pulsar 3P). The treadmill stress electrocardiogram testing was performed with the electrocardiograph Cardinal Health model Ergoline ER800. Exhaled breath was registered by an effort basal spirometer and an automatic system of analysis of exhaled gas (model Oxycom Alpha; Jaeger). The instruments were calibrated before each session according to protocol and barometric pressure, temperature and humidity correc- tions. CRF was dichotomized as higher and lower using the Cooper Insti- tute cut-off points for 20- to 30-year-old adults (VO2max 38 mL kg-1 min-1 for women and 43 mL kg-1 min-1 for men).

Evaluation of participants’ cardiopulmonary resuscitation ability

External chest compressions: after the training session, each partic- ipant performed CPR on a manikin Laerdal Resusci-Anne-SkillReporter (Medical Laerdal; Stavanger, Norway) without interruption (30:2 compression-ventilation ratio) for 20 minutes or until exhaustion.

Auditory feedback was provided and measured by the internal met- ronome of the manikin, and visual feedback was shown on a monitor that allowed visualization of the depth of compressions, incomplete re- lease, released pressure, increased duration, faster compression and slower compression.

During the test, ECCs were considered adequate items, according to the recommendations of the European Resuscitation Council [16], when the following conditions were achieved: (a) a rate of 100 to 120 min-1;

(b) 100% of compressions in the centre of the patient’s chest; (c) full chest recoil after each compression 100% of the time; (d) 100% of com- pressions with a depth ranging between 50 and 60 mm; and (e) taking approximately equal amounts of time for the compression and relaxa- tion phases 100% of the time.

The measurements were obtained minute by minute during the test, which ended once the participants reached the objective (20 minutes of ECC) or could not continue because of physical limitations such as phys- ical exhaustion or pain in their extremities.

All measurements were taken under standard conditions by the same researchers.

Statistical analysis

The variables were expressed as the mean +- SD. Statistical normal- ity of the variables was tested using both graphical (normal probability plot) and statistical procedures (Kolmogorov-Smirnov test). All vari- ables fit acceptably to a normal distribution.

Muscle strength was categorized in three levels according to quar-

tiles (low = Q1; medium = Q2-Q3; high = Q4). ANCOVA models were estimated to test the differences in correct ECC parameters by weight status and muscle strength categories, controlling for age, sex and CRF (model 1); in a second step, muscle strength or BMI were added depending on the fixed factor variable (model 2). Pairwise post hoc comparisons were examined using the Bonferroni test.

To examine whether the association between BMI and correct ECC pa- rameters was mediated by muscle strength, Linear regression models were estimated based on the procedures outlined by Baron and Kenny [15] by using the PROCESS macro for SPSS recommended by Preacher and Hayes [22]. The first equation regressed to the mediator (muscle strength) on the independent variable (BMI). The second equation regressed to the dependent variables (correct ECC parameters and adequate ECC) on the independent variable. The third equation regressed to the dependent var- iable on both the independent and the mediator variables.

The following criteria were used to establish mediation: (1) the medi- ator will be significantly related to the independent variable; (2) the de- pendent variable will be significantly related to the independent variable; (3) the dependent variable will be significantly related to the me- diator; and (4) when the mediator is included in the regression model, the association between the independent and dependent variables must be attenuated. In addition, following the steps described by Sobel, we also assessed mediation [23]: first, we estimated the attenuation or indirect ef- fect (ie, the effect of the independent variable on the mediator from the first regression model multiplied by the effect of the mediator on the de- pendent variable obtained from the third regression model); and second, we divided the indirect effect by its standard error and performed a Z-test under the null hypothesis in which the indirect effect is equal to zero. This analysis was adjusted by age, sex and CRF.

A bilateral criterion for statistical significance of P <= .05 was used. All statistical analyses were performed using the software IBM SPSS 22.0.

  1. Results

All participants except one completed the study, the exception be- cause he suffered from Arm pain. Table 1 displays the anthropometric and physical fitness characteristics by gender.

Mean differences in adequate ECC parameters according to both

weight status and muscle strength categories are shown in Table 2. Un- derweight subjects achieved lower results than those with normal weight and overweight/obese in several dependent variables including: compression rate (P = .033), correct compression depth (P b .001), re- lation compression/decompression (P = .001) and adequate ECC (P b .001) (model 1).

After adjusting for muscle strength (model 2), the differences remained, except for the compression rate. Moreover, participants in the low muscle strength quartile were lower in both correct compres- sion depth (P = .001) and adequate ECC (P b .001) than participants in the medium/high quartile after adjusting for confounding variables.

Mediation analysis

When we tested the mediator role of muscle strength in the rela- tionship between BMI and adequate ECC (Figure), in the first regres- sion equation BMI was positively associated with muscle strength (P <= .001). In the second equation, BMI was also positively associated with adequate ECC (P <= .001). Finally, in the third equation, when BMI and muscle strength were simultaneously included in the model, both muscular strength (P <= .001) and BMI (P <= .05) were pos- itively associated with adequate ECC. Both of them indicated that the effect of BMI on adequate ECC was partially mediated by muscle strength. The percentage of total effect mediated by muscle strength was 55% (z = 2.396; P = .008) when adequate ECC was the depen- dent variable.

Table 2

Mean differences in correct chest compression parameters according to weight status (BMI) and muscular fitness (handgrip/weight0.67) categories

BMI

Crude data Model 1 Model 2

Underweight (U)

Normal weight (N)

Overweight/Obese (O)

P

Post-hoc+

Post-hoc+

P

Post-hoc+

Compression rate (min-1)

99.1 +- 4.46

99.2 +- 4.55

106.9 +- 9.57

.063

.033

U b O

.053

Compressions with correct location (%)

90.7 +- 14.9

91.8 +- 16.6

98.9 +- 1.5

.893

.747

.788

Compressions with adequate release pressure on the

99.7 +- 0.9

96.1 +- 15.5

97.9 +- 3.3

.781

.492

.554

chest (%)

Correct compression depth (%)

36.4 +- 30.6

70.7 +- 28.3

87.7 +- 11.4

.018

U b O

b.001

U b N;

.006

U b O

U b O

Relation compression/decompression

37.5 +- 4.7

40.9 +- 4.3

46.1 +- 5.4

b.001

U b N;

.001

U b N;

.005

U b N;

U b O

U b O

U b O

Adequate compression (%)

34.1 +- 29.9

70.2 +- 25.4

84.2 +- 11.7

.012

U b N;

b.001

U b N;

.002

U b N;

U b O

U b O

U b O

P

Handgrip/weight0.67

Crude data Model 1 Model 2

Low (L)

Medium (M)

High (H)

P

Post-hoc+

P

Post-hoc+

P

Post-hoc+

Compression rate (min-1)

99.3 +- 7.23

99.5 +- 4.9

100.1 +- 2.0

.567

.907

.935

Compressions with correct location (%)

86.2 +- 2.6

96.2 +- 5.6

98.0 +- 3.3

.062

.055

.094

Compressions with adequate release pressure on the chest (%)

99.0 +- 2.0

96.8 +- 15.8

98.1 +- 3.8

.904

.815

.777

Correct compression depth (%)

35.6 +- 27.2

52.7 +- 32.4

87.6 +- 15.5

.010

L b H; M b H

b.001

L b H; M b H

.001

L b H; M b H

Relation compression/decompression

39.8 +- 5.1

38.6 +- 4.6

41.7 +- 5.3

.068

.133

.888

Adequate compression (%)

32.3 +- 24.7

52.5 +- 31.1

85.3 +- 14.9

.004

L b H; M b H

b.001

L b H; M b H

b.001

L b H; M b H

Values are means +- SD.

Model 1: adjusted for age, sex and cardiorespiratory fitness. Model 2: model 1 covariates plus handgrip/weight0.67 or body mass index (BMI) depending on the fixed factor variable. Categories of BMI are underweight, normal weight and overweight/obese according to cut-offs defined by the World Health Organization. Categories of muscular fitness (an index was measured by the sum of the standardized Z-score of handgrip dynamometry/weight and standing long jump) are low, medium and high, representing the first, second, third and fourth quartiles.

+ All the pairwise mean comparisons using the Bonferroni post-hoc test were statistically significant (P b .001).

Figure. Muscle strength mediation models of the relationship between BMI and adequate ECC controlling for age, sex and cardiorespiratory fitness (CRF). *P <= .05; **P <= .001.

Similar results were obtained in the analysis of the mediator role of muscle strength in the relationship between BMI and correct compres- sion depth; therefore, muscle strength may be considered as a partial mediator. Conversely, the relationship between BMI and the other cor- rect chest compression parameters was not mediated by muscle strength, since the abovementioned criteria for the mediation analysis were not observed (data not shown).

  1. Discussion

The main finding of this study is that there is a significant association between weight status and muscle strength with adequate ECC param- eters in college students in an extreme fatigue situation or after 20 mi- nutes of CPR. Students with normal weight and overweight/obesity and a high level of muscle strength are capable of performing better ECC ma- neuvers than those with underweight or those included in other muscle strength categories. The present study is the first to investigate the in- volvement of muscle strength in the relationship between BMI and the ability to perform adequate ECC in college students using mediation analysis. Taken together, these results suggest that muscle strength acts as a partial mediator on the relationship between BMI and adequate ECC in the population described.

The influence that a greater BMI has on adequate ECC has been dem- onstrated [4,9,23-27], and like other authors [6,9,10,27-29], our data in- dicate that adequate ECCs decrease in number as a consequence of the decrease of compression depth. Furthermore, in our study a lower BMI was also associated with decreased compression rate, and although it seems to contradict what previously reported by us and others [9,10], it confirms that it is a weak association that may be due to the feedback system, as others suggest [30].

Our data show that, in accordance with Hansen et al and Ock et al [5,11], high levels of handgrip strength were associated with a greater number of adequate ECCs; thus we claim that for prolonged CPR (N 5 min), the quality of ECC, and particularly, the depth of ECC, are positive- ly related to muscle strength.

Our mediation analysis revealed that the effect of muscular fitness on adequate ECC was partially mediated by BMI. We confirm the proven bivariate relationships between BMI and adequate ECC, and clarify the mediating role of muscle strength in the relationship between BMI and adequate ECC. Thus, there seems to be a direct and positive relation- ship between BMI and adequate ECC where the muscle strength is a me- diator factor.

Our results confirm that the heaviest people perform CPR better than those who are underweight, but also suggest that for low weight people, a high level of strength in arms might offset the negative influence of their weight status.

Limitations of this study include that it is a laboratory study and gen- eralization of the results to real situations should consider that many environmental variables, which can influence the quality of ECC (loca- tion of the patient, meteorological factors, individual factors of the pa- tient, stress, etc.), have not been included. A second limitation is that the muscle’s ability has only been measured as a single peak force against a physical object (maximal muscle strength). Repeated mea- surements of a muscle’s ability to continue generating peak forces for a prolonged period or during repeated contractions against a physical object (muscle strength endurance) could have provided greater power to the study’s conclusions. A third limitation is that the hand grip strength measures primarily forearm flexor strength. However, the muscles of the upper arm and shoulders do most of the work during ECC. Lastly, the influence on the performance of the study participants of the Real-time audiovisual feedback during the CPR maneuvers, might limit the generalizability of our findings in situations where this feedback procedure is not used.

Future research would elucidate this concern.

  1. Conclusions

We have shown that the ability to provide adequate ECC is influ- enced by the muscular strength of rescuers, which should be advised that exercises focused on improving upper body muscle strength might improve the ability to perform correct resuscitation maneuvers.

Conflict of interest statement

The authors report no conflicts of interest. The authors alone are re- sponsible for the content and writing of the paper.

Acknowledgements

The authors wish to thank the participants of this study for their en- thusiastic collaboration, and also want to acknowledge their gratitude to Margarita Carrion and Maria Jose Garcia, nurses of the Sports Medi- cine Centre from Albacete, Spain.

References

  1. Perkins GD, Jacobs IG, Nadkarni VM, Berg RA, Bhanji F, Biarent D, et al. Cardiac arrest and cardiopulmonary resuscitation outcome reports: update of the Utstein resusci- tation registry templates for out-of-hospital cardiac arrest: a statement for healthcare professionals from a task force of the international liaison committee on resuscitation (American Heart Association, European resuscitation council, Australian and New Zealand council on resuscitation, Heart and Stroke Foundation of Canada, InterAmerican Heart Foundation, resuscitation Council of Southern Africa, resuscitation council of Asia); and the American Heart Association emergency cardiovascular care committee and the council on cardiopulmonary, critical care, perioperative and resuscitation. Circulation 2015;132:1286-300.
  2. Perkins GD, Handley AJ, Koster RW, Castren M, Smyth MA, Olasveengen T, et al. European resuscitation council guidelines for resuscitation 2015: section 2. Adult basic life support and Automated external defibrillation. Resuscitation 2015;95: 81-99.
  3. Vaillancourt C, Midzic I, Taljaard M, Chisamore B. Performer fatigue and CPR quality comparing 30:2 to 15:2 compression to ventilation ratios in older bystanders: a ran- domized crossover trial. Resuscitation 2011;82:51-6.
  4. Ashton A, McCluskey A, Gwinnutt C, Keenan A. Effect of rescuer fatigue on perfor- mance of continuous external chest compressions over 3 min. Resuscitation 2002; 55:151-5.
  5. Hansen D, Vranckx P, Broekmans T, Eijnde BO, Beckers W, Vandekerckhove P, et al. Physical fitness affects the quality of single operator Cardiocerebral resuscitation in healthcare professionals. Eur J Emerg Med 2012;19:28-34.
  6. Ochoa FJ, Ramalle-Gomara E, Lisa V, Saralegui I. The effect of rescuer fatigue on the Quality of chest compressions. Resuscitation 1998;37:149-52.
  7. McDonald CH, Heggie J, Jones CM, Thorne CJ, Hulme J. Rescuer fatigue under the 2010 ERC guidelines, and its effect on cardiopulmonary resuscitation (CPR) perfor- mance. Emerg Med J 2013;30:623-7.
  8. Manders S, Geijsel FE. Alternating providers during Continuous chest compressions for cardiac arrest: every minute or every two minutes? Resuscitation 2009;80:1015-8.
  9. Russo SG, Neumann P, Reinhardt S, Timmermann A, Niklas A, Quintel M, et al. Im- pact of physical fitness and biometric data on the quality of external chest compres- sion: a randomised, crossover trial. BMC Emerg Med 2011;11:20.
  10. Lopez-Gonzalez A, Sanchez-Lopez M, Rovira-Gil E, Ferrer-Lopez V, Martinez- Vizcaino V. Influence of body mass index and physical fitness of university students on the ability to perform quality external chest compressions in manikin. Emergencias 2014;26:195-201.
  11. Ock SM, Kim YM, Chung J, Kim SH. Influence of physical fitness on the performance of 5-minute continuous chest compression. Eur J Emerg Med 2011;18:251-6.
  12. Chandrasekaran B, Ghosh A, Prasad C, Krishnan K, Chandrasharma B. Age and an- thropometric traits predict handgrip strength in healthy normals. J Hand Microsurg 2010;2:58-61.
  13. Hardy R, Cooper R, Aihie Sayer A, Ben-Shlomo Y, Cooper C, Deary IJ, et al. Body mass index, muscle strength and physical performance in older adults from eight cohort studies: the HALCyon programme. PLoS One 2013;8, e56483.
  14. Esco MR, Olson MS, Williford HN. The relationship between selected body composi- tion variables and muscular endurance in women. Res Q Exerc Sport 2010;81:272-7.
  15. Baron RM, Kenny DA. The moderator-mediator variable distinction in social psycho- logical research: conceptual, strategic, and statistical considerations. J Pers Soc Psychol 1986;51:1173-82.
  16. Koster RW, Baubin MA, Bossaert LL, Caballero A, Cassan P, Castren M, et al. European resuscitation council guidelines for resuscitation 2010 section 2. Adult basic life sup- port and use of automated external defibrillators. Resuscitation 2010;81:1277-92.
  17. Bonnie E, Graham N, Lance B, Tom P, Ahamed I. Effectiviness of a 30-min CPR self- instruction program for lay responders: a controlled randomized study. Resuscita- tion 2005;67(31):43.
  18. Expert panel on the identification, evaluation, and treatment of overweight in adults Clinical guidelines on the identification, evaluation, and treatment of overweight and obesity in adults: executive summaryAm J Clin Nutr 1998;68:899-917.
  19. EUROFIT. CoEoSR. Strassberg: Handbook for the EUROFit tests of physical fitness; 1993.
  20. Jaric S, Mirkov D, Markovic G. Normalizing physical performance tests for body size: a proposal for standardization. J Strength Cond Res 2005;19:467-74.
  21. Artero EG, Lee DC, LAvie CJ, et al. Effects of muscular strength on cardiovascular risk factors and prognosis. J Cariopulm Rehabil Prev 2012;32:351-8.
  22. Preacher KJ, Hayes AF. Asymptotic and resampling strategies for assessing and com- paring indirect effects in multiple mediator models. Behav Res Methods 2008;40(3): 879-91.
  23. Sobel M. Asymptotic confidence intervals for indirect effects in structural equation models. In: Leinhardt S, editor. Sociological methodology. American Sociological As- sociation: Washington, DC; 1982. p. 290-312.
  24. Hong DY, Park SO, Lee KR, Baek KJ, Shin DH. A different rescuer changing strategy between 30:2 cardiopulmonary resuscitation and hands-only cardiopulmonary re- suscitation that considers rescuer factors: a randomised cross-over simulation study with a time-dependent analysis. Resuscitation 2012;83:353-9.
  25. Plant N, Taylor K. How best to teach CPR to schoolchildren: a systematic review. Re- suscitation 2013;84:415-21.
  26. Sayee N, McCluskey D. Factors influencing performance of cardiopulmonary resusci- tation (CPR) by foundation year 1 hospital doctors. Ulster Med J 2012;81:14-8.
  27. Krikscionaitiene A, Stasaitis K, Dambrauskiene M, Dambrauskas Z, Vaitkaitiene E, Dobozinskas P, et al. Can lightweight rescuers adequately perform CPR according to 2010 resuscitation guideline requirements? Emerg Med J 2013;30:159-60.
  28. Peberdy MA, Silver A, Ornato JP. Effect of caregiver gender, age, and feedback prompts on chest compression rate and depth. Resuscitation 2009;80: 1169-74.
  29. Abelairas C, Romo V, Barcala R, Palacios A. Efecto de la fatiga fisica del socorrista en los primeros cuatro minutos de la reanimacion cardiopulmonar posrecate acuatico. Emergencias 2013;25:184-90.
  30. Bobrow BJ, Vadeboncoeur TF, Stolz U, Silver AE, Tobin JM, Crawford SA, et al. The in- fluence of scenario-based training and real-time audiovisual feedback on out-of- hospital cardiopulmonary Resuscitation quality and survival from out-of-hospital cardiac arrest. Ann Emerg Med 2013;62(1):47-56.

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