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Abstract Literature in psychology –particularly positive psychology—has extensively studied non-cognitive skills as a measure of wellbeing of individuals and as a “buffer” to reduce psychological disorders among young people (Park, 2004, Jordan and Rand, 2018). From the behavioral economic perspective, enhancing non-cognitive skills can be a relevant policy because these skills may influence decision making and economic behavior (Haushofer and Fehr, 2014; DellaVigna, 2009; Loewenstein, 2000). Particularly, in the context of poverty, stress and emotional instability may lead to short-sighted and risk-averse decision-making. In that sense, instead of adopting behaviors that may generate greater returns, individuals end up favoring habitual low yield ones. This, in turn, can generate vicious cycles or psychological poverty traps (Haushofer and Fehr, 2014). Moreover, exposure to high violence can exacerbate inefficiency in individuals’ economic decisions. Existing evidence indicates that exposure to risky environments may have unwanted results on socio-emotional skills and further welfare outcomes (Peterson and Seligman, 2003; Baysan et al., 2018; Card and Dahl, 2011; Loewenstein, 2000). For at-risk people, the inability to regulate their emotions can make them more susceptible to respond to some stimuli with violence. How can we tackle young people exposure to and participation in crime? After-school programs (ASP) are a type of intervention that can protect children, keeping them busy and off the streets during a time when they might be left alone and exposed to external risks, to preventing victimization and delinquent behavior (Gottfredson et al., 2004; Jacob and Lefgren, 2003; Newman et al., 2000). These programs can also act as an alternative source of learning and social development when they include a specific curriculum oriented to foster socio-emotional skills and impulsive responses control (Taheri and Welsh, 2016; Durlak et al., 2010; Eccles and Templeton, 2002). This project aims to contribute to the economic literature and policy in two ways. First, it provides experimental evidence of the impact of three types of interventions: (i) extracurricular activities (EA, i.e. sports at school), (ii) mindfulness and EA, and (iii) Cognitive Behavioral Therapy and EA. We measure those interventions’ impacts on academic performance, cognitive and non-cognitive development. Second, this project aims to separate these learning and protection services from the ASP. We argue that the effects we can find from EA are determined by children’s protection, while those from the other two interventions are mainly driven by the specific additional curriculum they are learning from the program. The first intervention consists to participate in extra-curricular sports activities. In this treatment, children are not learning a specific curriculum, but are under adult supervision and protected from their risky contexts during a couple of hours. The second intervention is a combination between extra-curricular activities and a curriculum that promotes character strengths. In this program variation, students are protected and learn how to enhance their character or socio-emotional skills. The third intervention is a combination between extra-curricular clubs and a mindfulness program, including directed meditation for stress and anxiety reduction and control of automatic responses. Schools in the comparison group will not receive any of the three interventions. Participants will meet once per week during one academic year (between 7-8 months). Each of the sessions is implemented after-school time, with an approximate duration of 1-1.5 hours. For methodological reasons, club sizes are between 13-15 participants on average. We study the impact of after-school programs (ASP) for teenagers in 21 public schools in the most violent neighborhoods of El Salvador, Honduras, and Guatemala. Schools were randomly assigned to one of three treatment conditions: activities such as sports, art, and dancing; a curriculum that aims to strengthen participants’ character; or a mindfulness-based and relaxation response program. We will evaluate the impact of these interventions on measures of well-being, academic performance, and social and emotional competence as well as cognitive and non-cognitive development. We also selected a group of eight schools as pure controls with a propensity score approach, which will allow us to study the mechanism of the ASP effect—that is, intervention or protection. Participants meet once per week during one academic year (between 7-8 months) after-school time, with an approximate duration of 1-1.5 hours. This research will permit us to test the effect of different strategies aimed at decreasing violence for young people in a highly violent context and to test their mechanisms.
Trial End Date March 31, 2020 August 31, 2020
Last Published February 11, 2020 02:13 PM February 13, 2020 03:28 PM
Intervention (Public) This project aims to evaluate the impact of three interventions oriented to enhance participants’ non-cognitive skills and character. Our target audience will consist of students enrolled in participants and comparison schools in Central America, with the ages between 12 and 16 years—second and third educational levels. The first intervention consists to participate in extra-curricular activities that include dance, sports, art, among others. In this alternative, children are not learning a specific curriculum, but remain under adult supervision and protected from their risky contexts during a couple of hours. The second intervention is a combination of extra-curricular activities and a curriculum that promotes character strengths. In this program variation, students are protected and learn how to enhance their character or socio-emotional skills. The third intervention is a combination of extra-curricular clubs and a mindfulness program, including directed meditation for stress and anxiety reduction and control of automatic responses. Schools in the comparison group will not receive any of the three interventions. Participants will meet once per week during one academic year (between 7-8 months). Each of the sessions is implemented after-school time, with an approximate duration of 1-1.5 hours. For methodological reasons, club sizes are between 13-15 participants on average. This project aims to evaluate the impact of three interventions oriented to enhance participants’ non-cognitive skills and character. Our target audience will consist of students enrolled in participants and comparison schools in Central America, with the ages between 12 and 16 years—second and third educational levels. The first intervention consists to participate in extra-curricular activities that include dance, sports, art, among others. In this alternative, children are not learning a specific curriculum, but remain under adult supervision and protected from their risky contexts during a couple of hours. The second psychological curriculum we study, Construcción de Fortaleza de carácter (“Character Strengths Development Program” or CSD), aims to strengthen participants’ character and increase their development and psychological well-being. According to the theory of change for this intervention, positive psychological resources developed through CSD will drive beneficial behaviors such as staying in school and increasing academic performance; improvement in relationships; decision making and establishment of life goals; and taking actions to achieve the latter. These positive resources will help participants to prevent and reduce harmful behaviors such as school dropouts, poor academic performance, violent behaviors, involvement in illegal activities, and other risky behaviors. CSD includes 32 sessions of training or reflection. The first type aims to reinforce the concepts and their importance in order for participants to achieve well-being. In the reflection sessions, participants are invited to perform self-analysis—that is, analysis of their history and environment. To achieve the desired level of reflection, implementers use an active learning methodology, which places the student at the center of the learning experience and motivates participation through individual and group activities. Participants actively practice the strengths, reflect their application in daily life, and acquire tools to adopt them easily. The third intervention is a combination of extra-curricular clubs and a mindfulness program, Salon Tranquilo (“Calm Classroom®” or MF), a mindfulness-based and relaxation response program. The program includes directed meditation for stress and anxiety reduction and control of automatic responses; it uses thought techniques to help participants develop self-awareness, mental concentration, and inner calm. Through several activities, MF provides students and staff with tools to manage stress more effectively, to regulate their emotions, and at the same time to lead more productive and well-balanced lives. The MF program includes 42 different activities of breathing, stretching, relaxation, and focusing techniques. Each script technique takes three minutes to implement. Mentors conduct these scheduled practices during the clubs and encourage participants to use the techniques naturally when appropriate. Participants will meet once per week during one academic year (between 7-8 months). Each of the sessions is implemented after-school time, with an approximate duration of 1-1.5 hours. For methodological reasons, club sizes are between 13-15 participants on average.
Primary Outcomes (End Points) (i) Strengths and Virtues (Peterson and Seligman, 2004), (ii) non-cognitive games using SoftGames App (Danon et al, 2018), (iii) Emotional reaction and regulation. (i) Administrative data on misbehavior and school attendance, and (ii) academic performance using school records.
Primary Outcomes (Explanation) For each strand of data that we mentioned before, we will use the following instruments: ● Strengths and Virtues. We will employ the Values in Action Inventory of Strengths (Peterson and Seligman, 2004). It is a catalog of positive psychological traits, consisting of 240 items, ten for each of 24 different character strengths. Following Jordan and Rand (2018), we will use an adapted version that consists of only 24 items that ask directly about each character strength. Participants will be asked to respond, “It is natural and effortless for me to express my X CS”. The scale is [Completely true; Very true; Somewhat true; Not true/untrue; Somewhat untrue; Very untrue; Completely untrue]. This instrument will be available in tablets. ● Non-cognitive skills. As a complement of the above, we will ask participants to run and complete the SoftGame App, a game-based digital instrument (in tablets) developed by Danon et al. (2018) that measures five non-cognitive traits: ○ GRIT: Grit Scale (Duckworth et al., 2007), Additions game, frustration task. ○ BigFive Scale ○ Locus of Control Scale ○ Impulsiveness: Barratt Impulsiveness Scale, Go-noGo Task, STEP ○ Risk taking behavior: Balloon Analogue Risk Task (BART). ● Emotions. We will proxy emotions using the artificial intelligence-based algorithm developed by Affectiva and the MIT Media Lab’s Affective Computing Group. It uses the analysis of videos captured from the front camera of smartphones or tablets to proxy for emotions. The level of accuracy of this methodology is around 75-80%. Then, we will use the specifications of Egana-delSol (2016) to construct arousal (proxy of stress) and valence indices (proxy of emotional regulation) at resting state and in the onset of a positive and negative stimuli. For each strand of data that we mentioned before, we will use the following instruments: ● Misbehavior at school. It will be measured from the student behavior reports in the schools, that we will obtain through administrative reports of the teachers. They are in scale [excellent; very good; well; average; below average]. These categories can be transformed into scores that can go from 0-10 points. ● Academic performance. Reports of math and student science notes on scales of 0-10 points will be standardized at the course level. These data will be collected from the administrative bases of the schools.
Experimental Design (Public) The randomized control trial that will generate the data and evidence we are looking for will be implemented in 21 schools, including 7 in El Salvador, 7 in Honduras, and 7 in Guatemala. Our randomization unit will be educational-level. In El Salvador, each educational level includes three courses: the first level includes first to third grades, the second level includes fourth to sixth courses, and the third level is constituted by grades seventh to ninth. Each level attends school either in the morning or evening shift. By stratifying at the country, school and school's risk level, all participating educational levels will be randomly assigned to three treatments: ● T1: Clubs: 1/3 of educational levels (14 levels) will be randomly assigned to the intervention of extracurricular clubs. Schools in this treatment will receive specific activities of the clubs including sports, languages, among others. ● T2: T1 + CS: 1/3 of educational levels (14 levels) will be randomly assigned to the intervention of CS + extracurricular clubs (T1). In each of the sessions, schools in this treatment will first receive the curricula that encourage CS and in the second part of the session, the specific activities of the clubs are developed. ● T3: T1 + Mindfulness: The remaining 1/3 of educational levels will be randomly assigned to the intervention of Mindfulness + extracurricular clubs (T1). In each of the sessions, schools in this treatment will first receive the curricula of Mindfulness and in the second part of the session, the specific activities of the extracurricular clubs. In addition, we will identify 7 schools, and their respective 14 educational levels, that will serve as a comparison group. Exploiting information from National Educational Censuses, we will use matching in propensity score approach to identify schools that are more like to those treated. From these comparison schools, we will gather information to characterize the potential demand for the Clubs. Randomization The randomized control trial that will generate the data and evidence we are looking for will be implemented in 21 schools, including 7 in El Salvador, 7 in Honduras, and 7 in Guatemala. By stratifying at the country and school-risk level, all participating schools will be randomly assigned to three treatments: ● T1: Clubs: 1/3 of schools will be randomly assigned to the intervention of extracurricular clubs. Schools in this treatment will receive specific activities of the clubs including sports, languages, among others. ● T2: T1 + CS: 1/3 of schools will be randomly assigned to the intervention of CS + extracurricular clubs (T1). In each of the sessions, schools in this treatment will first receive the curricula that encourage CS and in the second part of the session, the specific activities of the clubs are developed. ● T3: T1 + Mindfulness: The remaining 1/3 of schools will be randomly assigned to the intervention of Mindfulness + extracurricular clubs (T1). In each of the sessions, schools in this treatment will first receive the curricula of Mindfulness and in the second part of the session, the specific activities of the extracurricular clubs. In addition, we will identify 7 schools that will serve as a comparison group. Exploiting information from National Educational Censuses, we will use matching in propensity score approach to identify schools that are more like to those treated. From these comparison schools, we will gather information to characterize the potential demand for the Clubs. Thus, when comparing the outcomes of T1 group with control schools, we will provide causal evidence of the protection mechanism provided by the extra-curricular clubs. Then, in the comparison of outcomes of T2 or T3 group with those of the control group, it will provide causal evidence of the effect of applying this type of interventions—character strengths and mindfulness—to individuals living in highly violent contexts, which is equivalent to both protection and learning mechanisms. Finally, this experimental design and project structure allow us to disentangle learning and protection mechanisms. We argue that extra-curricular clubs mostly keep participants out of their violent environments. Then, those who also learn a specific curriculum on character strengths or mindfulness are learning life skills that these programs deliver while protected during a similar amount of time, i.e., school children in T1 receive only a protective service while children in T2 or T3 receive both protection and learning. Therefore, the difference in the results between T1 and any of the other interventions—CS (T2) and Mindfulness (T3)—can be interpreted as the separation between the mechanism of protection or learning.
Planned Number of Clusters 28 schools in total. 29 schools in total.
Planned Number of Observations The final sample should be 2552 students, 638 from comparison schools and 1582 from treated schools, that accounts for an average of 92 students per school. The final sample should be 1975 students, 556 from pure comparison schools and 1419 from treated schools, which accounts for an average of 49 students per school.
Sample size (or number of clusters) by treatment arms Assuming power of 0.80 and a reliability of 0.95, from a total of 28 schools we will require a sample with size of 2320 students, 580 from comparison and 1740 from treated schools. On average, we must recruit 83 students per school. However, estimating an attrition of 10%, the final sample should be 2552 students, 638 from comparison schools and 1582 from treated schools, that accounts for an average of 92 students per school. 7 schools in T1, 7 schools in T2, 7 schools in T3, 8 schools in pure control group.
Power calculation: Minimum Detectable Effect Size for Main Outcomes Using previous evidence of Dinarte and Egana-Del Sol (2018), the expected effect of an intervention aimed at improving socio-emotional skills of adolescents participating in these interventions is between 0.17 and 0.10 standard deviations on behavior in school and academic performance, respectively. From that data, we also use mean and standard deviations of these two outcomes from the control group, correlations between baseline and follow-up of 0.81 and an intra-school correlation of 0.03. Assuming power of 0.80 and a reliability of 0.95, from a total of 28 schools we will require a sample with size of 2320 students, 580 from comparison and 1740 from treated schools. On average, we must recruit 83 students per school. However, estimating an attrition of 10%, the final sample should be 2552 students, 638 from comparison schools and 1582 from treated schools, that accounts for an average of 92 students per school. For power estimations, we use existing evidence on the effects of psychological interventions on socio-emotional skills and academic performance for at-risk adolescents and adults (Castro et al., 2019; Flook et al, 2015; Chernikoff, 2019; and Dinarte and Egana-Del Sol, 2019 (DE, 2019)). Considering that the results from DE (2019) are (i) the most conservative, (ii) the intervention analyzed is similar to T1, and (iii) this sample is the most similar to the students in our project, we use DE’s (2019) data as a reference for minimum detectable effects and for estimations of intra-cluster correlation and correlation between baseline and follow-ups. DE (2019) finds that an expected average effect of an intervention aimed at improving the socio-emotional skills of adolescents is around 0.17 and 0.13 standard deviations on misbehavior in school and academic performance, respectively. From that data, we also estimate correlations between baseline and follow-up of 0.81 and an intra-school correlation of 0.04 (the most conservative scenario). Moreover, Chernikoff (2019) estimates that a mindfulness program for adults can have an effect of approximately 0.3 standard deviations. We use this result as an MDE of reference for T2 and T3 treatments. Considering these effects and assuming a power of 0.80 and an alpha of 0.05, the most conservative estimation of sample size indicates that we would need a sample of 1,616 students from the total 29 schools—404 from comparison and 1,212 from treated schools. On average, we must recruit 56 students per school. The current sample of 1,975 students allows us to handle attrition of up to 10%, 3 percentage points higher than the attrition from DE (2019).
Keyword(s) Crime Violence And Conflict, Education, Health, Post Conflict Crime Violence And Conflict, Education, Health
Intervention (Hidden) Randomization The randomized control trial that will generate the data and evidence we are looking for will be implemented in 21 schools, including 7 in El Salvador, 7 in Honduras, and 7 in Guatemala. The randomization unit will be educational levels. In El Salvador, the first educational level includes first to third grades, the second from fourth to sixth grades, and the third level includes seventh to ninth courses. In the participant schools, we will randomize only among the second and third levels. By stratifying at the country, school, and school's risk level, all participating educational levels will be randomly assigned to three treatments: ● T1: Clubs: 1/3 of educational levels (14 levels) will be randomly assigned to the intervention of extracurricular clubs. Schools in this treatment will receive specific activities of the clubs including sports, languages, among others. ● T2: T1 + CS: 1/3 of educational levels (14 levels) will be randomly assigned to the intervention of CS + extracurricular clubs (T1). In each of the sessions, schools in this treatment will first receive the curricula that encourage CS and in the second part of the session, the specific activities of the clubs are developed. ● T3: T1 + Mindfulness: The remaining 1/3 of educational levels will be randomly assigned to the intervention of Mindfulness + extracurricular clubs (T1). In each of the sessions, schools in this treatment will first receive the curricula of Mindfulness and in the second part of the session, the specific activities of the extracurricular clubs. In addition, we will identify 7 schools, and their respective 14 levels, that will serve as a comparison group. Exploiting information from National Educational Censuses, we will use matching in propensity score approach to identify schools that are more like to those treated. From these comparison schools, we will gather information to characterize the potential demand for the Clubs. Thus, when comparing the outcomes of T1 group with control schools, we will provide causal evidence of the protection mechanism provided by the extra-curricular clubs. Then, in the comparison of outcomes of T2 or T3 group with those of the control group, it will provide causal evidence of the effect of applying this type of interventions—character strengths and mindfulness—to individuals living in highly violent contexts, which is equivalent to both protection and learning mechanisms. Finally, this experimental design and project structure allow us to disentangle learning and protection mechanisms. We argue that extra-curricular clubs mostly keep participants out of their violent environments. Then, those who also learn a specific curriculum on character strengths or mindfulness are learning life skills that these programs deliver while protected during a similar amount of time, i.e., school children in T1 receive only a protective service while children in T2 or T3 receive both protection and learning. Therefore, the difference in the results between T1 and any of the other interventions—CS (T2) and Mindfulness (T3)—can be interpreted as the separation between the mechanism of protection or learning. This project aims to evaluate the impact of three interventions oriented to enhance participants’ non-cognitive skills and character. Our target audience will consist of students enrolled in participants and comparison schools in Central America, with the ages between 12 and 16 years—second and third educational levels. The first intervention consists to participate in extra-curricular activities that include dance, sports, art, among others. In this alternative, children are not learning a specific curriculum, but remain under adult supervision and protected from their risky contexts during a couple of hours. The second psychological curriculum we study, Construcción de Fortaleza de carácter (“Character Strengths Development Program” or CSD), aims to strengthen participants’ character and increase their development and psychological well-being. According to the theory of change for this intervention, positive psychological resources developed through CSD will drive beneficial behaviors such as staying in school and increasing academic performance; improvement in relationships; decision making and establishment of life goals; and taking actions to achieve the latter. These positive resources will help participants to prevent and reduce harmful behaviors such as school dropouts, poor academic performance, violent behaviors, involvement in illegal activities, and other risky behaviors. CSD includes 32 sessions of training or reflection. The first type aims to reinforce the concepts and their importance in order for participants to achieve well-being. In the reflection sessions, participants are invited to perform self-analysis—that is, analysis of their history and environment. To achieve the desired level of reflection, implementers use an active learning methodology, which places the student at the center of the learning experience and motivates participation through individual and group activities. Participants actively practice the strengths, reflect their application in daily life, and acquire tools to adopt them easily. The third intervention is a combination of extra-curricular clubs and a mindfulness program, Salon Tranquilo (“Calm Classroom®” or MF), a mindfulness-based and relaxation response program. The program includes directed meditation for stress and anxiety reduction and control of automatic responses; it uses thought techniques to help participants develop self-awareness, mental concentration, and inner calm. Through several activities, MF provides students and staff with tools to manage stress more effectively, to regulate their emotions, and at the same time to lead more productive and well-balanced lives. The MF program includes 42 different activities of breathing, stretching, relaxation, and focusing techniques. Each script technique takes three minutes to implement. Mentors conduct these scheduled practices during the clubs and encourage participants to use the techniques naturally when appropriate. Participants will meet once per week during one academic year (between 7-8 months). Each of the sessions is implemented after-school time, with an approximate duration of 1-1.5 hours. For methodological reasons, club sizes are between 13-15 participants on average.
Secondary Outcomes (End Points) (iv) Administrative data on misbehavior and school attendance, and (v) academic performance using school records. (i) Strengths and Virtues (Peterson and Seligman, 2004), (ii) socioemotional skills--impulsiveness, perseverance, and risk-taking behavior--collected using SoftGames App (Danon et al, 2018), (iii) socioemotional skills--grit, emotional regulation, and locus of control--using self-reported surveys, (iv) Emotional reaction and regulation, collected using an artificial intelligence-based algorithm.
Secondary Outcomes (Explanation) For each strand of data that we mentioned before, we will use the following instruments: ● Misbehavior at school and attendance. It will be measured from the student behavior reports in the schools, that we will obtain through administrative reports of the teachers. They are in scale [excellent; very good; well; average; below average]. These categories can be transformed into scores that can go from 0-10 points. ● Academic performance. Reports of math and student science notes on scales of 0-10 points will be standardized at the course level. These data will be collected from the administrative bases of the schools. In coordination with Ministries of Education, we will also develop a short quiz for math, to have a standardized test for all schools as in Rao (2018). For each strand of data that we mentioned before, we will use the following instruments: ● Strengths and Virtues. We will employ the Values in Action Inventory of Strengths (Peterson and Seligman, 2004). It is a catalog of positive psychological traits, consisting of 240 items, ten for each of 24 different character strengths. Following Jordan and Rand (2018), we will use an adapted version that consists of only 24 items that ask directly about each character strength. Each item is scored on a Likert scale from 1 to 5 points. The outcome will be an index estimated as the sum of all validated items and can take the value of 1 to 80. The greater the index, the higher the participant’s strength of character. ● Non-cognitive skills. 1. GRIT: the combination of passion and perseverance for a singularly important goal. We will estimate this outcome using two measures: • GRIT Scale: This variable will be the sum of validated items at the student level. This index will take a value between 1 and 60. A GRIT value close to 60 indicates that the student has a higher level of perseverance. • Addition games (Alan and Ertact Grit Task): In this game, participants are presented with a set of additions, which can be easy or difficult to solve. After each round, they are asked to select the level of difficulty for the next one. Thus, we have two proxies for perseverance: (i) the proportion of difficult games chosen in all rounds and (ii) if the student persisted after failing in round 1, when her or his choice was forced. A greater value of any of these proxies indicates that the participant is more perseverant. 2. Impulsiveness: This trait is defined as the tendency of an individual to act suddenly without thinking carefully about what might happen because of what s/he is doing. To proxy for impulsiveness, we used the Go-noGo game. In this game, the participant is presented with a square on the screen for a very short period and is asked to touch the screen every time the square is not black (the noGo stimulus). The outcome is the proportion of times the participant correctly responds to the noGo stimulus. The higher the level of this proportion, the less impulsive the participant is. 3. Risk-taking behavior: This is defined as any consciously or unconsciously controlled behavior with a perceived uncertainty about its benefits or costs for the well-being of oneself or others (Trimpop, 1994). We measure this outcome using the Balloon Analogue Risk Task (BART) Game. It consists of pumping a balloon. Each pump earns points for the participant, but s/he will lose all earned points if the balloon pops. The outcome is measured as the mean of pumps on the balloons that did not pop. The more points the participant earns, the more risk loving s/he is. 4. Locus of Control: This is defined as the degree to which people believe they have power over the outcome of events in their lives. We use a four-item survey. This outcome will be the sum of all items and therefore takes a value between 1 and 20 points. The greater the index, the higher the expectation that they can control their lives. ● Emotion regulation and stress: We will proxy regulation of emotions and stress using two instruments. a. Cognitive Emotion Regulation Questionnaire (CERQ): This instrument includes 36 items, each of them scored on a Likert scale from 1 to 5 points. The outcome will the sum of validated items at the student level. This index will take a value between 1 and 180. A higher index indicates the student’s increased ability to regulate her or his emotions. b. Reactiva: To proxy for emotional regulation and stress, we will rely on the artificial intelligence-based (AI) algorithm that uses the analysis of videos captured from the front camera of smartphones or tablets to proxy for emotions. Then, we will use the specifications of Egana-delSol (2016) to construct arousal (proxy of stress) and valence (proxy of emotional regulation) indices at a resting state and in the onset of positive and negative stimuli. A greater level of arousal or valence indicates higher levels of stress or emotional regulation, respectively.
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