MSc Laura Vagnoli°
email: lauravagnoli@virgilio.it

PhD Simona Caprilli°
email: simonacaprillis.caprilli@meyer.itandreamesseria.messeri@meyer.it

Andrea Messeri

Anesthesist Laura Vagnoli

Parental presence, clowns or sedative premedication to treat preoperative anxiety in children: what could be the most promising option?

Keywords: Preoperative anxiety, induction anesthesia, children, clowns, Premedication, PPIA Preoperative anxiety, induction anesthesia, children, clowns, Premedication, PPIA OR, operating room, m-YPAS, Modified Yale Preoperative Anxiety Scale, STAI, State-Trait Anxiety Inventory, PPIA, parental presence during induction of anesthesia, CG, Clown Group, PG, Premedication group, CG, Control group

    Parental presence, clowns or sedative premedication to treat preoperative anxiety in children: what could be the most promising option?

A) INTRODUCTION

Several studies have indicated that numerous children exhibit significant manifestations of anxiety in the presurgical period. The induction of anesthesia appears to be the most stressful procedure for a child during the preoperative period. Preoperative anxiety and fear have been associated with long-term negative postsurgery behaviours 1,2 .

At present, there are several types of pharmacological and non-pharmacological intervention to reduce the incidence of this phenomenon in children 3 . In order to treat preoperative anxiety some anaesthesiologists routinely opt for sedative premedication and parental presence during induction of anesthesia (PPIA), simultaneously or interchangeably 4 . Recent studies found that presence of clown together with PPIA was an effective intervention for managing child anxiety during preoperative period 5,6 . However the findings of the research presented in relevant literature were controversial and there was not an agreed view about the best technique to reduce anxiety in pediatric surgery. Therefore, the purpose of this randomized study was to investigate which intervention was more effective for reducing preoperative anxiety in children undergoing minor surgery: a pharmacological intervention with sedative premedication (Midazolam), or a nonpharmacological technique such as the presence of Clowns + PPIA, or only PPIA.

B) MATERIALS AND METHODS

B1) Patients

The population of this randomized prospective study consisted of children who were classified as physical status I-II according to the American Society of Anaesthesiologist standards, and who were scheduled to undergo general anesthesia for minor surgery at Anna Meyer Children's Hospital in Florence (Italy), and of their parents. We considered only Italian children as being eligible so as to avoid any misinterpretation of the evaluation instruments used.

The sample examined was composed of 75 randomly assigned consecutive children aged 5 to 12, residents in Florence or in the close surroundings of the city. Children with a history of chronic F o r P e e r R e v i e w 4 illness, premature birth, developmental delay or previous anaesthetic experience were excluded from this study. The subjects had to be chosen from a population of children who were supposed to undergo minor day surgery and were assigned to one of three groups by using computer-generated list random assignment.

The study protocol was approved by the hospital ethics committee and informed consent was obtained from the parents before inclusion of their children in the study.

Primary end point was the anxiety of the child in the preoperative period. The goal of the study was to determine whether the presence of clowns was more effective in reducing preoperative anxiety in the child than sedative premedication (with Midazolam), or only PPIA. As a secondary end point we aimed to identify the difference in the levels of parents' anxiety in the three groups.

B2) Study Groups

Eligible patients were randomly assigned following simple randomization procedures (computerized random numbers) to one of the three study groups:

(1) Clown group (CG): children were accompanied in the preoperative room by two clowns and a parent. They interacted with clowns before entering the OR (operating room) and stayed with them and their parent throughout the anesthesia-induction process.

(2) Premedication group (PG): children were premedicated with 0.5 mg/kg oral Midazolam at least 45 minutes before the surgical procedure began, and a parent was present throughout the anesthesiainduction process.

(3) Control group (CG): children were accompanied in the OR by one parent, without any clowns, other distractions or premedications, during induction of anesthesia. PPIA is considered control group because is routinely used in our hospital.

In each group, the children were observed during the preoperative process in two different rooms: the waiting room and the induction room. They personally chose the parent who stayed with them.

Anesthesia was induced in all patients by pediatric anaesthesiologists by means of a scented mask using a standardized oxygen (O 2 )/nitrous oxide(N 2 O)/sevoflurane technique. In the CG, two clowns stayed with the child during the whole process: they arrived approx. 30 minutes before the child was taken to the OR, and stayed with him/her for approx. 15 minutes. The clowns, taking into account the children's age and experience, used various methods to entertain them (eg, magic tricks, gags, music, games, puppets, word games, soap bubbles, etc). The clowns are professional performing artists with specialties ranging from music to magic who have been carefully selected and trained to apply their skills to a hospital's special needs. When the nurse took the child to the OR, the clowns accompanied the child and the parent and stayed with them during the anesthesia-induction process.

In the PG oral Midazolam was administered by a nurse approx. 45 minutes before the surgical procedure. Then, the same nurse accompanied the child with a parent in the OR.

The managing anaesthesiologist, the parents and the other observers were kept blinded to the purpose of the study and the groups involved, but it was impossible to be blind entirely to assignment for the children in the CG. In addition, parents of the PG were informed that their children had been given a drug.

B3) Evaluation Instruments

Modified Yale Preoperative Anxiety Scale

The Modified Yale Preoperative Anxiety Scale (m-YPAS) was used to evaluate the behaviour of the child in the waiting room and in the induction room. The m-YPAS is an observational behavioural checklist developed by Kain et al. 7 to measure the state anxiety of young children. It contains 27 items divided into 5 categories: activity, emotional expressivity, state of arousal, vocalization, use of parents. Each category receives a score on a scale of 4 (6 for vocalization) according to the behaviour of the patient. The m-YPAS score ranges from 23 to 100, with higher scores indicating greater anxiety. This scale has good-to-excellent interrater and intraobserver reliability and validity for measuring children's anxiety in the preoperative holding area and during induction of anesthesia 7 . For our study the coding method was translated from English into Italian 5 . The STAI trait subscale measures relatively stable individual differences in anxiety proneness (i.e., differences in the tendency to experience anxiety), and the STAI state subscale measures transitory anxiety state (i.e., subjective feelings of apprehension, tension and worry that vary in intensity and fluctuate depending on the situation).

State-Trait Anxiety Inventory

Parents responded on a 4-point scale. Total scores for state and trait sections separately range from 20 to 80, with higher scores denoting higher levels of anxiety. Test-retest correlations for the STAI are high (range: 0.73-0.86), and the studies have demonstrated good validity. In this study we used form Y (Y-1/Y-2) developed by Spielberger 8 , as well as with the table to calculate the score according to the Italian standard version 9 .

B4) Data Analysis

All the instruments were administered by two psychologists who had significant background in behavioural research. The two independent observers evaluated the child's anxiety (m-YPAS) in the waiting room and in the induction room. Parental anxiety was assessed on the same day as surgery with STAI (Y-1/Y-2) immediately after separation between parent and child, and during the operation. We measured trait and state anxiety in that moment in order to avoid organizational problems in keeping contacts with the families, trait anxiety being supposed to be a stable measure anyway.

Descriptive statistics provide an overview of the relationships between child and parent variables, as well as anxiety levels in child and parent. Data are presented as mean±SD.

The agreement between the two observers codifying the data of m-YPAS was verified through Cohen's k calculation. Differences between groups were examined using one-way analysis of variance and all pairwise multiple comparisons were performed using the Scheffé test: we compared the scores of anxiety level obtained by the three groups with m-YPAS in the surgery process and the scores of the level of state (STAI Y-1) and trait anxiety (STAI Y-2) of parents. The anxiety level of children within the same group, in the waiting room and in the induction room were compared by using a repeated-measures analysis of variance (within-subjects factors) for each group, and also using the Scheffé post hoc test. The Pearson's correlation coefficient (r) was used to evaluate the demographic characteristics and the relations between the child's anxiety level, the child's age and the parents' anxiety. The correlation was also calculated within the groups, correlating the scores of waiting room and induction room.

The sample size was based on some investigations involving clown, sedative premedication (with Midazolam), PPIA and children 3,5,6 . These studies show significant reduction in the level of anxiety of the children 3,5,6 . A sample size of 75 subjects was calculated to be sufficient to detect a difference in anxiety level considering the number of patients hospitalized routinely in day surgery in our hospital.

Data were analysed by using SPSS version 11.5 for Windows (SPSS Inc, Chicago, IL, USA). P was accepted as significant at < .05.

C) RESULTS

The 75 participants were recruited from April to December 2009. The demographic and clinical characteristics of the three groups of children and parents are presented in Table 1 and 2 and they are similar across groups, with no significant differences in age or in gender distribution. However, the ratio of mother to father is different: there are more mothers than fathers who accompany their child during preoperative process.

The two observers who codified the data are agree: the results of Cohen's k for every category m-YPAS and for both the preoperative rooms are broadly significant with values between .73 and .91.

In each group, the anxiety of children increased during the induction of anesthesia [F (2,72) = 12.994; p = .001]. Using post-hoc Scheffé test, we found that the level of anxiety was significantly lower in the CG compared to PG (p = .038) and to CG, whose level of anxiety was significantly higher (p = .000). There were not any significant differences between CG and PG. Furthermore there were no Using a repeated-measures ANOVA, we analysed changes in the level of anxiety in the two locations. We found that in each group there was an increased level of anxiety in the induction room in comparison to the waiting room: this difference was statistically significant for CG [F (1,24) = 30,300; p = .001] and PG [F (1,24) = 6,425; p = .005]), whereas it was not significant in the CG (Tab.

3). The post-hoc Scheffé about the results of repeated-measures ANOVA in the two rooms demonstrated that the increased of level of anxiety in children of CG is significantly higher compared to CG (p = .000), while there was no difference with PG (p = .279). In contrast, the anxiety of children in the CG was significantly lower compared with both the other groups: CG (p = .000); PG (p = .015) (Fig. 1). The Pearson's correlations were statistically significant between: state anxiety of parent and age of child (r = -.24; p < .05); anxiety of child in waiting room and age of child (r = .27; p < .05); level of anxiety in waiting room and level of anxiety in induction room (r = .35; p < .01).

The anxiety of parents attending the induction of anesthesia. Using one-way analysis of variance, we found no significant differences among the parents of three study groups: only state anxiety was lower in PG (Tab. 3). The correlations between the anxiety level of the child and that of the parents, and between the anxiety of the parents and demographic characteristics were not significant. As for level of anxiety of parents we found a significant correlation between state anxiety (STAI Y-1) and trait anxiety (STAI Y-2) (r = .23; p < .05).

D) DISCUSSION

Relieving preoperative anxiety in the child is necessary to reduce maladaptive postsurgery behaviours, as well as negative children's responses to successive medical care. The increase of anxiety in the presurgical period is associated with increased postoperative pain, analgesic consumption, general anxiety, incidence of emergence delirium, sleeping problems and poor postoperative eating improvement behavioural problems 10,11 . We found that the CG was significantly less anxious during the induction of anesthesia compared with CG and PG, and there were no significant differences between the level of anxiety in the two rooms the waiting room and the level of anxiety in the induction room in children who were accompanied by clowns.

Recent study 6 found that the use of preoperative medically trained clowns for children undergoing surgery can significantly alleviate preoperative anxiety compared to the CG and PG, but however, clowns do not have any effect once the anesthesia mask is introduced. Therefore our research demonstrates that the clowns could be the most promising option to treat preoperative anxiety in children.

Several researchers have shown the efficacy of a series of approaches to prevent and manage

anxiety and fear in the presurgical period, both with pharmacological 2 interventions (e.g. sedative premedication 2 ) and with non-pharmacological interventions 3 (e.g. preoperative visits in the O.R., PPIA, psychological preparation of the child and parents, with audio/video devices, leaflets, painting books 12 , acupuncture, toys 13,14 , flavoured anesthesia mask, fun transportation system -i.e. wagons 15 -, music 16 , clown 5,6 ).

Several researchers have shown the efficacy of a series of approaches to manage anxiety in the presurgical period, both with pharmacological 2 and with non-pharmacological interventions 3,5,6,12,13,14,15,16 .

Among drugs used in the preoperative period, Midazolam is the most commonly administered: this drug is effective in reducing anxiety prior and during the induction of anesthesia. It has proved more effective than only parental presence 17 in reducing anxiety and it is a drug which onsets rapidly and with short half-life, although it is not without disadvantages (e.g. delay in emergence, recovery and discharge, amnesia, increase in postrecovery anxiety) 16,18 . Many patients frequently show extreme distress and lack of compliance during induction of anesthesia despite premedication 18 : the administration of oral premedication to children is often met with apprehension, reluctance, or refusal 18 . The clown can facilitate the induction process, leave a pleasant memory and represent an alternative to Midazolam, which often leaves the child amnesic The presence of parents during the induction is controversial in relevant literature: numerous studies underline the benefits of this intervention 3 , highlighting that it helps reducing the use of premedication and increasing child cooperation 15 , whereas others studies point out the possibility that it may increase parental anxiety and child behavioural problems. As a matter of fact, PPIA is routinely used in some hospitals while actively discouraged in others. In our study we found that the CG maintained the same level of anxiety during all the preoperative period without differences between the two rooms locations. We can assume that the mask and the induction of anesthesia are less frightening for the children belonging to this group compared with the others. These results are consistent with previous studies that demonstrated the effectiveness of clowns in pediatric settings 5 and with other research that showed the influence of the environment on anxiety, especially in the induction room 25 . In this study, indeed, anxiety increased during the induction of anesthesia in every group. Furthermore we found that, both in CG and in PG, the level of anxiety was significantly higher in the induction room than in the waiting room. The level of anxiety of CG was significantly higher compared with CG, but there were no differences from PG. This finding is in line with some studies of relevant literature 26 that show that PPIA in addition to premedication has no additive effects in terms of reducing the child's anxiety.

As for non-pharmacological intervention, following the results of previous study on

These results are consistent also with those of other studies which compare the use of Midazolam to alternative interventions for managing preoperative anxiety in children 3,13,16 : as hand-held video games 3,13 , indeed children who received PPIA + hand-held video games showed less anxiety when the anesthesia mask was used compared to PPIA group and Midazolam Group and music 16. the results of one of these studies show that music therapy may be helpful on separation and entrance to the OR (depending on the therapist), but it doesn't appear to relieve anxiety during the induction of anesthesia: the Midazolam group was significantly less anxious during anaesthetic induction in comparison to both the music group and the control group 3,16 .

We can hypothesize that the clowns have a greater effect than music during induction because they involve the child actively, with mental and motor participation, performing gags and improvisations which are not standardised but created for every individual child in line with his/her characteristics and personality.

Previous studies 2,27 had shown that children over seven years had a higher level of anxiety in the waiting room than younger children and that the parents' anxiety was a predictor of the child's 12 anxiety during the preoperative period. In agreement with these finding we can affirm that anxiety in children seems to increase with age. Moreover, since in our study a correlation between child anxiety in the waiting room and age of the child, as well as a correlation between parent anxiety during surgery and child age exist, we found that the younger children are, the more anxious parents tend to get.

In addition, we noticed that a correlation can be also found between the child's level of anxiety in the two rooms waiting room and in the induction room: children who were more anxious during the wait were also more anxious during the induction, unlike children who were more relaxed during the wait, who also showed less anxiety during the induction.

We didn't find any correlations between level of anxiety and gender of the child. According to the literature, gender does not influence preoperative anxiety, nor development of postoperative behavioural problems 17 .

In according to the literature we didn't find any correlations between level of anxiety and gender of the child 17 .

Finally, in our study the secondary end point was the level of anxiety of parents present during the induction of anesthesia. There were not significant differences between each group. Only the scores obtained with the STAI by the parents of PG showed lower levels of anxiety. We can assume that parents who knew that their son or daughter had taken a specific drug to reduce preoperative anxiety were more reassured than parents who simply accompanied their children in the OR, or only with the support of some kind of distraction. Probably drugs give more security and guarantee: a qualitative study with interviews could help to identify the reasons of lower anxiety.

We didn't find any correlations between the level of anxiety of parents and the level of anxiety of children: on the contrary, many studies identify the anxiety of the parent as a predictor of the child's anxiety 15,27 . Study limitations include small sample size, lack of data on time of induction, and to know if there were any differences in adverse behavioural responses in the week post-discharge for each group.

In conclusion in our study we determined that PPIA + clown intervention is better to reduce anxiety in children during the preoperative period than PPIA alone or PPIA + oral Midazolam.

Considering the importance of non-pharmacological intervention in this context, it would be very interesting to study the application of different distraction techniques in order to assess which one is the most effective in different age group and cultures, in children with chronic illness and with behavioural problems.

Thus, in future studies it would be interesting to compare clown intervention alone with PPIA alone and with Midazolam alone, so as to determine if the presence of clowns, or parental presence, or Premedication, actually lessens the children's anxiety. In addition we might study the difference between populations of different cultures and traditions which may provide different results.

Knowing that the psychological impact of anesthesia and surgery on children covers many areas, the presence of professional clown doctors for managing the child's anxiety during the preoperative phase, should be encouraged in pediatrics hospitals. with correct information being provided to both child and parents. Methods for additional analyses, such as subgroup analyses and adjusted analyses -

E) ACKNOWLEDGEMENTS

Results

a

For each group, the numbers of participants who were randomly assigned, received intended treatment, and were analysed for the primary outcome For each primary and secondary outcome, results for each group, and the estimated effect size and its precision (such as 95% confidence interval)

Results:

The Clown group was significantly less anxious during the induction of anesthesia compared with Premedication group and Control group. There were not any significant differences between Control group and Premedication group.

There was an increased level of anxiety in the induction room in comparison to the waiting room:

this difference was statistically significant for Control group and Premedication group, whereas it was not significant in Clown group.

Conclusions:

PPIA+clown intervention is more effective in reducing anxiety in children during the preoperative period than PPIA alone or PPIA+oral Midazolam.

KEY WORDS

Preoperative anxiety, induction anesthesia, children, clowns, Premedication, PPIA.

ABBREVIATIONS

A) INTRODUCTION

Several studies have indicated that numerous children exhibit significant manifestations of anxiety in the presurgical period. The induction of anesthesia appears to be the most stressful procedure for a child during the preoperative period. Preoperative anxiety and fear have been associated with long-term negative postsurgery behaviours 1,2 .

At present, there are several types of pharmacological and non-pharmacological intervention to reduce the incidence of this phenomenon in children 3 . In order to treat preoperative anxiety some anaesthesiologists routinely opt for sedative premedication and parental presence during induction of anesthesia (PPIA), simultaneously or interchangeably 4 . Recent studies found that presence of clown together with PPIA was an effective intervention for managing child anxiety during preoperative period 5,6 . However the findings of the research presented in relevant literature were controversial and there was not an agreed view about the best technique to reduce anxiety in pediatric surgery. Therefore, the purpose of this randomized study was to investigate which intervention was more effective for reducing preoperative anxiety in children undergoing minor surgery: a pharmacological intervention with sedative premedication (Midazolam), or a nonpharmacological technique such as the presence of Clowns + PPIA, or only PPIA.

B) MATERIALS AND METHODS

B1) Patients

The population of this randomized prospective study consisted of children who were classified as physical status I-II according to the American Society of Anaesthesiologist standards, and who were scheduled to undergo general anesthesia for minor surgery at Anna Meyer Children's Hospital in 4 from this study. The subjects had to be chosen from a population of children who were supposed to undergo minor day surgery and were assigned to one of three groups by using computer-generated list random assignment.

The study protocol was approved by the hospital ethics committee and informed consent was obtained from the parents before inclusion of their children in the study.

Primary end point was the anxiety of the child in the preoperative period. The goal of the study was to determine whether the presence of clowns was more effective in reducing preoperative anxiety in the child than sedative premedication (with Midazolam), or only PPIA. As a secondary end point we aimed to identify the difference in the levels of parents' anxiety in the three groups.

B2) Study Groups

Eligible patients were randomly assigned following simple randomization procedures (computerized random numbers) to one of the three study groups:

(1) Clown group (CG): children were accompanied in the preoperative room by two clowns and a parent. They interacted with clowns before entering the OR (operating room) and stayed with them and their parent throughout the anesthesia-induction process.

(2) Premedication group (PG): children were premedicated with 0.5 mg/kg oral Midazolam at least 45 minutes before the surgical procedure began, and a parent was present throughout the anesthesiainduction process.

(3) Control group (CG): children were accompanied in the OR by one parent, without any clowns, other distractions or premedications, during induction of anesthesia. PPIA is considered control group because is routinely used in our hospital.

In each group, the children were observed during the preoperative process in two different rooms:

the waiting room and the induction room. They personally chose the parent who stayed with them.

Anesthesia was induced in all patients by pediatric anaesthesiologists by means of a scented mask In the CG, two clowns stayed with the child during the whole process: they arrived approx. 30 minutes before the child was taken to the OR, and stayed with him/her for approx. 15 minutes. The clowns, taking into account the children's age and experience, used various methods to entertain them (eg, magic tricks, gags, music, games, puppets, word games, soap bubbles, etc). The clowns are professional performing artists with specialties ranging from music to magic who have been carefully selected and trained to apply their skills to a hospital's special needs. When the nurse took the child to the OR, the clowns accompanied the child and the parent and stayed with them during the anesthesia-induction process.

In the PG oral Midazolam was administered by a nurse approx. 45 minutes before the surgical procedure. Then, the same nurse accompanied the child with a parent in the OR.

The managing anaesthesiologist, the parents and the other observers were kept blinded to the purpose of the study and the groups involved, but it was impossible to be blind entirely to assignment for the children in the CG. In addition, parents of the PG were informed that their children had been given a drug.

B3) Evaluation Instruments

Modified Yale Preoperative Anxiety Scale

The Modified Yale Preoperative Anxiety Scale (m-YPAS) was used to evaluate the behaviour of the child in the waiting room and in the induction room. The m-YPAS is an observational behavioural checklist developed by Kain et al. 7 to measure the state anxiety of young children. It contains 27 items divided into 5 categories: activity, emotional expressivity, state of arousal, vocalization, use of parents. Each category receives a score on a scale of 4 (6 for vocalization) according to the behaviour of the patient. The m-YPAS score ranges from 23 to 100, with higher scores indicating greater anxiety. This scale has good-to-excellent interrater and intraobserver reliability and validity for measuring children's anxiety in the preoperative holding area and during induction of anesthesia 7 . For our study the coding method was translated from English into Italian 5 . The STAI trait subscale measures relatively stable individual differences in anxiety proneness (i.e., differences in the tendency to experience anxiety), and the STAI state subscale measures transitory anxiety state (i.e., subjective feelings of apprehension, tension and worry that vary in intensity and fluctuate depending on the situation).

State-Trait Anxiety Inventory

Parents responded on a 4-point scale. Total scores for state and trait sections separately range from 20 to 80, with higher scores denoting higher levels of anxiety. Test-retest correlations for the STAI are high (range: 0.73-0.86), and the studies have demonstrated good validity. In this study we used form Y (Y-1/Y-2) developed by Spielberger 8 , as well as with the table to calculate the score according to the Italian standard version 9 .

B4) Data Analysis

All the instruments were administered by two psychologists who had significant background in behavioural research. The two independent observers evaluated the child's anxiety (m-YPAS) in the waiting room and in the induction room. Parental anxiety was assessed on the same day as surgery with STAI (Y-1/Y-2) immediately after separation between parent and child, and during the operation. We measured trait and state anxiety in that moment in order to avoid organizational problems in keeping contacts with the families, trait anxiety being supposed to be a stable measure anyway.

Descriptive statistics provide an overview of the relationships between child and parent variables, as well as anxiety levels in child and parent. Data are presented as mean±SD.

The agreement between the two observers codifying the data of m-YPAS was verified through Cohen's k calculation. Differences between groups were examined using one-way analysis of variance and all pairwise multiple comparisons were performed using the Scheffé test: we compared the scores of anxiety level obtained by the three groups with m-YPAS in the surgery process and the scores of the level of state (STAI Y-1) and trait anxiety (STAI Y-2) of parents. The anxiety level of children within the same group, in the waiting room and in the induction room were compared by using a repeated-measures analysis of variance (within-subjects factors) for each group, and also using the Scheffé post hoc test. The Pearson's correlation coefficient (r) was used to evaluate the demographic characteristics and the relations between the child's anxiety level, the child's age and the parents' anxiety. The correlation was also calculated within the groups, correlating the scores of waiting room and induction room.

The sample size was based on some investigations involving clown, sedative premedication (with Midazolam), PPIA and children 3,5,6 . These studies show significant reduction in the level of anxiety of the children 3,5,6 . A sample size of 75 subjects was calculated to be sufficient to detect a difference in anxiety level considering the number of patients hospitalized routinely in day surgery in our hospital.

Data were analysed by using SPSS version 11.5 for Windows (SPSS Inc, Chicago, IL, USA). P was accepted as significant at < .05.

C) RESULTS

The 75 participants were recruited from April to December 2009. The demographic and clinical characteristics of the three groups of children and parents are presented in Table 1 and 2 and they are similar across groups, with no significant differences in age or in gender distribution. However, the ratio of mother to father is different: there are more mothers than fathers who accompany their child during preoperative process.

The two observers who codified the data are agree: the results of Cohen's k for every category m-YPAS and for both the preoperative rooms are broadly significant with values between .73 and .91.

In each group, the anxiety of children increased during the induction of anesthesia [F (2,72) = 12.994; p = .001]. Using post-hoc Scheffé test, we found that the level of anxiety was significantly lower in the CG compared to PG (p = .038) and to CG, whose level of anxiety was significantly higher (p = .000). There were not any significant differences between CG and PG. Furthermore there were no Using a repeated-measures ANOVA, we analysed changes in the level of anxiety in the two locations. We found that in each group there was an increased level of anxiety in the induction room in comparison to the waiting room: this difference was statistically significant for CG [F (1,24) = 30,300; p = .001] and PG [F (1,24) = 6,425; p = .005]), whereas it was not significant in the CG (Tab.

3). The post-hoc Scheffé about the results of repeated-measures ANOVA in the two rooms demonstrated that the increased of level of anxiety in children of CG is significantly higher compared to CG (p = .000), while there was no difference with PG (p = .279). In contrast, the anxiety of children in the CG was significantly lower compared with both the other groups: CG (p = .000); PG (p = .015) (Fig. 1). The Pearson's correlations were statistically significant between: state anxiety of parent and age of child (r = -.24; p < .05); anxiety of child in waiting room and age of child (r = .27; p < .05); level of anxiety in waiting room and level of anxiety in induction room (r = .35; p < .01).

The anxiety of parents attending the induction of anesthesia. Using one-way analysis of variance, we found no significant differences among the parents of three study groups: only state anxiety was lower in PG (Tab. 3). The correlations between the anxiety level of the child and that of the parents, and between the anxiety of the parents and demographic characteristics were not significant. As for level of anxiety of parents we found a significant correlation between state anxiety (STAI Y-1) and trait anxiety (STAI Y-2) (r = .23; p < .05).xx

D) DISCUSSION

Relieving preoperative anxiety in the child is necessary to reduce maladaptive postsurgery behaviours, as well as negative children's responses to successive medical care. The increase of anxiety in the presurgical period is associated with increased postoperative pain, analgesic consumption, general anxiety, behavioural problems 10,11 . We found that the CG was significantly less anxious during the induction of anesthesia compared with CG and PG, and there were no Recent study 6 found that the use of preoperative medically trained clowns for children undergoing surgery can significantly alleviate preoperative anxiety compared to the CG and PG, but however, clowns do not have any effect once the anesthesia mask is introduced. Therefore our research demonstrates that the clowns could be the most promising option to treat preoperative anxiety in children.

Several researchers have shown the efficacy of a series of approaches to manage anxiety in the presurgical period, both with pharmacological 2 and with non-pharmacological interventions 3,5,6,12,13,14,15,16 .

Among drugs used in the preoperative period, Midazolam is the most commonly administered. It has proved more effective than only parental presence 17 in reducing anxiety and it is a drug which onsets rapidly and with short half-life, although it is not without disadvantages: many patients frequently show extreme distress and lack of compliance during induction of anesthesia despite premedication 16,18 . The clown can facilitate the induction process, leave a pleasant memory and represent an alternative to Midazolam, which often leaves the child amnesic of the induction itself.

Without the memory of this event, subsequent inductions may indeed appear frightening 19,20,21 .

The presence of parents during the induction is controversial in relevant literature: numerous studies underline the benefits of this intervention 3 , highlighting that it helps reducing the use of premedication and increasing child cooperation 15 , whereas others studies point out the possibility that it may increase parental anxiety and child behavioural problems. As a matter of fact, PPIA is routinely used in some hospitals while actively discouraged in others.

In recent times there has been an increase in the presence of clowns in pediatric hospitals: the successful of this activity is possible if it is carried out by professional artists having gone through careful and rigorous training programmes 22,23,24 . In our study we found that the CG maintained the same level of anxiety during all the preoperative period without differences between the two rooms: these results are consistent with previous studies that demonstrated the effectiveness of clowns in pediatric settings 5 and with other research that showed the influence of the environment on anxiety, especially in the induction room 25 . In this study, indeed, anxiety increased during the induction of anesthesia in every group.

Furthermore we found that, both in CG and in PG, the level of anxiety was significantly higher in the induction room than in the waiting room. The level of anxiety of CG was significantly higher compared with CG, but there were no differences from PG. This finding is in line with some studies of relevant literature 26 that show that PPIA in addition to premedication has no additive effects in terms of reducing the child's anxiety.

These results are consistent also with those of other studies which compare the use of Midazolam to alternative interventions for managing preoperative anxiety in children 3,13,16 : the results of one of these studies show that music therapy may be helpful on separation and entrance to the OR (depending on the therapist), but it doesn't appear to relieve anxiety during the induction of anesthesia 16 . We can hypothesize that the clowns have a greater effect than music during induction because they involve the child actively performing gags which are not standardised but created for every individual child.

Previous studies 2,27 had shown that children over seven years had a higher level of anxiety in the waiting room than younger children and that the parents' anxiety was a predictor of the child's anxiety during the preoperative period. In agreement with these finding we can affirm that anxiety in children seems to increase with age. Moreover, since in our study a correlation between child anxiety in the waiting room and age of the child, as well as a correlation between parent anxiety during surgery and child age exist, we found that the younger children are, the more anxious parents tend to get. In addition, we noticed that a correlation can be also found between the child's level of anxiety in the two rooms: children who were more anxious during the wait were also more anxious during the induction, unlike children who were more relaxed during the wait, who also showed less anxiety during the induction. In according to the literature we didn't find any correlations between level of anxiety and gender of the child 17 .

Finally, in our study the secondary end point was the level of anxiety of parents present during the induction of anesthesia. There were not significant differences between each group. Only the scores obtained with the STAI by the parents of PG showed lower levels of anxiety. We can assume that parents who knew that their son or daughter had taken a specific drug to reduce preoperative anxiety were more reassured than parents who simply accompanied their children in the OR, or only with the support of some kind of distraction. We didn't find any correlations between the level of anxiety of parents and the level of anxiety of children: on the contrary, many studies identify the anxiety of the parent as a predictor of the child's anxiety 15,27 .

As for parents' anxiety, we found a significant correlation between state anxiety (STAI Y-1) and trait anxiety (STAI Y-2): these data show that characteristics of personality influenced the level of anxiety during stressful moments.

Study limitations include small sample size, lack of data on time of induction, and to know if there were any differences in adverse behavioural responses in the week post-discharge for each group.

In conclusion in our study we determined that PPIA + clown intervention is better to reduce anxiety in children during the preoperative period than PPIA alone or PPIA + oral Midazolam.

Considering the importance of non-pharmacological intervention in this context, it would be very interesting to study the application of different distraction techniques in order to assess which one is the most effective in different age group and cultures. Thus, in future studies it would be interesting to compare clown intervention alone with PPIA alone and with Midazolam alone, so as to determine if the presence of clowns, or parental presence, or Premedication, actually lessens the children's anxiety.

Knowing that the psychological impact of anesthesia and surgery on children covers many areas, the presence of professional clown doctors for managing the child's anxiety during the preoperative phase, should be encouraged in pediatrics hospitals. Methods for additional analyses, such as subgroup analyses and adjusted analyses -

F

Results

a

For each group, the numbers of participants who were randomly assigned, received intended treatment, and were analysed for the primary outcome For each primary and secondary outcome, results for each group, and the estimated effect size and its precision (such as 95% confidence interval)

  Trait Anxiety Inventory (STAI) self-report anxiety behavioural instrument consists of two separate 20-item subscales that measure trait (baseline) and state (situational) anxiety in adults.

  the observed anxiety level (m-YPAS) among the three groups in the waiting room [F (2,72) = 2.515; p = .005] (Tab. 3).

  itself. Without the memory of this event, subsequent inductions may indeed appear novel, distressing and frightening 21,19 . It is even likely to leave them with a pleasant memory19,20, 20,21 .

  the efficacy of clowns during the induction of anesthesia 3,5,6 , we hypothesize that the presence of clowns stimulates the children's imagination and creativity, allowing them to participate actively in the induction experience while being in a playful state, to reduce muscle tension and to improve respiration. It is likely that children establish an alliance with clowns and are thus given the opportunity to take control over their playful experience in an environment where their power is generally limited 22 . In recent times there has been an increase in the presence of clowns in pediatric hospitals: clowns in health care settings use games and laughter to provide ill children with another way to express their emotions and to provide control and social interaction during hospitalisation and treatment 22,23,24 . This is possible if the activity is carried out by professional artists having gone through careful and rigorous training programmes, both about clowning and psychology of children in hospitals. Beside, in order to be successful, the clown programme should not interfere with the work of doctors and nurses. In recent times there has been an increase in the presence of clowns in pediatric hospitals: the successful of this activity is possible if it is carried out by professional artists having gone through careful and rigorous training programmes 22,23,24 .

  parents' anxiety, we found a significant correlation between state anxiety (STAI Y-1) and trait anxiety (STAI Y-2): these data show that characteristics of personality influenced the level of anxiety during stressful moments.

3 4a 5 6a 5 Implementa 10 5 F

 355105 of information to include when reporting a randomised trial* 1a Identification as a randomised trial in the title 1 1b Structured summary of trial design, methods, results, and conclusions (for specific guidance see CONSORT for abstracts) 2 Introduction 2a Scientific background and explanation of rationale 3 Background and objectives 2b Specific objectives or hypotheses 3 Methods 3a Description of trial design (such as parallel, factorial) including allocation ratio 3-4 Trial design 3b Important changes to methods after trial commencement (such as eligibility criteria), with reasons Eligibility criteria for participants 3 Participants 4b Settings and locations where the data were collected 3 Intervention s 5 The interventions for each group with sufficient details to allow replication, including how and when they were actually administered 4-Completely defined pre-specified primary and secondary outcome measures, including how and when they were assessed 4 Outcomes 6b Any changes to trial outcomes after the trial commenced, with reasons -7a How sample size was determined 7 Sample size 7b When applicable, explanation of any interim analyses and stopping guidelines randomisation; details of any restriction (such as blocking and block sizeto implement the random allocation sequence (such as sequentially numbered containers), describing any steps taken to conceal the sequence until interventions were assigned 4-Who generated the random allocation sequence, who enrolled participants, and who assigned participants to interventions 4-If done, who was blinded after assignment to interventions (for example, participants, care providers, those assessing outcomes)

♦♦♦ 1 2 ABSTRACT

 12 Not meeting inclusion criteria (n= ) ♦ Declined to participate (n= ) ♦ Other reasons (n= ) Analysed (n=25) ♦ Excluded from analysis (give reasons) (n= ) Lost to follow-up (give reasons) (n=0) Discontinued intervention (give reasons) (n= ) Allocated to intervention (n=25) ♦ Received allocated intervention (n=25) ♦ Did not receive allocated intervention (give reasons) (n= ) Allocated to intervention (n=25) Received allocated intervention (n=25) ♦ Did not receive allocated intervention (give reasons) Received allocated intervention (n=25) ♦ Did not receive allocated intervention (give reasons) (n= ) Parental presence, clowns or sedative premedication to treat preoperative anxiety in children: what could be the most promising option? Running title: Treat preoperative anxiety in children Laura Vagnoli°, MSc, Simona Caprilli°, PhD; Andrea Messeri*, MD ° Psychologist, *Anesthesist Laura Vagnoli lauravagnoli@virgilio.it (Corrisponding author) Simona Caprilli s.caprilli@meyer.it Andrea Messeri a.messeri@meyer.Background and Objectives: A significant number of children undergo surgery experience high levels of anxiety in the presurgical period. The aim of this study is to investigate which intervention is more effective in reducing preoperative anxiety. Methods/Materials: The sample was composed of 75 subjects (ages 5-12 years) who had to undergo minor day-surgery. Children were randomly assigned to: the Clowns group (N = 25), accompanied to the preoperative room by the clowns and by a parent; Premedication group (N=25) premedicated with oral Midazolam and accompanied to the preoperative room by one parent; or the Control group (N = 25) only accompanied by one parent. Anxiety in the preoperative period was measured by using the Modified Yale Preoperative Anxiety Scale (m-YPAS). Parental anxiety was measured by using the State-Trait Anxiety Inventory (STAI Y-1/Y-2).

Florence(

  Italy), and of their parents. We considered only Italian children as being eligible so as to avoid any misinterpretation of the evaluation instruments used.The sample examined was composed of 75 randomly assigned consecutive children aged 5 to 12, residents in Florence or in the close surroundings of the city. Children with a history of chronic illness, premature birth, developmental delay or previous anaesthetic experience were excluded

  using a standardized oxygen (O 2 )/nitrous oxide(N 2 O)/sevoflurane technique.

6 The

 6 State-Trait Anxiety Inventory (STAI) self-report anxiety behavioural instrument consists of two separate 20-item subscales that measure trait (baseline) and state (situational) anxiety in adults.

  the observed anxiety level (m-YPAS) among the three groups in the waiting room [F (2,72) = 2.515; p = .005] (Tab. 3).

  the level of anxiety in the two rooms in children who were accompanied by clowns.

5 6a 5 Implementa 10 5 F

 55105 for each group with sufficient details to allow replication, including how and when they were actually administered 4-Completely defined pre-specified primary and secondary outcome measures, including how and when they were assessed 4 Outcomes 6b Any changes to trial outcomes after the trial commenced, with reasons -7a How sample size was determined 7 Sample size 7b When applicable, explanation of any interim analyses and stopping guidelines randomisation; details of any restriction (such as blocking and block sizeto implement the random allocation sequence (such as sequentially numbered containers), describing any steps taken to conceal the sequence until interventions were assigned 4-Who generated the random allocation sequence, who enrolled participants, and who assigned participants to interventions4-If done, who was blinded after assignment to interventions (for example, participants, care providers, those assessing outcomes)

♦♦♦

  Not meeting inclusion criteria (n= ) ♦ Declined to participate (n= ) ♦ Other reasons (n= ) Analysed (n=25) Excluded from analysis (give reasons) (n= ) Lost to follow-up (give reasons) (n=0) Discontinued intervention (give reasons) (n= ) Allocated to intervention (n=25) ♦ Received allocated intervention (n=25) ♦ Did not receive allocated intervention (give reasons) (n= ) Allocated to intervention (n=25) ♦ Received allocated intervention (n=25) ♦ Did not receive allocated intervention (give reasons) Received allocated intervention (n=25) ♦ Did not receive allocated intervention (give reasons) (n= )

Table 3

 3 We strongly recommend reading this statement in conjunction with the CONSORT 2010 Explanation and Elaboration for important clarifications on all the items. If relevant, we also recommend reading CONSORT extensions for cluster randomised trials, non-inferiority and equivalence trials, non-pharmacological treatments, herbal interventions, and pragmatic trials. Additional extensions are forthcoming: for those and for up to date references relevant to this checklist, see www.consort-statement.org

	Outcomes
	and
	estimation	17	For binary outcomes, presentation of both absolute and relative effect	-
		b	sizes is recommended
	Ancillary	18 Results of any other analyses performed, including subgroup analyses	7-8
	analyses		and adjusted analyses, distinguishing pre-specified from exploratory
	Harms	19 All important harms or unintended effects in each group (for specific guidance	-
			see CONSORT for harms)
	Discussion
	Limitations	20 Trial limitations, addressing sources of potential bias, imprecision, and, if	13
			relevant, multiplicity of analyses
	Generalisab	21 Generalisability (external validity, applicability) of the trial findings	13
	ility
	Interpretatio	22 Interpretation consistent with results, balancing benefits and harms, and	13
	n		considering other relevant evidence
	Other information
	Registration 23 Registration number and name of trial registry	-
	Protocol	24 Where the full trial protocol can be accessed, if available	-
	Funding	25 Sources of funding and other support (such as supply of drugs), role of	-
			funders

*

Table 1 -

 1 2 Numbers analysed16 For each group, number of participants (denominator) included in each analysis and whether the analysis was by original assigned groups

	7

Table 3

 3 We strongly recommend reading this statement in conjunction with the CONSORT 2010 Explanation and Elaboration for important clarifications on all the items. If relevant, we also recommend reading CONSORT extensions for cluster randomised trials, non-inferiority and equivalence trials, non-pharmacological treatments, herbal interventions, and pragmatic trials. Additional extensions are forthcoming: for those and for up to date references relevant to this checklist, see www.consort-statement.org

	Outcomes
	and
	estimation	17	For binary outcomes, presentation of both absolute and relative effect	-
		b	sizes is recommended
	Ancillary	18 Results of any other analyses performed, including subgroup analyses	7-8
	analyses		and adjusted analyses, distinguishing pre-specified from exploratory
	Harms	19 All important harms or unintended effects in each group (for specific guidance	-
			see CONSORT for harms)
	Discussion
	Limitations	20 Trial limitations, addressing sources of potential bias, imprecision, and, if	13
			relevant, multiplicity of analyses
	Generalisab	21 Generalisability (external validity, applicability) of the trial findings	13
	ility
	Interpretatio	22 Interpretation consistent with results, balancing benefits and harms, and	13
	n		considering other relevant evidence
	Other information
	Registration 23 Registration number and name of trial registry	-
	Protocol	24 Where the full trial protocol can be accessed, if available	-
	Funding	25 Sources of funding and other support (such as supply of drugs), role of	-
			funders

*

TABLE 1 .

 1 Surgical Procedures in the 3 Groups Clown Group n (%) (N = 25)

We thank the Anna Meyer Foundation, which supporting "Clown in Corsia" project; the clowns of Soccorso Clown ONLUS who work in A. Meyer Children's Hospital, Florence, Italy.

E) ACKNOWLEDGEMENTS

We thank the Anna Meyer Foundation, which supporting "Clown in Corsia" project; the clowns of Soccorso Clown ONLUS who work in A. Meyer Children's Hospital, Florence, Italy.


Agent programming and adaptive serious games: A survey of the state of the art

Keywords: A.1 [Introductory and survey] Design, Human Factors Adaptive serious game, agents, state of the art

This paper provides a survey of software agents in adaptive serious games. It outlines the most important challenges of the game design such as adaptation. The study (i) overviews the state of the art of behavior programming in agent-based games (ii) provides our further reflection about the agent programming model dedicated to therapeutic serious game (iii) and finally introduces some major challenges to be addressed by the community in the medium term.

INTRODUCTION

Serious games are currently attracting the interest of researchers and professionals in various fields such as education, health, vocational training, governance and defense.

Currently, there is no formally accepted definition of serious games. However, one can state that serious games are commonly based on a fundamental principle which is reflected by taking into account simultaneously and consistently: (i) serious aspects that determine the pedagogical objectives such as the transmission and/or acquisition of knowledge, know-how, or information; (ii) and fun aspects, which focus on the motivation and the management of end users' frustration. In the rest of the paper, we will refer to end users as players-learners.

The answer concerning players-learners motivation has been analyzed by research works from different angles:

-The use of appropriate and attractive human-machine interfaces in order to facilitate the acceptance of player-learners. This implies, for instance the choice between visual and auditory interaction modalities, display frequency and the level of graphics rendering details in the game e.g [START_REF] Neerincx | Attuning speech-enabled interfaces to user and context for inclusive design: technology, methodology and practice[END_REF].

-The use of general principles and good practices of game design in order to create an immersion or a flow as described by Czikszentmihalyi [START_REF] Csikszentmihalyi | Flow: The Psychology of Optimal Experience[END_REF].

-Allow a dynamic adaptation of the serious game in order to individualize and contextualize the game experience for each player e.g [START_REF] Ram | Artificial intelligence for adaptive computer games[END_REF] We focus in this paper on the last two points. We are interested, particularly in review of works that exploit the advantages of agent-oriented programming to design adaptive serious games. In fact, we study the behavioral programming of software agents that can adapt a serious game according to pedagogical objectives and observed skills of the player-learner. This paper is organized as follows: we describe in the second section our motivation, identify the challenges we may confront during the design process of an adaptive game. We also discuss the use of agent-based approach to overcome these challenges. The following section aims to describe the main approaches of behavior modeling in agent-based game. We present in the fourth section the state of art of behavior programming in agent-based game. Finally, we conclude this paper by: (i) analyzing and discussing these works (ii) and describing our outlook concerning agents programming dedicated to therapeutic serious games.

MOTIVATIONS

We are interested in this paper in adaptation problem in serious games. In this context, we focus on the agent approach as a means of behavioral modeling and programming of adaptive games.

Thus, the objective of this paper is to describe the main work on behavioral programming in adaptive agent-based games. The purpose of this section is to: (i) specify the challenges posed by adaptive games and their influence on the behavioral programming process (ii) and discuss why an agent-based approach may be effective in this context.

Adaptive game design challenges

Among the challenges that may be confronted in the design process of an adaptive game, we can mention:

(i) Taking into account the assessment of players' capacity and skills during the game session. This challenge is also due to the heterogeneity of players who can be for example children, students, elderly people or patients with disabilities. We are interested in systems that rely on a game design process which is centered on the user (or player-centered game design) [START_REF] Sykes | Player-centred game design[END_REF]. In this case, the game must have adaptive behaviors to cognitive and motor skills of users and to their performances in the game.

(ii) Compliance to real-time constraints. Time constraints occur at various stages such as the computing of game entities behaviors, the control and adaptation overhead. These elements can deeply affect the game performance in terms of response time and interaction quality.

(iii) Creating a flow or an immersion in the game. The goal is to introduce the elements allowing involvement of the player in the game world. The aim is to keep his motivation and commitment during the game experience. This has been inspired from works on game flow and immersion [10] [6].

According to our vision concerning the case of serious games, immersion can be verified by responding to control process challenges which concern: (i) the game environment including the management of its interactions with the user (ii) and the virtual game world that includes the control of its entities such as the virtual characters. We can mention in this case the management of:

-Difficulty level in the game: The difficulty level should be adapted to the player progression and to the game experience goals.

-Feedback: the game must respond in a coherent and intelligible manner to the players' actions. We can cite for examples: encouragement messages, congratulations after success and help after failure or obstruction.

-Playability: we mean by playability the conditions that the system must check in order to satisfy the usability of the game. We can cite for example: an easy game interface to use, graphics and sound management, and anticipation of illusion that the system gives the choice to the player of his next state in the game.

Why an agent-based approach?

The realization of adaptive serious games can be achieved through an agent approach. As a matter of fact, the idea of using agent concept is not new in itself, as it has already been used in: (i) games based on artificial intelligence (or Game AI) [START_REF] Miikkulainen | Computational intelligence: principles and practice[END_REF] [40] (ii) and simulation systems and game-based virtual reality [START_REF] Silverman | Human Behavior Models for Agents in Simulators and Games: Part I: Enabling Science with PMFserv[END_REF].

In the first category, we can refer also to the use of agent concept in commercial games such as Half-Life2 [17] (for more discussion see [START_REF] Fairclough | Research directions for AI in computer games[END_REF]) Civilization IV [START_REF]Official site[END_REF] (for analysis see [START_REF] Amato | High-level Reinforcement Learning in Strategy Games[END_REF]) and Black & White [START_REF] Black | Official site[END_REF] (for a discussion see [START_REF] Wexler | Artificial Intelligence in Games: A look at the smarts behind Lionhead Studio's "Black and White" and where it can go and will go in the future[END_REF]). These games use agents to model virtual characters with intelligent behaviors.

The second category of works deals with the concept of virtual fidelity. In these virtual reality systems, the agent concept is used to model the virtual character representing the user in the game (human-like character) eg. [START_REF] Perlin | Improv: A System for Scripting Interactive Actors in Virtual Worlds[END_REF]. The agent must therefore have the same behavior as a user. In this case, the representation of the system behavior and its states is closely related to users' behavior. We focus in our analysis on the adaptation of game behavior that is related to the first category of these works.

In general, the design of agent-based adaptive games allows:

-A simple game structure: games often use software entities or virtual characters of the game world, such as PCs (Player Character) or NPCs (Non Player Character), as individualities that have a decision process.

-Facilitate management and control process in the game environment: the use of agent-based approach allows the distribution of control in the game.

-Overcome the most challenges in the management of real-time interactions, notifications and events in the game. This can be realized by exploiting the software agents' properties such as autonomy, reactivity and pro-activity, and by using agents that have a limited cycle of execution in the game session.

-Deals with the adaptation challenge in the context of serious games. This can be achieved by benefiting from the expressive and flexible decision-making models. These models are used to customize and contextualize the behavior of each game entity.

MODELING BEHAVIOR IN AN AGENT-BASED GAME

The purpose of this section is to describe the main approaches used to model the behavior of game characters so-called "agents". The used characters are usually the NPCs ones.

We can bring out two categories of works that concern behavior modeling in agent-based games. The first category deals with path finding [START_REF] Yue | The state of the art in game AI standardization[END_REF] so-called 'navigation' in game's virtual world. This category is based on artificial intelligence algorithms in order to plan paths of virtual characters in the game. We can cite for instance the A* algorithm [START_REF] Stout | Smart Moves: Intelligent Path Finding[END_REF] and real-time path planning algorithms such as RTA-RG [START_REF] Hernandez | LRTA*[END_REF].

We focus in our study on the second category. This latter refers to the main behavior modeling approaches of games and its entities. These works are usually based on Finite State Machines (FSM), rule-based systems, Goal-Oriented Action Planning (GOAP) and Machine Learning (ML) approach.

Finite state machines (FSM)

This approach uses a graph which has a finite number of states in order to model game entities behavior [START_REF] Fu | The ultimate guide to fsms in games[END_REF]. Each node in the graph represents a specific context for the virtual character, and the transitions between the states provide the conditions that are used to switch the behavior from one state to another.

FSM is considered as a traditional and a simple means to be used during the design process of a video game. For instance, FSMs have been already used in video games such as Age of Empires [START_REF] Goodman | Age of empires, developed by Ensemble Studios[END_REF].

Using FSM requires a prior planning of all game states by the programmer. This technique is therefore expensive in terms of game development and gives a limitation to the possible behaviors that a game should include.

Rule-based system

In this approach, the state of NPC depends on the rules that have been associated to it. This model has been proposed to facilitate the control of NPCs in complex games such as RPGs (Role-Playing Game). We can refer for instance to [START_REF] Christian | A simple inference engine for a rulebased architecture[END_REF] and [START_REF] Spronck | Online Adaptation of Game Opponent AI with Dynamic Scripting[END_REF] works. Behavior programming of the game-world entities was often performed via XML scripts. These scripts contain all events that reflect the NPC behavior at a given time. For instance, Baldur's Gate [START_REF] Bioware | Baldur's Gate[END_REF] and Virtual Fighter 2 [START_REF] Suzuki | Virtua fighter 2. Developed and published by Sega[END_REF] games use the rules-based systems approach. In these systems, rules are used to control the NPCs' behavior.

As in the case of FSM, prior planning of all game rules should only cover some behaviors expected during the game design phase without incorporating other behaviors. Introducing a new behavior to the system or a simple change in its rules may require a global checking of rules consistency to avoid conflicts among rules and behaviors.

Goal-oriented action planning (GOAP)

In this model, the graph nodes are considered as goals that are planned for a virtual character. Each character chooses its behavior according to its current goal. These goals are dynamically determined during the game session [START_REF] Orkin | Symbolic representation of game world state: Toward real-time planning in games[END_REF]. Among the first games that have used this approach, one can mention FEAR that is a first-person shooter game [START_REF] Hubbard | .r. first encounter assault recon, developed by Monolith Productions[END_REF]. [START_REF] Gordon | A goal processing architecture for game agents[END_REF] is another work that uses this model for an agent-based game architecture using dynamic generation of game goals. Agents in this architecture use a teleo-reactive program--composed of a set of pairs (actions, conditions)--, to determine or calculate their plans.

However, the real-time planning of agents' behavior requires a significant processing time. This can influence the performance of the game in terms of responsiveness time [START_REF] Yue | The state of the art in game AI standardization[END_REF].

Machine learning (ML)

Machine Learning gained the interest of many academic game projects on and commercial video games [START_REF] Stanley | Real-time evolution of neural networks in the NERO video game[END_REF] [23] [START_REF] Amato | High-level Reinforcement Learning in Strategy Games[END_REF]. These studies aims at creating game worlds that are composed of virtual characters that behave in an intelligent and adaptable manner. This can be realized using artificial intelligence algorithms. This approach consists in applying learning algorithms to model and calculate the behavior of agents. In this case, agents represent usually adversary characters of the game world. We can mention as an example of works that use this approach, the techniques of artificial neural networks (or Neuronal Networks: NN), evolutionary algorithms [START_REF] Eiben | Evolutionary Computing Tutorial Part 1: What is an Evolutionary Algorithm?[END_REF] and the reinforcement learning algorithms (or RL). This implies, for example the works of [START_REF] Tan | Personality-based Adaptation for Teamwork in Game Agents[END_REF] and [START_REF] Amato | High-level Reinforcement Learning in Strategy Games[END_REF]. These works are often based on the classical modeling aspect of game's virtual characters, and use dynamic programming of the agents' mental state to describe their reasoning.

SURVEY OF BEHAVIOR PROGRAMMING IN ADAPTIVE AGENT-BASED GAME

In this section we discuss the problem of designing adaptive agent-based games. A system is adaptive when it is able to change its behavior or the behavior of its entities, in response to certain number of well identified events [START_REF] Andresen | Seeking Optimal IT Strategies by the Determination of Adaptability in Domain-Specific Software Applications[END_REF]. In the case of games, the system can be adapted by modifying: (i) the behavior of PCs or NPCs in the virtual game world (ii) and the game environment and its various interactions with the player [START_REF] Ram | Artificial intelligence for adaptive computer games[END_REF]. Therefore, we are interested in this section in the principal works that deal with these two points. Our main goal is to study the manner through which the agent approach has been exploited to adapt the game behavior.

Analysis criteria

In order to analyze the works using agents to adapt the game behavior, we propose an evaluation framework that contains the following analysis criteria:

-Adaptation perimeter that can be: (i) Game agents: This consists in checking whether the adaptation concerns the virtual characters behavior in the game world.

(ii) Game environment: In this case the aim is to adapt global game's parameter such as objectives and quests, speed, enemies' appearance intervals, game rules and so on.

-Adaptation parameter: The user parameter that can be used by the adaptation process which can be:

(i) User performance: the player performance can be determined for instance by his score, success or failure rate and time to complete some tasks in the game.

(ii) User ability: This means that the adaptation process takes into account the cognitive and motor skills of the player.

-In-line/off-line adaptation: This criterion specifies whether the adaptation process is performed during the game session (or inline mode) or outside it (or offline mode). In the case of off-line adaptation, the management of the game state is carried out in an implicit manner i,e game behavior is pre-planned by the game programmer. However, in the case of in-line adaptation, the game state is determined during the game session and the behavior depends on this new state. -Game's behavior modeling: This criterion specifies the modeling approach which is used in the game design process.

-Single/multi player adaptation: In this case we specify whether the agent approach also takes into account the adaptation of the players' collective behavior.

-Adaptation of individual /collective behavior: This criterion specifies whether the adaptation process takes into account the adaptation of individual and/or collective behavior of game agents.

-Open-loop/closed-loop system: The system uses an open-loop controller (or non-feedback controller) when it does not use a feedback or return to determine whether its results (or outputs) have been accomplished. This system focuses on time factor because it supposes fast treatments that do not take into account errors' handling. However, in the case of closed-loop controller, feedback is used to ensure the adaptation control. This can be realized for instance through a decision tree or a learning algorithm.

Presentation of the state of the art

In this section we describe the main works on behavior programming of adaptive games that are based on an agent approach. [START_REF] Tan | Personality-based Adaptation for Teamwork in Game Agents[END_REF] This work is based on a player-centered game design. It proposes an agent-oriented framework implemented in the Truevision3D 6.2 game engine. The action scenario is built on a zombie's game. In this game, the player is represented by an avatar that possesses some weapons. The goal of this latter is to kill all the zombies in the game world.

Adaptive behavior programming using personality-based adaptation technique

In this work, game's behavior is programmed using a personality adaptation module encapsulated in a reinforcement learning framework. The parameter used for adaptation is the performance of the user in successive game sessions. The adaptation perimeter in this case is the virtual character so-called agent. This agent must be in compliance with the individual style and strategies of each player through the game session (i,e in-line mode). Each new personality of the player-character (PC) depends on the other personalities that have been created before.

This work uses a behavior's modeling based on the agents' goals GOAP [START_REF] Orkin | Symbolic representation of game world state: Toward real-time planning in games[END_REF]. The proposed game uses also a rule-based system to determine these NPCs' behavior. In addition, the learning process used by the framework is based on a reinforcement learning algorithm (RL [START_REF] Sutton | Reinforcement Learning: An Introduction[END_REF]). Therefore, this allows each agent to determine its personality according to the existing ones.

The control system used is closed-loop. In fact, the game loop starts with the execution of the adaptation process. During this process, each agent that has its own adaptation module activates this latter to generate its personality in the game. This module uses a neural network algorithm (NN). Indeed, the system calculates the new weights of the NN to generate new parameters in order to create the agent's personality. This is realized while taking into account the errors diffused by the execution module in the game. After this reinforced learning, the personality of the character can be created. This work is based on adapting the collective behavior of agents. It applies the same behavior policy for the entire agents during the game session. Agents in this framework represent virtual characters that have a low autonomy and social ability. An improvement of this Framework has been proposed in [START_REF] Tan | A combined tactical and strategic hierarchical learning framework in multi-agent games[END_REF]. Their contribution is to introduce tactics and strategy concepts during the generation of characters' personalities. In addition, they use the concept of multi-agent systems to incorporate social ability to agents in game.

Finally, we can note that the adaptation in this work concerns only the case of single player. [START_REF] Ram | Artificial intelligence for adaptive computer games[END_REF] In this work, the adaptation of game's behavior is founded on a case based reasoning algorithm (or CBR). The game's behavior is based on a prior planning of all possible game actions (or goaloriented action planning). In addition, behavior modification is related to the different cases that are anticipated in the game design steps.

Adaptive behavior programming using casebased reasoning

The adaptation perimeter in this work concerns the game environment. It is about the adaptation of the game experience that depends on the players' style and performance through a user model.

The behavior transformation is performed via specific system architecture of the game. This architecture contains two layers: a reactive one that allows the management of real-time interactions, and the other one is the reasoning layer to manage the virtual characters' states.

In the reactive layer, the developer uses a behavior programming language ABL (Adaptive Behavior Language) based on a reinforcement learning algorithm [START_REF] Mateas | Life-like Characters. Tools, Affective Functions and Applications[END_REF]. This language is based on the partial programming. This is a programming paradigm that assumes that the programmer must only specify some behaviors of the system and give the task to its execution module to create other more complex behaviors. The control system used is the open-loop one. The character or the agent in ABL is composed of a behaviors' library. The purpose of the use of this language is to create at the reactive layer credible and reactive agents.

The reasoning layer is responsible for behavioral adaptation. Changing behavior of the characters is based on an emotional user-model.

The adaptation is realized in off-line mode. The management of the game state is performed in an implicit manner as it implies the pre-planning of the game's actions.

Finally, this work did not address the case of multiplayer adaptation. It implies a process of user-centered game design and use reactive agents in order to satisfy the real-time requirement in the game. [START_REF] Stanley | Real-time evolution of neural networks in the NERO video game[END_REF] This work is part of the Nero video game research project. This project proposed a machine learning based on an artificial intelligence algorithm called Neuroevolution [START_REF] Miikkulainen | Computational intelligence: principles and practice[END_REF]. This technique was originally used by the agent simulation work in robotics field.

Adaptive behavior programming using neuronal networks

The adaptation perimeter concerns agents that adapt the game by learning from user actions during the game experience. NERO game uses the same adaptation policy, through the learning algorithm, for all game's agents. This is done while taking into account the user's performance as an adaptation parameter.

Behavior modeling is based on a ML approach that uses a neural network (NN, Neural Network). It applies rtNEAT learning method (realtime NeuroEvolution of Augmenting Topology, NEAT) [START_REF] Stanley | Real-time evolution of neural networks in the NERO video game[END_REF] which is invented under the Nero project.

The system controller is closed-loop as it uses a machine learning based on NEAT or neuroevolution method. The latter is based on the complexification of the neural network by adding nodes and connections to create complex behaviors for agents during the game session.

Adaptation in this case is in-line and involves the modification of agents' behavior and its base knowledge during the game session.

Finally, the proposed adaptive behavior programming technique is intended for games and simulation environments that deal with the single user adaptation.

Adaptive behavior programming based on evolutionary algorithm [3]

This work is introduced in the context of games which are based on virtual opponents' team (Team-oriented games). In these games, the adaptation concerns the behavior of the groups of virtual characters (or NPCs groups). TEAM (Team-Oriented Evolutionary, Adaptability Mechanism) defined in this work, uses an evolutionary learning algorithm. The agents' learning process is realized through the cooperation of evolutionary algorithms of each NPC that belong to the same opponents' group. Thus, the adaptation perimeter concerns virtual characters of the game world.

Adaptation parameter in the case of programming TEAM agents is also the player's performance. In addition, the control system used is open-loop as it does not control the generated agent team's behavior.

Agents' behaviors are programmed using the action planification based on an evolutionary algorithm. Moreover, a finite state machine is implemented as a modeling technique for each agent group behaviors. For each state in the FSM, representing the behavior of the agents that belong to the opponents' team, an evolutionary algorithm is associated. The goal of each algorithm is to develop or learn new behaviors of the opponent group for a given state. This work deals with the adaptation of collective agents' behavior intended for the real-time strategy games, it provides a single player adaptation process.

The experimentation of this work use Quake III commercial game [START_REF] Quake | Official site[END_REF] in order to develop new tactics of the game. Finally, we note that the adaptation is used in off-line mode. [START_REF] Amato | High-level Reinforcement Learning in Strategy Games[END_REF] This work introduces an agent-based adaptation dedicated to the popular Civilization [START_REF]Official site[END_REF] strategy game. In this game the player should build cities and then defend them while forming an army in the game virtual world. The idea is to integrate a dynamic generation of strategies through a learning algorithm.

Adaptive behavior programming using a reinforcement learning algorithm

The adaptation parameter, used to generate the new strategy during the game session, is the player's performance and style. Thus, adaptation in this case is performed in in-line mode.

The adaptation perimeter in question is the game agents. This concerns the adaptation of these agents' individual and collective behavior. Indeed, agents represent the NPCs in the game and only one of them resonates using a reinforcement learning algorithm (or RL: Reinforcement Learning). In fact, it determines strategies through the Q-learning algorithm [START_REF] Watkins | Q-learning[END_REF]. The control system is closed-loop because the feedback is used by the machine learning in order to compute new strategies in the game.

The RL-based agent is used in this work in order to provide adaptive behaviors. The modeling agents' behavior use a stochastic process represented by a hidden Markov automaton (or Markov chain). The behavior is based on the dynamic programming of the agents' mental state which is deduced from the reasoning of RL-agent.

Finally, we note that this technique has only treated the case of adaptation to individual user behavior (or single-player adaptation). [START_REF] Kim | Constructing a BDI Agent to Deploy in an Interactive Computer Game Environment[END_REF] This work uses the theory of mind for agent's behavior programming. In this type of work, adapting behavior of agents is based on the description of the agents' mental state. The experiment uses an agent called KGBot which is realized via a game simulation environment of UT (Epic's Unreal Tournament) [START_REF] Gerstmann | Unreal Tournament: Action Game of the Year[END_REF].

Adaptive behavior programming based on theory of mind

Adaptation in this case concerns the player avatar (or agent PC). This system communicates the game UT via a module allowing the control of the characters in the game world.

Modeling behavior defined in this work focuses on a GOAP approach. The internal state of the agent KGBot was realized using the BDI model which is base on the description of beliefs, goals and intentions of the agent game. The implementation of the internal state of KGBot uses, for its decision-making process, the BDI-agent engine called UM-PRS [START_REF] Jaeho | UM-PRS: An Implementation of The Procedural Reasoning System for Multirobot Applications[END_REF] and the real-time path planning algorithm RTA-RG [START_REF] Hernandez | LRTA*[END_REF].In fact, UM-PRS is a system based on traditional goal-directed reasoning and a reactive behavior. The control system is open-loop; agents do not use their feedback in order to determine their actions in the game.

The adaptation is performed in in-line mode. This means that the management of the state of the game depends on the real-time planning of agents' behaviors. Moreover, this work is based on the adaptation of collective agents' behavior as it requires behavior modification of KGBot agent. Finally, this work was also intended for single-player adaptation.

Adaptive behavior programming based on usermodel [9]

Various researches have been aborted on the adaptation of game behaviors by introducing system architectures that are based on a user model. Among these studies we choose to describe [START_REF] Conati | Evaluating Adaptive Feedback in an Educational Computer Game[END_REF] work. This work is based on designing an educational game called Prime/Climb. This is a game where the player should pass certain obstacles during his ascent of a mountain and the game offer him a contextualized help. The goal of adaptation is to generate appropriate feedback to the player's learning situation during the game session (or in-line mode). The adaptation parameter is the player performance. Programming behaviors in this case is based on a learning model. This latter allows the planning of the various system behaviors associated to a learner during the game experience.

The adaptation perimeter concerns agents that adapt their behavior according to the interactions' result and player progression in the game. Indeed, the game proposed represent the help associated to the player using a software entity called a pedagogical agent. Adaptation technique is based on behavioral programming of pedagogical agent in the game.

Behavior modeling is based on GOAP. In fact, these plans will be used by software agents to adapt the user's feedback.

Finally, the game uses an open-loop controller system. It uses a single agent in order to adapt the assistance to the user in a singleplayer game context. Table 1 gives an overview about the analysis of the principal works discussed in this paper. This analysis is based on the evaluation framework proposed before:

Adaptation parameter

According to Table 1, we deduce that the adaptation parameter in the reviewed works concerns either (i): the entities or virtual characters that represent usually the NPCs [START_REF] Bakkes | Team: The team-oriented evolutionary adaptability mechanism[END_REF] and the player's avatars in some cases [START_REF] Kim | Constructing a BDI Agent to Deploy in an Interactive Computer Game Environment[END_REF]. This can be performed through a dynamic change of their behavior in the game [START_REF] Stanley | Real-time evolution of neural networks in the NERO video game[END_REF] [9] (ii) or only the game environment without taking into account the behavior of its virtual characters [START_REF] Ram | Artificial intelligence for adaptive computer games[END_REF]. However, we note a lack of the techniques that deals with the two perimeters at once. In fact, we bring out on the basis of this analysis two axis of works: (i) the first one focuses on the adaptation of virtual characters' behavior, generally called agent game, which is analyzed in the context of game AI. In this case we distinguish between works that use a learning process or an agent based-reasoning [START_REF] Stanley | Real-time evolution of neural networks in the NERO video game[END_REF] [START_REF] Ram | Artificial intelligence for adaptive computer games[END_REF] [1], and works using agent communication [3] [36].

(ii) the second axis focuses on the adaptation which is based on a user-centered game design. It uses the player model and/or his profile in order to adapt the game's behavior. We also find in this axis works deals with educational games that are based on learners' models [START_REF] Conati | Evaluating Adaptive Feedback in an Educational Computer Game[END_REF]. However, in the context of serious games both perimeters may be involved. Adaptation in this case must be introduced at game design level. This requires: (i) taking into account the players-learners' actions (ii) and the control of the game environment and its components including the virtual characters of the game world.

Behavior modeling

Behavior modeling used in game design is usually focused on the prior planning of the game behavior. We can mention for instance, the use of FSM or rule-based systems [START_REF] Bakkes | Team: The team-oriented evolutionary adaptability mechanism[END_REF]. This implies the determination of all possible game actions before its realization. Some works such as [START_REF] Stanley | Real-time evolution of neural networks in the NERO video game[END_REF] [21] use machine learning or theory of mind concepts. These models assume that the agent: (i) may possess new states or unanticipated behavior that is usually not controlled by the system (ii) and has not a time-bounded execution cycles. This can affect the processing time and the game responsiveness. In addition, in the case of serious games, a new generated agent behavior, which is not controlled by the system, can have an undesirable effect on the player's motivation or on his training programs.

Adaptation of individual /collective behavior

The game adaptation in most works acts generally on the collective behavior of agents [START_REF] Amato | High-level Reinforcement Learning in Strategy Games[END_REF] [36] [START_REF] Tan | A combined tactical and strategic hierarchical learning framework in multi-agent games[END_REF].

In-line/off-line adaptation

The adaptation technique is commonly used during the game session (i,e in-line adaptation) [START_REF] Kim | Constructing a BDI Agent to Deploy in an Interactive Computer Game Environment[END_REF] [31] [START_REF] Tan | Personality-based Adaptation for Teamwork in Game Agents[END_REF], and sometimes outside it (i,e off-line adaptation) [3] [28]. However, this may have an impact on the system's or the agent's responsiveness in the game. This can depend on the processing and reasoning time during the game session.

Open/closed-loop system

The game's state management is related to the behavioral modeling technique used during the game design. We use an open-loop controller system [START_REF] Kim | Constructing a BDI Agent to Deploy in an Interactive Computer Game Environment[END_REF] [3] when we have a pre-planned behavior. In contrast, in closed-loop systems [START_REF] Amato | High-level Reinforcement Learning in Strategy Games[END_REF] [31], the agent uses its feedback to determine its future states or to learn from its experience [START_REF] Stanley | Real-time evolution of neural networks in the NERO video game[END_REF]. This learning process can be fulfilled through machine learning or communication between agents [1] [36].

The use of closed-loop system through agent programming allows to the agent to learn from its previous experiences during the serious game session.

Parameter adaptation, mono / multi player adaptation

Finally, we can also deduce that the behavioral adaptation of agent-based games concerns only the individual player's behavior (i.e single-player adaptation). Moreover, the adaptation technique in these works use only players' performance as an adaptation parameter without taking into account the user's cognitive and motor abilities and his motivations.

In addition, in the case of serious games, some challenges such as the heterogeneity of users (eg. in terms of age, skills training, and health) and the training programs diversity, should be taken into account while adapting the game behavior.

DISCUSSION

Adaptation can play an important role in proving the effectiveness of serious games in various fields such as in the therapy context. The question of acceptance and effectiveness of these games is subject to the possibility of involving player in his training program via the game. This can be performed through the realization of games that can be adapted to the player needs, preferences and cognitive and motor abilities. In addition, the introduction of collaborative and social aspects in the game can also have a positive effect on the motivation of players-learners.

In order to meet these constraints during the design process of adaptive games, we have proposed in this paper to study the state of the art of behavioral programming in adaptive game context. This study which is based on an agent approach, seeks to answer to the key issues concerning the design of adaptive serious games.

As a perspective, we hope to develop this work by specifying an agent programming model dedicated to collaborative therapeutic games. The aim is to overcome most game design challenges which have been discussed in this paper.

The desired programming model should be reusable and flexible. In fact, it should be appropriate for different types and genres of therapeutic serious games. The aim is to reduce the cost of developing such games. In addition, the model should take into account the maintaining of responsiveness and process time performed by the adaptation process, using a time-bounded game agent. This is the purpose of guaranteeing the performance and service quality of the game.

CONCLUSION

This paper presented and analyzed the principal works that deals with behavioral programming in agent-based adaptive games. The analysis of the state of the art shows that the adaptation process is generally based on the player's performance and style. However, in the case of serious games, taking into consideration the user's cognitive and motor ability as well as his preferences may be important as it affects his motivation and consequently the usability and the effectiveness of the serious game.

Moreover, these studies deal only with the adaptation of individual behavior in a context of single-player game. Indeed, adaptation in a multi-player context raises important challenges such as managing the consistency of players-learners' views of the game. Thus, this leads us to identify the development of adaptive multiplayer serious games as a major challenge to be addressed by the community in the medium term.

Analysis