Julie Vallée

Emmanuelle Cadot

Francesca Grillo

Isabelle Parizot

Pierre Chauvin

The combined effects of activity space and neighbourhood of residence on participation in preventive health-care activities. The case of cervical screening in the Paris metropolitan area (France)

Keywords: activity space, daily mobility, neighbourhood of residence, cross-level interaction, preventive health care significant (p>0.05)

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The combined effects of activity space and neighbourhood of residence on participation in preventive health-care activities: The case of cervical screening in the Paris metropolitan area (France).

Background

Daily mobility, determined by observing people's routine "activity space", is arousing a great deal of interest in the social sciences in the tradition of time geography, as originally developed by [START_REF] Hägerstrand | Innovation diffusion as a spatial process[END_REF][START_REF] Hägerstrand | What about people in regional science[END_REF]. Activity space may be defined as the space within which people move about or travel in the course of their daily activities. Various measures of activity space have been used in time geography to identify social differences in people's access to opportunities [START_REF] Golledge | Spatial Behaviour -A geographic perspective[END_REF], in particular, access to health-care facilities [START_REF] Arcury | The Effects of Geography and Spatial Behavior on Health Care Utilization among the Residents of a Rural Region[END_REF][START_REF] Nemet | Distance and health care utilization among the rural elderly[END_REF][START_REF] Sherman | A suite of methods for representing activity space in a healthcare accessibility study[END_REF]. In addition to the conventional notion of distance (e.g., the spatial separation between a patient's residence and his/her care provider's office), activity space is considered in these studies an "enabling" factor for health services utilization, as per Andersen's health behaviour model [START_REF] Andersen | Revisiting the Behavioral Model and Access to Medical Care: Does It Matter?[END_REF].

Historically, activity space has been operationalized using the standard deviational ellipse of the locations of regular activities [START_REF] Lefever | Measuring geographic concentration by means of the standard deviational ellipse[END_REF][START_REF] Yuill | The standard deviational ellipse: an updated tool for spatial description[END_REF]. This ellipse was used to compare daily activity space and health-care seeking spaces [START_REF] Cromley | Locating ambulatory medical care facilities for the elderly[END_REF][START_REF] Gesler | Locational and population factors in health care-seeking behavior in Savannah, Georgia[END_REF][START_REF] Shannon | The search for medical care: an exploration of urban black behavior[END_REF]. More recently, geographers implemented daily travel datasets in geographical information systems (GIS) to represent an individual's activity space in three dimensions (with two axes specifying the location on the Earth's surface and the third, a time axis) as a space-time aquarium [START_REF] Kwan | Gender and Individual Access to Urban Opportunities:A Study Using Space-Time Measures[END_REF][START_REF] Kwan | Geovisualization of Human Activity Patterns Using 3D GIS: A Time-Geographic Approach[END_REF]. This geovisualization of human activity patterns has been used to study exposure to infectious disease transmission [START_REF] Löytönen | GIS, Time Geography and Health[END_REF][START_REF] Schaerstrom | Pathogenic Paths? a Time Geographical Approach to Medical Geography[END_REF][START_REF] Watts | The study of human behavior and schistosomiasis transmission in an irrigated area in Morocco[END_REF] and could be advantageously used in connection with health-care utilization. However, this approach involves the use of travel datasets, which are difficult to collect and analyse, particularly in a survey with a large population sample.

We propose here to use a simplified measure of activity space based on the respondents' statements: they were asked whether some of their social and domestic activities took place within their neighbourhood of residence. This measure of activity space actually corresponds to a spatial overlap between what respondents consider the space of their neighbourhood of residence and what they consider the spatial extent of their daily activities. This measure of activity space was, therefore, not defined on the basis of the precise location of the daily activities, but was instead directly linked to the respondents' neighbourhood representation, since they were asked to place their activities within or outside what they considered their neighbourhood of residence. In this paper, we therefore propose to define activity space as a measure of the concentration of daily activities in the perceived neighbourhood.

The first objective of this paper was to identify individual and contextual characteristics statistically associated with this measure of activity space in the Paris metropolitan area and to discuss the validity of this simplified measure, which may reflect the spatial extent of daily mobility but which is also closely linked to perceived neighbourhood boundaries.

The second objective of this study was to determine if this measure of activity space was associated with participation in preventive health-care activities (in this case, cervical screening in the Paris metropolitan area). We postulated that women reporting an activity space centred within their perceived neighbourhood had a greater likelihood of not having a cervical screening test performed regularly, since it can be assumed that access to healthcare facilities and to a number of social interaction opportunities, which contribute to changing health-care norms, can vary according to the activity space.

Lastly, the third objective of this article was to study the combined effects of neighbourhood characteristics and activity space on participation in cervical screening. We postulated that the effects of neighbourhood characteristics on health behaviour might be modified by the respondent's activity space. Neighbourhoods of residence have recently emerged in social epidemiology, health geography and public health literature as a relevant contextual characteristic to be fruitfully taken into account. Many studies based on multilevel regression models have shown that neighbourhoods possess both physical and social attributes that can promote or damage people's health [START_REF] Diez-Roux | Investigating Neighborhood and Area Effects on Health[END_REF][START_REF] Macintyre | Ecological approaches: Rediscovering the role of the physical and social environment[END_REF][START_REF] Macintyre | Neighborhoods and Health: an overview[END_REF]. With regard to health care utilization and, more specifically, the use of preventive care services, the multilevel approach has revealed, among other things, the effect of area-level poverty rate on participation in cancer screening, after adjustment for individual factors [START_REF] Schootman | Effect of area poverty rate on cancer screening across US communities[END_REF]. Moreover, studies using multilevel methods have underscored the importance of not assuming that the health effects of the residential context operate identically for different types of people [START_REF] Stafford | Gender differences in the associations between health and neighbourhood environment[END_REF]. As pointed out by Macintyre and Ellaway, there is no a priori reason to assume that neighbourhood influences on health are similar for all populations [START_REF] Macintyre | Neighborhoods and Health: an overview[END_REF]. Indeed, it has been shown that the effects of the residential environment on health outcomes vary according to the resident's sex [START_REF] Macintyre | Inequalities in health: is research gender blind?[END_REF][START_REF] Raleigh | Life expectancy in England: variations and trends by gender, health authority, and level of deprivation[END_REF][START_REF] Stafford | Gender differences in the associations between health and neighbourhood environment[END_REF], age [START_REF] Chaix | Assessment of the magnitude of geographical variations and socioeconomic contextual effects on ischaemic heart disease mortality: a multilevel survival analysis of a large Swedish cohort[END_REF]Chaix et al., 2005b;[START_REF] Waitzman | Phantom of the area: poverty-area residence and mortality in the United States[END_REF], race and ethnicity [START_REF] Benjamins | County characteristics and racial and ethnic disparities in the use of preventive services[END_REF][START_REF] Coughlin | Contextual analysis of breast and cervical cancer screening and factors associated with health care access among United States women[END_REF] and socioeconomic status [START_REF] Cummins | Neighbourhood environment and its association with self rated health: evidence from Scotland and England[END_REF][START_REF] Ecob | Small area variations in health related behaviours; do these depend on the behaviour itself, its measurement, or on personal characteristics?[END_REF][START_REF] Stafford | Characteristics of individuals and characteristics of areas: investigating their influence on health in the Whitehall II study[END_REF][START_REF] Van Lenthe | Neighbourhood deprivation and overweight: the GLOBE study[END_REF][START_REF] Yen | Neighborhood social environment and risk of death: multilevel evidence from the Alameda County Study[END_REF]. In a previous paper describing how residential contextual effects on the health status of Vientiane population (Laos) differed significantly according to the respondent's age, sex and level of deprivation, we suggested that the magnitude of neighbourhood effects may be closely associated both with neighbourhood attachment and daily mobility within Vientiane city [START_REF] Vallée | Les disparités spatiales de santé en ville. L'exemple de Vientiane (Laos) [Spatial health disparities within city: the case of Vientiane, Lao PDR[END_REF].

Despite the interest shown in the interactions between individual and contextual effects, to the best of our knowledge, interactions between individual activity space and residential neighbourhood effects have not been investigated empirically. It is even reasonable to assume that the residential environment might promote or damage, to a lesser extent, the health of people whose activity space extends beyond their residential neighbourhood, since they have less exposure to their residential neighbourhood. Considering only the effect of the neighbourhood of residence on health and excluding nonresidential exposure would lead to a "local trap", as pointed out by [START_REF] Cummins | Commentary: investigating neighbourhood effects on health-avoiding the 'local trap[END_REF]. [START_REF] Inagami | Non-residential neighborhood exposures suppress neighborhood effects on self-rated health[END_REF] showedin one of the few studies that consider the nonresidential neighbourhood environment in addition to residential neighbourhood characteristics -the need to include nonresidential neighbourhood exposure in order to accurately measure the association between the residential neighbourhood and self-rated health. Therefore, in urban areas in particular, people with a large activity space could be less influenced by their residential environment, since their daily mobility within the entire city could be seen as a way to escape from the constraints of their neighbourhood of residence. The third objective of this paper was, therefore, to determine if the effects of the administrative-neighbourhood characteristics on cervical screening participation were actually stronger among women reporting that they did the vast majority of their activities within their perceived neighbourhood.

In short, the underlying idea of this paper was to improve the characterization of "personal exposure area" [START_REF] Chaix | Neighbourhoods in ecoepidemiologic research: delimiting personal exposure areas. A response to Riva, Gauvin, Apparicio and Brodeur[END_REF] by taking into account the activity space and the neighbourhood of residence.

-The activity space -defined from a concentration score for daily activities in the perceived neighbourhood -was used as a proxy of exposure to the neighbourhood of residence.

-The administrative neighbourhood -with fixed boundaries, whose scale was chosen to correspond as best possible to the collective perceived neighbourhood -was used as a proxy of the neighbourhood of residence.

The conceptual framework that guided the analysis is presented in Figure 1. The two hypotheses in this paper can be summarized as follows: the more respondents reported concentrating their daily activities within their perceived neighbourhood of residence, (1) the less they participated in preventive health-care activities and (2) the more they were influenced by the characteristics of their administrative neighbourhood.

Materials and methods

Study sample

The The SIRS survey employed a stratified, multistage cluster sampling procedure. This sample design is commonly used in health geography because it provides appropriate datasets for studying the heterogeneity of health characteristics between different neighbourhoods and the homogeneity of characteristics within a given neighbourhood [START_REF] Vallée | Sampling in health geography: reconciling geographical objectives and probabilistic methods. An example of a health survey in Vientiane (Lao PDR)[END_REF]. The primary sampling units were census blocks called "IRISs" ("IRIS" is a French acronym for blocks for incorporating statistical information). They constitute the smallest census unit areas in France (with about 2,000 inhabitants each) whose aggregate data can be used on a routine basis. The Paris metropolitan area was divided into six strata according to the population's socioeconomic profile [START_REF] Préteceille | La division sociale de l'espace francilien[END_REF] in order to overrepresent the poorest neighbourhoods, and census blocks were randomly chosen within each stratum. In all, 50 census blocks were selected from the 2,595 eligible census blocks in Paris and its suburbs.

Subsequently, within each selected census block, 60 households were randomly chosen from a complete list of households. Lastly, one adult was randomly selected from each household by the birthday method. A questionnaire containing numerous social and healthrelated questions was administered face-to-face during home visits. Further details on the SIRS sampling methodology were published previously [START_REF] Chauvin | Les inégalités sociales et territoriales de santé dans l'agglomération parisienne : une analyse de la cohorte SIRS[END_REF][START_REF] Renahy | Health information seeking on the Internet: a double divide? Results from a representative survey in the Paris metropolitan area, France, 2005-2006[END_REF].

Variables of interest

Measure of activity space

In this paper, activity space was measured from the respondents' statements about the location of their domestic and social activities. In the SIRS survey, people were asked where they usually 1) go food shopping; 2) use services (bank, post office); 3) go for a walk; 4) meet friends; and 5) go to a restaurant or café. These five activities were selected in order to involve cognitive routines that people can easily remember [START_REF] Enaux | Processus de décision et Espace d'activités/déplacements. Une approche articulant routine cognitive et adaptation événementielle [Decision process and Activity space. An approach linking cognitive routine and occurrence adaptation[END_REF].

For each of these five activities, three answers were proposed: 1) mainly within one's residential neighbourhood; 2) mainly outside one's residential neighbourhood; 3) both within and outside one's residential neighbourhood. As stated in the introduction, the neighbourhood of residence was not defined, and its boundaries were left to the individual's own assessment and perception.

A measure of activity space was subsequently created: activities said to be done "mainly within the neighbourhood" were assigned a value of 1, while those done "both within and outside the neighbourhood" or "mainly outside the neighbourhood" were assigned a value of 0.5 and 0, respectively. By adding these values together and dividing the sum by the total number of reported activities, we obtained an individual score measuring the concentration of daily activities in the perceived neighbourhood. The respondents were then ranked on the basis of this score. It ranged from 0 (for people who reported doing all the activities of interest mainly outside their neighbourhood of residence) to 1 (for people who reported doing all the activities of interest mainly within their neighbourhood of residence) and can be viewed as a proxy of personal exposure to the neighbourhood of residence.

To facilitate the cross-level interaction analysis, we also decided to isolate the respondents who reported doing the vast majority of their daily activities within their perceived neighbourhood of residence.

Cervical screening

Cervical cancer screening with a Papanicolaou (Pap) smear test is the key procedure to early detection and improved chances of survival from this type of cancer [START_REF] Baker | Cervical screening and health inequality in England in the 1990s[END_REF]. In France, gynaecologists perform -in independent practice -the vast majority of cervical screening, even if general practitioners can perform or order screening tests. Since 1995, in France, it is recommended that a smear test be performed every three years after two normal annual smear tests (ANDEM, 1995). However, this recommended screening interval appears not to be well known and/or adhered to by patients and practitioners. Actually, a two-year interval appears to be the interval that practitioners more commonly recommend to their patients [START_REF] Inca | Etat des lieux du dépistage du cancer du col utérin en France[END_REF]. In addition, it is not easy to obtain accurate information from women about the dates of their previous two smear tests. In this research, we therefore decided to use a two-year threshold to divide the adult female population into two subpopulations (2 years or less since their last smear test, or more than 2 years). In the SIRS survey, the date of the last screening test was self-reported by the women.

Additional individual variables

In addition to age, we distinguished between French people born to two French parents, those born to at least one foreign parent, and foreigners (this variable is referred to as "origin" in the rest of this paper). The respondents' socioeconomic status was characterised by the following variables: the level of monthly household income (range: 50 10 000 € per consumption unit; tertile values: 1 150/1 900 €/CU), the level of education, and occupational status. To calculate the monthly household income, we added up the individual incomes of all the members of the household and divided this sum by an adjusted number of people living in that household, or consumption unit (CU). As for occupational status, we distinguished between those in the workforce, those unemployed, those retired, those at home, and students. Functional limitation was also investigated on the basis of a report of a severe limitation of at least six months' duration in performing activities people usually engage in. Also, the length of residence in the neighbourhood was examined in relation to the daily activities performed in the perceived neighbourhood. Lastly, health insurance status and whether the person was living in a couple relationship were studied in relation to participation in cervical screening.

Administrative neighbourhood variables

Administrative neighbourhood delimitation

Since the available data (collected in 2005) did not enable us to delimit the perceived neighbourhood, we had to set the boundaries of neighbourhood areas to be able to characterize the neighbourhood context. This delimitation involved defining (1) the shape and

(2) the scale of these neighbourhood areas.

(1) The literature offers two distinct ways to delimit neighbourhoods in connection with health outcomes: as fixed and collective areas defined in a uniform manner for all the respondents or as areas centred on the respondents' residences (Chaix et al., 2005a). In this research, we based our neighbourhood delimitation on administrative census blocks (IRISs) because data on the number of practitioners were available only for these administrative units.

(2) To choose an administrative delimitation of a neighbourhood whose scale would correspond as best possible to the perceived neighbourhood of residents of the Paris metropolitan area, we used results from a survey carried out in 2006 and 2007 among 1124 residents of that area (14 neighbourhoods in Paris per se and 6 neighbourhoods in suburban areas). This survey attempted, among other things, to determine the scale used by respondents to define their neighbourhood of residence. An analysis showed that very few residents of the Paris metropolitan area (0.1%) perceive their neighbourhood at a scale larger than a district (called, in French, an "arrondissement"

within Paris and a "commune" outside Paris). A larger number of residents (20%)

considered their neighbourhood at the district scale. Actually, the vast majority of the residents (75%) perceived their neighbourhood at a scale smaller than an urban district.

Lastly, two other local areas were more rarely mentioned, with 5% of the residents considering their neighbourhood at the street or square scale, and 7% referring to equipment or a monument [START_REF] Humain-Lamoure | Faire des territoires de démocratie locale. Géographie sociopolitique des quartiers en Ile-de-France[END_REF].

Urban districts appear to be too large to accurately depict perceived neighbourhoods, and census blocks appear to be too small. We therefore decided to create an intradistrict spatial unit by grouping census blocks together. We selected from a geographical information system (ESRI ArcMap 9.2) all the census blocks sharing a line segment with a given surveyed census block. After grouping these selected blocks together, we obtained 50 different administrative neighbourhood areas containing an average of 15,200 residents (range: 8,700-24,500), according to the last census (1999), with a mean area of 2.5 km² (range: 0.3-13.5). These administrative neighbourhood areas were larger in the suburbs (mean area of 3.1 km²; range: 0.8-13.5) than within Paris (mean area of 0.6 km²; range: 0.3-1.6). Based on an example of four different locations (two within Paris and two outside),

Figure 2 shows selected neighbourhood areas and helps visualise their shape, with the urban districts and census block boundaries, street networks and buildings superimposed. -The density of general practitioners and gynaecologists. The practitioner number was obtained from the INSEE database and was divided by the size of the population living in the area. Practitioner density, which ranged from 16 to 188/100 000 population, was divided into tertiles (59 and 110 practitioners/100 000 population).

-Location of the neighbourhood in the Paris metropolitan area. The neighbourhoods were in Paris per se (urban areas) or outside Paris (suburban areas).

-The proportion of people in the neighbourhood with a recent preventive consultation. We calculated the proportion of the respondents (including men and women) who reported having seen a physician in the previous 12 months for a preventive consultation (e.g., for a check-up, to see if everything was all right or for a vaccination). The proportion of individuals with a recent preventive consultation was determined for every surveyed census block in the SIRS dataset. It ranged from 10% to 43%. We then divided it into tertiles (25%, 33%).

The first three variables were based on the administrative neighbourhood area obtained by grouping adjacent census blocks together, while the last two were based only on the surveyed census blocks. These variables were introduced in statistical models to study their associations either with the concentration of daily activities in the perceived neighbourhood (mean income, shop density, and urban or suburban location) or with delayed cervical screening (mean income, urban or suburban location, practitioner density, and proportion of individuals with a recent preventive consultation).

Statistical methods

All the proportions and mean values presented in this paper were weighted to account for the complex sample design (specifically, the design effect associated with cluster sampling and the stratification that overrepresented the poorest neighbourhoods) and for the poststratification adjustment for age and gender according to the general population census data (using the "svy" command in Stata10 software). Significant differences between weighted proportions and between weighted means were measured by the Pearson chisquared test and an adjusted Wald test, respectively.

Multilevel linear regression models (using the "xtmixed" command in Stata10 software, specifying that the collected data were clustered by census block) were utilized to identify individual and residential neighbourhood characteristics associated with the concentration of daily activities in the perceived neighbourhood.

Multilevel logistic regression models (using the "xtmelogit" command in Stata10 software, specifying that the collected data were clustered by census block) were utilized to identify individual and residential neighbourhood characteristics associated with delayed cervical screening (> 2 years). In these models, between-area variation was measured using variance components.

The variance inflation factors (VIFs) were computed to check for colinearity between the independent variables in regression models. VIF values were overall under 3.0 (with slightly higher values -not exceeding 5.5-for age and occupational status), suggesting that multicollinearity was no a severe problem in these regression models.

To investigate whether the effects of neighbourhood characteristics in terms of delayed cervical screening differ across women's activity space, we calculated, in multilevel logistic regression models, the cross-level interaction term between the administrative-neighborhood characteristics and the concentration of daily activities in the perceived neighbourhood (divided into two subgroups). Lastly, we compared the odds ratios associated with the administrative-neighbourhood characteristics according to the women's activity space.

A p-value < 0.05 was considered significant for all the statistical analyses presented.

Results

Description of the survey population

In the SIRS survey, 29% of the people contacted declined to answer, and 5% were excluded because they did not speak French (3%) or because they were too sick to answer our questions (2%) [START_REF] Renahy | Health information seeking on the Internet: a double divide? Results from a representative survey in the Paris metropolitan area, France, 2005-2006[END_REF]. The final SIRS sample consisted of 3,023 persons, including 1,843 women.

The mean age of the SIRS population was 44.9 years (similar for men and women). As regards occupational status, 56% were in the workforce, 9% were unemployed, 19% were retired, 8% were at home, and 7% were students. The proportion of individuals in the workforce was statistically higher for men (62%) than for women (52%; p <0.01), and the proportion of individuals at home was statistically higher for women (13%) than for men (2%; p <0.01). As for the level of education, 51% had a postsecondary education, while 10% had a primary school education or less (with no statistical differences between men and women).

With regard to origin, 68% were French, born to two French parents; 18% were French, born to at least one foreign parent; and 14% were foreigners.

Of the 1,843 women surveyed, 66 were not asked about cervical screening because they had had a hysterectomy in the past, and 3 others did not answer this question. Therefore, the sample for studying cervical screening in the Paris metropolitan area consisted of 1,774 women (aged 18 to 97 years).

Description of the measure of activity space Table 1 presents, for each of the five selected daily activities, the number and proportion of respondents who reported doing it mainly within their neighbourhood of residence, both within and outside their neighbourhood of residence, or mainly outside. It can be seen that the majority of the respondents reported engaging in domestic activities (going food shopping and using services) within their neighbourhood of residence and engaging in social and leisure activities (going to a restaurant or café, going for a walk and meeting friends) partly or mainly outside their neighbourhood. Scores measuring the concentration of daily activities in the perceived neighbourhood were not available for the 12 respondents (8 of whom were women) who did not provide answers regarding the five activities in question. The concentration scores were well distributed among the general population of the Paris metropolitan area (Figure 3). The (weighted) mean score was 0.51 [95% CI: 0.47-0.55].

To isolate people who reported doing the vast majority of their daily activities within their perceived neighbourhood, we used grouped together the respondents with a score greater than or equal to 0.8. They were those who reported doing either (a) every activity within their perceived neighbourhood of residence, (b) one or two activities both within and outside their perceived neighbourhood, or (c) only one activity mainly outside their perceived neighbourhood of residence. Lastly, 520 of the 3,011 individuals surveyed (17.5%) were thus considered as having an activity space substantially limited to their perceived neighbourhood, while 2,491 (82.5%) were considered as having an activity space larger than their perceived neighbourhood. Of the 1,768 women studied with regard to their last cervical screening test (and for whom daily activity concentration scores were available), 313 (19.6%) and 1455 (80.4%) were considered, respectively, as having an activity space limited to or larger than their perceived neighbourhood. 2), we found that there was no statistical difference between men and women (a mean score of 0.52 and 0.50, respectively). With a mean score of 0.60, people aged 60 years or older reported an activity space statistically centred more within their neighbourhood than did younger people. We also observed a statistical difference in the mean concentration scores according to origin, the level of education, occupational status, the length of residence in the neighbourhood, and functional limitation status. Lastly, there was no statistical difference between concentration scores according to household income.

In the multilevel linear regression model, several individual characteristics were statistically associated with the concentration of daily activities in the perceived neighbourhood (Table 2).

Being a foreigner, having a low level of education, living in a low-income household, being unemployed, retired or at home, having lived in the neighbourhood for more than 20 years and being physically limited were all positively associated with an activity space centred more within the perceived neighbourhood. On the other hand, when these characteristics were taken into account, neither gender nor age was significantly associated with this measure of activity space. After the individual sociodemographic characteristics were controlled for in the multilevel models, living in Paris, living in a neighbourhood with a high shop density and with a high mean income were all positively associated with an activity space centred more within the perceived neighbourhood. Lastly, we observed that individual and neighbourhood factors associated with this measure of activity space were broadly similar in the general population and in the female-only population. 3).

After introducing the neighbourhood characteristics into the model, in addition to individual characteristics, we observed that the concentration of daily activities in the perceived neighbourhood was statistically associated with delayed cervical screening, regardless of the administrative-neighbourhood variables introduced into the model, not only the location in the Paris metropolitan area (Model 2), but also the practitioner density (Model 3a), the proportion of residents with a recent preventive consultation (Model 3b) and the mean neighbourhood income (Model 3c). The more the women reported concentrating their daily activities within their neighbourhood of residence, the more they had delayed undergoing cervical screening (e.g., OR=1.93; 95% CI=1.20-3.11. See Model 3c). The association between the concentration score and delayed cervical screening was also statistically significant when these four neighbourhood characteristics were introduced into the model together (Model 4).

Individual characteristics and cervical screening

Several other individual characteristics were statistically associated with delayed cervical screening (Table 3). Being less than 30 or more than 60 years of age, being a foreigner, not being fully covered by health insurance, being a student, not living in a couple relationship and being physically limited were all positively associated with delayed cervical screening in the multivariate analysis.

Spatial disparities in cervical screening in the Paris metropolitan area

Depending on the census block surveyed, the proportion of women with delayed cervical screening varied from 11% to 58%, as shown in Figure 4. The crude between-area variation (VarU 0j =0.149; standard error=0.060) was statistically significant, which indicates that there were spatial disparities in cervical screening between the 50 census blocks surveyed in the Paris metropolitan area (Table 3). When the individual characteristics were added to the model (Model 1), the between-area variation decreased considerably, but it remained statistically positive, which indicates that spatial variations in participation in cervical screening are not fully explained. When location in the Paris metropolitan area, practitioner density or the proportion of people with a recent preventive consultation were included in the model, the between-area variation decreased even more (Models 2, 3a and 3b). However, it is only when the mean neighbourhood income was taken into account that this variation strongly decreased (Model 3c), and it even became statistically null when the mean neighbourhood income was added to the model with the other neighbourhood characteristics (Model 4).

Significant interaction between measure of activity space and administrative-neighbourhood characteristics on delayed cervical screening Cross-level interactions between concentration of daily activities in the perceived neighbourhood and administrative-neighbourhood characteristics were calculated in regression models (after adjustment for age, occupational status, health insurance status, couple relationship status and functional limitation status). They were statistically significant for two of the four neighbourhood variables (Table 4). We observed significant cross-level interaction for practitioner density and the proportion of people with a recent preventive consultation, i.e., the neighbourhood variables that were not statistically associated with delayed cervical screening in the general population.

In the subpopulation models (Table 4), we observed that living in a neighbourhood with a low practitioner density significantly increased the likelihood (OR=2.91; 95% CI=1.43-5.92) of delayed cervical screening among the women with an activity space limited to their perceived neighbourhood, while it did not significantly impact the likelihood (OR= 1.19; 95% CI=0.85-1.67) of delayed cervical screening among those with an activity space larger than their perceived neighbourhood.

Similarly, we observed that living in a neighbourhood with a low proportion of people with a recent preventive consultation statistically increased the likelihood (OR=2.42; 95% CI=1.30-4.48) of delayed cervical screening among the women with an activity space limited to their perceived neighbourhood, while it did not significantly impact the likelihood (OR= 1.00; 95% CI=0.71-1.417) of delayed cervical screening among those with an activity space larger than their perceived neighbourhood.

On the other hand, we did not observe a significant cross-level interaction for mean neighbourhood income or neighbourhood location in the Paris metropolitan area (Table 4),

i.e., the variables that were statistically associated with delayed cervical screening in the general population.

Discussion

Self-reporting of cervical screening

In our study, the date of the last cervical screening test was self-reported by the women and there may be several reasons for doubting the accuracy with which women report cervical screening histories. The self-reporting of Pap smear tests relies on remembering events dating back many years, with less recent events being subject to greater memory biases.

There is also a social desirability bias, i.e., a certain degree of social pressure to report in questionnaires a behaviour that conforms to accepted health norms [START_REF] Bowman | The Accuracy of Pap Smear Utilization Self-Report: A Methodological Consideration in Cervical Screening Research[END_REF].

Yet, we postulated that for cervical screening tests, such biases may be less problematic than for other, more sensitive health behaviours.

Organization of cervical screening in France

In the Paris metropolitan area (and in the vast majority of France's departments), cervical screening is of the opportunistic type only, since there is no organized cervical screening program. Women are thus free to decide when and where they want to have their Pap smear test. Consequently, the location of cervical cancer screening is not determined by the national health system: women can choose to have their screening test performed close to or far from their place of residence. It was therefore relevant to study the cross-implication of the measure of activity space and neighbourhood practitioner density for participation in cervical screening.

In France, smear tests are not fully covered by the social health security system, which could explain why women without voluntary insurance were found, in this study, to be more likely not to have undergone cervical screening during the previous two years.

Although cervical screening is recommended in France only for women from 25 to 65 years of age, we decided not to set a lower or upper age limit in our sample, since it is known that younger and older women undergo also this screening test [START_REF] Inca | Etat des lieux du dépistage du cancer du col utérin en France[END_REF]. The results presented in this paper are consistent with the national recommendations, as younger and older women had a greater likelihood of not having undergone cervical screening during the previous two years.

About the measure of activity space

We proposed above a simplified measure of activity space based on the respondents' statements. This self-definition of activity space was associated with individual and neighbourhood profiles because daily mobility may vary according to individual and neighbourhood characteristics and because individual and neighbourhood characteristics may also influence the size of the perceived neighbourhood. The social sciences have recognized that perceived neighbourhood boundaries are specific to every inhabitant, even for those living in close proximity [START_REF] Coulton | Mapping residents' perceptions of neighborhood boundaries: a methodological note[END_REF]. In this paper, we observed that foreigners, people with a low level of education and those living in a low-income household reported daily activities that were centred more within their perceived neighbourhood. These individuals may have reported that they concentrated their activities within their neighbourhood (i) because their daily mobility was actually spatially limited and/or (ii) because they tended to perceive their neighbourhood as being larger than the other individuals did. This second possibility seems less likely since certain papers have pointed out that recent immigrants, people who are less educated and those with a lower income are more likely to view their neighbourhood as smaller than do other respondents [START_REF] Guest | How urbanites define their neighborhoods[END_REF][START_REF] Lee | Common ground ? Urban neighborhoods as survey respondents see them[END_REF][START_REF] Logan | Residents' Perceptions of Suburban Community Differences[END_REF][START_REF] Sastry | Neighborhood Definitions and the Spatial Dimension of Daily Life in Los Angeles[END_REF].

Whatever, the available data did not enable us to delimit individual perceived neighbourhoods or identify the factors specifically associated with the size of a perceived neighbourhood. Consequently, it was not possible, in this paper, to identify (i) the factors directly associated with the spatial extent of daily mobility or (ii) those associated with the size of the perceived neighbourhood. This is the main limitation of the simplified measure of activity space proposed in this paper.

In addition, it can be assumed that as a cognitive construct, the perceived neighbourhood can vary according the spatial extent of daily activities, and vice versa. Behavioural geographers do, in fact, point out that "perceived territories act to constrain and direct an individual's trip though space" [START_REF] Golledge | Spatial Behaviour -A geographic perspective[END_REF] and that "activity spaces represent an important process though which we gain information and attachment to our environment" [START_REF] Jakle | Human spatial behavior: A social geography[END_REF]. The identification of territories and movement in the environment may thus be closely linked [START_REF] Golledge | Spatial Behaviour -A geographic perspective[END_REF]. Consequently, the spatial extent of daily mobility and the spatial extent of the perceived neighbourhood of residence may interact with each other (see the conceptual framework presented in Figure 1).

About the administrative neighbourhood delimitation

We chose to delimit neighbourhood areas as a group of adjacent census blocks so that they would correspond as best possible to the scale of the perceived neighbourhood of the majority of the residents of the Paris metropolitan area (Humain-Lamoure, 2008). When we calculated the size of these administrative neighbourhood areas, we observed that they were larger in the suburban areas than in Paris per se (mean area of 3.1 km² and 0.6 km², respectively). This difference appeared to correspond to the difference in perceivedneighbourhood size, since suburbanites tend to consider their neighbourhood at a larger scale than do city dwellers, as shown recently by Humain-Lamoure in the Paris metropolitan area ( 2008) and previously by [START_REF] Haney | Perception of neighborhoods by city and suburban residents[END_REF]. To take into account differences in the perceived neighbourhoods according urban and suburban location, we controlled for neighbourhood location in the Paris metropolitan area in the regression models.

Unfortunately, it was not possible in this research to examine more closely the spatial correspondence between individual perceived neighbourhoods and our administrative territorial neighbourhood delimitation. This spatial correspondence will be studied as soon as data concerning the boundaries of perceived neighbourhood (collected in 2009-2010 within the framework of the SIRS cohort) are available.

Bias resulting from potential spatial incongruity between the perceived neighbourhoods and the administrative neighbourhoods

The inability to examine the spatial correspondence between the perceived neighbourhoods and the administrative neighbourhoods may have led to a misinterpretation of personal exposure to the neighbourhood of residence for certain individuals. Depending on the individual, the perceived neighbourhood may be the same, smaller or larger than the administrative neighbourhood. Actually, there may be two types of misinterpretation of personal exposure to the neighbourhood of residence:

-On the one hand, a person whose perceived neighbourhood was smaller than the administratively delimited neighbourhood and whose activities were clustered just beyond the boundary of his/her perceived neighbourhood was categorized as having an activity space larger than his/her perceived neighbourhood and was consequently wrongly considered slightly exposed to the administrative-neighbourhood characteristics (bias no.

1).

-On the other hand, a person whose perceived neighbourhood was larger than the administratively delimited neighbourhood and whose activities took place mainly within the perceived neighbourhood was categorized as having an activity space centred within his/her perceived neighbourhood and was consequently wrongly considered as highly exposed to the administrative-neighbourhood characteristics (bias no. 2).

These two types of misclassification are presently impossible to quantify. Furthermore, these misclassifications cannot be dismissed as random, as they probably vary according to the neighbourhood and individual factors (see above). However, we can assume that they were relatively uncommon, since they did not hinder the model's ability to detect cross-level interaction between administrative-neighbourhood characteristics and activity space within perceived neighbourhood.

Omission of the workplace in the measure of activity space

Employment is a routine activity that has been found to have an influence on the spatial extent of his/her activity space [START_REF] Golledge | Spatial Behaviour -A geographic perspective[END_REF]. However, in this research, employment was not among the activities included in the measure of activity space. This information was not available, since the people surveyed were not asked to situate their work activities within or outside what they perceived as their neighbourhood of residence.

Workplace omission thus constitutes a limitation of our measure of activity space. However, we could postulate that we accounted for workplace exposure through the domestic and social activities done within the workplace neighbourhood. Actually, our measure of activity space included "discretionary" activities -whose location is intentionally chosen by people and excluded "obligatory" activities, such as work , whose location is not chosen [START_REF] Golledge | Spatial Behaviour -A geographic perspective[END_REF].

Double and opposite effect of poverty on the concentration of daily activities in the perceived neighbourhood

The results of the multilevel linear regression (Table 2) indicate that poor people and those living in more privileged neighbourhoods (in terms of the shop density and the mean neighbourhood income) are both more inclined to concentrate their daily activities within their perceived neighbourhood. In other words, at the individual level, poverty leads to a higher concentration of daily activities within the perceived neighbourhood, while neighbourhood deprivation leads to a lower concentration of daily activities within the perceived neighbourhood. This apparent contradiction is easily explainable. People living in privileged and well-equipped neighbourhoods do not necessarily need to travel to another place to access urban facilities, such as food shops, services, restaurants and recreational sites. On the other hand, wealthier people with financial, cultural and social capital have more power over space [START_REF] Bourdieu | The weight of the world: social suffering in contemporary society[END_REF]. Overall, they have a wider "spatial capital", that is, a greater potential for mobility, or what [START_REF] Kaufmann | Re-thinking mobility[END_REF] refers to as "motility", even if they do not necessarily exercise this potential.

The fact that the statistical association between income and activity space varied in opposite directions when individual income or the mean neighbourhood income was considered was useful for discussions of the distinction between people and places, and composition and context [START_REF] Macintyre | Neighborhoods and Health: an overview[END_REF]. In this multilevel analysis, the double and opposite effect of poverty on activity space according to individual or neighbourhood income indicates that the contextual effect of a neighbourhood's socioeconomic profile cannot be seen as a confounding factor of an individual's socioeconomic status. This double and opposite effect of poverty might also illustrate the danger of ecological fallacy, since it would be erroneous to infer, at the individual level, an association observed at the neighbourhood level. This ecological fallacy, which has been well known since the 1950s [START_REF] Robinson | Ecological correlations and the behavior of individuals[END_REF], was underscored more recently in contextual analysis, social epidemiology and public health [START_REF] Macintyre | Ecological approaches: Rediscovering the role of the physical and social environment[END_REF].

Investigating associations between our measure of activity space and participation in cervical screening Health studies previously identified the link between functional limitation in daily activities and health services consumption in the elderly [START_REF] Avlund | Functional ability and oral health among older people: a longitudinal study from age 75 to 80[END_REF]Chaix et al., 2005b;[START_REF] Fernandez-Mayoralas | Health services accessibility among Spanish elderly[END_REF]. With no age restrictions, a number of North American studies have also shown that women with reduced mobility are significantly less likely to avail themselves of cervical and breast cancer screening on a regular basis [START_REF] Chevarley | Health, preventive health care, and health care access among women with disabilities in the 1994-1995 National Health Interview Survey, Supplement on Disability[END_REF][START_REF] Cooper | Cancer screening behaviors among Canadian women living with physical disabilities[END_REF][START_REF] Iezzoni | Mobility impairments and use of screening and preventive services[END_REF][START_REF] Nosek | Use of cervical and breast cancer screening among women with and without functional limitations--United States, 1994-1995[END_REF]. In this research, a similar association in the Paris metropolitan area was observed, too, as women with a severe functional limitation had a greater likelihood of delayed cervical screening (Table 3).

However, reducing daily mobility to its functional limitation dimension seems too restrictive.

Indeed, in our study, positive and significant associations regarding delayed cervical screening were observed both with severe functional limitations and with an activity space limited to the perceived neighbourhood independently of other individual or neighbourhood characteristics. The effect of daily mobility on participation in preventive health-care activities can thus be fruitfully linked to both functional limitations and the activity space. It could thus be highly useful to take the activity space within or outside the perceived neighbourhood into consideration more often when studying health care utilization.

An activity space larger than the perceived neighbourhood might be seen as reflecting people's ability to move about and as resulting in a higher diversity of social interaction opportunities, which may contribute to modifying health-care norms. Through their daily activities, women may indeed become familiar with people, institutions, services, spatial structures, and norms -particularly health norms [START_REF] Hanson | Perspectives on the geographic stability and mobility of people in cities[END_REF] and, ultimately, may be more motivated to participate in cervical screening. This hypothesis is consistent with studies suggesting that one's social network may be important in determining health behaviour [START_REF] Berkman | From social integration to health: Durkheim in the new millennium[END_REF]. Two more-specific studies have also stressed the importance of social networks in cancer screening participation [START_REF] Gotay | Social support and cancer screening in African American, Hispanic, and Native American women[END_REF][START_REF] Suarez | Social networks and cancer screening in four U.S. Hispanic groups[END_REF].

Certain individual characteristics, such as origin and functional limitation status, were associated in the same direction with an activity space limited to the perceived neighbourhood (Table 2) and with delayed cervical screening (Table 3). Foreigners and those with a severe functional limitation had a statistically greater likelihood (i) of concentrating their daily activities within their perceived neighbourhood and (ii) of delayed cervical screening. We can thus suspect strong correlations between the measure of activity space, origin and functional limitation in the logistic regression concerning delayed cervical screening. Besides, we observed that certain characteristics, such as the mean neighbourhood income and location in the Paris metropolitan area, were associated in an opposite direction with an activity space limited to the perceived neighbourhood (Table 2)

and with delayed cervical screening (Table 3). People living in wealthy neighbourhoods and in Paris did, in fact, have a greater likelihood (i) of concentrating their daily activities within their perceived neighbourhood, but a lower likelihood (ii) of delayed cervical screening. The measure of activity space is a useful variable that could not be summarized (or replaced) in the statistical models with other characteristics.

Methodological comments

Two methodological comments need to be made here. First, the data collected in 2005 were examined cross-sectionally. Therefore, we can only speculate on causal inferences. To understand the mechanism through which neighbourhood characteristics and activity space are associated with participation in preventive health-care activities, a longitudinal analysis will be performed as soon as data collected in 2009-10 on the same population (within the framework of the SIRS cohort) are available. Second, we determined the proportion of the neighbourhood population with a recent preventive consultation by aggregating information from the people surveyed in each census block. This aggregation procedure has often been used in multilevel analysis, for example, to create a neighbourhood deprivation index [START_REF] Brown | Population mobility, deprivation and self-reported limiting longterm illness in small areas across Scotland[END_REF][START_REF] Van Lenthe | Neighbourhood deprivation and overweight: the GLOBE study[END_REF]. However, this procedure may have resulted in incorrect estimates of the health behaviour of the neighbourhood population.

Relevance of neighbourhood characteristics in cervical screening participation

Health care utilization has often been linked to the distance between a patient's residence and his/her provider's office. Recent advances in the field of health geography have identified associations between the spatial distribution of primary care services and health status [START_REF] Gulliford | Availability of primary care doctors and population health in England: is there an association?[END_REF] or health care utilization (Chaix et al., 2005b;[START_REF] Coughlin | Contextual analysis of breast and cervical cancer screening and factors associated with health care access among United States women[END_REF][START_REF] Fortney | The impact of geographic accessibility on the intensity and quality of depression treatment[END_REF][START_REF] Nattinger | Relationship of distance from a radiotherapy facility and initial breast cancer treatment[END_REF]. However, most of these studies were carried out either in rural areas or at the national level. In urban areas, some authors have pointed out that provider-to-population ratios in neighbourhoods have significant limitations, as these measures do not account for patient border crossing, which commonly occurs in small geographic areas, such as urban census blocks [START_REF] Guagliardo | Spatial accessibility of primary care: concepts, methods and challenges[END_REF]. Some authors have therefore suggested considering the distribution of health-care opportunities within a spatial unit larger than the neighbourhood (such as a county), which would be more in line with the exposures supply-related characteristics of the health-care system [START_REF] Litaker | Health care resource allocation and individuals' health care needs: examining the degree of fit[END_REF].

In our paper, the nonrelevance of neighbourhood practitioner density to delayed cervical screening in the general adult female population may have to do with the residents' overall mobility and the high practitioner density in the Paris metropolitan area. In the Paris area at least, but perhaps also, more generally, in urban areas with a high practitioner density, inequalities in participation in preventive health care may not be directly associated with the spatial distribution of primary care providers, with the notable exception of people whose activity space is limited. We did in fact observe that the provider-to-population ratio in a neighbourhood was statistically associated with participation in cervical screening among people with an activity space limited to their perceived neighbourhood of residence. In our opinion, it is not relevant to postulate that every urban resident has the ability to seek health care outside his/her neighbourhood of residence and to consequently assert that the neighbourhood is the wrong scale in urban areas for measuring the distribution of health-care opportunities.

We also observed that the odds ratios associated with the proportion of people with a recent preventive consultation were statistically greater for women whose daily activities were concentrated within their perceived neighbourhood. This greater sensitivity could be due to the fact that a limited activity space can prevent people from diversifying their social interaction opportunities. Spatial neighbourhood confinement may reduce the likelihood of being influenced by other women's health behaviours. Women who remain isolated in their neighbourhoods may thus be more inclined to adhere to the local community standard of health behaviour [START_REF] Inagami | Non-residential neighborhood exposures suppress neighborhood effects on self-rated health[END_REF]. On the contrary, an activity space larger than the neighbourhood may permit exposure to other behavioural norms, thus creating an opportunity for adopting other habits. Urban geographers and environmental psychologists who have studied the role of daily mobility in neighbourhood attachment previously described daily travels within the overall city as a way to escape the constraints of the residential neighbourhood [START_REF] Authier | Le quartier à l'épreuve des mobilités "métapolitaines[END_REF][START_REF] Gustafson | Mobility and Territorial Belonging[END_REF][START_REF] Ramadier | Mobilité quotidienne et attachement au quartier : une question de position?[END_REF].

This paper might be useful for discussions of those aspects of a neighbourhood that might promote or hinder health services utilization. In research conducted in western Scotland starting in 1987, Macintyre and Ellaway conceptualized five "opportunity structures" of neighbourhoods that can influence health through the possibilities they provide to people [START_REF] Macintyre | Ecological approaches: Rediscovering the role of the physical and social environment[END_REF][START_REF] Macintyre | Neighborhoods and Health: an overview[END_REF]. Apart from the physical features of the environment shared by all the residents in a given locality (such as air and water quality), the existence of healthy home, work and recreational environments and the area's reputation, these two researchers included sociocultural features (including norms and values) and the services provided in the neighbourhood to support people in their daily lives, such as education, transportation and health services. Our research found (i) that neighbourhood sociocultural features were associated with preventive health care in the general population and (ii) that the neighbourhood health services density and the health behaviours of the neighbourhood population were also associated with preventive health care, but only among people with an activity space limited to their perceived neighbourhood, who make up a sizeable proportion (20%) of the Paris metropolitan area population, according to our definition. When examining the "opportunity structures" of neighbourhoods that could influence health, it might thus be relevant not only to consider the general population. but also to focus the analysis on the less mobile population.

Conclusion

Through the example concerning women's cervical screening behaviour in the Paris metropolitan area, this research provides strong arguments in favour of the influence of the activity space on participation in health-care activities. Studying people's activity helped elucidate how residential and nonresidential spaces matter in health behaviours. In the introduction of this paper, we mention studies that showed that the effect of the residential environment varies according to the resident's gender, age, race/ethnicity and socioeconomic status. With the notable exception of Inagami, Cohen and Finch's study of self-rated health (2007), these studies only allude to the role of daily mobility. Stafford, Cummins, Macintyre et al. write, for instance, that the "stronger association between neighbourhood characteristics and health seen amongst women may be due to the fact that women spend more of their time in the neighbourhood" (2005). Our paper shows that it may be useful to examine how activity space -measured in terms of the concentration of daily activities in the perceived neighbourhood -can modify the extent of residential neighbourhood effects on health-care behaviours. We believe that research on interactions between individual and neighbourhood characteristics on heath could be profitably developed, with special attention given to people's activity space.

This research might also contribute to the social sciences discussion of the importance to be attributed to the urban neighbourhood as a social space. In the Paris metropolitan area, we found that the neighbourhood of residence plays a significant role in the health behaviour of people whose daily activities are spatially limited, as it provides them with health-care facilities and social interaction opportunities.

Figure 1 .

 1 Figure 1. Conceptual framework for the combined impact of activity space and neighbourhood of residence on health behaviour

  SIRS (French acronym for Health, Inequalities and Social Ruptures) survey was conducted in the fall of 2005 among a representative sample of the adult French-speaking population in the Paris metropolitan area (Paris and its suburbs, a region with a population of 6.5 million). This survey constituted the first wave of a socioepidemiological population-based cohort study, which is a collaborative research project between the French National Institute for Health and Medical Research (INSERM) and the National Centre for Scientific Research (CNRS). Another wave was conducted during the fall and winter of 2009-2010. In this paper, data collected in 2005 were examined cross-sectionally.

Figure 2 .

 2 Figure 2. Selected neighbourhood areas in the Paris metropolitan area

Figure 3 .

 3 Figure 3. Histogram of the distribution of the score measuring the concentration of daily activities in the perceived neighbourhood

Figure 4 .

 4 Figure 4. Spatial disparities in cervical screening in the Paris metropolitan area in 2005

Table 1 .

 1 Number and percentage of Paris metropolitan area residents who reported doing their daily activities within their perceived neighbourhood of residence in 2005.

		Number (and percentage*) of people who reported doing the following activities
		Mainly within their neighbourhood of residence	Both within and outside their neighbourhood of residence	Mainly outside their neighbourhood of residence	Activity not reported
	Food shopping	1532 (54)	770 (24)	664 (19)	57 (2)
	Using services (post office, bank, etc.)	1759 (61)	450 (14)	776 (24)	38 (1)
	Going for a walk	754 (25)	966 (34)	1,132 (36)	171 (5)
	Meeting friends	529 (16)	1,074 (38)	1,232 (41)	188 (5)
	Going to a restaurant or café	448 (16)	553 (20)	1,426 (47)	596 (16)

* Complex sample design taken into account when calculating the percentage.

Table 2 .

 2 Individual and neighbourhood factors for the concentration of daily activities within the neighbourhood of residence among the population in the Paris metropolitan area (2005), as determined by multilevel linear regression

		Score measuring the concentration of daily activities in the perceived neighbourhood (0 to 1)	General population n=3011 1 Mean score Coef. (95% CI)	Mean score 1	Female population n=1835 Coef. (95% CI)
		Mean neighbourhood income (per
		household, per CU)
	Neighbourhood	Low Middle High Neighbourhood shop density (per km²) Low High Location	0.39 0.51 0.55 0.43 0.54	* *	Ref. .073 (-.002 to .144) .151 (.077 to .225)* Ref. .075 (.010 to .140)*	0.39 0.51 0.57 0.45 0.55	* *	Ref. .074 (.000 to .147)* .167 (.090 to .243)* Ref. .064 (-.004 to .131)
		Suburban In Paris	0.45 0.64	*	Ref. .135 (.061 to .208)*	0.46 0.66	*	Ref. .148 (.072 to .223)*
		Sex
		Women Men	0.50 0.52	NS	Ref. .012 (-.005 to .029)	--		-	--
		Age
		18-29 years	0.47		Ref.	0.48			Ref.
		30-44 years 45-59 years	0.49 0.50	*	.024 (-.003 to .051) .007 (-.022 to 0.036)	0.50 0.51	*	.024 (-.011 to .059) .000 (-.038 to 0.038)
		≥ 60 years	0.60		.037 (-.006 to .081)	0.60			.022 (-.035 to .079)
		Origin
		French, born to French parents	0.51		Ref.	0.52			Ref.
		French, born to at least one foreign parent	0.48	*	.013 (-.009 to .036)	0.48	NS	.032 (.003 to .061)*
		Foreigners	0.55		.059 (.033 to .086)*	0.57			.068 (.033 to .104)*
		Level of education
		Postsecondary	0.50		Ref.	0.51			Ref.
		Secondary school -2 Secondary school -1	0.48 0.52	*	.027 (.004 to .050)* .033 (.007 to .059)*	0.51 0.52			.031 (.001 to .061)* .027 (-.006 to .061)
		None or primary school	0.61		.110 (.077 to .143)*	0.62

*

.

116 (.075 to .158)* Household income (per CU)

  Concentration of daily activities within the perceived neighbourhood and cervical screeningIn all, one-fourth of the women (25.7%) reported not having had a cervical screening test during the previous two years. The mean concentration of daily activities in the perceived neighbourhood was 0.51 [95% CI: 0.47-0.55] for women who had recently had a test and

	0.55 [95% CI: 0.49-0.61] for those with a delay in being tested. These scores were not
	statistically different (p=0.10). After taking into account only the individual characteristics
	(age, origin, level of education, health insurance status, household income, occupational
	status, couple relationship status and functional limitation status), we observed that the
	concentration score was not statistically associated with delayed cervical screening
	(OR=1.46; 95% CI=0.91-2.334. See Model 1 in Table
	Individual	High	0.52		Ref.	0.53		Ref.
		Middle	0.49	NS	.022 (.000 to .045)*	0.50	NS	.017 (-.012 to .046)
		Low	0.53		.074 (.047 to .101)*	0.54		.068 (.034 to .103)*
		Occupational status
		Working	0.47		Ref.	0.49		Ref.
		Unemployed	0.54		.063 (.005 to .067)*	0.53		.015 (-.026 to .055)
		Retired	0.61	*	.060 (.022 to .099)*	0.60	*	.065 (.015 to .115)*
		At home	0.58		.056 (.023 to .088)*	0.58		.049 (.011 to .087)*
		Student	0.44		-.025 (-.070 to .020)	0.43		-.047 (-.106 to .011)
		Length of residence in the
		neighbourhood
		< 20 years ≥ 20 years	0.49 0.55	*	Ref. .027 (.006 to .048)*	0.50 0.56	*	Ref. .022 (-.005 to .049)
		Severe functional limitation
		No Yes	0.50 0.64	*	Ref. .078 (.045 to .112)*	0.51 0.63	*	Ref. .059 (.016 to .101)*

1 Complex sample design taken into account when calculating the mean.

Table 3 .

 3 Individual and neighbourhood risk factors for not having undergone cervical screening in the previous two years in the population in the Paris metropolitan area (2005), as determined by multilevel logistic regression

		No cervical screening in the previous two years (n=1768)	%	1	Model 1	Model 2	Model 3a Odds Ratio (95% CI) Model 3b	Model 3c	Model 4
		Location
		Suburban In Paris	27 22	NS	--	Ref. 0.62 (0.45-0.85)*	Ref. 0.61 (0.44-0.86)*	Ref. 0.62 (0.45-0.87)*	Ref. 0.69 (0.50-0.64)*	Ref. 0.68 (0.49-0.95)*
		Density of general practitioners and
		gynaecologists
	Neighbourhood	High Intermediate Low Prop. of people who reported a recent preventive consultation Lowest Intermediary Highest	25 23 30 29 26 22	NS NS	------	------	Ref. 0.90 (0.66-1.24) 1.04 (0.45-1.16) ---	---Ref. 1.25 (0.92-1.69) 1.10 (0.81-1.49)	------	Ref. 0.93 (0.68-1.28) 1.02 (0.73-1.41) Ref. 1.20 (0.89-1.62) 1.08 (0.80-1.45)
		Mean neighbourhood income (per
		household, per CU)
		High	19		-	-	-	-	Ref.	Ref.
		Middle	31	*	-	-	-	-	1.38 (1.02-1.86)*	1.37 (1.01-1.85)*
		Low	36		-	-	-	-	1.63 (1.14-2.33)*	1.60 (1.12-2.82)*
		Age
		18-29 years	34		2.11 (1.43-3.10)*	2.18 (1.49-3.21)*	2.20 (1.49-3.23)*	2.21 (1.50-3.25)*	2.14 (1.46-3.15)*	2.17 (1.48-3.20)*
		30-44 years 45-59 years	12 18	*	Ref. 1.35 (0.95-1.94)	Ref. 1.40 (0.98-2.00)	Ref. 1.41 (0.98-2.02)	Ref. 1.40 (0.97-2.00)	Ref. 1.40 (0.98-2.014)	Ref. 1.40 (0.98-2.01)
		≥ 60 years	42		4.87 (2.87-8.29)*	5.27 (3.09-8.99)*	5.33 (3.12-9.10)*	5.28 (3.09-9.00)*	5.58 (3.26-9.54)*	5.60 (3.28-9.57)*
		Origin
		French, born to French parents	23		Ref.	Ref.	Ref.	Ref.	Ref.	Ref.
		French, born to at least one foreign parent	30	*	1.32 (0.97-1.81)	1.30 (0.95-1.78)	1.30 (0.95-1.77)	1.30 (0.95-1.78)	1.26 (0.91-1.71)	1.25 (0.91-1.71)
		Foreigners	39		1.85 (1.27-2.70)*	1.84 (1.26-2.69)*	1.83 (1.25-2.67)*	1.83 (1.26-2.67)*	1.79 (1.23-2.61)*	1.77 (1.22-2.57)*
		Level of education
		Postsecondary	19		Ref.	Ref.	Ref.	Ref.	Ref.	Ref.
		Secondary school -2 Secondary school -1	29 33	*	1.17 (0.84-1.64) 1.42 (0.99-2.03)	1.12 (0.80-1.57) 1.36 (0.95-1.94)	1.12 (0.80-1.57) 1.36 (0.95-1.94)	1.13 (0.81-1.58) 1.38 (0.96-1.97)	1.10 (0.79-1.55) 1.30 (0.91-1.85)	1.11 (0.79-1.55) 1.31 (0.92-1.87)
		None or primary school	41		1.51 (0.99-2.30)	1.39 (0.91-2.12)	1.38 (0.90-2.12)	1.40 (0.92-2.15)	1.27 (0.83-1.94)	1.28 (0.83-1.960)
		Health insurance
		Social security + voluntary insurance	23		Ref.	Ref.	Ref.	Ref.	Ref.	Ref.
		Free health care for low-income individuals	33	*	1.32 (0.83-2.10)	1.34 (0.85-2.14)	1.35 (0.85-2.140)	1.34 (0.85-2.14)	1.30 (0.82-2.07)	1.31 (0.823-2.07)
		Social security only	46		2.67 (1.79-3.95)*	2.70 (1.82-4.00)*	2.69 (1.82-3.99)*	2.75 (1.86-4.09)*	2.57 (1.74-3.82)*	2.62 (1.77-3.90)*
		None	60		5.46 (1.51-19.79)* 5.95 (1.63-21.71)*	5.97 (1.63-21.93)*	6.09 (1.66-22.40)*	6.39 (1.75-23.28)* 6.55 (1.77-24.24)*
		Monthly household income (per CU)
		High	16		Ref.	Ref.	Ref.	Ref.	Ref.	Ref.
		Middle	28	*	1.42 (1.01-2.00)*	1.36 (0.97-1.91)	1.36 (0.97-1.92)	1.36 (0.97-1.92)	1.30 (0.92-1.83)	1.30 (0.92-1.84)
		Low	34		1.43 (0.97-2.10)	1.36 (0.92-2.01)	1.37 (0.92-2.02)	1.36 (0.92-2.00)	1.23 (0.83-1.83)	1.23 (0.83-1.83)
		Occupational status
		Working	15		Ref.	Ref.	Ref.	Ref.	Ref.	Ref.
		Unemployed	20		0.87 (0.55-1.37)	0.86 (0.54-1.36)	0.86 (0.55-1.37)	0.86 (0.54-1.36)	0.86 (0.55-1.37)	0.87 (0.55-1.37)
		Retired	42	*	1.18 (0.71-1.96)	1.14 (0.68-1.90)	1.14 (0.68-1.89)	1.13 (0.68-1.89)	1.10 (0.66-1.84)	1.09 (0.66-1.82)
		At home	32		1.23 (0.81-1.85)	1.19 (0.79-1.79)	1.20 (0.79-1.81)	1.18 (0.78-1.785)	1.18 (0.78-1.78)	1.18 (0.79-1.78)
		Student	52		2.

70 (1.54-4.74)* 2.70 (1.53-4.73)* 2.68 (1.53-4.72)* 2.760 (1.57-4.84)* 2.77 (1.58-4.88)* 2.83 (1.61-4.98)* Lives in a couple relationship

	Yes No	20 36	*	1.	Ref.	Ref.	Ref.	Ref.	Ref.	Ref.

64 (1.28-2.11)* 1.71 (1.33-2.21)* 1.70 (1.32-2.19)* 1.70 (1.32-2.20)* 1.68 (1.31-2.17)* 1.67 (1.30-2.15)* Severe functional limitation

	No Yes	24 42	*	1.	Ref.	Ref.	Ref.	Ref.	Ref.	Ref.

59 (1.03-2.44)* 1.57 (1.02-2.42)* 1.57 (1.02-2.42)* 1.59 (1.03-2.45)* 1.59 (1.03-2.44)* 1.61 (1.04-2.47)* Concentration of daily activities within the perceived neighbourhood Individual

	with delayed cervical screening when introduced into the multilevel models: women had a
	greater likelihood of delayed cervical screening if they were living in a neighbourhood where
	the mean income was low (OR=1.63; 95% CI=1.14-2.33; see Model 3c). Furthermore,
	women living in a neighbourhood in Paris per se had a lower likelihood of delayed cervical
	screening than those living in a suburban area, regardless of the other administrative-
	neighbourhood variables introduced in the model (OR=0.62; 95% CI=0.45-0.84; see Model
	3b, for example).
	When these four neighbourhood variables were introduced into the model together, we
	observed that a low mean neighbourhood income and location in Paris per se remained both
	significantly associated with delayed cervical screening (OR=1.60; 95% CI=1.12-2.82, and
	OR=0.68; 95% CI=0.49-0.95, respectively, in Model 4).
	Score (0 to 1)	-	-	1.46 (0.91-2.33)	1.76 (1.09-2.84)*	1.79 (1.10-2.90)*	1.75 (1.09-2.83)*	1.93 (1.20-3.11)*	1.94 (1.21-3.11)*
	Between-area variation:	Null Model		Model 1	Model 2	Model 3a	Model 3b	Model 3c	Model 4
	VarU0j (std. error)	0.1487 ( 0.060)		0.0396 (0.048)	0.0204 (0.041)	0.0164 (0.041)	0.0145 (0.040)	0.0025 (0.036)	0 (0)
	1 Proportion of women who reported not having undergone cervical screening during the previous two years (complex sample
	design taken into account). * p<0.05 ; NS: Not significant (p>0.05)
	Administrative-neighbourhood characteristics and cervical screening
	It can be seen from Table 3 that neither a low practitioner density nor a low proportion of
	people with a recent preventive consultation was statistically associated with delayed cervical
	screening (OR=1.04; 95% CI=0.45-1.16 in Model 3a, and OR=1.10; 95% CI=0.81-1.49 in
	Model 3b). On the other hand, the mean neighbourhood income was statistically associated

Table 4 .

 4 Effect of residential neighbourhood characteristics on delayed cervical screening (after adjustment for age, occupational status, health insurance status, couple relationship status, and functional limitation status), as determined from the multilevel logistic regression model for two subpopulations (according to the concentration of their daily activities within their perceived neighbourhood).

	No cervical screening in the previous two years	Women with daily activities concentrated within their perceived	Women with daily activity space larger than their perceived	p: Interaction Term	Entire adult female population
	after adjustment for age, occupational status, health insurance status, couple relationship status and functional limitation status	neighbourhood n=313 Odds Ratio (95% CI) neighbourhood n=1455	Activity space x neighbourhood variable	n=1768 Odds Ratio (95% CI)
	Location
	Suburban In Paris	Ref. 0.37 (0.20-0.66)*	Ref. 0.62 (0.42 -0.91)*	0.15	Ref. 0.59 (0.43-0.82)*
	Density of general practitioners and
	gynaecologists [tertiles]
	High and intermediate Low	Ref. 2.91 (1.43-5.92)*	Ref. 1.19 (0.85-1.67)	0.03	Ref. 1.28 (0.94-1.75)
	Proportion of people who reported a
	recent preventive consultation [tertiles]
	High and intermediate Low	Ref. 2.42 (1.30-4.48)*	Ref. 1.00 (0.71-1.41)	0.02	Ref. 1.16 (0.85-1.59)
	Mean neighbourhood income (per
	household, per CU) [tertiles]
	High and intermediate Low	Ref. 2.63 (1.28-5.38)*	Ref. 1.61 (1.15-2.25)*	0.33	Ref. 1.66 (1.22-2.26)*
	* p<0.05

Acknowledgements.

We thank the reviewers for their valuable comments and suggestions regarding our manuscript. We also thank Anne-Lise Humain-Lamoure (Univ. Paris I -UMR Geographie-Cités) for her advice concerning the perceived neighbourhoods of the people living in the Paris metropolitan area and Nora Liberalotto (EHESS -CERMES) for her information on the organization of cervical screening in France.

Funding/Support. The SIRS survey was supported by the French National Institute for Health and Medical Research (INSERM), the Institute for Public Health Research (IReSP), the Directorate-General of Health (DGS), the Interministerial Delegation for Urban Affairs (DIV), the European Social Fund, the Regional Council of Ile-de-France, and the City of Paris. Support for Julie Vallée's postdoctoral research was provided by the Fondation de France.

Ethics approval.

This cohort study was approved by France's privacy and personal data protection authority (Commission Nationale de l'Informatique et des Libertés [CNIL]).

No financial disclosure; no conflict of interest.

References ANDEM, 1995. Pratique des frottis cervicaux pour le dépistage et diagnostique biologique du cancer du col de l'utérus. Recommandations et Références Médicale.


Nicolas Decultot

Vincent Velay

Laurent Robert

Gérard Bernhart

Elisabeth Massoni

Behaviour modelling of aluminium alloy sheet for Single Point Incremental Forming

come   L'archive ouverte pluridisciplinaire

INTRODUCTION

This paper refers to the new forming procedures used in sheet metal forming processes, commonly named Single Point Incremental Forming (SPIF) process. It is characterised by a high flexibility which allows an interesting technology improvement to manufacture sheet metal parts in controlling only a simple tool. Different steps of this process are shown in figure 1 [START_REF] Kim | Improvement of formability for the incremental sheet metal forming process[END_REF]. Incremental displacements of the punch in various directions allow to form the sheet in order to provide the required shape. Due to specific strain paths induced by the process and the fact that the plastic zone is strictly limited to the contact region between the tool and the workpiece, forming-limit curves and forming strategies are different from the classical deep drawing or stamping processes. Moreover this technology, in comparison with stamping process avoids using moulds and allows reducing costs when prototypes or batches have to be manufactured. However, Finite Element simulations are time-consuming because of the incremental characteristics of this process [START_REF] He | Effect of FEM choices in the modelling of incremental forming of aluminium sheets[END_REF]. In this paper, we focus on the behaviour of an aluminium alloy 2024-T3 sheet that is forming with a incremental stamping test, process less complex than SPIF. Behaviour model parameters have been identified by tensile tests in 3 directions.

EXPERIMENTAL TESTS

Tensile tests

Simple tensile tests in 3 directions, 0° (x axis), 45° and 90° have been performed and shown a weak anisotropy as shown in figure 2. ABSTRACT: The aim of this work is to identify behaviour models of an aluminium alloy sheet formed by incremental stamping process by using both numerical simulations (FEM) and experimental procedures. The procedure developed will be used in Single Point Incremental Forming (SPIF) in using several original experimental tests allowing to reproduce loading paths close to those induced in the industrial operations and full-field measurements by 3D-Digital Image Correlation (DIC).

Key words: Incremental Forming, Numerical Simulations, 3D-Digital Image Correlation, Behaviour Models Behaviour modelling of aluminium alloy sheet for Single Point Incremental Forming

N. Decultot 1 , V. Velay 1 , L. Robert 1 , G. Bernhart 1 , E. Massoni 2 ,
The x-axis simulated curve is used to identify the model behaviour parameters (see section 3.2)

Incremental stamping test

The incremental stamping test is carried out on a servo-electric tensile testing machine. The experimental set up is slightly modified in order to clamp the sheet and to consider the punch displacement to stamp it. The tool is 30 mm in diameter and presents a spherical active part like shown in figure 3. In this case, punch displacement and global force induced are measured. This device is also instrumented by a cameras stereo-rig in order to perform displacement/strain fields measurements by 3D-Digital Image Correlation (3D-DIC) [START_REF] Robert | Use of 3-D Digital Image Correlation to characterize the mechanical behavior of a Fiber Reinforced Refractory Castable[END_REF] (Vic-3D ® system). The boundary conditions include a punch displacement, which are considered as a rigid body, and a clamping of all the external nodes. The value of the coefficient of friction is chosen equal to 0,2 according to stamping value found in the literature.

NUMERICAL SIMULATIONS

Meshing and boundary conditions

Behaviour model

In a first approach, elasto-plastic model is used. It includes a Von Mises yield criterion and an isotropic hardening law as presented in equations ( 1) and ( 2) . Thus, it is deduced from the relation 0 :

. 0 R R f eq - - = σ (1) ) e - Q(1 R -bλ = (
= ∂ ∂ + ∂ ∂ • • R R f f σ σ . • • ∂ ∂ = σ σ λ : 1 ) ( f h f H
where h=b(Q-R).

Parameters of the elasto-plastic model have been identified with x-axis direction tensile test. The following values have been found: R 0 =300 MPa; Q=250 MPa; b=10; E=70 000 MPa (Young Modulus).

RESULTS

First, some displacement/strain fields measurements obtained by 3D-DIC are shown in figure 5 To explain these differences, several hypothesis are proposed. First of them concerns the study of clamping boundary condition influence.

In the model, the sheet dimensions was reduced to the dimensions of the AOI. The experimental mesh provided by the 3D-DIC computation was projected on the FE mesh as shown in figure 7. For each FE mesh node of the external AOI, the measured displacement vectors of the corresponding experimental node are extracted as shown in figure 8. Thus, the displacement vectors of the AOI external nodes are imposed boundary conditions and the sheet is not more clamped. However, the sheet tensioning in the incremental stamping test beginning can explain that FE response over assess the experimental curve for the lower punch displacement. Figure 10 shows the 3D-DIC measured and the FE obtained sheet z-displacement fields. For an imposed punch displacement of 15 mm, the maximum sheet displacement measured by 3D-DIC is 14.65 mm, about 2.33% error. The sheet thickness diminution (1 mm to 0,8 mm), not considered by shell elements, can explain this difference.

CONCLUSIONS AND DISCUSSIONS

The comparison between experimental and FE displacements fields and evolution of the global force versus punch displacement give very similar results. At this stage, strain fields values are quite different and work is going on about that point. Nevertheless, one can explain these differences:

-Vic-3D software and Abaqus do not use the same method to calculate strains. -The boundary conditions in displacement for the external nodes add actually strains on the sheet border that are not observed in the experimental strain field.

-The behaviour model does not consider damage and sheet anisotropy.

Procedure used in incremental stamping (3D-DIC measures, imposed boundary conditions, model developed) will be used and improved for SPIF. In order to reproduce the strain paths observed in the industrial SPIF process, a SPIF test prototype is actually developed in the laboratory (see figure 11). This prototype is multi-instrumented (3D force sensor, 3D-DIC or multi-vision based DIC) and allows to generate complex shape pieces. The 3D force sensor of this prototype will allow to measure friction between punch and sheet.

Fig. 1 .

 1 Fig. 1. Different steps of the Single Point Incremental Forming

Fig. 2 .

 2 Fig. 2. Tensile tests in 3 directions and simulated tensile test identified by the x-axis direction results (rational curve)

Fig. 3 .

 3 Fig. 3. Incremental stamping test

  Fig. 4. ABAQUS meshing

R

  : Yield strength eq σ : Von Mises equivalent stress Q et b : Materials parameters The plastic multiplier, λ is calculated from the

  Fig. 5. Displacement/strain fields are obtained by 3D-DIC technique Figure 6 presents the evolution of the global force versus punch displacement. FE response over assess the experimental curve for a punch displacement up to 4 mm. Crack initiation of the sheet was observed for a punch displacement up to 15 mm.

Fig. 6 .

 6 Fig. 6. Comparison between the experimental and simulated global force in function of the punch displacement

Fig. 7 .

 7 Fig. 7. FE mesh in blue circle and experimental mesh in red cross

Fig. 9 .

 9 Fig. 9. Comparison between the experimental and the new simulated global force in function of the punch displacement Taking into account true (measured) boundary conditions improves greatly the simulation results.

Fig. 10 .

 10 Fig. 10. 3D-DIC measured (bottom) and the FE results (top) sheet displacement fields for a 15 mm imposed punch displacement

Fig. 11 .

 11 Fig. 11. SPIF test prototype

Research Centre on Tools Materials and Processes (CROMeP) Ecole Mines Albi -81013 ALBI Cedex 9, France URL:http://www.enstimac.fr/recherche/cromep

Centre for Material Forming (CEMEF)Ecole des Mines de Paris -BP 207 -06904 Sophia-Antipolis, Cedex URL: http://www-cemef.cma.fr/eng/welcome.html e-mail: Elisabeth.massoni@ensmp.fr;


Sarah Filippi
email: sarah.filippi@telecom-paristech.fr

Olivier Cappé
email: olivier.cappe@telecom-paristech.fr

Aurélien Garivier
email: aurelien.garivier@telecom-paristech.fr

Olivier Cappé Ltci

Garivier Aurélien

Ltci

Session : Apprentissage par renforcement Optimisme en apprentissage par renforcement et divergence de

We consider model-based reinforcement learning in nite Markov Decision Processes (MDPs), focussing on so-called optimistic strategies. Optimism is usually implemented by carrying out extended value iterations, under a constraint of consistency with the estimated model transition probabilities. In this paper, we strongly argue in favor of using the Kullback-Leibler (KL) divergence for this purpose. By studying the linear maximization problem under KL constraints, we provide an ecient algorithm for solving KLoptimistic extended value iteration. When implemented within the structure of UCRL2, the near-optimal method introduced by [Auer&al, 2009], this algorithm also achieves bounded regrets in the undiscounted case. We however provide some geometric arguments as well as a concrete illustration on a simulated example to explain the observed improved practical behavior, particularly when the MDP has reduced connectivity. To analyze this new algorithm, termed KL-UCRL, we also rely on recent deviation bounds for the KL divergence which compare favorably with the L 1 deviation bounds used in previous works.


A Sinha

S Johnson

C Hunt

H Woolnough

F P Vidal

N W John

P.--F Villard

R Holbray

F Bello

D A Gould

Importance of virtual reality simulators in interventional radiology: the ImaGiNe

Keywords: Simulation, Virtual reality, Face validation, Content validation 1. Purpose

To determine face and content validity of a physics based virtual reality interventional radiology simulator, Imagine--S (Imaging guided interventional needle puncture simulation).

BACKGROUND:

Image--guided needle puncture procedures are commonly performed in interventional radiology (IR) and use hand--eye coordination to direct needles to perform biopsy, nephrostomy and abscess drainage. Currently, the perceptual--motor skills required are learnt in a traditional apprenticeship model, with drawbacks such as involvement of patients, limited case mix and reducing in--hospital work hours of trainees. While animal and fixed models can reproduce many training objectives, they are an imperfect substitute for the 'real patient' experience. Computer based VR simulators can generate variable virtual environments from imaging data with stereo 3D visual presentation and devices to convey feel, realistically mimicking procedures on patients. Application of such simulations to training requires evidence of efficacy. ImaGiNe--S is a computer--based VR training simulator, using virtual environments with stereo 3D visual representation and devices to convey feel, realistically mimicking a percutaneous nephrostomy procedure. Use of such simulator to train IR requires evidence of correct development before studies of efficacy.

TECHNICAL INFORMATION:

The simulator is composed of four components, image processing, haptics rendering, metrics processing and graphic rendering. Each module is described below: Image processing The patient voxel data based is used in the virtual environment. The CT scan Hounsfield units are used to compute the haptic rendering. Moreover, these data have been segmented to extract no--go areas. These two voxel data are used in the simulator either for the haptic rendering of for the metric measurement.

Haptic rendering

The haptic rendering is processing the ultrasound probe and the needle separately. On the one hand, a force response is given when the probe is touching the skin to have a stiff contact so it cannot penetrate the body, at the same time it triggers the ultrasound rendering based on the position and direction of the probe. On the other hand, the needle could penetrate the skin a force feedback is rendered based on the gradient of the voxel the needle is going through.

Metric processing

The simulator provides the user with information about his performance on the simulator. While inserting the needle, a red triangle is displayed showing if the user is touching a no--go area. In the same way, a message is displayed when the target has been reached.

Graphic rendering

The external skin of the patient is rendered in 3D by using specialised glasses. A 2D simulated ultrasound is generated by using CT scan data. Noise and bone shadowing have also been added.

TASK ANALYSIS:

Accurate simulation requires incorporation of data from procedural task analysis into the development phase, including critical procedure steps and their metrics for objective measures of operator competence.

VALIDATION:

Correct reproduction of the simulator task and appropriate fidelity are the cornerstone of producing a simulation that has relevance to a particular training objective. Face validity is the extent to which the simulation appears to be a correct representation of the real world task. Content validity is the degree to which an expert judges the simulator as correctly replicating the physical processes of the real world task. In our study, validation draws on the teams' occupational psychology expertise, along with évaluation by clinical radiologists.

BENEFITS:

Evidence to support the use of VR simulator training and assessment of IR skills could, as an end result, shorten the early learning curve, remove basic skills training from patients, improve safety and efficiency in the NHS, reduce the time to attain and maintain competence, and provide evidence for accreditation and revalidation.

Material and Methods

Local research ethics committee and research governance approvals were sought for a pilot study to carry out face and content validation of Imagine--S. A prospective study was carried out at the CIRSE conference, Copenhagen 2008. 53 subjects used the Imagine--S simulation to perform simulated percutaneous nephrostomy task. Subjects then completed a 5--point Likert scale questionnaire to assess face and content validity (where 1scored = not realistic at all; 3 scored =averagely realistic; and 5 scored =very realistic).

Results

53 participants filled out qualitative questionnaires (92% male and 8% female; 56% trainees and 44% subject matter experts SMEs). Outcomes for face validity showed the following:

• 44% participants thought that the design of Imagine--S was averagely realistic; 32% rated it as moderately realistic • 44% participant rated realism of procedure as averagely realistic with a mean score of 2.9/5 • 40% participant rated response to manipulation of probe, ultrasound image and depth • perception as averagely realistic Outcomes for content validity were rated as moderately average for all critical task steps.

• Use of image guidance to identify the collecting system scored poorly with a third of participants rating it as moderately realistic, and another third rating it as moderately unrealistic. This discrepancy was due to the confusion caused in locating the renal collecting systems which appeared as bone density due to data segmentation errors from contrast CT images. • 50% participants found the optimum position for puncturing and entering the collecting system to be moderately realistic, with a mean score of 3.3/5 • 67% participants found positioning needle on the virtual patient to be moderately realistic, with a mean score of 3.3/5 44/53 (83%) participants considered Imagine--S to be a useful model for training skills for nephrostomy.

Conclusion

The role of virtual reality in Interventional Radiology is positive. ImaGINe--S may be used to train core skills and procedure steps. Review by subject experts has provided invaluable information in the form of repeated face and content validations, contributing tot he re--design of each iteration and hence increasing relevance to the procedure in the real world. From the results gathered, face validity scored in the majority as average and content validity scored as moderately realistic. There is ongoing development still taking place. The limitations found in the hardware during this study are in the process of being addressed. The "feel" from real world data is now incorporated into the existing model. There are now improved metrics for objective assessments used for repeat validation tests including construct validation and transfer of training tests.