Assessing neighborhood disorder: Validation of a three-factor observational scale | The European Journal of Psychology Applied to Legal Context

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Tomás, Antonio López-Quílez" "autores" => array:4 [ 0 => array:4 [ "nombre" => "Miriam" "apellidos" => "Marco" "email" => array:1 [ 0 => "Miriam.Marco-Francisco@uv.es" ] "referencia" => array:2 [ 0 => array:2 [ "etiqueta" => "a" "identificador" => "aff0005" ] 1 => array:2 [ "etiqueta" => "*" "identificador" => "cor0005" ] ] ] 1 => array:3 [ "nombre" => "Enrique" "apellidos" => "Gracia" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "a" "identificador" => "aff0005" ] ] ] 2 => array:3 [ "nombre" => "José M." "apellidos" => "Tomás" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "b" "identificador" => "aff0010" ] ] ] 3 => array:3 [ "nombre" => "Antonio" "apellidos" => "López-Quílez" "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "c" "identificador" => "aff0015" ] ] ] ] "afiliaciones" => array:3 [ 0 => array:3 [ "entidad" => "Department of Social Psychology, University of Valencia, Spain" "etiqueta" => "a" "identificador" => "aff0005" ] 1 => array:3 [ "entidad" => "Department of Methodology of the Behavioral Sciences, University of Valencia, Spain" "etiqueta" => "b" "identificador" => "aff0010" ] 2 => array:3 [ "entidad" => "Department of Statistics and Operations Research, University of Valencia, Spain" "etiqueta" => "c" "identificador" => "aff0015" ] ] "correspondencia" => array:1 [ 0 => array:3 [ "identificador" => "cor0005" "etiqueta" => "⁎" "correspondencia" => "Corresponding author." ] ] ] ] "titulosAlternativos" => array:1 [ "es" => array:1 [ "titulo" => "Evaluación del desorden en los vecindarios: validación de una escala observacional de tres factores" ] ] "resumenGrafico" => array:2 [ "original" => 0 "multimedia" => array:7 [ "identificador" => "fig0005" "etiqueta" => "Figure 1" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr1.jpeg" "Alto" => 1944 "Ancho" => 1870 "Tamanyo" => 235222 ] ] "descripcion" => array:1 [ "en" => "Standardized factor loadings and correlations for the confirmatory factor analyses of the Neighborhood Disorder Observational Scale. Note. All coefficients statistically significant (p < .01); Intoxicat = intoxication; Dealing = drug dealing; Vacant = vacant houses; Vandal. = vandalized buildings; Residen. = residential deterioration; Deter. = deteriorated facilities." ] ] ] "textoCompleto" => "In recent decades, a large body of literature has examined the influence of neighborhood characteristics on a wide range of outcomes, including health, violence, or crime (<a class="elsevierStyleCrossRefs" href="#bib0090">Diez-Roux & Mair, 2010; Kawachi & Berkman, 2003; O’Campo et al., 2015; Sampson, 2012; Sampson, Raudenbush, & Earls, 1997</a>). Among these neighborhood characteristics, the concept of neighborhood disorder has played a central role and has received the attention of scholars from different disciplines like sociology, criminology, social psychology or epidemiology. Neighborhood disorder can be defined as “observed or perceived physical and social features of neighborhoods that may signal the breakdown of order and social control, and that can undermine the quality of life” (<a class="elsevierStyleCrossRef" href="#bib0160">Gracia, 2014</a>, p. 4325). Examples of neighborhood disorder may include behaviors such as prostitution, drug dealing, and fighting in the streets, or physical characteristics such as abandoned cars, vandalized buildings, or litter in the streets (<a class="elsevierStyleCrossRefs" href="#bib0495">Sampson & Raudenbush, 1999; Skogan, 1990; Taylor, 2001; Wilson & Kelling, 1982</a>).The concept of neighborhood disorder can be linked to social disorganization theories and their idea that structural characteristics of neighorhoods, like concentrated disadvantage, can undermine social control and increase levels of violence, crime, and other negative outcomes (<a class="elsevierStyleCrossRefs" href="#bib0160">Gracia, 2014; Kingston, Huiziga, & Elliot, 2009; Kubrin & Weitzer, 2003; Maimon & Browning, 2010; Park, Burgess, & McKenzie, 1925; Sampson et al., 1997; Shaw & McKay, 1942; Wilson, 1987</a>). Also, the Broken Windows Theory of urban decay has been of particular relevance for the wide appeal of the concept of neighborhood disorder (<a class="elsevierStyleCrossRef" href="#bib0595">Wilson & Kelling, 1982</a>). According to this perspective, physical and social cues of neighborhood disorder signal the breakdown of formal and informal social controls leading to further disorder and crime (<a class="elsevierStyleCrossRefs" href="#bib0160">Gracia, 2014; Perkins, Meeks, & Taylor, 1992; Sampson & Raudenbush, 1999; Skogan, 1990; Taylor, 1997, 2005; Toet & van Schaik, 2012; Wei, Hipwell, Pardini, Beyers, & Loeber, 2005; York Cornwell & Cagney, 2014</a>). According to <a class="elsevierStyleCrossRef" href="#bib0160">Gracia (2014)</a> “as neither residents nor external agencies (e.g., police and other authorities) are able or willing to intervene and maintain social order, more disorder is facilitated, and criminal activity is attracted” (p. 4325). Neighborhood disorder would also trigger a number of community processes like fear, insecurity, powerlessness, or mistrust that lead residents to disinvest in and withdraw from community life, increasing social disorganization and neighborhood decline (<a class="elsevierStyleCrossRefs" href="#bib0145">Geis & Ross, 1998; Kawachi, Kennedy, & Wilkinson, 1999; Kim & Conley, 2011; Ross, Mirowsky, & Pribesh, 2001; Skogan, 1986, 1990</a>). In this regard, neighborhood disorder has been linked to urban decay, concentration of social problems, racial or ethnic segregation, social integration, confidence in the police, or public social control strategies like reporting crime (<a class="elsevierStyleCrossRefs" href="#bib0170">Gracia, Garcia, & Musitu, 1995; Gracia & Herrero, 2006a, 2006b, 2007; Perkins et al., 1992; Perkins & Taylor, 1996; Ross & Mirowsky, 1999; Skogan, 1990; Taylor, 1997; Toet & van Schaik, 2012</a>).Although neighborhood disorder has traditionally been studied in relation to street-level outcomes, an increasing body of literature has also examined its influence on processes and outcomes that occur “behind closed doors” (<a class="elsevierStyleCrossRef" href="#bib0610">Wright & Benson, 2011</a>), such as parental socialization practices (<a class="elsevierStyleCrossRefs" href="#bib0165">Gracia, Fuentes, García, & Lila 2012; Lila & Gracia, 2005; McDonell, 2007; Roosa et al., 2005; Tendulkar, Buka, Dunn, Subramanian, & Koenen, 2010; White, Roosa, Weaver, & Nair, 2009; Worton et al., 2014</a>), child maltreatment (<a class="elsevierStyleCrossRefs" href="#bib0065">Coulton, Crampton, Irwin, Spilsbury, & Korbin, 2007; Coulton, Korbin, & Su, 1999; Freisthler, Bruce, & Needell, 2007; Freisthler, Merritt, & LaScala, 2006; Garbarino & Sherman, 1980; Gracia & Musitu, 2003; Lila & Gracia, 2005; Martin-Storey et al., 2012</a>), or intimate partner violence (<a class="elsevierStyleCrossRefs" href="#bib0075">Cunradi, 2007, 2009; Gracia, Herrero, Lila, & Fuente, 2009; Gracia, López-Quílez, Marco, Lladosa, & Lila, 2014, 2015; Kirst, Lazgare, Zhang, & O’Campo, 2015</a>; see <a class="elsevierStyleCrossRefs" href="#bib0010">Beyer, Wallis, & Hamberger, 2015; Pinchevsky & Wright, 2012</a>, for reviews).More recently, research on social disorder has also examined its influences on individual well-being indicators like subjective well-being, psychological distress, anxiety, or depression (<a class="elsevierStyleCrossRefs" href="#bib0135">García-Ramírez, Balcázar, & de Freitas, 2014; Herrero, Gracia, Fuente, & Lila, 2012; Hill & Angel, 2005; Hombrados-Mendieta & López-Espigares, 2014; Latkin & Curry, 2003; Latkin, German, Hua, & Curry, 2009; O’Campo et al., 2015; Ross & Mirowsky, 2009</a>), and how this may affect negative health behaviors such as low physical activity, heavy drinking, smoking, or obesity (<a class="elsevierStyleCrossRefs" href="#bib0030">Burdette & Hill, 2008; Echeverría, Diez-Roux, Shea, Borrell, & Jackson, 2008; Hill, Ross, & Angel, 2005; Keyes et al., 2012; O’Campo et al., 2015; Ross & Mirowsky, 2001</a>). Research has also examined the association between neighborhood disorder and different public health issues such as health service usage, low body weight at birth in children, injuries, sexually transmitted diseases, loss of physical function in older adults, and mortality risk (<a class="elsevierStyleCrossRefs" href="#bib0005">Balfour & Kaplan, 2002; Cohen et al., 2000, 2003; Martin-Storey et al., 2012; Pearl, Braveman, & Abrams, 2001; Winkleby & Cubbin, 2003</a>).Assessing Neighborhood DisorderAssessment of neighborhood disorder tipycally considers two types of disorder, physical and social (<a class="elsevierStyleCrossRefs" href="#bib0455">Robinson, Lawton, Taylor, & Perkins, 2003; Skogan & Maxfield, 1981; Taylor & Shumaker, 1990</a>). Physical disorder refer to urban landscapes with high levels of decay and deterioration. For example, abandoned houses, graffiti, trash on the streets, abandoned cars, used needles, and vacant lots would exemplify physical disorder (<a class="elsevierStyleCrossRefs" href="#bib0020">Brunton-Smith, 2011; Garvin, Cannuscio & Branas, 2013; Robinson et al., 2003; Sampson & Raudenbush, 1999; Skogan, 1990; Taylor, 2001</a>, <a class="elsevierStyleCrossRef" href="#bib0570">Toet & van Schaik, 2012</a>). Some scholars, however, make a further distinction between physical disorder and physical decay: physical disorder would refer to features like dirt in the streets (litter, bottles, condoms), graffiti, abandoned cars, etc. (i.e., behavioral manifestations), whereas physical decay would refer to structural characteristics that can arise from lack of institutional investments and have long term effects, such as abandoned buildings, burn-out houses, badly deteriorated recreational facilities, etc. (<a class="elsevierStyleCrossRefs" href="#bib0485">Sampson, 2009; Sampson & Raudenbush, 2004</a>). As <a class="elsevierStyleCrossRef" href="#bib0500">Sampson and Raudenbush (2004)</a> argue, it is important to make this distinction because physical disorder is “limited to behavioral manifestations (e.g., graffiti, garbage in the streets) that can be conceptually decoupled from structural resources” (p. 326). Social disorder refer, on the other hand, to events in public places seen as potentially threatening, and can be exemplified by the presence of people taking drugs or alcohol in the street, drug dealing, fights and arguments, presence of homeless people, public drunkenness, street prostitution, high levels of police activity, and other criminal or not criminal activities that create a sense of danger (<a class="elsevierStyleCrossRefs" href="#bib0160">Gracia, 2014; Gracia & Herrero, 2007; Robinson et al., 2003; Ross & Mirowsky, 2001; Sampson, 2009; Sampson & Raudenbush, 2004</a>). Despite some studies suggesting that physical and social disorder may overlap, being order and disorder two ends of a single continuum (<a class="elsevierStyleCrossRefs" href="#bib0465">Ross & Mirowsky, 1999; Xu, Fielder, & Flaming, 2005</a>), most studies support the distinction between physical and social disorder (<a class="elsevierStyleCrossRefs" href="#bib0025">Brunton-Smith, Sindall, & Tarling, 2010; LaGrange, Ferraro, & Supancic, 1992; Sampson & Raudenbush, 2004; Taylor & Shumaker, 1990</a>).In order to assess neighborhood disorder, researchers generally use three different approaches (<a class="elsevierStyleCrossRefs" href="#bib0365">McDonell & Waters, 2011; Mooney et al., 2014</a>). One approach, based on a more objective perspective, draws from neighborhood information from governmental or commercial data sources (<a class="elsevierStyleCrossRefs" href="#bib0045">Cerdá et al., 2009; McDonell, 2007; Mooney et al., 2014</a>). Although these data is freer from the variability and subjectivity of subjective perceptions of disorder (<a class="elsevierStyleCrossRef" href="#bib0285">Kubrin, 2008</a>), however, this information is “often collected for administrative purposes, may not fully capture the construct of research interest, and may be collected at a spatial resolution that is not optimal for research purposes” (<a class="elsevierStyleCrossRef" href="#bib0370">Mooney et al., 2014</a>, p. 626-627). A second, and widely used, approach is based on resident's perceptions of their neighborhood physical or social characteristics. A number of limitations have been noted, however, regarding this approach, including “same source bias” (e.g., same source reporting perceived neighborhood disorder and related outcomes), confusion with other psychological constructs (e.g., fear of crime), or the influence of stereotypes and neighborhood prejudices (e.g., racial, ethnic, or socioeconomic composition) in perceptions of disorder (<a class="elsevierStyleCrossRefs" href="#bib0040">Caughy, O’Campo, & Patterson, 2001; Duncan & Raudenbush, 1999; Gómez, Johnson, Selva, & Sallis, 2004; Mooney et al., 2014; Sampson, 2009; Sampson & Raudenbush, 1999, 2004; Schaefer-McDaniel, Caughy, O’ Campo, & Gearey, 2010</a>). Finally, a third approach, that aims to overcome the above limitations, emphasizes the importance of using direct and systematic observations of neighborhood characteristics by trained researchers (<a class="elsevierStyleCrossRefs" href="#bib0115">Franzini, Caughy, Nettles, & O’Campo, 2008; McDonell, 2007; McDonell & Waters, 2011; Neil, Parke, & McDowell, 2001; Raudenbush & Sampson, 1999; Reiss, 1971; Sampson & Raudenbush, 1999</a>). This approach aims to obtain objective measures of neighborhood conditions, to capture a wide range of factors, which are not always available otherwise, and to allow its replication in other contexts (<a class="elsevierStyleCrossRefs" href="#bib0040">Caughy et al., 2001; Cohen et al., 2000; Franzini et al., 2008; McDonell & Waters, 2011; Sampson & Raudenbush, 2004; Taylor, 2001</a>).The Present StudyThis study aims to add to this body of research by validating an observational measure of neighborhood disorder in the context of a European city that may differ from the culture and structure of Anglo-Saxon cities where most of this type of measures have been developed and validated (<a class="elsevierStyleCrossRefs" href="#bib0335">Le Galès & Zagrodzki, 2006; Summers, Cheshire, & Senn, 1999</a>). The availability of a reliable and valid measure of neighborhood disorder in this context may be an important addition to the growing body of literature exploring neighborhood effects (<a class="elsevierStyleCrossRef" href="#bib0490">Sampson, 2012</a>). To this end, independent observations by trained raters of neighborhood disorder will be conducted using small-areas of the city as the ecological units (i.e., census block groups, which are the smallest administrative sections of the city available). By using the smallest posible geographical units of the city we expect greater homogeneity of neighborhood characteristics (<a class="elsevierStyleCrossRef" href="#bib0400">Ocaña-Riola et al., 2008</a>). Also, by using all census block groups of the city we will obtain greater variability and, as neighborhood characteristics tend to cluster in space, this will provide the possibility to explore the clustering of these characteristics for validation purposes (<a class="elsevierStyleCrossRef" href="#bib0200">Gracia et al., 2014</a>).This study presents data on the development and preliminary validation of an observational instrument to assess neighborhood disorder. The specific objectives of the study are: (1) to test the inter-rater reliability of the scale; (2) to test the factorial validity of the scale using confirmatory factor analysis: we expect a factorial structure reflecting three theoretically a priori factors, physical disorder, social disorder, and physical decay (<a class="elsevierStyleCrossRef" href="#bib0500">Sampson & Raudenbush, 2004</a>); (3) to test the reliability of the scale by means of the composite reliability index; and (4) to test the criterion-related validity of the scale also employing structural equations. Drawing from social disorganization theory we expect associations between neighborhood disorder and three neighborhood structural characteristics, central in this theoretical perspective: neighborhood socioeconomic status, immigrant concentration, and residential instability (<a class="elsevierStyleCrossRefs" href="#bib0040">Caughy et al., 2001; Jones, Pebley, & Sastry, 2011; Kubrin & Weitzer, 2003; McDonell & Waters, 2011; Mooney et al., 2014; Sampson et al., 1997; Sampson & Raudenbush, 1999</a>). Also, for validation purposes, a spatial perspective will be applied. As we expect that disordered neighborhoods will cluster in space, rather than be randomly distributed in the city, spatial correlation analyses will be conducted to test whether neighborhood disorder shows a significant spatial pattern (<a class="elsevierStyleCrossRefs" href="#bib0015">Bruinsma, Pauwels, Weerman, & Bernasco, 2013; Gracia et al., 2015; Quick, 2013; Veysey & Messner, 1999</a>).MethodSampleThis study was conducted in the city of Valencia, the third largest city of Spain. As proxy of neighborhood units we used census block groups that were the smallest administrative unit of the city available. Census block groups can be defined as walkable areas within a few number of city blocks and as they are smaller than census tracks, they are particularly appropriate for neighborhood studies (<a class="elsevierStyleCrossRefs" href="#bib0200">Gracia et al., 2014; Sampson & Raudenbush, 2004</a>). Observations by trained raters were conducted in each of the 552 census block groups in which the city is divided. The total population for these census block groups was 736,580 inhabitants (2013 data), with an average of 1,334 inhabitants per census block group (ranging from 630 to 2,845).MeasuresNeighborhood disorder observation scale. A neighborhood disorder scale was initially constructed with a total of 20 items based on three dimensions of neighborhood disorder proposed by Sampson and Raudenbush (<a class="elsevierStyleCrossRef" href="#bib0500">Sampson & Raudenbush, 2004</a>). Thus, the scale included three theoretically motivated subscales measuring physical disorder, social disorder, and physical decay. Physical disorder was defined by 8 items: cigarettes in the street, trash in the street, empty bottles in the street, graffiti, abandoned cars, used condoms and syringes in the street, and political or protest message graffiti. Social disorder was defined by 7 items: adults or young people loitering, people drinking alcohol in public, gangs, public intoxication, adults fighting or arguing, selling drugs, and street prostitution. Physical decay was defined by 5 items: vacant or abandoned houses, abandoned commercial buildings, vandalized and run-down buildings, deteriorated residential units and deteriorated recreation places. The observations are rated on a 5-point response scale (from 0 = no presence, to 4 = highly present). Two trained raters walked each census block group in order to complete the observational scale. All observations were made during business hours.Criterion-related validity measures. Drawing from social disorganization theory, to test criterion-related validity we will explore relationships between neighborhood disorder and three neighborhood characteristics measured at census block group level: neighborhood socioeconomic status, immigrant concentration, and residential instability. The City of Valencia Statistics Office provided these data for each census block group. Neigbhorhood socioeconomic status was measured with an indicator created through factor analysis (this factor included educational level, property value, percentage of high-end cars, and financial and commercial activities). Immigrant concentration was the percentage of immigrant population in each census block, and residential instability was the proportion of the population who had moved into or out of each census block group during the previous year (rate per 1,000 inhabitants).Statistical AnalysisTo measure inter-rater reliability, two pairs of trained undergraduate students walked a random sample of the census block groups. They observed a subset of 15% of them aproximately (N = 86). Inter-rater reliability scores were computed per each of the three scales by calculating intraclass correlation coefficients (ICC) due to the quantitative nature of data. This analysis was performed with SPSS 22 for Windows.Several competing confirmatory factor analyses (CFA) were specified, estimated and tested in Mplus 7.3. According to the ordinal nature of the data and its non-normality, WLSMV (weighted least squares mean and variance corrected) estimation was used, the one recommended in the literature (<a class="elsevierStyleCrossRef" href="#bib0110">Finney & DiStefano, 2006</a>). Several criteria were used to assess goodness-of-fit: (a) the chi-square statistic, (b) the comparative fit index (CFI), and (c) the root mean squared error of approximation (RMSEA). A model with a CFI of .95 or larger and a RMSEA of .08 or lower would be indicative of very good fit between the hypothesized model and the data (<a class="elsevierStyleCrossRef" href="#bib0235">Hu & Bentler, 1999</a>). Nevertheless, overall fit must be accompanied by a careful diagnosis of the analytical fit (parameter estimates) in the model in order to not blindly use the aforementioned thresholds (<a class="elsevierStyleCrossRef" href="#bib0280">Kline, 2011</a>). For model comparison, a modeling approach that uses practical fit indices to determine the overall adequacy of a fitted model has been used as recommended by <a class="elsevierStyleCrossRef" href="#bib0050">Cheung and Rensvold (2002)</a> or <a class="elsevierStyleCrossRef" href="#bib0345">Little (1997)</a>. From this point of view, if a parsimonious model evidences adequate levels of practical fit, then it is preferred over the more complex model. Usually, CFI differences (ΔCFI) are used to evaluate measurement invariance. CFI differences lower than .01 (<a class="elsevierStyleCrossRef" href="#bib0050">Cheung & Rensvold, 2002</a>) or .05 (<a class="elsevierStyleCrossRef" href="#bib0345">Little, 1997</a>) are usually employed as cut-off criteria.Additionally, internal consistency of the dimensions in the scale has been estimated with the composite reliability index (CRI). Although Cronbach's coefficient alpha is the most widely used estimator of internal consistency, it has been criticized as being only completely appropriate with essentially tau-equivalent items (and tests) and also by being a lower bound for the true reliability (<a class="elsevierStyleCrossRef" href="#bib0445">Raykov, 2004</a>). More explicitly, a tau-equivalent test assumes all items measure the same latent variable, on the same scale, with the same degree of precision, with all true scores being equal (<a class="elsevierStyleCrossRef" href="#bib0210">Graham, 2006</a>). When tau-equivalence does not hold, alpha will over- or under-estimate (more often the latter) the population value. An alternative to the coefficient alpha is the CRI, which is usually calculated using estimates from confirmatory factor analyses (<a class="elsevierStyleCrossRef" href="#bib0210">Graham, 2006</a>). Accordingly, the more adequate CRI was employed.Criterion-related validity was established by correlating neighborhood disorder factors with other neighborhood constructs theorically linked in the literature (<a class="elsevierStyleCrossRefs" href="#bib0160">Gracia, 2014; Gracia et al., 2015; Kubrin & Weitzer, 2003; Sampson & Raudenbush, 1999; Sampson et al., 1997; Shaw & McKay, 1942</a>). This correlation was obtained within the context of a structural equation modeling in order to prevent as much as possible the correlation attenuation due to measurement error. Specifically, neighborhood disorder was correlated to neighborhood socioeconomical status, immigrant concentration, and residential instability (see Measures section).To test criterion-related validity we also used a spatial methodology approach. To assess spatial autocorrelation, we computed Moran's I (<a class="elsevierStyleCrossRef" href="#bib0375">Moran, 1950</a>) per each of the three subscales or factors, considering as the observation the midpoint of each of the census block groups. We expected a significant spatial distribution of neighborhood disorder, rather than a random distribution, because we expect that disorder, as other neighborhood characteristics, will show a tendency towards spatial clustering (<a class="elsevierStyleCrossRefs" href="#bib0015">Bruinsma et al., 2013; DiMaggio, 2015; Quick, 2013; Veysey & Messner, 1999</a>).ResultsInter-Rater ReliabilityIntraclass correlation coefficients were computed to assess inter-rater agreement for the three subscales (see <a class="elsevierStyleCrossRef" href="#bib0405">Odgers, Caspi, Bates, Sampson, & Moffit, 2012</a>, for a similar approach). Intraclass correlations ranged from .25 to .71 (see <a class="elsevierStyleCrossRef" href="#tbl0010">Table 1</a>). <a class="elsevierStyleCrossRef" href="#bib0300">Landis and Koch's (1977)</a> criteria were used to interpret results regarding inter-rater agreements: < .20 slight, .21 – .40 fair, .41 – .60 moderate, .61 – .80 substantial, and .81 – 1 almost perfect agreement. Our results indicated fair to substantial levels of agreement between raters (<a class="elsevierStyleCrossRef" href="#bib0300">Landis & Koch, 1977</a>). Social disorder obtained the lowest value and physical disorder and physical decay showed similar results.<elsevierMultimedia ident="tbl0010"></elsevierMultimedia>Confirmatory Factor AnalysisThree a priori competing models were specified. The theoretical model that supports the content validity of the scale a priori hypothesizes three dimensions: physical disorder, social disorder, and physical decay. Indicators were developed to tap these three theoretical dimensions. However, there was doubt about whether two of these dimensions could be too overlapped to have discriminant validity: physical disorder and physical decay. Accordingly, another a priori model was specified with two dimensions: social disorder and all the indicators of physical disorder and physical decay specified to load onto a single dimension. Finally, the most parsimonious latent structure, a one-factor model underlying all the indicators, was also specified. Goodness-of-fit indices for these three a priori models are shown in <a class="elsevierStyleCrossRef" href="#tbl0015">Table 2</a>. Model fit for the three models was extremely poor, and none of them could be retained as a good approximation to the observed data. Nevertheless, the three-factor model showed a relative better fit compared to the other two models: ΔCFI = .06, compared to the one-factor model and ΔCFI = .04, compared to the two-factor model. Taking this information into account, plus the fact that the theoretical model that supports the scale was three-dimensional, this model was retained for further psychometric scrutiny.<elsevierMultimedia ident="tbl0015"></elsevierMultimedia>A careful look at the factor loadings, together with the lack of variability in some indicators, allows to remove some of them. Those removed lacked variability and/or had poor consistency with their dimension. The final version of the questionnaire was presumed to measure three factors (physical disorder, social disorder, and physical decay) with 5, 6, and 4 indicators each (see Appendix). This depurated version of the original scale was tested and its goodness-of-fit indices are shown in <a class="elsevierStyleCrossRef" href="#tbl0015">Table 2</a>. There was a huge improvement in model fit, and it can be said that the model seems to adequately represent the observed data. Factor loadings are shown in <a class="elsevierStyleCrossRef" href="#fig0005">Figure 1</a>. They were all statistically significant (p < .01) and, in general, pretty large. These results are indicative of good analytical fit.<elsevierMultimedia ident="fig0005"></elsevierMultimedia>Internal ConsistencyReliability (internal consistency) estimates were calculated for each dimension or factor in the scale. The calculated reliability estimates were composite reliability indices (CRI), as already mentioned in the method section. All the CRI were large, indicating a good reliability for all the dimensions. Specifically, CRI for physical disorder was .83, .82 was the estimate for social disorder, and .82 the internal consistency estimated for physical decay.Criterion-Related ValidityFinally, evidence of criterion-related validity was also found. Three criteria were used (neighborhood socioeconomical status, immigrant concentration, and residential instability). The relationship between the criteria and the latent variables were calculated at the latent level, not the observed one. A first structural model included the measurement model found to fit well to the data, plus the first criterion (neighborhood socioeconomical status). Again, this structural model fitted the data well, χ2(99) = 339.78, p < .001; CFI = .93, RMSEA = .066 [.059 - .074]. The correlations between neighborhood socioeconomic status and the criteria and the factors were: ρ = -.13, p < .01 with physical disorder; ρ = .04, p > .05 with social disorder; and ρ = -.29, p < .01 with physical decay. With respect to immigrant concentration, the structural model also adequately fitted the data, χ2(99) = 309.38, p < .001; CFI = .93, RMSEA = .062 [.054 - .070]. The correlations among the criterion and the factors were: ρ = .44, p > .05 with physical disorder; ρ = .13, p < .05 with social disorder; and ρ = .21, p < .01 with physical decay. Finally, a third structural model was specified and tested to relate the three factors with residential instability. Again the model fitted the data well, χ2(99) = 333.54, p < .001; CFI = .92, RMSEA = .066 [.058 - .073], and its correlations with the factors were: ρ = .05, p > .05 with physical disorder; ρ = .15, p < .05 with social disorder; and ρ = .22, p < .01 with physical decay.Also, for criterion-related validity purposes, tests for spatial correlation were conducted for the three dimensions. Results showed spatial autocorrelation in the three scales as all Moran's I values were positive and significant (p < .001). Moran's I values for the three measures were .20 for social disorder, .39 for physical decay, and .49 for physical disorder, indicating a stronger spatial pattern for physical disorder and physical decay than for social disorder. These results indicate a positive non-random distribution of all types of neighborhood disorder in the city (i.e., rather than being randomly distributed across the city, they tend to cluster in space).DiscussionIn this paper we describe the development and the psychometric properties of a preliminary validation of an observational scale assessing neighborhood disorder. This scale was implemented in the city of Valencia (Spain), using independent observations of all census block groups of the city conducted by trained raters. In general, results have shown that this scale is a psychometrically sound and valid instrument to assess three neighborhood disorder dimensions: physical disorder, social disorder, and physical decay.Results regarding inter-rater reliability showed fair to substantial levels of agreement (<a class="elsevierStyleCrossRef" href="#bib0300">Landis & Koch, 1977</a>), with stronger agreements for physical disorder and physical decay factors, and lower inter-rater reliability for social disorder. Although these results are slightly lower than in other studies (e.g., <a class="elsevierStyleCrossRefs" href="#bib0040">Caughy et al., 2001; Franzini et al., 2008; Jones et al., 2011</a>), they are, however, comparable to others (e.g., <a class="elsevierStyleCrossRefs" href="#bib0370">Mooney et al., 2014; Wei et al., 2005</a>). As to why social disorder showed lower levels of agreement, one possibility is that social disorder cues such as fights or public intoxication tend to be less stable over time (e.g., depending on the time of the day) than other physical features of neighborhoods, like those indicating physical decay and disorder, that are more temporally stable (<a class="elsevierStyleCrossRef" href="#bib0240">Jones et al., 2011</a>).With respect to the factor structure of the observational scale, our analyses aimed to validate a three theoretically-based neighborhood disorder dimensions (<a class="elsevierStyleCrossRef" href="#bib0500">Sampson & Raudenbush, 2004</a>). To this end, several competing confirmatory factor analyses were first estimated and discarded, yielding a final and depurated version of the scale with good analytical fit. This final scale supported a three-factor model measuring physical disorder, social disorder, and physical decay, as theorized by <a class="elsevierStyleCrossRef" href="#bib0500">Sampson and Raudenbush (2004)</a>.This final three-factor model was obtained after removing some items for their low variability or poor consistency with their dimension. Although these items are usually present in other scales measuring neighborhood disorder, however, indicators such as abandoned cars, used condoms and syringes (physical disorder), prostitution (social disorder), or abandoned commercial buildings (physical decay) were discarded in the final model. The presence of these items was very low and, in the case of syringes, there was no presence at all in any of the census block groups observed. Although the time of the observation may have influenced the low presence of some of these indicators (e.g., prostitution), another posible explanation is that, given the characteristics of cities like Valencia, with high density in a relative small area (<a class="elsevierStyleCrossRefs" href="#bib0335">Le Galès & Zagrodzki, 2006; Summers et al., 1999</a>), some of these indicators could be more present in the outskirts of the city, and therefore outside of the boundaries where the observations were made. This also suggests that differences between the present scale and others developed elsewhere may reflect context-specific features of the cities. Given that these results may be context-dependent, we do not favour the uncritical use of the short-version of the originally proposed scale destilled for this particular study. On the contrary, careful theoretical considerations previous to the use of this scale in other cities should consider whether some (or all) of the items removed could have enough variability and importance as to be included in the instrument. Clearly, a subsequent depuration of the scale according to its psychometric properties is always possible. On the other hand, results for internal consistency of the final three-factor scale by confirmatory analyses also supported its reliability, with CRI values between .82 and .83 for the three scales.Two different criterion-related validity tests of this observational measure of neighborhood disorder were conducted. For the first one, and drawing from social disorganization theory, we explored associations with three criteria tapping neighborhood characteristics central to this theoretical perspective: neighborhood socioeconomic status, immigrant concentration, and residential instability, masured at the census block group level. As expected, correlations between measures of neighborhood disorder and these structural characteristics of neighborhoods were mostly in the expected direction (<a class="elsevierStyleCrossRefs" href="#bib0290">Kubrin & Weitzer, 2003; Sampson & Raudenbush, 1999; Sampson et al., 1997</a>), although with stronger associations for physical decay. For example, high levels of physical decay were significantly associated with lower neighborhood socioeconomic status, higher rates of immigrant concentrarion, and higher residential instability. Social disorder was positively related to levels of immigrant concentration and residential instability, but its association with neighborhood socioeconomic status was not statistically significant. Physical disorder was also negatively related to neighborhood socioeconomic status; however, associations with immigrant concentration and residential instability did not reach significance. These results partly support previous research where significant associations between disorder and a number of neighborhood characteristics were also found, especially those regarding the relationship between physical disorder and decay and neighborhood socioeconomic indicators (<a class="elsevierStyleCrossRefs" href="#bib0040">Caughy et al., 2001; Jones et al., 2011; McDonell & Waters, 2011; Mooney et al., 2014; Sampson & Raudenbush, 1999</a>). Also, some of our results support studies that fail to find a significant relationship between physical disorder and residential instability (<a class="elsevierStyleCrossRef" href="#bib0495">Sampson & Raudenbush, 1999</a>), or between physical disorder and immigrant concentration (<a class="elsevierStyleCrossRef" href="#bib0240">Jones et al., 2011</a>). It is interesting to note that physical decay was associated with all neighborhood characteristics (socieconomic status, immigrant concentration, and residential instability), suggesting that differentiating between physical disorder and physical decay is an important theoretical distinction that may provide a more detailed analysis when assessing neighborhood disorder and exploring its relationships with different outcomes and processess (<a class="elsevierStyleCrossRefs" href="#bib0485">Sampson, 2009; Sampson & Raudenbush, 2004</a>).As we expected that disordered neighborhoods would tend to cluster together in space (<a class="elsevierStyleCrossRefs" href="#bib0015">Bruinsma et al., 2013; DiMaggio, 2015; Quick, 2013; Veysey & Messner, 1999</a>), for the second criterion-related validity test we used a spatial analytical approach to assess the spatial distribution of the different types of neighborhood disorder across all census block groups observed. Results showed that the three types of disorder (physical disorder, social disorder, and physical decay) were spatially clustered, confirming that they were not randomly distributed in the city. This reflects the existence of different areas of the cities where neighborhood disorder tends to concentrate and shows that this neighborhood risk factor tend to cluster in space. These results support the idea that different manifestations of neighborhood disorder, as other characteristics of the cities, are not randomly distributed in space. As illustrated by a growing body of literature linking neighborhood disorder with a wide array of outcomes, including crime, violence, or health, the spatially patterned nature of this risk factor makes more likely that related outcomes will also be spatially patterned (<a class="elsevierStyleCrossRefs" href="#bib0085">Cunradi, Mair, Ponicki, & Remer, 2011; Diez-Roux & Mair, 2010; Freisthler et al., 2007; Gracia et al., 2015; Kawachi & Berkman, 2003; Law, Quick, & Chan, 2014; O’Campo et al., 2015; Sampson, 2012</a>).Finally, this study has both strengths and limitations. Among the strenghts, the use of independent observations of neighborhood conditions, rather than residents’ subjective perceptions, allows to overcome some of the limitations noted in the literature regarding this later approach (<a class="elsevierStyleCrossRefs" href="#bib0040">Caughy et al., 2001; Mooney et al., 2014; Sampson & Raudenbush, 1999; Schaefer-McDaniel et al., 2010</a>). Relatedly, for the observation of neighborhood disorder at the level of ecological units (rather than the personal level), we also use a high-resolution approach. We used the smallest administrative units available (i.e., census block groups) that allow greater homogeneity and precision than lower resolutions such as census tracks or postal codes, commonly used in other neighborhood studies (<a class="elsevierStyleCrossRefs" href="#bib0010">Beyer et al., 2015; Bursik, Grasmick, & Chamlin, 1990; Kaufman, Dole, Savitz, & Herring, 2003; Campo, Xue, Wang, & Caughy, 1997</a>). By using small-area units, we also reduced potential ecological bias, as this resolution is closer to the individual level (<a class="elsevierStyleCrossRefs" href="#bib0205">Gracia et al., 2015; Lawson, 2006</a>, <a class="elsevierStyleCrossRef" href="#bib0400">Ocaña-Riola et al., 2008</a>). We used census block groups in our study, which substantially reduced this potential bias. Finally, we used all census block groups of the city, rather than selecting only a sample of them, which provided greater variablity and the possibility to explore potential significant spatial patterns in the distribution of neighborhood disorder across the city (<a class="elsevierStyleCrossRefs" href="#bib0040">Caughy et al., 2001; Mooney et al., 2014</a>). In this regard, the use of spatial methods to complement the criterion-related validity of our observational scale is an important addition to the existing literature, as neighborhoods, from this perspective, are not treated as independent units (<a class="elsevierStyleCrossRefs" href="#bib0155">Gorman, Gruenewald, & Waller, 2013; Mooney et al., 2014; Morenoff, Sampson, & Raudenbush, 2001</a>). Although widely used in epidemiological studies (<a class="elsevierStyleCrossRef" href="#bib0330">Lawson, 2009</a>), and despite its advantages, this methodological approach is still uncommon in neighborhood studies, and future research would clearly benefit from incorporating a spatial perspective (<a class="elsevierStyleCrossRefs" href="#bib0085">Cunradi et al., 2011; Gracia et al., 2014, 2015; Law & Quick, 2013; Law et al., 2014; Sparks, 2011</a>). As for limitations, as noted above, some measures of neighborhood disorder may have been affected by the time of the day they were observed. Our observations were limited to business hours, and the same places may have shown different characteristics at night (<a class="elsevierStyleCrossRef" href="#bib0040">Caughy et al., 2001</a>). Future research would benefit from including different observations during the day, and revisiting the same areas during night hours. Also, other neighborhood indicators such as trash in the streets may be present only at specific moments, and repeated obervations of the same area would be advisable, although clearly more costly (<a class="elsevierStyleCrossRef" href="#bib0580">Wei et al., 2005</a>). In this regard, recently new technologies, such as virtual environments, or Google Street View, provide powerful and easy accesible tools that may help to enhance neighborhood research (<a class="elsevierStyleCrossRefs" href="#bib0405">Odgers et al., 2012; Toet & van Schaik, 2012</a>).In conclusion, this paper provides evidence of a reliable and valid observational measure to assess neighborhood disorder. Adequate measures to assess neighborhood characteristics are important research and intervention tools, as they are key to better understanding neighborhood proceses, as well as to evaluate related outcomes and monitor changes after grass-roots efforts or oficial initiatives to reduce neighborhood inequalities.Conflict of InterestThe authors of this article declare no conflict of interest.Financial SupportThis research was supported by the Spanish Ministerio de Economía y Competitividad (PSI2014-54561-P). Miriam Marco was supported by the FPU program of the Spanish Ministerio de Educación, Cultura y Deporte (FPU2013/00164)." "textoCompletoSecciones" => array:1 [ "secciones" => array:12 [ 0 => array:3 [ "identificador" => "xres526123" "titulo" => "Abstract" "secciones" => array:1 [ 0 => array:1 [ "identificador" => "abst0005" ] ] ] 1 => array:2 [ "identificador" => "xpalclavsec546309" "titulo" => "Keywords" ] 2 => array:3 [ "identificador" => "xres526122" "titulo" => "Resumen" "secciones" => array:1 [ 0 => array:1 [ "identificador" => "abst0010" ] ] ] 3 => array:2 [ "identificador" => "xpalclavsec546310" "titulo" => "Palabras clave" ] 4 => array:2 [ "identificador" => "sec0005" "titulo" => "Assessing Neighborhood Disorder" ] 5 => array:2 [ "identificador" => "sec0010" "titulo" => "The Present Study" ] 6 => array:3 [ "identificador" => "sec0015" "titulo" => "Method" "secciones" => array:3 [ 0 => array:2 [ "identificador" => "sec0020" "titulo" => "Sample" ] 1 => array:2 [ "identificador" => "sec0025" "titulo" => "Measures" ] 2 => array:2 [ "identificador" => "sec0030" "titulo" => "Statistical Analysis" ] ] ] 7 => array:3 [ "identificador" => "sec0035" "titulo" => "Results" "secciones" => array:4 [ 0 => array:2 [ "identificador" => "sec0040" "titulo" => "Inter-Rater Reliability" ] 1 => array:2 [ "identificador" => "sec0045" "titulo" => "Confirmatory Factor Analysis" ] 2 => array:2 [ "identificador" => "sec0050" "titulo" => "Internal Consistency" ] 3 => array:2 [ "identificador" => "sec0055" "titulo" => "Criterion-Related Validity" ] ] ] 8 => array:2 [ "identificador" => "sec0060" "titulo" => "Discussion" ] 9 => array:2 [ "identificador" => "sec0065" "titulo" => "Conflict of Interest" ] 10 => array:2 [ "identificador" => "sec9065" "titulo" => "Financial Support" ] 11 => array:1 [ "titulo" => "References" ] ] ] "pdfFichero" => "main.pdf" "tienePdf" => true "fechaRecibido" => "2015-05-20" "fechaAceptado" => "2015-05-25" "PalabrasClave" => array:2 [ "en" => array:1 [ 0 => array:4 [ "clase" => "keyword" "titulo" => "Keywords" "identificador" => "xpalclavsec546309" "palabras" => array:8 [ 0 => "Confirmatory factor analysis" 1 => "Neighborhood disorder" 2 => "Observational scale" 3 => "Physical decay" 4 => "Physical disorder" 5 => "Spatial clustering" 6 => "Social disorder" 7 => "Social disorganization" ] ] ] "es" => array:1 [ 0 => array:4 [ "clase" => "keyword" "titulo" => "Palabras clave" "identificador" => "xpalclavsec546310" "palabras" => array:8 [ 0 => "Análisis factorial confirmatorio" 1 => "Desorden del vecindario" 2 => "Deterioro físico" 3 => "Desorden físico" 4 => "Distribución especial" 5 => "Desorden social" 6 => "Desorganización social" 7 => "Escala observacional" ] ] ] ] "tieneResumen" => true "resumen" => array:2 [ "en" => array:2 [ "titulo" => "Abstract" "resumen" => "This study presents data on the development and preliminary validation of an observational scale assessing neighborhood disorder. Independent observations by trained raters of neighborhood disorder were conducted in 552 census block groups in the city of Valencia (Spain). Intraclass correlation coefficients assessing inter-rater reliability indicated fair to substantial levels of agreement among raters. Confirmatory factor analyses supported a final three-factor model scale measuring physical disorder, social disorder, and physical decay. Results for the internal consistency showed large composite reliability indices indicating good reliability for all neighborhood disorder factors. Evidence of criterion-related validity was found by exploring associations between neighborhood disorder factors and three neighborhood characteristics: neighborhood socioeconomic status, immigrant concentration, and residential instability. Also for criterion-related validity, Moran's I test results for spatial correlation showed that the three types of neighborhood disorder tend to cluster in space and are not randomly distributed across the city. In general, this paper provides evidence of a reliable and valid observational measure to assess neighborhood disorder." ] "es" => array:2 [ "titulo" => "Resumen" "resumen" => "Este estudio presenta el desarrollo y validación preliminar de una escala observacional para la evaluación del desorden en los vecindarios. Se realizaron observaciones independientes del desorden por evaluadores entrenados en 552 sectores censales de la ciudad de Valencia (España). Los coeficientes de correlación intraclase para la evaluación de la fiabilidad interjueces indicaron unos niveles adecuados de acuerdo entre jueces. Los resultados del análisis factorial confirmatorio apoyaron un modelo final de tres factores: desorden físico, desorden social y deterioro físico. La evaluación de la consistencia interna mediante composite reliability indices mostró valores elevados para todos los factores. La validez de criterio fue determinada mediante la exploración de las asociaciones entre los factores de desorden del vecindario y tres características del mismo: estatus socioeconómico, concentración de inmigrantes e inestabilidad residencial. Además, como medida de validez de criterio, el test de Moran que evalúa la correlación espacial mostró que los tres tipos de desorden tienden a agruparse espacialmente y no se distribuyen aleatoriamente en la ciudad. En general, este artículo proporciona evidencias de la fiabilidad y validez de una escala para la medida del desorden en los vecindarios." ] ] "apendice" => array:1 [ 0 => array:1 [ "seccion" => array:1 [ 0 => array:4 [ "apendice" => "<elsevierMultimedia ident="tbl0005"></elsevierMultimedia>" "etiqueta" => "Appendix" "titulo" => "Neighborhood Disorder Observation Scale" "identificador" => "sec0075" ] ] ] ] "multimedia" => array:4 [ 0 => array:7 [ "identificador" => "fig0005" "etiqueta" => "Figure 1" "tipo" => "MULTIMEDIAFIGURA" "mostrarFloat" => true "mostrarDisplay" => false "figura" => array:1 [ 0 => array:4 [ "imagen" => "gr1.jpeg" "Alto" => 1944 "Ancho" => 1870 "Tamanyo" => 235222 ] ] "descripcion" => array:1 [ "en" => "Standardized factor loadings and correlations for the confirmatory factor analyses of the Neighborhood Disorder Observational Scale. Note. All coefficients statistically significant (p < .01); Intoxicat = intoxication; Dealing = drug dealing; Vacant = vacant houses; Vandal. = vandalized buildings; Residen. = residential deterioration; Deter. = deteriorated facilities." ] ] 1 => array:7 [ "identificador" => "tbl0010" "etiqueta" => "Table 1" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "tabla" => array:2 [ "leyenda" => "Note. ICC1 = index of reliability for a single rater.ICC2 = index of reliability for multiple raters averaged together.* < .05, ** < .01, *** < .001" "tablatextoimagen" => array:1 [ 0 => array:2 [ "tabla" => array:1 [ 0 => """ <table border="0" frame="\n \t\t\t\t\tvoid\n \t\t\t\t" class=""><thead title="thead"><tr title="table-row"><th class="td" title="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">Scales \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">No. of items \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">M (SD) \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">ICC1 \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">ICC2 \t\t\t\t\t\t\n \t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><td class="td" title="table-entry " align="left" valign="top">Physical disorder \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">8 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">5.97 (3.54) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">.55*** \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">.71*** \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " align="left" valign="top">Social disorder \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">7 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">0.57 (0.79) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">.25*** \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">.40*** \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " align="left" valign="top">Physical decay \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">5 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">2.64 (2.82) \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">.46*** \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">.63*** \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab847902.png" ] ] ] ] "descripcion" => array:1 [ "en" => "Inter-rater Agreement. Intra-class Correlations Coefficients (ICC)" ] ] 2 => array:7 [ "identificador" => "tbl0015" "etiqueta" => "Table 2" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "tabla" => array:1 [ "tablatextoimagen" => array:1 [ 0 => array:2 [ "tabla" => array:1 [ 0 => """ <table border="0" frame="\n \t\t\t\t\tvoid\n \t\t\t\t" class=""><thead title="thead"><tr title="table-row"><th class="td" title="table-head " align="" valign="top" scope="col" style="border-bottom: 2px solid black"> \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">χ2 \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">df \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">p \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">CFI \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">RMSEA \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">90% CI \t\t\t\t\t\t\n \t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><td class="td" title="table-entry " align="left" valign="top">One-factor model \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">1471.75 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">152 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">< .001 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">.643 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">.12 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">.12 - .13 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " align="left" valign="top">Two-factor model \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">1407.56 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">151 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">< .001 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">.660 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">.12 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">.11 - .12 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " align="left" valign="top">Three-factor model \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">1272.59 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">70 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">< .001 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">.700 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">.11 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">.11 - .12 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " align="left" valign="top">Modified three-factor model \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">278.61 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">87 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">< .001 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">.940 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">.06 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="char" valign="top">.05 - .07 \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab847904.png" ] ] ] ] "descripcion" => array:1 [ "en" => "Goodness of Fit Indices for the Tested Models" ] ] 3 => array:5 [ "identificador" => "tbl0005" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => false "mostrarDisplay" => true "tabla" => array:2 [ "leyenda" => "Note. * Items in Spanish in the original scale / item translation for information purposes" "tablatextoimagen" => array:1 [ 0 => array:2 [ "tabla" => array:1 [ 0 => """ <table border="0" frame="\n \t\t\t\t\tvoid\n \t\t\t\t" class=""><thead title="thead"><tr title="table-row"><th class="td" title="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">Item no. \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">Scale \t\t\t\t\t\t\n \t\t\t\t</th><th class="td" title="table-head " align="left" valign="top" scope="col" style="border-bottom: 2px solid black">Item content * \t\t\t\t\t\t\n \t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><td class="td" title="table-entry " align="left" valign="top">1 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">Physical disorder \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">Colillas en la calle / Cigarettes in the street \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " align="left" valign="top">2 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">Physical disorder \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">Basura en la calle o acera / Trash in the street \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " align="left" valign="top">3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">Physical disorder \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">Botellas o latas vacías de cerveza u otras bebidas en la calle / Empty bottles or cans in the street \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " align="left" valign="top">4 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">Physical disorder \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">Graffitis / Graffiti \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " align="left" valign="top">5 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">Physical disorder \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">Pintadas de carácter político o reivindicativo / Political or protest message graffiti \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " align="left" valign="top">1 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">Social disorder \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">Jóvenes o adultos merodeando por el barrio / Adults or young people loitering \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " align="left" valign="top">2 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">Social disorder \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">Gente bebiendo alcohol en la vía pública / People drinking alcohol in public \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " align="left" valign="top">3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">Social disorder \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">Bandas / Gangs \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " align="left" valign="top">4 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">Social disorder \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">Gente borracha o drogada por la calle / Public intoxication \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " align="left" valign="top">5 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">Social disorder \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">Peleas o discusiones agresivas entre jóvenes o adultos / Adultos or young people fighting or arguing \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " align="left" valign="top">6 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">Social disorder \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">Venta de droga / Selling drugs \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="" valign="top"> \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " align="left" valign="top">1 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">Physical decay \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">Casas vacías / Vacant houses \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " align="left" valign="top">2 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">Physical decay \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">Viviendas abandonadas, quemadas o tapiadas / Abandoned, vandalized and run-down buildings \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " align="left" valign="top">3 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">Physical decay \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">Zonas residenciales muy deterioradas / Deteriorated residential units \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry " align="left" valign="top">4 \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">Physical decay \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="table-entry " align="left" valign="top">Zonas recreativas muy deterioradas / Deteriorated recreation places \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab847903.png" ] ] ] ] ] ] "bibliografia" => array:2 [ "titulo" => "References" "seccion" => array:1 [ 0 => array:2 [ "identificador" => "bibs0005" "bibliografiaReferencia" => array:124 [ 0 => array:3 [ "identificador" => "bib0005" "etiqueta" => "Balfour and Kaplan, 2002" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Neighborhood environment and loss of physical function in older adults: Evidence from the Alameda County study" "autores" => array:1 [ 0 => array:2 [ …2] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1093/aje/155.6.507" "Revista" => array:6 [ "tituloSerie" => "American Journal of Epidemiology" "fecha" => "2002" "volumen" => "155" "paginaInicial" => "507" "paginaFinal" => "551" "link" => array:1 [ …1] ] ] ] ] ] ] 1 => array:3 [ "identificador" => "bib0010" "etiqueta" => "Beyer et al., 2015" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Neighborhood environment and intimate partner violence: A systematic review" "autores" => array:1 [ 0 => array:2 [ …2] ] ] ] "host" => array:1 [ 0 => array:2 [ "doi" => "10.1177/1524838013515758" "Revista" => array:6 [ "tituloSerie" => "Trauma Violence Abuse" "fecha" => 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Assessing neighborhood disorder: Validation of a three-factor observational scale

Evaluación del desorden en los vecindarios: validación de una escala observacional de tres factores

Miriam Marcoa,

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Miriam.Marco-Francisco@uv.es

Corresponding author.

, Enrique Graciaa, José M. Tomásb, Antonio López-Quílezc

a Department of Social Psychology, University of Valencia, Spain

b Department of Methodology of the Behavioral Sciences, University of Valencia, Spain

c Department of Statistics and Operations Research, University of Valencia, Spain

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        "titulo" => "Evaluaci&#243;n del desorden en los vecindarios&#58; validaci&#243;n de una escala observacional de tres factores"
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          "en" => "<p id="spar0020" class="elsevierStyleSimplePara elsevierViewall">Standardized factor loadings and correlations for the confirmatory factor analyses of the Neighborhood Disorder Observational Scale&#46;</p> <p id="spar0025" class="elsevierStyleSimplePara elsevierViewall"><span class="elsevierStyleItalic">Note</span>&#46; All coefficients statistically significant &#40;<span class="elsevierStyleItalic">p</span> &#60; &#46;01&#41;&#59; Intoxicat &#61; intoxication&#59; Dealing &#61; drug dealing&#59; Vacant &#61; vacant houses&#59; Vandal&#46; &#61; vandalized buildings&#59; Residen&#46; &#61; residential deterioration&#59; Deter&#46; &#61; deteriorated facilities&#46;</p>"
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    "textoCompleto" => "<span class="elsevierStyleSections"><p id="par0005" class="elsevierStylePara elsevierViewall">In recent decades&#44; a large body of literature has examined the influence of neighborhood characteristics on a wide range of outcomes&#44; including health&#44; violence&#44; or crime &#40;<a class="elsevierStyleCrossRefs" href="#bib0090">Diez-Roux &#38; Mair&#44; 2010&#59; Kawachi &#38; Berkman&#44; 2003&#59; O&#8217;Campo et al&#46;&#44; 2015&#59; Sampson&#44; 2012&#59; Sampson&#44; Raudenbush&#44; &#38; Earls&#44; 1997</a>&#41;&#46; Among these neighborhood characteristics&#44; the concept of neighborhood disorder has played a central role and has received the attention of scholars from different disciplines like sociology&#44; criminology&#44; social psychology or epidemiology&#46; Neighborhood disorder can be defined as &#8220;observed or perceived physical and social features of neighborhoods that may signal the breakdown of order and social control&#44; and that can undermine the quality of life&#8221; &#40;<a class="elsevierStyleCrossRef" href="#bib0160">Gracia&#44; 2014</a>&#44; p&#46; 4325&#41;&#46; Examples of neighborhood disorder may include behaviors such as prostitution&#44; drug dealing&#44; and fighting in the streets&#44; or physical characteristics such as abandoned cars&#44; vandalized buildings&#44; or litter in the streets &#40;<a class="elsevierStyleCrossRefs" href="#bib0495">Sampson &#38; Raudenbush&#44; 1999&#59; Skogan&#44; 1990&#59; Taylor&#44; 2001&#59; Wilson &#38; Kelling&#44; 1982</a>&#41;&#46;</p><p id="par0010" class="elsevierStylePara elsevierViewall">The concept of neighborhood disorder can be linked to social disorganization theories and their idea that structural characteristics of neighorhoods&#44; like concentrated disadvantage&#44; can undermine social control and increase levels of violence&#44; crime&#44; and other negative outcomes &#40;<a class="elsevierStyleCrossRefs" href="#bib0160">Gracia&#44; 2014&#59; Kingston&#44; Huiziga&#44; &#38; Elliot&#44; 2009&#59; Kubrin &#38; Weitzer&#44; 2003&#59; Maimon &#38; Browning&#44; 2010&#59; Park&#44; Burgess&#44; &#38; McKenzie&#44; 1925&#59; Sampson et al&#46;&#44; 1997&#59; Shaw &#38; McKay&#44; 1942&#59; Wilson&#44; 1987</a>&#41;&#46; Also&#44; the Broken Windows Theory of urban decay has been of particular relevance for the wide appeal of the concept of neighborhood disorder &#40;<a class="elsevierStyleCrossRef" href="#bib0595">Wilson &#38; Kelling&#44; 1982</a>&#41;&#46; According to this perspective&#44; physical and social cues of neighborhood disorder signal the breakdown of formal and informal social controls leading to further disorder and crime &#40;<a class="elsevierStyleCrossRefs" href="#bib0160">Gracia&#44; 2014&#59; Perkins&#44; Meeks&#44; &#38; Taylor&#44; 1992&#59; Sampson &#38; Raudenbush&#44; 1999&#59; Skogan&#44; 1990&#59; Taylor&#44; 1997&#44; 2005&#59; Toet &#38; van Schaik&#44; 2012&#59; Wei&#44; Hipwell&#44; Pardini&#44; Beyers&#44; &#38; Loeber&#44; 2005&#59; York Cornwell &#38; Cagney&#44; 2014</a>&#41;&#46; According to <a class="elsevierStyleCrossRef" href="#bib0160">Gracia &#40;2014&#41;</a> &#8220;as neither residents nor external agencies &#40;e&#46;g&#46;&#44; police and other authorities&#41; are able or willing to intervene and maintain social order&#44; more disorder is facilitated&#44; and criminal activity is attracted&#8221; &#40;p&#46; 4325&#41;&#46; Neighborhood disorder would also trigger a number of community processes like fear&#44; insecurity&#44; powerlessness&#44; or mistrust that lead residents to disinvest in and withdraw from community life&#44; increasing social disorganization and neighborhood decline &#40;<a class="elsevierStyleCrossRefs" href="#bib0145">Geis &#38; Ross&#44; 1998&#59; Kawachi&#44; Kennedy&#44; &#38; Wilkinson&#44; 1999&#59; Kim &#38; Conley&#44; 2011&#59; Ross&#44; Mirowsky&#44; &#38; Pribesh&#44; 2001&#59; Skogan&#44; 1986&#44; 1990</a>&#41;&#46; In this regard&#44; neighborhood disorder has been linked to urban decay&#44; concentration of social problems&#44; racial or ethnic segregation&#44; social integration&#44; confidence in the police&#44; or public social control strategies like reporting crime &#40;<a class="elsevierStyleCrossRefs" href="#bib0170">Gracia&#44; Garcia&#44; &#38; Musitu&#44; 1995&#59; Gracia &#38; Herrero&#44; 2006a&#44; 2006b&#44; 2007&#59; Perkins et al&#46;&#44; 1992&#59; Perkins &#38; Taylor&#44; 1996&#59; Ross &#38; Mirowsky&#44; 1999&#59; Skogan&#44; 1990&#59; Taylor&#44; 1997&#59; Toet &#38; van Schaik&#44; 2012</a>&#41;&#46;</p><p id="par0015" class="elsevierStylePara elsevierViewall">Although neighborhood disorder has traditionally been studied in relation to street-level outcomes&#44; an increasing body of literature has also examined its influence on processes and outcomes that occur &#8220;behind closed doors&#8221; &#40;<a class="elsevierStyleCrossRef" href="#bib0610">Wright &#38; Benson&#44; 2011</a>&#41;&#44; such as parental socialization practices &#40;<a class="elsevierStyleCrossRefs" href="#bib0165">Gracia&#44; Fuentes&#44; Garc&#237;a&#44; &#38; Lila 2012&#59; Lila &#38; Gracia&#44; 2005&#59; McDonell&#44; 2007&#59; Roosa et al&#46;&#44; 2005&#59; Tendulkar&#44; Buka&#44; Dunn&#44; Subramanian&#44; &#38; Koenen&#44; 2010&#59; White&#44; Roosa&#44; Weaver&#44; &#38; Nair&#44; 2009&#59; Worton et al&#46;&#44; 2014</a>&#41;&#44; child maltreatment &#40;<a class="elsevierStyleCrossRefs" href="#bib0065">Coulton&#44; Crampton&#44; Irwin&#44; Spilsbury&#44; &#38; Korbin&#44; 2007&#59; Coulton&#44; Korbin&#44; &#38; Su&#44; 1999&#59; Freisthler&#44; Bruce&#44; &#38; Needell&#44; 2007&#59; Freisthler&#44; Merritt&#44; &#38; LaScala&#44; 2006&#59; Garbarino &#38; Sherman&#44; 1980&#59; Gracia &#38; Musitu&#44; 2003&#59; Lila &#38; Gracia&#44; 2005&#59; Martin-Storey et al&#46;&#44; 2012</a>&#41;&#44; or intimate partner violence &#40;<a class="elsevierStyleCrossRefs" href="#bib0075">Cunradi&#44; 2007&#44; 2009&#59; Gracia&#44; Herrero&#44; Lila&#44; &#38; Fuente&#44; 2009&#59; Gracia&#44; L&#243;pez-Qu&#237;lez&#44; Marco&#44; Lladosa&#44; &#38; Lila&#44; 2014&#44; 2015&#59; Kirst&#44; Lazgare&#44; Zhang&#44; &#38; O&#8217;Campo&#44; 2015</a>&#59; see <a class="elsevierStyleCrossRefs" href="#bib0010">Beyer&#44; Wallis&#44; &#38; Hamberger&#44; 2015&#59; Pinchevsky &#38; Wright&#44; 2012</a>&#44; for reviews&#41;&#46;</p><p id="par0020" class="elsevierStylePara elsevierViewall">More recently&#44; research on social disorder has also examined its influences on individual well-being indicators like subjective well-being&#44; psychological distress&#44; anxiety&#44; or depression &#40;<a class="elsevierStyleCrossRefs" href="#bib0135">Garc&#237;a-Ram&#237;rez&#44; Balc&#225;zar&#44; &#38; de Freitas&#44; 2014&#59; Herrero&#44; Gracia&#44; Fuente&#44; &#38; Lila&#44; 2012&#59; Hill &#38; Angel&#44; 2005&#59; Hombrados-Mendieta &#38; L&#243;pez-Espigares&#44; 2014&#59; Latkin &#38; Curry&#44; 2003&#59; Latkin&#44; German&#44; Hua&#44; &#38; Curry&#44; 2009&#59; O&#8217;Campo et al&#46;&#44; 2015&#59; Ross &#38; Mirowsky&#44; 2009</a>&#41;&#44; and how this may affect negative health behaviors such as low physical activity&#44; heavy drinking&#44; smoking&#44; or obesity &#40;<a class="elsevierStyleCrossRefs" href="#bib0030">Burdette &#38; Hill&#44; 2008&#59; Echeverr&#237;a&#44; Diez-Roux&#44; Shea&#44; Borrell&#44; &#38; Jackson&#44; 2008&#59; Hill&#44; Ross&#44; &#38; Angel&#44; 2005&#59; Keyes et al&#46;&#44; 2012&#59; O&#8217;Campo et al&#46;&#44; 2015&#59; Ross &#38; Mirowsky&#44; 2001</a>&#41;&#46; Research has also examined the association between neighborhood disorder and different public health issues such as health service usage&#44; low body weight at birth in children&#44; injuries&#44; sexually transmitted diseases&#44; loss of physical function in older adults&#44; and mortality risk &#40;<a class="elsevierStyleCrossRefs" href="#bib0005">Balfour &#38; Kaplan&#44; 2002&#59; Cohen et al&#46;&#44; 2000&#44; 2003&#59; Martin-Storey et al&#46;&#44; 2012&#59; Pearl&#44; Braveman&#44; &#38; Abrams&#44; 2001&#59; Winkleby &#38; Cubbin&#44; 2003</a>&#41;&#46;</p><span id="sec0005" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0025">Assessing Neighborhood Disorder</span><p id="par0025" class="elsevierStylePara elsevierViewall">Assessment of neighborhood disorder tipycally considers two types of disorder&#44; physical and social &#40;<a class="elsevierStyleCrossRefs" href="#bib0455">Robinson&#44; Lawton&#44; Taylor&#44; &#38; Perkins&#44; 2003&#59; Skogan &#38; Maxfield&#44; 1981&#59; Taylor &#38; Shumaker&#44; 1990</a>&#41;&#46; Physical disorder refer to urban landscapes with high levels of decay and deterioration&#46; For example&#44; abandoned houses&#44; graffiti&#44; trash on the streets&#44; abandoned cars&#44; used needles&#44; and vacant lots would exemplify physical disorder &#40;<a class="elsevierStyleCrossRefs" href="#bib0020">Brunton-Smith&#44; 2011&#59; Garvin&#44; Cannuscio &#38; Branas&#44; 2013&#59; Robinson et al&#46;&#44; 2003&#59; Sampson &#38; Raudenbush&#44; 1999&#59; Skogan&#44; 1990&#59; Taylor&#44; 2001</a>&#44; <a class="elsevierStyleCrossRef" href="#bib0570">Toet &#38; van Schaik&#44; 2012</a>&#41;&#46; Some scholars&#44; however&#44; make a further distinction between physical disorder and physical decay&#58; physical disorder would refer to features like dirt in the streets &#40;litter&#44; bottles&#44; condoms&#41;&#44; graffiti&#44; abandoned cars&#44; etc&#46; &#40;i&#46;e&#46;&#44; behavioral manifestations&#41;&#44; whereas physical decay would refer to structural characteristics that can arise from lack of institutional investments and have long term effects&#44; such as abandoned buildings&#44; burn-out houses&#44; badly deteriorated recreational facilities&#44; etc&#46; &#40;<a class="elsevierStyleCrossRefs" href="#bib0485">Sampson&#44; 2009&#59; Sampson &#38; Raudenbush&#44; 2004</a>&#41;&#46; As <a class="elsevierStyleCrossRef" href="#bib0500">Sampson and Raudenbush &#40;2004&#41;</a> argue&#44; it is important to make this distinction because physical disorder is &#8220;limited to behavioral manifestations &#40;e&#46;g&#46;&#44; graffiti&#44; garbage in the streets&#41; that can be conceptually decoupled from structural resources&#8221; &#40;p&#46; 326&#41;&#46; Social disorder refer&#44; on the other hand&#44; to events in public places seen as potentially threatening&#44; and can be exemplified by the presence of people taking drugs or alcohol in the street&#44; drug dealing&#44; fights and arguments&#44; presence of homeless people&#44; public drunkenness&#44; street prostitution&#44; high levels of police activity&#44; and other criminal or not criminal activities that create a sense of danger &#40;<a class="elsevierStyleCrossRefs" href="#bib0160">Gracia&#44; 2014&#59; Gracia &#38; Herrero&#44; 2007&#59; Robinson et al&#46;&#44; 2003&#59; Ross &#38; Mirowsky&#44; 2001&#59; Sampson&#44; 2009&#59; Sampson &#38; Raudenbush&#44; 2004</a>&#41;&#46; Despite some studies suggesting that physical and social disorder may overlap&#44; being order and disorder two ends of a single continuum &#40;<a class="elsevierStyleCrossRefs" href="#bib0465">Ross &#38; Mirowsky&#44; 1999&#59; Xu&#44; Fielder&#44; &#38; Flaming&#44; 2005</a>&#41;&#44; most studies support the distinction between physical and social disorder &#40;<a class="elsevierStyleCrossRefs" href="#bib0025">Brunton-Smith&#44; Sindall&#44; &#38; Tarling&#44; 2010&#59; LaGrange&#44; Ferraro&#44; &#38; Supancic&#44; 1992&#59; Sampson &#38; Raudenbush&#44; 2004&#59; Taylor &#38; Shumaker&#44; 1990</a>&#41;&#46;</p><p id="par0030" class="elsevierStylePara elsevierViewall">In order to assess neighborhood disorder&#44; researchers generally use three different approaches &#40;<a class="elsevierStyleCrossRefs" href="#bib0365">McDonell &#38; Waters&#44; 2011&#59; Mooney et al&#46;&#44; 2014</a>&#41;&#46; One approach&#44; based on a more objective perspective&#44; draws from neighborhood information from governmental or commercial data sources &#40;<a class="elsevierStyleCrossRefs" href="#bib0045">Cerd&#225; et al&#46;&#44; 2009&#59; McDonell&#44; 2007&#59; Mooney et al&#46;&#44; 2014</a>&#41;&#46; Although these data is freer from the variability and subjectivity of subjective perceptions of disorder &#40;<a class="elsevierStyleCrossRef" href="#bib0285">Kubrin&#44; 2008</a>&#41;&#44; however&#44; this information is &#8220;often collected for administrative purposes&#44; may not fully capture the construct of research interest&#44; and may be collected at a spatial resolution that is not optimal for research purposes&#8221; &#40;<a class="elsevierStyleCrossRef" href="#bib0370">Mooney et al&#46;&#44; 2014</a>&#44; p&#46; 626-627&#41;&#46; A second&#44; and widely used&#44; approach is based on resident&#39;s perceptions of their neighborhood physical or social characteristics&#46; A number of limitations have been noted&#44; however&#44; regarding this approach&#44; including &#8220;same source bias&#8221; &#40;e&#46;g&#46;&#44; same source reporting perceived neighborhood disorder and related outcomes&#41;&#44; confusion with other psychological constructs &#40;e&#46;g&#46;&#44; fear of crime&#41;&#44; or the influence of stereotypes and neighborhood prejudices &#40;e&#46;g&#46;&#44; racial&#44; ethnic&#44; or socioeconomic composition&#41; in perceptions of disorder &#40;<a class="elsevierStyleCrossRefs" href="#bib0040">Caughy&#44; O&#8217;Campo&#44; &#38; Patterson&#44; 2001&#59; Duncan &#38; Raudenbush&#44; 1999&#59; G&#243;mez&#44; Johnson&#44; Selva&#44; &#38; Sallis&#44; 2004&#59; Mooney et al&#46;&#44; 2014&#59; Sampson&#44; 2009&#59; Sampson &#38; Raudenbush&#44; 1999&#44; 2004&#59; Schaefer-McDaniel&#44; Caughy&#44; O&#8217; Campo&#44; &#38; Gearey&#44; 2010</a>&#41;&#46; Finally&#44; a third approach&#44; that aims to overcome the above limitations&#44; emphasizes the importance of using direct and systematic observations of neighborhood characteristics by trained researchers &#40;<a class="elsevierStyleCrossRefs" href="#bib0115">Franzini&#44; Caughy&#44; Nettles&#44; &#38; O&#8217;Campo&#44; 2008&#59; McDonell&#44; 2007&#59; McDonell &#38; Waters&#44; 2011&#59; Neil&#44; Parke&#44; &#38; McDowell&#44; 2001&#59; Raudenbush &#38; Sampson&#44; 1999&#59; Reiss&#44; 1971&#59; Sampson &#38; Raudenbush&#44; 1999</a>&#41;&#46; This approach aims to obtain objective measures of neighborhood conditions&#44; to capture a wide range of factors&#44; which are not always available otherwise&#44; and to allow its replication in other contexts &#40;<a class="elsevierStyleCrossRefs" href="#bib0040">Caughy et al&#46;&#44; 2001&#59; Cohen et al&#46;&#44; 2000&#59; Franzini et al&#46;&#44; 2008&#59; McDonell &#38; Waters&#44; 2011&#59; Sampson &#38; Raudenbush&#44; 2004&#59; Taylor&#44; 2001</a>&#41;&#46;</p></span><span id="sec0010" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0030">The Present Study</span><p id="par0035" class="elsevierStylePara elsevierViewall">This study aims to add to this body of research by validating an observational measure of neighborhood disorder in the context of a European city that may differ from the culture and structure of Anglo-Saxon cities where most of this type of measures have been developed and validated &#40;<a class="elsevierStyleCrossRefs" href="#bib0335">Le Gal&#232;s &#38; Zagrodzki&#44; 2006&#59; Summers&#44; Cheshire&#44; &#38; Senn&#44; 1999</a>&#41;&#46; The availability of a reliable and valid measure of neighborhood disorder in this context may be an important addition to the growing body of literature exploring neighborhood effects &#40;<a class="elsevierStyleCrossRef" href="#bib0490">Sampson&#44; 2012</a>&#41;&#46; To this end&#44; independent observations by trained raters of neighborhood disorder will be conducted using small-areas of the city as the ecological units &#40;i&#46;e&#46;&#44; census block groups&#44; which are the smallest administrative sections of the city available&#41;&#46; By using the smallest posible geographical units of the city we expect greater homogeneity of neighborhood characteristics &#40;<a class="elsevierStyleCrossRef" href="#bib0400">Oca&#241;a-Riola et al&#46;&#44; 2008</a>&#41;&#46; Also&#44; by using all census block groups of the city we will obtain greater variability and&#44; as neighborhood characteristics tend to cluster in space&#44; this will provide the possibility to explore the clustering of these characteristics for validation purposes &#40;<a class="elsevierStyleCrossRef" href="#bib0200">Gracia et al&#46;&#44; 2014</a>&#41;&#46;</p><p id="par0040" class="elsevierStylePara elsevierViewall">This study presents data on the development and preliminary validation of an observational instrument to assess neighborhood disorder&#46; The specific objectives of the study are&#58; &#40;1&#41; to test the inter-rater reliability of the scale&#59; &#40;2&#41; to test the factorial validity of the scale using confirmatory factor analysis&#58; we expect a factorial structure reflecting three theoretically a priori factors&#44; physical disorder&#44; social disorder&#44; and physical decay &#40;<a class="elsevierStyleCrossRef" href="#bib0500">Sampson &#38; Raudenbush&#44; 2004</a>&#41;&#59; &#40;3&#41; to test the reliability of the scale by means of the composite reliability index&#59; and &#40;4&#41; to test the criterion-related validity of the scale also employing structural equations&#46; Drawing from social disorganization theory we expect associations between neighborhood disorder and three neighborhood structural characteristics&#44; central in this theoretical perspective&#58; neighborhood socioeconomic status&#44; immigrant concentration&#44; and residential instability &#40;<a class="elsevierStyleCrossRefs" href="#bib0040">Caughy et al&#46;&#44; 2001&#59; Jones&#44; Pebley&#44; &#38; Sastry&#44; 2011&#59; Kubrin &#38; Weitzer&#44; 2003&#59; McDonell &#38; Waters&#44; 2011&#59; Mooney et al&#46;&#44; 2014&#59; Sampson et al&#46;&#44; 1997&#59; Sampson &#38; Raudenbush&#44; 1999</a>&#41;&#46; Also&#44; for validation purposes&#44; a spatial perspective will be applied&#46; As we expect that disordered neighborhoods will cluster in space&#44; rather than be randomly distributed in the city&#44; spatial correlation analyses will be conducted to test whether neighborhood disorder shows a significant spatial pattern &#40;<a class="elsevierStyleCrossRefs" href="#bib0015">Bruinsma&#44; Pauwels&#44; Weerman&#44; &#38; Bernasco&#44; 2013&#59; Gracia et al&#46;&#44; 2015&#59; Quick&#44; 2013&#59; Veysey &#38; Messner&#44; 1999</a>&#41;&#46;</p></span><span id="sec0015" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0035">Method</span><span id="sec0020" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0040">Sample</span><p id="par0045" class="elsevierStylePara elsevierViewall">This study was conducted in the city of Valencia&#44; the third largest city of Spain&#46; As proxy of neighborhood units we used census block groups that were the smallest administrative unit of the city available&#46; Census block groups can be defined as walkable areas within a few number of city blocks and as they are smaller than census tracks&#44; they are particularly appropriate for neighborhood studies &#40;<a class="elsevierStyleCrossRefs" href="#bib0200">Gracia et al&#46;&#44; 2014&#59; Sampson &#38; Raudenbush&#44; 2004</a>&#41;&#46; Observations by trained raters were conducted in each of the 552 census block groups in which the city is divided&#46; The total population for these census block groups was 736&#44;580 inhabitants &#40;2013 data&#41;&#44; with an average of 1&#44;334 inhabitants per census block group &#40;ranging from 630 to 2&#44;845&#41;&#46;</p></span><span id="sec0025" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0045">Measures</span><p id="par0050" class="elsevierStylePara elsevierViewall"><span class="elsevierStyleItalic">Neighborhood disorder observation scale</span>&#46; A neighborhood disorder scale was initially constructed with a total of 20 items based on three dimensions of neighborhood disorder proposed by Sampson and Raudenbush &#40;<a class="elsevierStyleCrossRef" href="#bib0500">Sampson &#38; Raudenbush&#44; 2004</a>&#41;&#46; Thus&#44; the scale included three theoretically motivated subscales measuring physical disorder&#44; social disorder&#44; and physical decay&#46; <span class="elsevierStyleItalic">Physical disorder</span> was defined by 8 items&#58; cigarettes in the street&#44; trash in the street&#44; empty bottles in the street&#44; graffiti&#44; abandoned cars&#44; used condoms and syringes in the street&#44; and political or protest message graffiti<span class="elsevierStyleItalic">&#46; Social disorder</span> was defined by 7 items&#58; adults or young people loitering&#44; people drinking alcohol in public&#44; gangs&#44; public intoxication&#44; adults fighting or arguing&#44; selling drugs&#44; and street prostitution&#46; <span class="elsevierStyleItalic">Physical decay</span> was defined by 5 items&#58; vacant or abandoned houses&#44; abandoned commercial buildings&#44; vandalized and run-down buildings&#44; deteriorated residential units and deteriorated recreation places&#46; The observations are rated on a 5-point response scale &#40;from 0 &#61; <span class="elsevierStyleItalic">no presence</span>&#44; to 4 &#61; <span class="elsevierStyleItalic">highly present</span>&#41;&#46; Two trained raters walked each census block group in order to complete the observational scale&#46; All observations were made during business hours&#46;</p><p id="par0055" class="elsevierStylePara elsevierViewall"><span class="elsevierStyleItalic">Criterion-related validity measures</span>&#46; Drawing from social disorganization theory&#44; to test criterion-related validity we will explore relationships between neighborhood disorder and three neighborhood characteristics measured at census block group level&#58; neighborhood socioeconomic status&#44; immigrant concentration&#44; and residential instability&#46; The City of Valencia Statistics Office provided these data for each census block group&#46; Neigbhorhood socioeconomic status was measured with an indicator created through factor analysis &#40;this factor included educational level&#44; property value&#44; percentage of high-end cars&#44; and financial and commercial activities&#41;&#46; Immigrant concentration was the percentage of immigrant population in each census block&#44; and residential instability was the proportion of the population who had moved into or out of each census block group during the previous year &#40;rate per 1&#44;000 inhabitants&#41;&#46;</p></span><span id="sec0030" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0050">Statistical Analysis</span><p id="par0060" class="elsevierStylePara elsevierViewall">To measure inter-rater reliability&#44; two pairs of trained undergraduate students walked a random sample of the census block groups&#46; They observed a subset of 15&#37; of them aproximately &#40;<span class="elsevierStyleItalic">N</span> &#61; 86&#41;&#46; Inter-rater reliability scores were computed per each of the three scales by calculating intraclass correlation coefficients &#40;ICC&#41; due to the quantitative nature of data&#46; This analysis was performed with SPSS 22 for Windows&#46;</p><p id="par0065" class="elsevierStylePara elsevierViewall">Several competing confirmatory factor analyses &#40;CFA&#41; were specified&#44; estimated and tested in Mplus 7&#46;3&#46; According to the ordinal nature of the data and its non-normality&#44; WLSMV &#40;weighted least squares mean and variance corrected&#41; estimation was used&#44; the one recommended in the literature &#40;<a class="elsevierStyleCrossRef" href="#bib0110">Finney &#38; DiStefano&#44; 2006</a>&#41;&#46; Several criteria were used to assess goodness-of-fit&#58; &#40;a&#41; the chi-square statistic&#44; &#40;b&#41; the comparative fit index &#40;CFI&#41;&#44; and &#40;c&#41; the root mean squared error of approximation &#40;RMSEA&#41;&#46; A model with a CFI of &#46;95 or larger and a RMSEA of &#46;08 or lower would be indicative of very good fit between the hypothesized model and the data &#40;<a class="elsevierStyleCrossRef" href="#bib0235">Hu &#38; Bentler&#44; 1999</a>&#41;&#46; Nevertheless&#44; overall fit must be accompanied by a careful diagnosis of the analytical fit &#40;parameter estimates&#41; in the model in order to not blindly use the aforementioned thresholds &#40;<a class="elsevierStyleCrossRef" href="#bib0280">Kline&#44; 2011</a>&#41;&#46; For model comparison&#44; a modeling approach that uses practical fit indices to determine the overall adequacy of a fitted model has been used as recommended by <a class="elsevierStyleCrossRef" href="#bib0050">Cheung and Rensvold &#40;2002&#41;</a> or <a class="elsevierStyleCrossRef" href="#bib0345">Little &#40;1997&#41;</a>&#46; From this point of view&#44; if a parsimonious model evidences adequate levels of practical fit&#44; then it is preferred over the more complex model&#46; Usually&#44; CFI differences &#40;&#916;CFI&#41; are used to evaluate measurement invariance&#46; CFI differences lower than &#46;01 &#40;<a class="elsevierStyleCrossRef" href="#bib0050">Cheung &#38; Rensvold&#44; 2002</a>&#41; or &#46;05 &#40;<a class="elsevierStyleCrossRef" href="#bib0345">Little&#44; 1997</a>&#41; are usually employed as cut-off criteria&#46;</p><p id="par0070" class="elsevierStylePara elsevierViewall">Additionally&#44; internal consistency of the dimensions in the scale has been estimated with the composite reliability index &#40;CRI&#41;&#46; Although Cronbach&#39;s coefficient alpha is the most widely used estimator of internal consistency&#44; it has been criticized as being only completely appropriate with essentially tau-equivalent items &#40;and tests&#41; and also by being a lower bound for the true reliability &#40;<a class="elsevierStyleCrossRef" href="#bib0445">Raykov&#44; 2004</a>&#41;&#46; More explicitly&#44; a tau-equivalent test assumes all items measure the same latent variable&#44; on the same scale&#44; with the same degree of precision&#44; with all true scores being equal &#40;<a class="elsevierStyleCrossRef" href="#bib0210">Graham&#44; 2006</a>&#41;&#46; When tau-equivalence does not hold&#44; alpha will over- or under-estimate &#40;more often the latter&#41; the population value&#46; An alternative to the coefficient alpha is the CRI&#44; which is usually calculated using estimates from confirmatory factor analyses &#40;<a class="elsevierStyleCrossRef" href="#bib0210">Graham&#44; 2006</a>&#41;&#46; Accordingly&#44; the more adequate CRI was employed&#46;</p><p id="par0075" class="elsevierStylePara elsevierViewall">Criterion-related validity was established by correlating neighborhood disorder factors with other neighborhood constructs theorically linked in the literature &#40;<a class="elsevierStyleCrossRefs" href="#bib0160">Gracia&#44; 2014&#59; Gracia et al&#46;&#44; 2015&#59; Kubrin &#38; Weitzer&#44; 2003&#59; Sampson &#38; Raudenbush&#44; 1999&#59; Sampson et al&#46;&#44; 1997&#59; Shaw &#38; McKay&#44; 1942</a>&#41;&#46; This correlation was obtained within the context of a structural equation modeling in order to prevent as much as possible the correlation attenuation due to measurement error&#46; Specifically&#44; neighborhood disorder was correlated to neighborhood socioeconomical status&#44; immigrant concentration&#44; and residential instability &#40;see Measures section&#41;&#46;</p><p id="par0080" class="elsevierStylePara elsevierViewall">To test criterion-related validity we also used a spatial methodology approach&#46; To assess spatial autocorrelation&#44; we computed Moran&#39;s I &#40;<a class="elsevierStyleCrossRef" href="#bib0375">Moran&#44; 1950</a>&#41; per each of the three subscales or factors&#44; considering as the observation the midpoint of each of the census block groups&#46; We expected a significant spatial distribution of neighborhood disorder&#44; rather than a random distribution&#44; because we expect that disorder&#44; as other neighborhood characteristics&#44; will show a tendency towards spatial clustering &#40;<a class="elsevierStyleCrossRefs" href="#bib0015">Bruinsma et al&#46;&#44; 2013&#59; DiMaggio&#44; 2015&#59; Quick&#44; 2013&#59; Veysey &#38; Messner&#44; 1999</a>&#41;&#46;</p></span></span><span id="sec0035" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0055">Results</span><span id="sec0040" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0060">Inter-Rater Reliability</span><p id="par0085" class="elsevierStylePara elsevierViewall">Intraclass correlation coefficients were computed to assess inter-rater agreement for the three subscales &#40;see <a class="elsevierStyleCrossRef" href="#bib0405">Odgers&#44; Caspi&#44; Bates&#44; Sampson&#44; &#38; Moffit&#44; 2012</a>&#44; for a similar approach&#41;&#46; Intraclass correlations ranged from &#46;25 to &#46;71 &#40;see <a class="elsevierStyleCrossRef" href="#tbl0010">Table 1</a>&#41;&#46; <a class="elsevierStyleCrossRef" href="#bib0300">Landis and Koch&#39;s &#40;1977&#41;</a> criteria were used to interpret results regarding inter-rater agreements&#58; &#60; &#46;20 slight&#44; &#46;21 &#8211; &#46;40 fair&#44; &#46;41 &#8211; &#46;60 moderate&#44; &#46;61 &#8211; &#46;80 substantial&#44; and &#46;81 &#8211; 1 almost perfect agreement&#46; Our results indicated fair to substantial levels of agreement between raters &#40;<a class="elsevierStyleCrossRef" href="#bib0300">Landis &#38; Koch&#44; 1977</a>&#41;&#46; Social disorder obtained the lowest value and physical disorder and physical decay showed similar results&#46;</p><elsevierMultimedia ident="tbl0010"></elsevierMultimedia></span><span id="sec0045" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0065">Confirmatory Factor Analysis</span><p id="par0090" class="elsevierStylePara elsevierViewall">Three a priori competing models were specified&#46; The theoretical model that supports the content validity of the scale a priori hypothesizes three dimensions&#58; physical disorder&#44; social disorder&#44; and physical decay&#46; Indicators were developed to tap these three theoretical dimensions&#46; However&#44; there was doubt about whether two of these dimensions could be too overlapped to have discriminant validity&#58; physical disorder and physical decay&#46; Accordingly&#44; another a priori model was specified with two dimensions&#58; social disorder and all the indicators of physical disorder and physical decay specified to load onto a single dimension&#46; Finally&#44; the most parsimonious latent structure&#44; a one-factor model underlying all the indicators&#44; was also specified&#46; Goodness-of-fit indices for these three a priori models are shown in <a class="elsevierStyleCrossRef" href="#tbl0015">Table 2</a>&#46; Model fit for the three models was extremely poor&#44; and none of them could be retained as a good approximation to the observed data&#46; Nevertheless&#44; the three-factor model showed a <span class="elsevierStyleItalic">relative</span> better fit compared to the other two models&#58; &#916;CFI &#61; &#46;06&#44; compared to the one-factor model and &#916;CFI &#61; &#46;04&#44; compared to the two-factor model&#46; Taking this information into account&#44; plus the fact that the theoretical model that supports the scale was three-dimensional&#44; this model was retained for further psychometric scrutiny&#46;</p><elsevierMultimedia ident="tbl0015"></elsevierMultimedia><p id="par0095" class="elsevierStylePara elsevierViewall">A careful look at the factor loadings&#44; together with the lack of variability in some indicators&#44; allows to remove some of them&#46; Those removed lacked variability and&#47;or had poor consistency with their dimension&#46; The final version of the questionnaire was presumed to measure three factors &#40;physical disorder&#44; social disorder&#44; and physical decay&#41; with 5&#44; 6&#44; and 4 indicators each &#40;see Appendix&#41;&#46; This depurated version of the original scale was tested and its goodness-of-fit indices are shown in <a class="elsevierStyleCrossRef" href="#tbl0015">Table 2</a>&#46; There was a huge improvement in model fit&#44; and it can be said that the model seems to adequately represent the observed data&#46; Factor loadings are shown in <a class="elsevierStyleCrossRef" href="#fig0005">Figure 1</a>&#46; They were all statistically significant &#40;<span class="elsevierStyleItalic">p</span> &#60; &#46;01&#41; and&#44; in general&#44; pretty large&#46; These results are indicative of good analytical fit&#46;</p><elsevierMultimedia ident="fig0005"></elsevierMultimedia></span><span id="sec0050" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0070">Internal Consistency</span><p id="par0100" class="elsevierStylePara elsevierViewall">Reliability &#40;internal consistency&#41; estimates were calculated for each dimension or factor in the scale&#46; The calculated reliability estimates were composite reliability indices &#40;CRI&#41;&#44; as already mentioned in the method section&#46; All the CRI were large&#44; indicating a good reliability for all the dimensions&#46; Specifically&#44; CRI for physical disorder was &#46;83&#44; &#46;82 was the estimate for social disorder&#44; and &#46;82 the internal consistency estimated for physical decay&#46;</p></span><span id="sec0055" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0075">Criterion-Related Validity</span><p id="par0105" class="elsevierStylePara elsevierViewall">Finally&#44; evidence of criterion-related validity was also found&#46; Three criteria were used &#40;neighborhood socioeconomical status&#44; immigrant concentration&#44; and residential instability&#41;&#46; The relationship between the criteria and the latent variables were calculated at the latent level&#44; not the observed one&#46; A first structural model included the measurement model found to fit well to the data&#44; plus the first criterion &#40;neighborhood socioeconomical status&#41;&#46; Again&#44; this structural model fitted the data well&#44; &#967;<span class="elsevierStyleSup">2</span>&#40;99&#41; &#61; 339&#46;78&#44; <span class="elsevierStyleItalic">p</span> &#60; &#46;001&#59; CFI &#61; &#46;93&#44; RMSEA &#61; &#46;066 &#91;&#46;059 - &#46;074&#93;&#46; The correlations between neighborhood socioeconomic status and the criteria and the factors were&#58; &#961; &#61; -&#46;13&#44; <span class="elsevierStyleItalic">p</span> &#60; &#46;01 with physical disorder&#59; &#961; &#61; &#46;04&#44; <span class="elsevierStyleItalic">p</span> &#62; &#46;05 with social disorder&#59; and &#961; &#61; -&#46;29&#44; <span class="elsevierStyleItalic">p</span> &#60; &#46;01 with physical decay&#46; With respect to immigrant concentration&#44; the structural model also adequately fitted the data&#44; &#967;<span class="elsevierStyleSup">2</span>&#40;99&#41; &#61; 309&#46;38&#44; <span class="elsevierStyleItalic">p</span> &#60; &#46;001&#59; CFI &#61; &#46;93&#44; RMSEA &#61; &#46;062 &#91;&#46;054 - &#46;070&#93;&#46; The correlations among the criterion and the factors were&#58; &#961; &#61; &#46;44&#44; <span class="elsevierStyleItalic">p</span> &#62; &#46;05 with physical disorder&#59; &#961; &#61; &#46;13&#44; <span class="elsevierStyleItalic">p</span> &#60; &#46;05 with social disorder&#59; and &#961; &#61; &#46;21&#44; <span class="elsevierStyleItalic">p</span> &#60; &#46;01 with physical decay&#46; Finally&#44; a third structural model was specified and tested to relate the three factors with residential instability&#46; Again the model fitted the data well&#44; &#967;<span class="elsevierStyleSup">2</span>&#40;99&#41; &#61; 333&#46;54&#44; <span class="elsevierStyleItalic">p</span> &#60; &#46;001&#59; CFI &#61; &#46;92&#44; RMSEA &#61; &#46;066 &#91;&#46;058 - &#46;073&#93;&#44; and its correlations with the factors were&#58; &#961; &#61; &#46;05&#44; <span class="elsevierStyleItalic">p</span> &#62; &#46;05 with physical disorder&#59; &#961; &#61; &#46;15&#44; <span class="elsevierStyleItalic">p</span> &#60; &#46;05 with social disorder&#59; and &#961; &#61; &#46;22&#44; <span class="elsevierStyleItalic">p</span> &#60; &#46;01 with physical decay&#46;</p><p id="par0110" class="elsevierStylePara elsevierViewall">Also&#44; for criterion-related validity purposes&#44; tests for spatial correlation were conducted for the three dimensions&#46; Results showed spatial autocorrelation in the three scales as all Moran&#39;s I values were positive and significant &#40;<span class="elsevierStyleItalic">p</span> &#60; &#46;001&#41;&#46; Moran&#39;s I values for the three measures were &#46;20 for social disorder&#44; &#46;39 for physical decay&#44; and &#46;49 for physical disorder&#44; indicating a stronger spatial pattern for physical disorder and physical decay than for social disorder&#46; These results indicate a positive non-random distribution of all types of neighborhood disorder in the city &#40;i&#46;e&#46;&#44; rather than being randomly distributed across the city&#44; they tend to cluster in space&#41;&#46;</p></span></span><span id="sec0060" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0080">Discussion</span><p id="par0115" class="elsevierStylePara elsevierViewall">In this paper we describe the development and the psychometric properties of a preliminary validation of an observational scale assessing neighborhood disorder&#46; This scale was implemented in the city of Valencia &#40;Spain&#41;&#44; using independent observations of all census block groups of the city conducted by trained raters&#46; In general&#44; results have shown that this scale is a psychometrically sound and valid instrument to assess three neighborhood disorder dimensions&#58; physical disorder&#44; social disorder&#44; and physical decay&#46;</p><p id="par0120" class="elsevierStylePara elsevierViewall">Results regarding inter-rater reliability showed fair to substantial levels of agreement &#40;<a class="elsevierStyleCrossRef" href="#bib0300">Landis &#38; Koch&#44; 1977</a>&#41;&#44; with stronger agreements for physical disorder and physical decay factors&#44; and lower inter-rater reliability for social disorder&#46; Although these results are slightly lower than in other studies &#40;e&#46;g&#46;&#44; <a class="elsevierStyleCrossRefs" href="#bib0040">Caughy et al&#46;&#44; 2001&#59; Franzini et al&#46;&#44; 2008&#59; Jones et al&#46;&#44; 2011</a>&#41;&#44; they are&#44; however&#44; comparable to others &#40;e&#46;g&#46;&#44; <a class="elsevierStyleCrossRefs" href="#bib0370">Mooney et al&#46;&#44; 2014&#59; Wei et al&#46;&#44; 2005</a>&#41;&#46; As to why social disorder showed lower levels of agreement&#44; one possibility is that social disorder cues such as fights or public intoxication tend to be less stable over time &#40;e&#46;g&#46;&#44; depending on the time of the day&#41; than other physical features of neighborhoods&#44; like those indicating physical decay and disorder&#44; that are more temporally stable &#40;<a class="elsevierStyleCrossRef" href="#bib0240">Jones et al&#46;&#44; 2011</a>&#41;&#46;</p><p id="par0125" class="elsevierStylePara elsevierViewall">With respect to the factor structure of the observational scale&#44; our analyses aimed to validate a three theoretically-based neighborhood disorder dimensions &#40;<a class="elsevierStyleCrossRef" href="#bib0500">Sampson &#38; Raudenbush&#44; 2004</a>&#41;&#46; To this end&#44; several competing confirmatory factor analyses were first estimated and discarded&#44; yielding a final and depurated version of the scale with good analytical fit&#46; This final scale supported a three-factor model measuring physical disorder&#44; social disorder&#44; and physical decay&#44; as theorized by <a class="elsevierStyleCrossRef" href="#bib0500">Sampson and Raudenbush &#40;2004&#41;</a>&#46;</p><p id="par0130" class="elsevierStylePara elsevierViewall">This final three-factor model was obtained after removing some items for their low variability or poor consistency with their dimension&#46; Although these items are usually present in other scales measuring neighborhood disorder&#44; however&#44; indicators such as abandoned cars&#44; used condoms and syringes &#40;physical disorder&#41;&#44; prostitution &#40;social disorder&#41;&#44; or abandoned commercial buildings &#40;physical decay&#41; were discarded in the final model&#46; The presence of these items was very low and&#44; in the case of syringes&#44; there was no presence at all in any of the census block groups observed&#46; Although the time of the observation may have influenced the low presence of some of these indicators &#40;e&#46;g&#46;&#44; prostitution&#41;&#44; another posible explanation is that&#44; given the characteristics of cities like Valencia&#44; with high density in a relative small area &#40;<a class="elsevierStyleCrossRefs" href="#bib0335">Le Gal&#232;s &#38; Zagrodzki&#44; 2006&#59; Summers et al&#46;&#44; 1999</a>&#41;&#44; some of these indicators could be more present in the outskirts of the city&#44; and therefore outside of the boundaries where the observations were made&#46; This also suggests that differences between the present scale and others developed elsewhere may reflect context-specific features of the cities&#46; Given that these results may be context-dependent&#44; we do not favour the uncritical use of the short-version of the originally proposed scale destilled for this particular study&#46; On the contrary&#44; careful theoretical considerations previous to the use of this scale in other cities should consider whether some &#40;or all&#41; of the items removed could have enough variability and importance as to be included in the instrument&#46; Clearly&#44; a subsequent depuration of the scale according to its psychometric properties is always possible&#46; On the other hand&#44; results for internal consistency of the final three-factor scale by confirmatory analyses also supported its reliability&#44; with CRI values between &#46;82 and &#46;83 for the three scales&#46;</p><p id="par0135" class="elsevierStylePara elsevierViewall">Two different criterion-related validity tests of this observational measure of neighborhood disorder were conducted&#46; For the first one&#44; and drawing from social disorganization theory&#44; we explored associations with three criteria tapping neighborhood characteristics central to this theoretical perspective&#58; neighborhood socioeconomic status&#44; immigrant concentration&#44; and residential instability&#44; masured at the census block group level&#46; As expected&#44; correlations between measures of neighborhood disorder and these structural characteristics of neighborhoods were mostly in the expected direction &#40;<a class="elsevierStyleCrossRefs" href="#bib0290">Kubrin &#38; Weitzer&#44; 2003&#59; Sampson &#38; Raudenbush&#44; 1999&#59; Sampson et al&#46;&#44; 1997</a>&#41;&#44; although with stronger associations for physical decay&#46; For example&#44; high levels of physical decay were significantly associated with lower neighborhood socioeconomic status&#44; higher rates of immigrant concentrarion&#44; and higher residential instability&#46; Social disorder was positively related to levels of immigrant concentration and residential instability&#44; but its association with neighborhood socioeconomic status was not statistically significant&#46; Physical disorder was also negatively related to neighborhood socioeconomic status&#59; however&#44; associations with immigrant concentration and residential instability did not reach significance&#46; These results partly support previous research where significant associations between disorder and a number of neighborhood characteristics were also found&#44; especially those regarding the relationship between physical disorder and decay and neighborhood socioeconomic indicators &#40;<a class="elsevierStyleCrossRefs" href="#bib0040">Caughy et al&#46;&#44; 2001&#59; Jones et al&#46;&#44; 2011&#59; McDonell &#38; Waters&#44; 2011&#59; Mooney et al&#46;&#44; 2014&#59; Sampson &#38; Raudenbush&#44; 1999</a>&#41;&#46; Also&#44; some of our results support studies that fail to find a significant relationship between physical disorder and residential instability &#40;<a class="elsevierStyleCrossRef" href="#bib0495">Sampson &#38; Raudenbush&#44; 1999</a>&#41;&#44; or between physical disorder and immigrant concentration &#40;<a class="elsevierStyleCrossRef" href="#bib0240">Jones et al&#46;&#44; 2011</a>&#41;&#46; It is interesting to note that physical decay was associated with all neighborhood characteristics &#40;socieconomic status&#44; immigrant concentration&#44; and residential instability&#41;&#44; suggesting that differentiating between physical disorder and physical decay is an important theoretical distinction that may provide a more detailed analysis when assessing neighborhood disorder and exploring its relationships with different outcomes and processess &#40;<a class="elsevierStyleCrossRefs" href="#bib0485">Sampson&#44; 2009&#59; Sampson &#38; Raudenbush&#44; 2004</a>&#41;&#46;</p><p id="par0140" class="elsevierStylePara elsevierViewall">As we expected that disordered neighborhoods would tend to cluster together in space &#40;<a class="elsevierStyleCrossRefs" href="#bib0015">Bruinsma et al&#46;&#44; 2013&#59; DiMaggio&#44; 2015&#59; Quick&#44; 2013&#59; Veysey &#38; Messner&#44; 1999</a>&#41;&#44; for the second criterion-related validity test we used a spatial analytical approach to assess the spatial distribution of the different types of neighborhood disorder across all census block groups observed&#46; Results showed that the three types of disorder &#40;physical disorder&#44; social disorder&#44; and physical decay&#41; were spatially clustered&#44; confirming that they were not randomly distributed in the city&#46; This reflects the existence of different areas of the cities where neighborhood disorder tends to concentrate and shows that this neighborhood risk factor tend to cluster in space&#46; These results support the idea that different manifestations of neighborhood disorder&#44; as other characteristics of the cities&#44; are not randomly distributed in space&#46; As illustrated by a growing body of literature linking neighborhood disorder with a wide array of outcomes&#44; including crime&#44; violence&#44; or health&#44; the spatially patterned nature of this risk factor makes more likely that related outcomes will also be spatially patterned &#40;<a class="elsevierStyleCrossRefs" href="#bib0085">Cunradi&#44; Mair&#44; Ponicki&#44; &#38; Remer&#44; 2011&#59; Diez-Roux &#38; Mair&#44; 2010&#59; Freisthler et al&#46;&#44; 2007&#59; Gracia et al&#46;&#44; 2015&#59; Kawachi &#38; Berkman&#44; 2003&#59; Law&#44; Quick&#44; &#38; Chan&#44; 2014&#59; O&#8217;Campo et al&#46;&#44; 2015&#59; Sampson&#44; 2012</a>&#41;&#46;</p><p id="par0145" class="elsevierStylePara elsevierViewall">Finally&#44; this study has both strengths and limitations&#46; Among the strenghts&#44; the use of independent observations of neighborhood conditions&#44; rather than residents&#8217; subjective perceptions&#44; allows to overcome some of the limitations noted in the literature regarding this later approach &#40;<a class="elsevierStyleCrossRefs" href="#bib0040">Caughy et al&#46;&#44; 2001&#59; Mooney et al&#46;&#44; 2014&#59; Sampson &#38; Raudenbush&#44; 1999&#59; Schaefer-McDaniel et al&#46;&#44; 2010</a>&#41;&#46; Relatedly&#44; for the observation of neighborhood disorder at the level of ecological units &#40;rather than the personal level&#41;&#44; we also use a high-resolution approach&#46; We used the smallest administrative units available &#40;i&#46;e&#46;&#44; census block groups&#41; that allow greater homogeneity and precision than lower resolutions such as census tracks or postal codes&#44; commonly used in other neighborhood studies &#40;<a class="elsevierStyleCrossRefs" href="#bib0010">Beyer et al&#46;&#44; 2015&#59; Bursik&#44; Grasmick&#44; &#38; Chamlin&#44; 1990&#59; Kaufman&#44; Dole&#44; Savitz&#44; &#38; Herring&#44; 2003&#59; Campo&#44; Xue&#44; Wang&#44; &#38; Caughy&#44; 1997</a>&#41;&#46; By using small-area units&#44; we also reduced potential ecological bias&#44; as this resolution is closer to the individual level &#40;<a class="elsevierStyleCrossRefs" href="#bib0205">Gracia et al&#46;&#44; 2015&#59; Lawson&#44; 2006</a>&#44; <a class="elsevierStyleCrossRef" href="#bib0400">Oca&#241;a-Riola et al&#46;&#44; 2008</a>&#41;&#46; We used census block groups in our study&#44; which substantially reduced this potential bias&#46; Finally&#44; we used all census block groups of the city&#44; rather than selecting only a sample of them&#44; which provided greater variablity and the possibility to explore potential significant spatial patterns in the distribution of neighborhood disorder across the city &#40;<a class="elsevierStyleCrossRefs" href="#bib0040">Caughy et al&#46;&#44; 2001&#59; Mooney et al&#46;&#44; 2014</a>&#41;&#46; In this regard&#44; the use of spatial methods to complement the criterion-related validity of our observational scale is an important addition to the existing literature&#44; as neighborhoods&#44; from this perspective&#44; are not treated as independent units &#40;<a class="elsevierStyleCrossRefs" href="#bib0155">Gorman&#44; Gruenewald&#44; &#38; Waller&#44; 2013&#59; Mooney et al&#46;&#44; 2014&#59; Morenoff&#44; Sampson&#44; &#38; Raudenbush&#44; 2001</a>&#41;&#46; Although widely used in epidemiological studies &#40;<a class="elsevierStyleCrossRef" href="#bib0330">Lawson&#44; 2009</a>&#41;&#44; and despite its advantages&#44; this methodological approach is still uncommon in neighborhood studies&#44; and future research would clearly benefit from incorporating a spatial perspective &#40;<a class="elsevierStyleCrossRefs" href="#bib0085">Cunradi et al&#46;&#44; 2011&#59; Gracia et al&#46;&#44; 2014&#44; 2015&#59; Law &#38; Quick&#44; 2013&#59; Law et al&#46;&#44; 2014&#59; Sparks&#44; 2011</a>&#41;&#46; As for limitations&#44; as noted above&#44; some measures of neighborhood disorder may have been affected by the time of the day they were observed&#46; Our observations were limited to business hours&#44; and the same places may have shown different characteristics at night &#40;<a class="elsevierStyleCrossRef" href="#bib0040">Caughy et al&#46;&#44; 2001</a>&#41;&#46; Future research would benefit from including different observations during the day&#44; and revisiting the same areas during night hours&#46; Also&#44; other neighborhood indicators such as trash in the streets may be present only at specific moments&#44; and repeated obervations of the same area would be advisable&#44; although clearly more costly &#40;<a class="elsevierStyleCrossRef" href="#bib0580">Wei et al&#46;&#44; 2005</a>&#41;&#46; In this regard&#44; recently new technologies&#44; such as virtual environments&#44; or Google Street View&#44; provide powerful and easy accesible tools that may help to enhance neighborhood research &#40;<a class="elsevierStyleCrossRefs" href="#bib0405">Odgers et al&#46;&#44; 2012&#59; Toet &#38; van Schaik&#44; 2012</a>&#41;&#46;</p><p id="par0150" class="elsevierStylePara elsevierViewall">In conclusion&#44; this paper provides evidence of a reliable and valid observational measure to assess neighborhood disorder&#46; Adequate measures to assess neighborhood characteristics are important research and intervention tools&#44; as they are key to better understanding neighborhood proceses&#44; as well as to evaluate related outcomes and monitor changes after grass-roots efforts or oficial initiatives to reduce neighborhood inequalities&#46;</p></span><span id="sec0065" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0085">Conflict of Interest</span><p id="par0155" class="elsevierStylePara elsevierViewall">The authors of this article declare no conflict of interest&#46;</p></span><span id="sec9065" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0090">Financial Support</span><p id="par0165" class="elsevierStylePara elsevierViewall">This research was supported by the Spanish Ministerio de Econom&#237;a y Competitividad &#40;PSI2014-54561-P&#41;&#46; Miriam Marco was supported by the FPU program of the Spanish Ministerio de Educaci&#243;n&#44; Cultura y Deporte &#40;FPU2013&#47;00164&#41;&#46;</p></span></span>"
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          "titulo" => "Assessing Neighborhood Disorder"
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    "fechaRecibido" => "2015-05-20"
    "fechaAceptado" => "2015-05-25"
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            0 => "Confirmatory factor analysis"
            1 => "Neighborhood disorder"
            2 => "Observational scale"
            3 => "Physical decay"
            4 => "Physical disorder"
            5 => "Spatial clustering"
            6 => "Social disorder"
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            0 => "An&#225;lisis factorial confirmatorio"
            1 => "Desorden del vecindario"
            2 => "Deterioro f&#237;sico"
            3 => "Desorden f&#237;sico"
            4 => "Distribuci&#243;n especial"
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        "titulo" => "Abstract"
        "resumen" => "<span id="abst0005" class="elsevierStyleSection elsevierViewall"><p id="spar0005" class="elsevierStyleSimplePara elsevierViewall">This study presents data on the development and preliminary validation of an observational scale assessing neighborhood disorder&#46; Independent observations by trained raters of neighborhood disorder were conducted in 552 census block groups in the city of Valencia &#40;Spain&#41;&#46; Intraclass correlation coefficients assessing inter-rater reliability indicated fair to substantial levels of agreement among raters&#46; Confirmatory factor analyses supported a final three-factor model scale measuring physical disorder&#44; social disorder&#44; and physical decay&#46; Results for the internal consistency showed large composite reliability indices indicating good reliability for all neighborhood disorder factors&#46; Evidence of criterion-related validity was found by exploring associations between neighborhood disorder factors and three neighborhood characteristics&#58; neighborhood socioeconomic status&#44; immigrant concentration&#44; and residential instability&#46; Also for criterion-related validity&#44; Moran&#39;s I test results for spatial correlation showed that the three types of neighborhood disorder tend to cluster in space and are not randomly distributed across the city&#46; In general&#44; this paper provides evidence of a reliable and valid observational measure to assess neighborhood disorder&#46;</p></span>"
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        "resumen" => "<span id="abst0010" class="elsevierStyleSection elsevierViewall"><p id="spar0010" class="elsevierStyleSimplePara elsevierViewall">Este estudio presenta el desarrollo y validaci&#243;n preliminar de una escala observacional para la evaluaci&#243;n del desorden en los vecindarios&#46; Se realizaron observaciones independientes del desorden por evaluadores entrenados en 552 sectores censales de la ciudad de Valencia &#40;Espa&#241;a&#41;&#46; Los coeficientes de correlaci&#243;n intraclase para la evaluaci&#243;n de la fiabilidad interjueces indicaron unos niveles adecuados de acuerdo entre jueces&#46; Los resultados del an&#225;lisis factorial confirmatorio apoyaron un modelo final de tres factores&#58; desorden f&#237;sico&#44; desorden social y deterioro f&#237;sico&#46; La evaluaci&#243;n de la consistencia interna mediante <span class="elsevierStyleItalic">composite reliability indices</span> mostr&#243; valores elevados para todos los factores&#46; La validez de criterio fue determinada mediante la exploraci&#243;n de las asociaciones entre los factores de desorden del vecindario y tres caracter&#237;sticas del mismo&#58; estatus socioecon&#243;mico&#44; concentraci&#243;n de inmigrantes e inestabilidad residencial&#46; Adem&#225;s&#44; como medida de validez de criterio&#44; el test de Moran que eval&#250;a la correlaci&#243;n espacial mostr&#243; que los tres tipos de desorden tienden a agruparse espacialmente y no se distribuyen aleatoriamente en la ciudad&#46; En general&#44; este art&#237;culo proporciona evidencias de la fiabilidad y validez de una escala para la medida del desorden en los vecindarios&#46;</p></span>"
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          "en" => "<p id="spar0020" class="elsevierStyleSimplePara elsevierViewall">Standardized factor loadings and correlations for the confirmatory factor analyses of the Neighborhood Disorder Observational Scale&#46;</p> <p id="spar0025" class="elsevierStyleSimplePara elsevierViewall"><span class="elsevierStyleItalic">Note</span>&#46; All coefficients statistically significant &#40;<span class="elsevierStyleItalic">p</span> &#60; &#46;01&#41;&#59; Intoxicat &#61; intoxication&#59; Dealing &#61; drug dealing&#59; Vacant &#61; vacant houses&#59; Vandal&#46; &#61; vandalized buildings&#59; Residen&#46; &#61; residential deterioration&#59; Deter&#46; &#61; deteriorated facilities&#46;</p>"
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          "leyenda" => "<p id="spar0035" class="elsevierStyleSimplePara elsevierViewall"><span class="elsevierStyleItalic">Note</span>&#46; ICC<span class="elsevierStyleInf">1</span> &#61; index of reliability for a single rater&#46;</p><p id="spar0040" class="elsevierStyleSimplePara elsevierViewall">ICC<span class="elsevierStyleInf">2</span> &#61; index of reliability for multiple raters averaged together&#46;</p><p id="spar0045" class="elsevierStyleSimplePara elsevierViewall">&#42; &#60; &#46;05&#44; &#42;&#42; &#60; &#46;01&#44; &#42;&#42;&#42; &#60; &#46;001</p>"
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                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">Physical disorder&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">Colillas en la calle &#47; Cigarettes in the street&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry  " align="left" valign="top">2&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">Physical disorder&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">Basura en la calle o acera &#47; Trash in the street&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry  " align="left" valign="top">3&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">Physical disorder&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">Botellas o latas vac&#237;as de cerveza u otras bebidas en la calle &#47; Empty bottles or cans in the street&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry  " align="left" valign="top">4&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">Physical disorder&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">Graffitis &#47; Graffiti&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry  " align="left" valign="top">5&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">Physical disorder&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">Pintadas de car&#225;cter pol&#237;tico o reivindicativo &#47; Political or protest message graffiti&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry  " align="" valign="top">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="" valign="top">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="" valign="top">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry  " align="left" valign="top">1&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">Social disorder&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">J&#243;venes o adultos merodeando por el barrio &#47; Adults or young people loitering&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry  " align="left" valign="top">2&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">Social disorder&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">Gente bebiendo alcohol en la v&#237;a p&#250;blica &#47; People drinking alcohol in public&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry  " align="left" valign="top">3&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">Social disorder&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">Bandas &#47; Gangs&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry  " align="left" valign="top">4&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">Social disorder&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">Gente borracha o drogada por la calle &#47; Public intoxication&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry  " align="left" valign="top">5&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">Social disorder&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">Peleas o discusiones agresivas entre j&#243;venes o adultos &#47; Adultos or young people fighting or arguing&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry  " align="left" valign="top">6&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">Social disorder&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">Venta de droga &#47; Selling drugs&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry  " align="" valign="top">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="" valign="top">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="" valign="top">&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry  " align="left" valign="top">1&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">Physical decay&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">Casas vac&#237;as &#47; Vacant houses&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry  " align="left" valign="top">2&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">Physical decay&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">Viviendas abandonadas&#44; quemadas o tapiadas &#47; Abandoned&#44; vandalized and run-down buildings&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry  " align="left" valign="top">3&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">Physical decay&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">Zonas residenciales muy deterioradas &#47; Deteriorated residential units&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="table-entry  " align="left" valign="top">4&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">Physical decay&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="table-entry  " align="left" valign="top">Zonas recreativas muy deterioradas &#47; Deteriorated recreation places&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr></tbody></table>
                  """
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      "titulo" => "References"
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                      "titulo" => "Neighborhood environment and loss of physical function in older adults&#58; Evidence from the Alameda County study"
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                    0 => array:2 [
                      "titulo" => "Neighborhood environment and intimate partner violence&#58; A systematic review"
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                        "fecha" => "2015"
                        "volumen" => "16"
                        "paginaInicial" => "16"
                        "paginaFinal" => "47"
                        "link" => array:1 [ …1]
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                0 => array:2 [
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                      "titulo" => "Social disorganization&#44; social capital&#44; collective efficacy and the spatial distribution of crime and offenders&#58; An empirical test of six neighbourhood models for a Dutch city"
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                        0 => array:2 [ …2]
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                      "titulo" => "The effect of demographic make-up on perceptions of anti-social behaviour in London as measured by the British Crime Survey and 2008 Place Survey"
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                    0 => array:2 [
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Article information

ISSN: 18891861
Original language: English

DOI:10.1016/j.ejpal.2015.05.001

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2024 August	31	1	32
2024 July	85	3	88
2024 June	34	1	35
2024 May	37	8	45
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2023 December	29	0	29
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2023 April	50	1	51
2023 March	63	1	64
2023 February	37	6	43
2023 January	17	4	21
2022 December	15	3	18
2022 November	17	5	22
2022 October	12	5	17
2022 September	14	5	19
2022 August	10	7	17
2022 July	13	8	21
2022 June	7	3	10
2022 May	9	4	13
2022 April	31	5	36
2022 March	34	6	40
2022 February	20	5	25
2022 January	57	8	65
2021 December	26	5	31
2021 November	8	6	14
2021 October	7	4	11
2021 September	7	10	17
2021 August	5	4	9
2021 July	4	6	10
2021 June	5	6	11
2021 May	7	4	11
2021 April	30	14	44
2021 March	16	6	22
2021 February	10	8	18
2021 January	7	12	19
2020 December	9	2	11
2020 November	11	2	13
2020 October	6	2	8
2020 September	13	12	25
2020 August	13	3	16
2020 July	8	8	16
2020 June	4	0	4
2020 May	16	5	21
2020 April	7	3	10
2020 March	8	0	8
2020 February	14	4	18
2020 January	16	1	17
2019 December	8	4	12
2019 November	8	5	13
2019 October	6	1	7
2019 September	10	1	11
2019 August	2	0	2
2019 July	12	5	17
2019 June	15	4	19
2019 May	103	9	112
2019 April	146	6	152
2019 March	192	16	208
2019 February	148	8	156
2019 January	157	20	177
2018 December	175	8	183
2018 November	172	6	178
2018 October	224	3	227
2018 September	81	2	83
2018 August	41	3	44
2018 July	53	5	58
2018 June	50	3	53
2018 May	41	3	44
2018 April	45	4	49
2018 March	68	2	70
2018 February	40	5	45
2018 January	38	4	42
2017 December	39	3	42
2017 November	70	6	76
2017 October	64	7	71
2017 September	60	7	67
2017 August	55	5	60
2017 July	51	4	55
2017 June	110	10	120
2017 May	110	10	120
2017 April	79	15	94
2017 March	64	11	75
2017 February	70	10	80
2017 January	32	12	44
2016 December	77	22	99
2016 November	91	17	108
2016 October	110	12	122
2016 September	161	16	177
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2016 July	126	14	140
2016 June	106	22	128
2016 May	114	19	133
2016 April	120	19	139
2016 March	104	15	119
2016 February	131	19	150
2016 January	91	11	102
2015 December	143	32	175
2015 November	119	36	155
2015 October	153	40	193
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