{"paper_id":"03b3469a-458d-4e0d-b1be-f2c04ef1b094","body_text":"1 \n \n 1 \n 2 \nFamily Vulnerability Scale: evidence of content and internal structure validity 3 \n 4 \n 5 \nEvelyn Lima de Souza¹ *¶, Ilana Eshriqui¹¶, Flávio Rebustini²¶, Eliana Tiemi Masuda¹ &, 6 \nFrancisco Timbó de Paiva Neto¹&, Ricardo Macedo Lima¹&, Daiana Bonfim¹¶ 7 \n 8 \n 9 \n¹ Center for Studies, Research and Practices in Primary Health Care and Networks 10 \n(CEPPAR), Hospital Israelita Albert Einstein, São Paulo, São Paulo, Brazil 11 \n² Department of Gerontology, School of Arts, Sciences and Humanities (EACH), 12 \nUniversity of São Paulo, São Paulo, São Paulo, Brazil 13 \n 14 \n*Corresponding author 15 \nE-mail: evelyn.lima@einstein.br (ELS) 16 \n 17 \n¶ These authors were responsible for substancial contributions to conception and study 18 \ndesign, acquisition, analysis and interpretation of data, drafting and revising the content, 19 \nfinal approval of the version to be published and agreement to be accountable for all 20 \naspects of the work. 21 \n& These authors were responsible for analysis and interpretation of data, drafting and 22 \nrevising the content, final approval of the version to be published and agreement to be 23 \naccountable for all aspects of the work. 24 \n 25 \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted January 12, 2023. ; https://doi.org/10.1101/2023.01.12.23284419doi: medRxiv preprint \nNOTE: This preprint reports new research that has not been certified by peer review and should not be used to guide clinical practice.\n\n \n2 \n \nAbstract 26 \nIntroduction: territory view based on families’ vulnerability strata allows identifying 27 \ndifferent health needs that, in their turn, can guide healthcare at primary care scope. 28 \nAlthough there are instruments aimed at measuring family vulnerability, they still need 29 \nrobust validity evidences; therefore, they represent a limitation for usability in a country 30 \nshowing multiple socioeconomic and cultural realities, such as Brazil. The present study 31 \nintroduces the development and search for evidences about the validity of the Family 32 \nVulnerability Scale for Brazil, known as EVFAM-BR. Methods: items were generated 33 \nthrough exploratory qualitative study carried out with 123 professionals. Collected data 34 \nsubsidized the generation of 92 initial items that were subjected to a panel of multi-35 \nregional and multi-disciplinary judges (n = 73) to calculate the Content Validity Ratio 36 \n(CVR) – this process resulted in a version of the scale comprising 38 items. 37 \nSubsequently, it was applied to 1,255 individuals to find evidences about the internal-38 \nstructure validity by using the Exploratory Factor Analysis (EFA). Dimensionality was 39 \nassessed through Robust Parallel Analysis and the model was tested through cross-40 \nvalidation to find EVFAM-BR’s final version. Results: the final version comprised 14 41 \nitems distributed into four domains, with explained variance of 79.02%. All indicators 42 \nwere within adequate and satisfactory limits, without any cross-loading and Heywood 43 \nCase issues. Reliability indices also reached adequate levels ( α  = 0.71; ω  = 0.70; glb = 44 \n0.83 and ORION ranging from 0.80 to 0.93, between domains). Instrument’s score was 45 \nsubjected to normalization, and it pointed towards three vulnerability strata (0 to 4 – 46 \nLow; 5 to 6 – Moderate; 7 to 14 - High). Conclusion: the scale showed satisfactory 47 \nvalidity evidences, which were consistent, reliable ad robust; it led to a synthesized 48 \ninstrument capable of accurately measuring and differentiating family vulnerability in 49 \nthe primary care territory, in Brazil. 50 \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted January 12, 2023. ; https://doi.org/10.1101/2023.01.12.23284419doi: medRxiv preprint \n\n \n3 \n \n  51 \nIntroduction 52 \nThe term vulnerability is the core of debates in different knowledge fields; 53 \netymologically it would come from Latin “vulnerare” (harm, impair) and “bile” 54 \n(susceptible) [1]. However, the understanding about vulnerability shows variations 55 \nwhen different dimensions linked to this topic are taken into account [2]. Vulnerability, 56 \nin the Bioethics field, refers to being in danger or exposed to risk due to individual 57 \nweakness, which is a feature inherent to human beings [3]. As for the healthcare field, 58 \nthis term has a broader meaning; it is associated with acknowledging humans as 59 \nsusceptible to damage or to risks within the health/illness process due to social 60 \ndisadvantages [4]. 61 \nAlthough the literature presents different vulnerability definitions and assesses 62 \nindividual predictors, the concept of family vulnerability is measurable through 63 \ndifferent ways [4] because it must take into consideration this phenomenon from 64 \nmultiple aspects that, in their turn, are linked to health needs of members from a given 65 \nfamily. Aspects related to the health condition of members composing the family 66 \nnucleus, as well as the community and social context, are elements to be taken into 67 \naccount at the time to investigate vulnerability in families [5,6]. 68 \nThus, health services and managers must consider family vulnerability to 69 \norganize healthcare practices, mainly from the population perspective [7]. Accordingly, 70 \nterritory view from vulnerability strata perspectives subsidizes the process to identity 71 \nhealth needs in different population groups [2]. Besides, family vulnerability 72 \nstratification is essential at the time to plan the offer of services in a given territory, 73 \nsince it would help achieving equity and qualified of population-based care 74 \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted January 12, 2023. ; https://doi.org/10.1101/2023.01.12.23284419doi: medRxiv preprint \n\n \n4 \n \nmanagement. Hence, considering health teams activities and the care provision order in 75 \nthe Health Care Network based on the needs identified through family vulnerability 76 \ndemands, it is needed to deepening in aspects composing family vulnerability.  77 \nInstruments and initiatives to ensure the observation of aspects likely presented 78 \nby family vulnerability as components to labor process organizations remain scarce. 79 \nSome global experiences are linked to this phenomenon: vulnerability-measuring 80 \nbackground lies on the United Nations Program for Development (UNPD); back in 81 \n2004, it elaborated the Disaster Risk Index (DRI) to measure and compare countries 82 \nwithin a process based on physical, social, economic and environmental factors [8]. 83 \nSubsequently, in 2006, the Autonomous University of Madrid (Spain) estimated the 84 \ndegree of vulnerability of citizens assumingly susceptible to lack of social protection, 85 \nbased on countries belonging to the Organization for Economic Cooperation and 86 \nDevelopment (OECD) [9]. With respect to the Latin scene, one research aimed at 87 \nmeasuring family vulnerability rates in a Colombian municipality based on a sample of 88 \nfamilies from all socioeconomic strata living in an urban zone and in a rural one [10]. 89 \nOther initiatives have been introduced and they aimed at developing instruments 90 \nto be used by primary healthcare (PHC) teams to measure family vulnerability and, 91 \nconsequently, to contribute to plan healthcare provision in the Brazilian territory [11-92 \n15]. However, instruments so far developed and used for such a purpose still need 93 \nrobust evidences of their validity, since they present limitations to be used in a country 94 \nwith continental dimensions, and multiple socioeconomic and cultural realities, like 95 \nBrazil.  96 \nThus, it is essential reasoning about the concept of family vulnerability, with 97 \nemphasis on a diversified population and from this perspective, to develop an 98 \ninstrument which could be used in a standardized way in national scope. Then, the 99 \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted January 12, 2023. ; https://doi.org/10.1101/2023.01.12.23284419doi: medRxiv preprint \n\n \n5 \n \npresent study aim to seek validity evidences about the content and internal structure of 100 \nthe Family Vulnerability Scale for Brazil (EVFAM-BR). 101 \n 102 \nMaterials and methods 103 \nThe present study followed a psychometric nature design to seek evidences 104 \nabout both content validity (stage 1) and internal structure (stage 2) based on current 105 \nrecommendations by the Educational Research Association (AERA), the American 106 \nPsychological Association (APA) and the National Council on Measurement in 107 \nEducation (NCME) [16]. The study was approved by the Ethics Research Committee of 108 \nHospital Israelita Albert Einstein , which was approved on October 22, 2019 (nº 109 \n3.674.106, CAAE 12395919.0.0000.0071). 110 \n 111 \nStage 1: content validity evidences 112 \nPHC professionals from all Brazilian geographic regions were invited to join the 113 \nfirst qualitative exploratory stage of the study to define the concept of “family 114 \nvulnerability” and to identify factors likely associated with it, in order to subsidize the 115 \ndevelopment of items for the instrument. It was done to identify different 116 \nunderstandings about family vulnerability in different geographic regions countrywide.  117 \nThe invitation was made based on the snowball method [17], by WhatsApp and 118 \ne-mail. Using the RedCap® electronic tool [18,19], an online semi-structured 119 \nquestionnaire was made available for participants after they read the free consent form 120 \nand formally accepted to join the study. 121 \nThe questionnaire comprised (i) respondents’ socioeconomic, demographic and 122 \nhealth profile identification, (ii) open questions about the concept of vulnerability and 123 \nscale applicability, and (iii) multiple-choice questions about the relevance of measuring 124 \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted January 12, 2023. ; https://doi.org/10.1101/2023.01.12.23284419doi: medRxiv preprint \n\n \n6 \n \nfamily vulnerability; the questions were distributed into 46 items elaborated from 125 \nindividual and domestic registration forms used at the Brazilian public healthcare 126 \nsystem through e-SUS PHC system [20,21]. Frequencies of responses for items 127 \nexpressed in multi-choice questions and the group of aspects identified in open 128 \nquestions were taken into consideration based on the Content Analysis Technique in 129 \norder to elaborate the first version of items [22] – they were developed in an 130 \ninterrogative way to allow dichotomous answers (“0 – no” and “1 – yes”). 131 \nItems developed from the previous stage were subjected to an extensive panel of 132 \nmulti-regional and multi-disciplinary judges. The panel encompassed health 133 \nprofessionals, scholars and psychometrists who were invited to join the study through 134 \nthe snowball method.  135 \nThe large number of judges was explained by the need of calculating and 136 \napplying the instrument at national scope. The judges judged the items in the first 137 \nversion of the instrument based on relevance and clarity criteria, as well as were 138 \nenquired about the need of changing the writing of any item. Then, option was made to 139 \napply the Content Validity Ratio (CVR) scale [23] as the validity index to select the 140 \nitems. CVR is calculated based on the number of judges in the panel [24,25] in order to 141 \nallow the adoption of a larger number of judges. CVR was initially applied to assess the 142 \nrelevance of a given item in order to check whether it effectively measures the latent 143 \nvariable: family vulnerability. CVR was represented as CVR-1 (the Item’s CVR) and 144 \nCVR-E (Scale CVR) – this last one corresponds to mean recorded for the CVR criteria. 145 \nIt is important highlighting that a modified CVR version with two points, namely “no” 146 \nand “yes”, was adopted. The original version had three points and did not have an 147 \neffective practical effect, since, for CVR calculation purposes, it used to become 148 \ndichotomous. This procedure was already adopted in studies [26,27].     149 \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted January 12, 2023. ; https://doi.org/10.1101/2023.01.12.23284419doi: medRxiv preprint \n\n \n7 \n \nOftentimes, the mean recorded for the assessed questionnaires is adopted; 150 \ntherefore, a hierarchic flow was herein adopted, since other indicators, such as item’s 151 \nclarity, were only analyzed after judges showed its relevance to testify that the item 152 \nactually assesses the instrument’s latent variable. The application of requirements in the 153 \nsame stage tends to inflate mean CVR and to launch items that do not measure the latent 154 \nvariable to the next stage. Accordingly, as pointed out by DeVellis [28], a given item 155 \ncan be relevant, but its words might be problematic. Thus, the second stage refers to 156 \nitems’ clarity (whether the item is well written in terms of its semantics). The third stage 157 \nassessed the need of changing the items’ writing. The mean recorded for CVR was only 158 \napplied to items that adhered to the phenomenon.  159 \n 160 \nStage 2: Evidences about internal structure validity 161 \nThe version subjected to content evidences was applied to users of PHC services 162 \nto find evidences about internal structure validity. 163 \nAll data collectors were previously trained and clarified about the informed 164 \nconsent form application, as well as about research aim, methodology and questions. 165 \nStudy presentation and data collection flow were also previously carried out with teams 166 \nfrom the participating PHC services. 167 \nPHC services selection was based on municipalities presenting the largest 168 \npopulation of attendees of the Program to Support the Institutional Development by the 169 \nUnified Healthcare System (Proadi-SUS) in Brazil, PlanificaSUS [29]. It was done by 170 \nincluding at least one PHC service from each geographic region in the country. Thus, 171 \ndata collection was carried out in 11 PHC services: 1 in Northern Brazil (Roraima 172 \nState), 1 in the Northeastern region (Pernambuco State) and 2 in Midwestern Brazil 173 \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted January 12, 2023. ; https://doi.org/10.1101/2023.01.12.23284419doi: medRxiv preprint \n\n \n8 \n \n(Mato Grosso State), 5 in the Southeastern region (São Paulo and Minas Gerais states) 174 \nand 2 in Southern Brazil (Paraná State).  175 \nThe Covid-19 pandemic met the first data collection stage (from June to 176 \nNovember 2020); therefore, interviews with São Paulo healthcare unit users were 177 \ncarried out by phone. Service managers were aware of it, since they provided 178 \ninformation to identify interviewees in the territory. As for the second data collection 179 \ntime (from May to August 2022), users who had attended the participating PHC service 180 \nat data-collection day were asked to join the study. 181 \nOver 18-year-old participants were informed about the informed consent form at 182 \nboth data-collection times and they only joined the research after signing it. 183 \nSubsequently, the structured questionnaire about the family vulnerability scale was 184 \napplied, and it was followed by participants featuring in RedCap® [18,19]. 185 \n 186 \nStatistical analysis  187 \nExploratory factor analysis 188 \nThe first stage of the analysis aimed at assessing whether the collected data were 189 \nprone to factorial through Measure of Sampling Adequacy (MSA). Bartlett sphericity, 190 \ndeterminant of the matrix and Kaiser-Meyer-Olkin (KMO) were assessed at this stage. 191 \nBesides assessing the dataset items, individual analysis was also assessed, as 192 \nrecommended by Lorenzo-Seva and Ferrando [30]. The inadequacy of items to be 193 \nfactored can affect model solution. Missing data were treated through the multiple 194 \nimputation technique [31].  195 \nDimensionality testing was carried out through Parallel Analysis, based on 196 \nOptimal implementation of Parallel Analysis (PA) and Minimun rank factor analysis to 197 \nminimize the common variance of residues [32]. PA was implemented through 198 \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted January 12, 2023. ; https://doi.org/10.1101/2023.01.12.23284419doi: medRxiv preprint \n\n \n9 \n \npermutation with 500 random matrices. Dimensionality in exploratory factorial analysis 199 \n(unrestricted model) was tested through Parallel Analysis, which has been considered 200 \nmore robust and accurate to test it [33-37]. 201 \nTetrachoric matrix estimates were carried out through Bayes Modal Estimation 202 \n[38], with Smoothing Ridge [39]. The use of tetrachoric/polychoric correlations tends to 203 \nincrease the model’s accuracy in comparison to Pearson’s correlation [40,41]. 204 \nFactors’ extraction was performed through the RULS technique (Robust 205 \nUnweighted Least Squares), which reduces the residues in matrices that are more robust 206 \nin terms of abnormal data [42]. Promin oblique rotation would be used in case the 207 \ninstrument emerged as multi-dimensional [43].  208 \nUNICO (Unidimensional Congruence > 0.95), ECV (Explained Common 209 \nVariance > 0.80 – Quinn, 2014) and MIREAL (Mean of Item Residual Absolute 210 \nLoadings < 0.30) were adopted as unidimensionality assessment indicator [44]. 211 \nQuality parameters of the instrument 212 \nInstrument explained variance must be close to 60% [45]. Initial factorial load of 213 \n0.30 is recommended when the sample comprises less than 300 individuals [45]; 214 \ncommunities must present values higher than 0.40 [46]. The maintenance or removal of 215 \na given model item depend on factorial load magnitude, on the communities and on the 216 \nexistence of cross-loading and Heywood cases, as well as on the impermeability of 217 \nfactors. The unique directional correlation (Eta) through Pratt’s Measure was adopted to 218 \nincrease the accuracy of decision-making about the maintenance or removal of a given 219 \nitem [47,48].    220 \nReliability 221 \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted January 12, 2023. ; https://doi.org/10.1101/2023.01.12.23284419doi: medRxiv preprint \n\n \n10 \n \nReliability was measured through four indicators: Cronbach's alpha [49], 222 \nGreatest Lower Bound – glb [50], Omega [51] - all three by means of Bayesian 223 \nestimates - and ORION (Overall Reliability of Fully-Informative prior Oblique N-EAP 224 \nscores) [52]. 225 \nCross-validation was applied to increase the model’s reliability and replicability; 226 \nthe Houdolt technique was also herein applied [53]. This technique divides the dataset 227 \ninto a training sample - that can range from 10%, 30% to 50% - and into a dataset 228 \nknown as test dataset [53]. The dataset in the present study was split in half by 229 \nrandomly choosing the items. The Solomon technique [54] was adopted, so that dataset 230 \ndivision could be random and respect factorability’s equivalence. The datasets were 231 \nlabeled as follows: Full Sample (FS; n = 1,255); Training Sample (TrS n = 627) and 232 \nTest Sample (TsS; n = 628). According to Brown [55], cross-validation can be carried 233 \nout either through EFA or Confirmatory Factor Analysis (CFA). FS analysis will only 234 \ntake place if the model found in TrS and TsS can be replicated. This procedure was 235 \nalready adopted in previous studies [56,57], and it follows contemporary 236 \nrecommendations [58]. 237 \nDescriptive study and standardization 238 \nAn exploratory descriptive study of general scores recorded for the Family 239 \nVulnerability Scale (FVS - EVFAM-BR, in Brazilian Portuguese) was carried out after 240 \na solution for the internal structure was found. Results recorded for the items and for 241 \ntotal score were represented by answers’ frequency, median (Md), interquartile interval 242 \n(IIQ), amplitude (amp), minimum (min) and maximun (max) value.  243 \nStandardization, in the first stage, was performed by identifying score cuts based 244 \non participants’ distribution. Despite this process, although participants’ distribution is 245 \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted January 12, 2023. ; https://doi.org/10.1101/2023.01.12.23284419doi: medRxiv preprint \n\n \n11 \n \nrecurrent in standardization studies, it can present distortions, because the score is not 246 \ndirectly analyzed, but it can be taken as consequence of participants’ position in the 247 \ncutting points. Discriminant analysis of each one of the limits and Family Vulnerability 248 \nScale scores were used to improve the accuracy of proposed cuts (within the limit) and 249 \nto assess the predictive ability to classify the individuals. The discriminant analysis aims 250 \nat better understanding group differences and at predicting the probability of an entity 251 \n(individual or object) to perceive a specific class or group, based on several independent 252 \nvariables of the metrics [59]. Boedeker and Kearns [60] identified a better performance 253 \nby the discriminating analysis in comparison to many other techniques applied for the 254 \nsame purpose. Besides, it allows determining the independent variable mostly 255 \naccounting for differences in mean score profiles in two or more groups [59]. 256 \nTabachnick and Fidell [61] added to this information by stating that the aim of the 257 \ndiscriminating analysis is to predict the group’s participation based on a set of 258 \npredictors. Accordingly, it is possible confirming whether the groups formed from the 259 \ndistribution process have properly classified individuals within the established limits.  260 \nData were analyzed in statistic software Factor 12.01.01, SPSS v.23 and JASP 261 \n16.04. 262 \n 263 \nResults 264 \nContent validity evidences 265 \nIn total, 123 professionals from the five Brazilian regions joined the first stage of 266 \nthe research to define the concept of “family vulnerability”: 48.8% of them came from 267 \nNortheastern Brazil; 21.1% from Southeastern Brazil; 17.9% from Southern Brazil, 268 \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted January 12, 2023. ; https://doi.org/10.1101/2023.01.12.23284419doi: medRxiv preprint \n\n \n12 \n \n8.9% from Northern Brazil and 3.3% from Midwestern Brazil. Most professionals 269 \nbelonged to the female sex (82.9%), approximately 40% of them had at least 10-year 270 \nexperience in PHC and 48.8% reported to have specialization degree and higher 271 \nschooling profiles. Nurses were the professional category accounting for the highest 272 \nparticipation in this stage (48.3%); they were followed by Community Health Agents – 273 \nCHA – (10.7%). The first version of the instrument counted on 92 items; it was 274 \ndeveloped from factors’ responses that, at first, could be associated with the concept of 275 \nfamily vulnerability.  276 \nA panel of multi-regional and multi-disciplinary judges was set for the second 277 \nstage; it aimed at identifying content validity evidences. This panel comprised 73 278 \njudges: 61.7% from Southeastern Brazil, 15.1% from Southern Brazil, 9.6% 279 \nNortheastern Brazil, 6.8% from Northern Brazil and 6.8% from Midwestern Brazil. 280 \nMost of them belonged to the female sex (79.5%), more than half of them had less than 281 \n10-year experience in PHC (57.5%) and specialization as higher schooling profile 282 \n(51.4%). Nurses were the professional category accounting for the highest participation 283 \nin the panel (50.7%), they were followed by physicians (16.55). CVR was applied to 284 \njudges’ answers. CVR critical value was established at CVR > 0.12, which was defined 285 \nbased on the participation of 73 judges.  286 \nCVR calculation led to the exclusion of 54 items, and it resulted in scale version 287 \ncomprising 38 items linked to socioeconomic and demographic aspects, access to 288 \nhealthcare services, health condition and life style. In order to achieve a better 289 \nunderstanding of it, 12 of the 38 items were rewritten based on recommendations from 290 \nthe panel of judges. It must be clear that only items 2 and 15 (Table 1) recorded CVR 291 \nlower than the critical value; therefore, their text was revised. The other 10 items did not 292 \nsuffer any change; writing adjustments were made in the original text just to meet 293 \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted January 12, 2023. ; https://doi.org/10.1101/2023.01.12.23284419doi: medRxiv preprint \n\n \n13 \n \nCVR’s critical value. The version presenting evidence of content validity (38 items) was 294 \ntaken into consideration in the stage to evidence internal structure validity. 295 \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted January 12, 2023. ; https://doi.org/10.1101/2023.01.12.23284419doi: medRxiv preprint \n\n \n14 \n \nTable 1. Items that remained in the scale after Content Validity Ratio (CVR) application. 296 \nItem \n \nContent Validity Ratio (CVR) \nRelevance Clarity Need of changeª New text of the item \n1. Is there lack of basic sanitation system in the neighborhood \nyou live in? 0.12 0.12 0.78 Is there open sewer in your \nneighborhood? \n2. Do you drink untreated water in your house? 0.12 0.07 0.86 Does the water in your house lack \ntreatment? \n3. Does your house face the risk of flood? 0.18 0.40 1.00 - \n4. Do you live close to drug dealing areas? 0.12 0.40 0.95 - \n5. Does anyone at your house live close to violent people? 0.21 0.32 0.97 - \n6. Has anyone in your house been victim of violence? 0.26 0.34 1.00 - \n7. Is there violence in your house? 0.23 0.32 1.00 - \n8. Is anyone in your house in legal custody condition? 0.12 0.26 0.86 Is anyone in your Family in jail? \n9. Is anyone in your house facing financial issues? 0.15 0.12 0.97 - \n10. Does anyone lack money to fulfill household needs ? 0.12 0.21 0.97 - \n11. Does anyone in your house is a Bolsa Família beneficiary? 0.12 0.32 1.00 - \n12. Is anyone in your house a BPC (continued benefit)/LOAS \n(Social Security Organic Law) beneficiary?  0.15 0.21 0.86 Does anyone in your house get health \nbenefit (BPC /LOAS)? \n13. Have any health professional ever mentioned that someone \nin your house presents obesity? 0.12 0.15 0.86 - \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted January 12, 2023. ; https://doi.org/10.1101/2023.01.12.23284419doi: medRxiv preprint \n\n \n15 \n \n14. Have any health professional ever mentioned that someone \nin your house suffers with malnutrition? 0.15 0.12 0.89 - \n15. Is there any difficulty in making sure about food variety in \nyour house? 0.15 0.10 0.92 It is hard to make sure about the access to \ndifferent food types? \n16. Does anyone in your house starve? 0.21 0.26 0.92 - \n17. Does anyone in your house have drug addiction? 0.23 0.26 0.89 Does anyone in your house use illegal \ndrugs? \n18. Is anyone in your house an alcohol abuser? 0.23 0.26 0.92 - \n19. Does anyone in your house use controlled medication? 0.15 0.37 0.95 - \n20. Does anyone in your house use 5, or more, medications a \nday? 0.18 0.40 0.95 Does anyone in your house uses 5, or \nmore, medications on a daily basis? \n21. Does anyone in your house have a health condition that \ndemands long-term caregiving? 0.21 0.26 0.97 Does anyone in your house have a health \ncondition that requires continuous care? \n22. Is anyone in your house impaired to perform daily activities? 0.18 0.23 0.86 - \n23. Is anyone in your house helped by others to accomplish its \nown daily healthcare procedures? 0.15 0.21 0.95 \nDoes anyone in your house need help to \naccomplish its own daily healthcare \nprocedures? \n24. Does anyone in your house present any disability? 0.12 0.37 1.00 - \n25. Does anyone in your house have any intellectual/cognitive \ndisability? 0.15 0.29 0.84 - \n26. Does anyone in your house have mental issues? 0.21 0.34 1.00 - \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted January 12, 2023. ; https://doi.org/10.1101/2023.01.12.23284419doi: medRxiv preprint \n\n \n16 \n \n27. Does anyone in your house have HIV/aids? 0.15 0.32 0.97 - \n28. Is anyone in your house sick in bed? 0.15 0.32 1.00 - \n29. Does anyone in your house often go to urgency and \nemergency units? 0.18 0.29 0.95 - \n30. Does anyone in your house do not know the UBS/healthcare \nunit team in charge of your family? 0.15 0.32 0.95 - \n31. Did anyone in your house have a child without wanting it? 0.15 0.29 0.95 Has anyone in your house had an \nunplanned child? \n32. Did anyone in your house have a child before turning 20 \nyears old? 0.12 0.37 0.97 - \n33. Has anyone in your house had its mother absent in \nchildhood? 0.18 0.34 1.00 - \n34. Has anyone in your house had an absent father in the \nchildhood? 0.12 0.32 1.00 - \n35. Has anyone in your house faced abandonment by the family? 0.21 0.18 0.95 - \n36. Are children in your house out of school? 0.12 0.32 0.92 Are there children in your house out of \nschool? \n37. Are there adolescents in your hose out of school? 0.12 0.37 0.97 Do you have any adolescent in your \nhouse out of school? \n38. Are there under 14-year-old individuals in your house that \nhave a job? 0.21 0.23 0.95 - \nMean CVR 0.16 0.27 0.94 - \nª Accordingly, CVR values higher than the critical value point towards no need of changing the writings, although some items un der this 297 \ncondition were rewritten in order to improve semantics’ adequacy. 298 \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted January 12, 2023. ; https://doi.org/10.1101/2023.01.12.23284419doi: medRxiv preprint \n\n \n17 \n \n 299 \nEvidences about internal structure validity 300 \nIn total, 1,584 users who attended the 11 PHC services during data collection 301 \nwere invited to join this research stage. However, only 1,505 (95%) of them accepted 302 \nthe invitation and signed the informed consent form. Only 1,255 of them completed the 303 \ninterview for the application of the scale version presenting content validity evidences. 304 \nThis sample represented the study’s final sample and this version presented content 305 \nvalidity evidences. Table 2 introduces participants’ description of this study stage.  306 \nTable 2. Participants’ featuring.    307 \nVariables (n=1255) Categories N (%) \nAge in yearsa - 43.3 (15.5%) \nSex (n=756) Female 551 (43.9%) \nMale 205 (16.3%) \nRace/skin color \n(n=1217) \nWhite 386 (30.8%) \nBrown 640 (51.0%) \nBlack 150 (12.0%) \nYellow 23 (1.8%) \nIndigenous 18 (1.4%) \nSchooling (in years) \n(n=1237) \n0 to 4 years 160 (12.7%) \n5 to 8 years 225 (17.9%) \n9 to 11 years 247 (19.7%) \n12 to 15 years 480 (38.2%) \nOver 16 years 125 (10.0%) \nJob (n=1237) \nUnemployed or does not have a job 447 (35.6%) \nEmployer 1 (0.1%) \nSelf-employed without social security 111 (8.8%) \nSelf-employed with social security 47 (3.7%) \nWage owner 413 (32.9%) \nretired/pensioner 181 (14.4%) \nOthers 37 (2.9%) \nincome (in minimum \nwage)b (n=726) \nNo income 58 (4.6%) \nUp to 1 minimum wage 327 (26.1%) \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted January 12, 2023. ; https://doi.org/10.1101/2023.01.12.23284419doi: medRxiv preprint \n\n \n18 \n \n> 1 and lower than 2 minimum wages  179 (14.3%) \n>= 2 and lower than 4 minimum wages 115 (9.2%) \n>= 4 lower than 10 minimum wages 31 (2.5%) \n>= 10 minimum wages 4 (0.3%) \nDoes not know 12 (1.0%) \nNumber of children \n(n=759) \n1 child 140 (11.2%) \n2 children 198 (15.8%) \n3 children 129 (10.3%) \nMore than 3 children 129 (10.3%) \nExpecting the first child 19 (1.5%) \nDoes not have children 144 (11.5%) \nNumber of households \nper room in the house \n(n=1223) \n<1 406 (32.4%) \n1 697 (55.5%) \n>1 120 (9.6%) \nPrivate healthcare \ninsurance (n=1231) \nYes 180 (14.3%) \nNo 1,051 (83.7%) \nSystemic High Blood \nPressure (n=1240) \nYes 212 (16.9%) \nNo 1,028 (81.9%) \nDiabetes Mellitus \n(n=1238) \nYes 96 (7.6%) \nNo 1,142 (91%) \nCancer (current) \n(n=1237) \nYes 6 (0.5%) \nNo 1,231 (98.1%) \nHeart disease \n(n=1240) \nYes 72 (5.7%) \nNo 1,168 (93.1%) \nIntellectual/cognitive \nimpairment (n=812) \nYes 15 (1.2%) \nNo 797 (63.5%) \nTuberculosis (n=1240) Yes 3 (0.2%) \nNo 1,237 (98.6%) \nLeprosy (n=1239) Yes 1 (0.1%) \nNo 1,238 (98.6%) \nKidney issues \n(n=1237) \nYes 35 (2.8%) \nNo 1,202 (95.8%) \nBreathing issues \n(n=1232) \nYes 96 (7.6%) \nNo 1,136 (90.5%) \nMental issues \ndiagnosis (n=1238) \nYes 30 (2.4%) \nNo 1,208 (96.3%) \na continuous numerical variable described as mean and standard deviation. 308 \nbone minimum wage corresponds to R$1,212.00 (in Brazilian Real, in 2022). 309 \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted January 12, 2023. ; https://doi.org/10.1101/2023.01.12.23284419doi: medRxiv preprint \n\n \n19 \n \nFactorability 310 \nThe evaluation of sample adequacy measures is the first step of the factorability 311 \nanalysis; it aims at assessing dataset factorability and whether factorial analyses are 312 \napplicable. Dataset’s general data have shown good factorability: Fs recorded KMO 313 \n(0.75), Bartlett Sphericity = 6,084.6 (df = 91; P < 0.0001) and determinant of the matrix 314 \n= 0.00001. As for TrS: KMO (0.74), Bartlett Sphericity = 6,153.7 (df = 91; P < 0.0001) 315 \nand determinant of the matrix = 0.00001; TsS: KMO (0.71), Bartlett Sphericity = 316 \n2,617.3 (df = 91; P < 0.0001) and determinant of the matrix = 0.0002. Although general 317 \nindices presented good indicators, 4 of the 38 initial items have shown factorability 318 \nissues in three datasets (27 - Does anyone in your house have HIV/aids?; 36 - Are there 319 \nchildren in your house out of school?; 37 - Do you have any adolescent in your house 320 \nout of school?; and 38 - Are there under 14-year-old individuals in your house that have 321 \na job?). They were excluded from the analyses based on recommendations by Lorenzo-322 \nSeva and Ferrando [30].  323 \nDimensionability 324 \nThe first analyses were carried out in TrS. Dimensionality analyzed through 325 \nparallel analysis pointed towards a 4-dimension model. Closeness of dimensionality 326 \nvalues kept the indication for multi-dimensional model: Single = 0.82; ECV = 0.65 and 327 \nMIREAL = 0.37. Thirteen (13) of the 34 items forming the initial analysis did not 328 \npresent substantial factorial load in the model. Accordingly, the process to remove items 329 \nin order to adjust the model followed two principles: quantitative (statistical adjustment) 330 \nand qualitative (interpretability) adjustment. The choice for removing an item was 331 \ncarried out by taking into consideration the set of primary indicators: factorial load, 332 \ncommunality, Eta of Pratt’s Importance Measure, existence of cross-loading, Heywood 333 \ncase and model adjustment indices. The items were removed from the scale up to the 334 \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted January 12, 2023. ; https://doi.org/10.1101/2023.01.12.23284419doi: medRxiv preprint \n\n \n20 \n \ntime the two principles were congruent to each other, and it resulted in a model for 4-335 \ndimension TrS, with 14 items with proper statistical adjustment, open for 336 \ninterpretability. The parallel analysis kept on pointing out a 4-dimension solution and 337 \nexplained variance of 78.66%. This model was replicated in TsS and FS. Both datasets 338 \nconfirmed the 4-dimension model; furthermore, the closeness of dimensionality values 339 \nreinforced the multi-dimensional model (Table 3) for the three datasets.    340 \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted January 12, 2023. ; https://doi.org/10.1101/2023.01.12.23284419doi: medRxiv preprint \n\n \n21 \n \nTable 3. Items’ I-Unico, I-ECV and I-Real values 341 \nItem I-UNICO I-ECV I-REAL \nTrS TsS FS TrS TsS FS TrS TsS FS \n1. Is anyone in your house facing financial issues?  1.000 0.958 1.000 0.991 0.770 0.984 0.063 0.352 0.084 \n2. Do you lack money to fulfill household needs? 1.000 0.931 1.000 0.996 0.719 0.990 0.038 0.389 0.061 \n3. It is hard to make sure about access to different food types? 1.000 0.988 1.000 0.976 0.865 0.992 0.094 0.232 0.053 \n4. Does anyone in your house use controlled medication? 0.957 0.983 0.970 0.766 0.844 0.799 0.328 0.275 0.320 \n5. Does anyone in your house use 5, or more medications, on a daily basis? 0.662 0.988 0.926 0.469 0.863 0.711 0.491 0.261 0.361 \n6. Does anyone in your house have a health condition that requires continuous care? 0.927 0.968 0.963 0.711 0.795 0.782 0.449 0.383 0.374 \n7. Is anyone in your house impaired to perform daily activities? 0.850 0.966 0.941 0.617 0.789 0.735 0.560 0.400 0.439 \n8. Does anyone in your house need help to accomplish its own daily healthcare procedures? 0.742 0.961 0.887 0.525 0.777 0.657 0.538 0.378 0.478 \n9. Did anyone in your house have its mother absent in childhood? 0.291 0.347 0.387 0.233 0.270 0.295 0.600 0.493 0.516 \n10. Did anyone in your house have an absent father in childhood? 0.495 0.240 0.511 0.363 0.198 0.373 0.465 0.535 0.389 \n11. Has anyone in your house faced abandonment by the family? 0.927 0.583 0.912 0.711 0.418 0.690 0.329 0.439 0.297 \n12. Does anyone in your house live close to violent people? 0.868 0.936 0.488 0.636 0.727 0.358 0.481 0.115 0.616 \n13. Have anyone in your house been victim of violence? 0.861 0.914 0.731 0.628 0.693 0.517 0.450 0.295 0.564 \n14. Is there violence in your house? 0.914 0.963 0.349 0.692 0.782 0.272 0.381 0.021 0.503 \nI-UNICO, Unidimensional Congruence; I-ECV, Explained Common Variance; I-REAL, Residual Absolute Loadings; TrS, Training Sample; TsS, Test \nSample; FS, Full Sample. \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted January 12, 2023. ; https://doi.org/10.1101/2023.01.12.23284419doi: medRxiv preprint \n\n \n22 \n \n 342 \nTrS primary data (Table 4) presented factorial data ranging from 0.597 to 0.975, 343 \ncommunality ranging from 0.449 to 0.967, and Eta ranging from 0.640 to 0.941. The 344 \nmodel recorded explained variable of 76.18%. Items 1 and 3 comprised dimension 345 \nIncome, items from 4 to 8 comprised dimension Healthcare, dimension Family was in 346 \nitems 9 to 11, and the single dimension called Violence was observed in items 12 to 14. 347 \nAccordingly, the model points towards good factorial and interpretable (quantitatively) 348 \nsolution, with content alignment in coherent and interpretable (quantitatively) items. 349 \nThe final version of the scale represented reduction by approximately 63% in the 38 350 \nitems assessed through judges’ panel in the first stage. This value is close to that 351 \npresented by DeVellis [28], according to whom the researcher must project items lost by 352 \n50% throughout the process.  353 \nBased on the four dimensions composing the scale, it is possible taking into 354 \naccount the key role played by social determinants within the health/illness process. 355 \nDimensions embody items related to income, social and family cohesion, and to life and 356 \nhousing conditions associated with psychosocial and behavioral aspects [62]. Thus, it 357 \nextrapolates the biological view of health, which is overall acknowledged in a 358 \nreductionist way, centered in medical practices [62-65]. Nevertheless, the present 359 \ninstrument emerges as multi-disciplinary work-tool available for PHC teams that have 360 \nthe potential to promote social justice by taking into consideration social inequities at 361 \nthe time to plan healthcare services.  362 \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted January 12, 2023. ; https://doi.org/10.1101/2023.01.12.23284419doi: medRxiv preprint \n\n \n23 \n \nTable 4. Training dataset: Factorial loads, communality and Eta. 363 \nItem \nFactorial Load \nh2 \nPratt’s Measure - (Eta) \nIncome Healthcare Family Violence Income Healthcare Family Violence \n1. Is anyone in your house facing financial issues? 0.893 0.027 -0.012 0.059 0.849  0.904 0.098 0.000 0.146 \n2. Do you lack money to fulfill household needs? 0.895 -0.013 0.013 -0.067 0.762  0.872 0.000 0.049 0.000 \n3. Is there any difficulty in making sure about food variety in your \nhouse? 0.597 0.091 0.102 0.110 0.516  0.642 0.180 0.174 0.203 \n4. Does anyone in your house use controlled medication? -0.100 0.693 0.101 0.067 0.500  0.000 0.680 0.146 0.130 \n5. Does anyone in your house use 5, or more, medications on a \ndaily basis? -0.080 0.711 0.031 -0.118 0.449  0.000 0.668 0.051 0.000 \n6. Does anyone in your house have a health condition that \nrequires continuous care? -0.032 0.805 0.020 0.069 0.671  0.000 0.805 0.059 0.139 \n7. Is anyone in your house impaired to perform daily activities? 0.094 0.862 -0.131 0.029 0.798  0.189 0.869 0.000 0.084 \n8. Does anyone in your house need help to accomplish its own \ndaily healthcare procedures? 0.062 0.737 -0.053 -0.090 0.540  0.132 0.723 0.000 0.000 \n9. Did anyone in your house have its mother absent in childhood? 0.012 -0.140 0.798 0.013 0.630  0.042 0.000 0.790 0.061 \n10. Did anyone in your house have its father absent in childhood? 0.056 -0.033 0.741 -0.097 0.514  0.099 0.000 0.710 0.000 \n11. Has anyone in your house faced abandonment by the family? 0.018 0.148 0.630 0.073 0.504  0.065 0.203 0.658 0.163 \n12. Does anyone in your house live close to violent people? 0.192 -0.130 -0.108 0.975 0.967 0.284 0.000 0.000 0.941 \n13. Have anyone in your house been victim of violence? -0.118 0.086 0.290 0.605 0.574 0.000 0.146 0.379 0.640 \n14. Is there violence in your house? -0.124 0.055 -0.091 0.937 0.787 0.000 0.117 0.000 0.880 \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted January 12, 2023. ; https://doi.org/10.1101/2023.01.12.23284419doi: medRxiv preprint \n\n \n24 \n \n 364 \nFactorial loads recorded for the TsS dataset (Table 5) ranged from 0.643 to 365 \n0.976, communality ranged from 0.482 to 0.910 and Eta ranged from 0.658 to 0.951. 366 \nThis model presented explained variance of 76.18%. Once again, the observed model 367 \nwas equal to the training dataset model; consequently, it was quantitatively and 368 \nqualitatively interpretable.  369 \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted January 12, 2023. ; https://doi.org/10.1101/2023.01.12.23284419doi: medRxiv preprint \n\n \n25 \n \nTable 5. Test dataset: Factor loading, communality and Eta    370 \nItem \nFactorial Load \nh2 \nPratt’s Measure - (Eta) \nIncome Healthcare Family Violence Income Healthcare Family Violence \n1. Is anyone in your house facing financial issues? 0.801 0.032 0.046 0.056 0.702  0.818 0.108 0.128 0.075 \n2. Do you lack money to fulfill household needs? 0.976 -0.072 0.013 -0.008 0.910  0.951 0.000 0.068 0.000 \n3. Is there any difficulty in making sure about food variety in \nyour house? 0.805 0.063 -0.084 -0.006 0.647  0.790 0.151 0.000 0.000 \n4. Does anyone in your house use controlled medication? 0.059 0.671 -0.009 -0.006 0.482  0.138 0.681 0.000 0.000 \n5. Does anyone in your house use 5, or more, medications on a \ndaily basis? 0.141 0.639 -0.078 0.066 0.493  0.227 0.658 0.000 0.094 \n6. Does anyone in your house have a health condition that \nrequires continuous care? -0.047 0.882 0.023 -0.012 0.753  0.000 0.865 0.063 0.000 \n7. Is anyone in your house impaired to perform daily activities? 0.001 0.881 -0.030 0.011 0.770  0.015 0.876 0.000 0.035 \n8. Does anyone in your house need help to accomplish its own \ndaily healthcare procedures? -0.080 0.856 0.037 -0.033 0.690  0.000 0.827 0.078 0.000 \n9. Did anyone in your house have its mother absent in childhood? -0.024 -0.030 0.727 0.036 0.514  0.000 0.000 0.715 0.059 \n10. Did anyone in your house have its father absent in childhood? -0.015 -0.090 0.752 0.037 0.546  0.000 0.000 0.736 0.059 \n11. Has anyone in your house faced abandonment by the family? -0.035 0.077 0.757 -0.062 0.575  0.000 0.123 0.748 0.000 \n12. Does anyone in your house live close to violent people? 0.067 -0.016 -0.037 0.918 0.843 0.076 0.000 0.000 0.915 \n13. Have anyone in your house been victim of violence? 0.138 0.096 0.310 0.643 0.652 0.211 0.164 0.370 0.666 \n14. Is there violence in your house? -0.177 -0.041 -0.172 0.923 0.893 0.196 0.042 0.167 0.909 \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted January 12, 2023. ; https://doi.org/10.1101/2023.01.12.23284419doi: medRxiv preprint \n\n \n26 \n \n 371 \nThese results ranged from 0.308 to 0.785 for factorial loads, from 0.212 to 0.967 372 \nfor communality, and Eta ranged from 0.640 to 0.941. The model based on the total 373 \nsample recorded explained variance of 79.02%. Number of dimensions’ stability and 374 \nmodel interpretability are essential aspects of dimensionality. It reinforces the relevance 375 \nof carrying out the cross-validation.   376 \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted January 12, 2023. ; https://doi.org/10.1101/2023.01.12.23284419doi: medRxiv preprint \n\n \n27 \n \nTable 6. Full dataset: Factor loading, communality and Eta. 377 \nItem \nFactorial load \nh2 \nPratt´s Measure - (Eta) \nIncome Healthcare Family Violence Income Healthcare Family Violence \n1. Is anyone in your house facing financial issues? 0.733 0.009 0.004 0.023 0.548  0.736 0.049 0.029 0.047 \n2. Do you lack money to fulfill household needs? 0.785 -0.045 -0.015  -0.020 0.585  0.765 0.000 0.000 0.000 \n3. Is there any difficulty in making sure about food variety in \nyour house? 0.555 0.059 0.019 0.027 0.346  0.569 0.124 0.060 0.050 \n4. Does anyone in your house use controlled medication? -0.001 0.523 0.056 0.016 0.287  0.000 0.528 0.087 0.035 \n5. Does anyone in your house use 5, or more, medications a day? 0.019 0.489 -0.012 -0.010 0.243  0.060 0.489 0.000 0.000 \n6. Does anyone in your house have a health condition that \nrequires continuous care? 0.007 0.639 0.032 0.013 0.421  0.041 0.644 0.065 0.032 \n7. Is anyone in your house impaired to perform daily activities? 0.008 0.723 -0.048 0.001 0.518  0.044 0.718 0.000 0.008 \n8. Does anyone in your house need help to accomplish its own \ndaily healthcare procedures? -0.036 0.624 -0.017 -0.024 0.371  0.000 0.609 0.000 0.000 \n9. Did anyone in your house have its mother absent in \nchildhood? -0.027 -0.049 0.594 0.004 0.339\n 0.000 0.000 0.582 0.013 \n10. Did anyone in your house have an absent father in \nchildhood? 0.009 -0.043 0.552 -0.009 0.302\n 0.037 0.000 0.548 0.000 \n11. Has anyone in your house faced abandonment by the family? 0.004 0.060 0.471 0.001 0.236  0.026 0.089 0.476 0.007 \n12. Does anyone in your house live close to violent people? 0.025 -0.034 0.011 0.743 0.554 0.047 0.000 0.029 0.742 \n13. Has anyone in your house been victim of violence? 0.028 0.084 0.273 0.308 0.212 0.069 0.119 0.296 0.325 \n14. Is there violence in your house? -0.047 -0.005 -0.018  0.597 0.351 0.000 0.000 0.000 0.593 \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted January 12, 2023. ; https://doi.org/10.1101/2023.01.12.23284419doi: medRxiv preprint \n\n \n28 \n \n 378 \nReliability indices between analysis datasets ranged from 0.69 to 0.71 in 379 \nCronbach’s alpha, it reached 0.70 in the three dataset for Omega, it ranged from 0.83 to 380 \n0.84 for glb and from 0.80 to 0.96 ORION, between dimensions and datasets. Factorial 381 \nsolution quality indices also showed adequate levels, and this finding reinforced the 382 \nmodel’s stability (Table 7). Accordingly, the set of applied techniques and indices 383 \npointed towards a set of internal structure validity evidences that are adequate, 384 \nconsistent, robust and interpretable.      385 \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted January 12, 2023. ; https://doi.org/10.1101/2023.01.12.23284419doi: medRxiv preprint \n\n \n29 \n \nTable 7. Synthesis of the models   386 \nSynthesis Index Technique Training Sample (TrS) Test Sample (TsS) Full Sample (FS) \nExploratory \nAdequacy of \ncorrelation \nmatrix \nDeterminant of the matrix < 0.000001 < 0.000001 0.0002 \nBartlett 6084.6 (df = 91) 6153.7 (df = 91) 8936.7 \nKMO (Kaiser-Meyer-Olkin) 0.75 0.74 0.71 \nExplained Variance (AP) 77.73% 76.18% 79.02% \nPolychoric Correlation (rp = ) -0.08 to 0.80 -0.21 to 0.81 -0.04 to 0.82 \nReliability \n Cronbach's Alpha  0.69 0.71 0.71 \nMcDonald's Omega  0.70 0.70 0.70 \nGreatest Lower Bound – glb  0.83 0.84 0.83 \nORIONª 0.90; 0.96; 0.80; 0.91 0.81; 0.91; 0.93; 0.93  0.80; 0.93; 0.90; 0.92  \nUnidimensional \nAssessment \nUnidimensional Congruence (UNICO) 0.82 0.83 0.79 \nExplained Common Variance (ECV) 0.65 0.70 0.66 \nMean of item residual absolute loading \n(MIREAL) 0.37 0.32 0.36 \nQuality and \nEffectiveness \nFactor Determinacy Index (FDI)ª 0.94; 0.98; 0.89; 0.95 0.90; 0.95; 0.96; 0.96  0.89; 0.96; 0.95; 0.95  \nSensivity Ratio (SR)ª 3.02; 5.37; 2.04; 3.20  2.09; 3.29; 3.77; 3.90 2.00; 3.74; 3.11; 3.37  \nExpected percentage of true differences \n(EPTD)ª 92.6%; 96.6%; 88.9%; 93.0%  89.1%; 93.3%; 94.3%; 94.6%  88.7%; 94.2%; 92.8%; 93.5%  \nª from dimension 1 to 4, respectively     \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted January 12, 2023. ; https://doi.org/10.1101/2023.01.12.23284419doi: medRxiv preprint \n\n \n30 \n \nStandardization 387 \nThe internal structure of the instrument was extrapolated and found. Now, the 388 \ndescriptive study and score standardization will be addressed to allow instrument 389 \ninterpretability and participants’ proper classification based on the scores. Accordingly, 390 \nTable 8 depicts the frequency of answers to items in the questionnaire. There was clear 391 \nprevalence of “No” answers for all items in the instrument. Some items presented 392 \nhigher frequency of “yes” answers: “Lack of money to fulfill household needs” 393 \n(40.34%), “someone in the house uses controlled medication” (36.41%), “someone in 394 \nthe house has a health condition that requires continuous care” (36.77%) and “someone 395 \nin the house had an absent father in childhood” (34.07%).  396 \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted January 12, 2023. ; https://doi.org/10.1101/2023.01.12.23284419doi: medRxiv preprint \n\n \n31 \n \nTable 8. Frequency of answers for the items.  397 \nItem Frequency of answer to the item (N/%) \nNo Yes Missing \n1. Is anyone in your house facing financial issues? 870 (69.10) 377 (29.94) 12 (0.95) \n2. Do you lack money to fulfill household needs? 742 (58.93) 508 (40.34) 9 (0.71) \n3. Is there any difficulty in making sure about food variety in your house? 928 (73.70) 322 (25.57) 9 (0.71) \n4. Does anyone in your house use controlled medication? 793 (62.98) 461 (36.61) 5 (0.39) \n5. Does anyone in your house use 5, or more, medications a day? 1,020 (81.01) 231 (18.34) 8 (0.63) \n6. Does anyone in your house have a health condition that requires continuous care? 788 (62.58) 463 (36.77) 8 (0.63) \n7. Is anyone in your house impaired to perform daily activities? 1,026 (81.43) 232 (18.42) 1 (0.07) \n8. Does anyone in your house need help to accomplish its own daily healthcare procedures? 1,066 (84.67) 190 (15.09)  3 (0.23) \n9. Did anyone in your house have its mother absent in childhood? 1,048 (83.24) 207 (16.44) 4 (0.31) \n10. Did anyone in your house have an absent father in childhood? 826 (65.60) 429 (34.07) 4 (0.31) \n11. Has anyone in your house faced abandonment by the family? 1,129 (89.67) 125 (9.92) 5 (0.39) \n12. Does anyone in your house live close to violent people? 1,221 (96.98) 34 (2.70) 4 (0.31) \n13. Has anyone in your house been victim of violence? 1,088 (86.41) 167 (13.26) 4 (0.31) \n14. Is there violence in your house? 1,232 (97.85) 25 (1.98) 2 (0.15) \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted January 12, 2023. ; https://doi.org/10.1101/2023.01.12.23284419doi: medRxiv preprint \n\n \n32 \n \n 398 \nTable 9 presents the scores recorded for the dimensions and the general score of 399 \nthe Family Vulnerability Scale. All dimensions had all their amplitudes answered. 400 \nDimensions Income, Family and Violence recorded median = 0, Healthcare showed 401 \nmedian = 1 and total score recorded median = 2. An interesting aspect of the total score 402 \nlies on the fact that amplitude ranged from 0 to 14 and the maximum score recorded in 403 \nthe current sample reached 12. Medians in the minimum limit, and close to it, 404 \npreviously pointed out that the instrument can accurately differentiate individuals who 405 \nare eventually facing family vulnerability situations.    406 \nTable 9. Description of dimensions and scores recorded for the Family 407 \nVulnerability Scale.       408 \nDimension / Score \nCentral Trend Measurements and Dispersion \nMedian Minimum Maximum Amplitude Interquartile \nIncome dimension 0.00 0.00 3 3 2.00 \nHealthcare dimension 1.00 0.00 5 5 2.00 \nFamily dimension 0.00 0.00 3 3 1.00 \nViolence Dimension 0.00 0.00 3 3 0.00 \nTotal Score Total 2.00 0.00 12 12 3.00 \n     409 \nBecause these scores are closer to the minimum limit, they only started 410 \npresenting greater difference when they got far from the median that, in this case, was 411 \nclose to the minimum; therefore, in the upper quartile. Thus, three initial classifications 412 \nwere suggested: model 1 had cut in the median (low and high vulnerability), model 2 413 \nscores were separated until percentile 75, from 76 to 89, and higher than 90; model 3 414 \nscores were separated up to percentile 70, from 70 to 89, or higher.    415 \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted January 12, 2023. ; https://doi.org/10.1101/2023.01.12.23284419doi: medRxiv preprint \n\n \n33 \n \nThe discriminant analysis of each classification developed to assess whether it 416 \nwas possible accurately identifying participants within the limit was applied after the 417 \nfirst cuts were made. 418 \nThe first analysis adopted a binary classification (low and high). The 419 \ndiscriminant analysis showed MBox = 446.58 p < 0.001. λ wilks = 0.36; F (1, 1257)  = 420 \n1,268.77; p < 0.001; canonical correlation = 0.797; the model with two limits properly 421 \nclassified 85.7% of the cases. The discriminant analysis applied to model 2 was MBox 422 \n= 49.64 p < 0.001. λ wilks = 0.18; F (2, 1256) = 2,094.25; p < 0.001; canonical correlation = 423 \n0.907. Model 2 properly classified 100% of cases. The analysis applied to model 3 424 \npresented MBox = 49.64 p < 0.001. λ wilks = 0.25; F (2, 1256)  = 1,838.71; p < 0.001; 425 \ncanonical correlation = 0.863; it was possible properly classifying 89% of cases. The 426 \nrecommended classification and scores interpretations are depicted in Table 10.  427 \nTable 10. Limits, classification and interpretation of Family Vulnerability Scale 428 \nscores 429 \nClassification results  Percentile Name Score \nLimit \nUp to 75 low 0 to 4 \n76 to 89 Moderate 5 to 6 \nHigher than 90 High Higher than 7  \n          430 \nFamily Vulnerability Scale – final version 431 \nThe final version of the Family Vulnerability scale (EVFAM-BR) comprised 14 432 \nitems (or questions) applied to each family in the PHC territory in Brazil, due to the 433 \naction by Community Health Agents (CHA). EVFAM-BR has four dimensions; each 434 \none of them has a score corresponding to the number of items in the dimension – at the 435 \nend of its application, the score must range from zero (0) to fourteen (14). Healthcare is 436 \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted January 12, 2023. ; https://doi.org/10.1101/2023.01.12.23284419doi: medRxiv preprint \n\n \n34 \n \nthe dimension accounting for the largest number of items; consequently, it has the 437 \ngreatest potential in the scale (n=5). The final EVFAM-BR presented three family 438 \nvulnerability classification limits if one sums the scores of each dimension: Low (0 to 439 \n4), Moderate (5 to 6) and High (7 to 14). Table 11 presents a summary of the Family 440 \nVulnerability Scale, and its respective dimensions, items and scores.  441 \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted January 12, 2023. ; https://doi.org/10.1101/2023.01.12.23284419doi: medRxiv preprint \n\n \n35 \n \nTable 11. Family Vulnerability Scale (EVFAM-BR). 442 \nDimension Item Item score Dimension score \nIncome \n1. Is anyone in your house facing financial issues? 1 \n3 2. Do you lack money to fulfill household needs? 1 \n3. Is there any difficulty in making sure about food variety in your house? 1 \nHealthcare \n4. Does anyone in your house use controlled medication? 1 \n5 \n5. Does anyone in your house use 5, or more, medications on a daily basis? 1 \n6. Does anyone in your house have a health condition that requires continuous care? 1 \n7. Is anyone in your house impaired to perform daily activities? 1 \n8. Does anyone in your house need help to accomplish its own daily healthcare procedures? 1 \nFamily \n9. Did anyone in your house have its mother absent in childhood? 1 \n3 10. Did anyone in your house have an absent father in childhood? 1 \n11. Has anyone in your house faced abandonment by the family? 1 \nViolence \n12. Does anyone in your house live close to violent people? 1 \n3 13. Has anyone in your house been victim of violence? 1 \n14. Is there violence in your house? 1 \nTotal 14 14 \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted January 12, 2023. ; https://doi.org/10.1101/2023.01.12.23284419doi: medRxiv preprint \n\n \n36 \n \n 443 \nDiscussion  444 \nThe Family Vulnerability Scale (EVFAM-BR) has shown evidences of content 445 \nand internal structure validity based on the multi-regional and multi-professional 446 \ncontext, and this finding allows measuring family vulnerability in Brazil.  447 \nEVFAM-BR comprises 14 items distributed into the following dimensions: 448 \nIncome, Healthcare, Family and Violence. It is worth highlighting that EVFAM-BR 449 \naims at measuring social vulnerability within the family context; consequently, all items 450 \nrefer to the family nucleus, they are not oriented to one specific resident, or to the 451 \nrespondent, itself.  452 \nJust to exemplify EVFAM-BR application to a family in a given local or time: 453 \none of the residents in a given house is facing financial issues. However, lack of money 454 \nto fulfill household needs is not identified and there is no hard time accessing different 455 \nfood types; one of the residents has a chronic disease that requires continuous care and 456 \nuses controlled medication (less than 5 medication types a day), but none of the 457 \nresidents has any difficulty in performing daily activities and does not need daily 458 \nhealthcare; none of the residents lacked mother or father presence in childhood and no 459 \nfamily member faced abandonment situations; there was no violence in the house and 460 \nno one in the house lives with violent people, but one of the residents was a victim of 461 \nviolence. Given the positive answers to items financial issue by one of the residents (1), 462 \nhealth condition requiring continuous care (1), the use of medication (1) and person 463 \nwho was violence victim (1), this family would reach score 4, and – based on the 464 \nclassification limit of EVFAM-BR final score - it represents a family classified as “low 465 \nfamily vulnerability”.        466 \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted January 12, 2023. ; https://doi.org/10.1101/2023.01.12.23284419doi: medRxiv preprint \n\n \n37 \n \nThe literature consistently states that income is a relevant social health 467 \ndeterminant and that it must be taken into account to allow planning equitable 468 \nhealthcare provision [66]. The subsequent discussion about this topic led to different 469 \nviews on how income inequality affects health. Rich or poor individuals, in low social 470 \ncohesion societies, would be the target of problems such as crime, lack of public 471 \ninvestments, and it makes people adopt unhealthy behaviors such as smoking, excessive 472 \nalcohol consumption and sedentary life [67]. These outcomes can help better 473 \nunderstanding the relationship between variables linked to income and enable 474 \ninterventions at macroeconomic level, as well as assessing these changes in population 475 \nhealth.  476 \nThe healthcare dimension is timely, given the accelerated population aging in 477 \nthe country and abroad, a fact that demands healthcare services’ reorganization to 478 \ncontinuously fulfill population needs, in an organized way, based on quality and safety. 479 \nWith respect to the family dimension, several studies have shown the association 480 \nbetween absence of parents and different health outcomes, among them one finds 481 \ncognitive development loss [68,69], impacts on mental health [70,71], and early 482 \ndevelopment of risk behavior for health, such as smoking and alcohol abuse [72]. 483 \nFinally, dimension “violence” corroborated the discussion observed in WHO’s 484 \n2030 agenda for the sustainable development of millennium goals; this agenda 485 \nhighlights violence prevention as fundamental component for both development and 486 \nimproved quality of life, worldwide. It is known that violence affects health and 487 \nbroadens the demands for healthcare in a way wider than simply through initial trauma, 488 \nit extrapolates the probability of other important causes for diseases and death [73]. It is 489 \npossible identifying association among exposure to violence, undesired health outcomes 490 \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted January 12, 2023. ; https://doi.org/10.1101/2023.01.12.23284419doi: medRxiv preprint \n\n \n38 \n \nand unhealthy behaviors, such as drug and alcohol abuse, mainly among low-income 491 \nmothers in urban locations [74].  492 \nAlthough the urgency in having research focused on low and medium income countries 493 \nthat account for 90% of the global violence, only 10% of studies in this field are 494 \nperformed in them [73]. Thus, EVFAM-BR emerges as a tool to allow structurally and 495 \nroutinely introducing the approach of social factors associated with the health/illness 496 \nprocess in healthcare services, in developing countries.  497 \nAccordingly, EVFARM-BR validity evidences, along with the four family 498 \nvulnerability strata proposed based on its application, present the potential of this tool to 499 \nhelp the role played by PHCs in performing their attributes, mainly in coordinating 500 \ncaregiving based on population-base management within the community and family 501 \ncontext [75]. 502 \nIt is important highlighting that EVFAM-BR is an instrument presenting robust 503 \nand synthesized evidences that, at first, demand low workload investment by 504 \nprofessionals and low financial resources. Because it is an objective instrument (only 505 \n“yes” and “no” answers are expected), it suggests that all PHC professionals must be 506 \ntrained to use it. This instrument emerges as powerful tool to support the work by 507 \ncommunity health agents (CHA), since these actors are community members and are 508 \nclosely bond to families in the territory; this process makes the “interview environment” 509 \nmore comfortable and trustful for users who answer the questions on behalf of the 510 \nhousehold. Thus, EVFAM-BR can be applied through printed materials or, yet, online, 511 \nsince it is a tool used as work instrument added to the teams’ routine. One must take 512 \ninto account its potential for inclusion in the digital registration system of the Brazilian 513 \nUnified Health System (SUS). 514 \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted January 12, 2023. ; https://doi.org/10.1101/2023.01.12.23284419doi: medRxiv preprint \n\n \n39 \n \nIt is possible guiding the teams at the time to plan their actions and health 515 \ninterventions (based on exposing families to conditions that increase vulnerability and 516 \nrisk to develop illnesses) by applying EVFAM-BR and by interpreting its household-517 \nclassification results based on the four predicted strata. It is worth highlighting how 518 \nvulnerability contexts can be changed overtime; instrument application must be 519 \nperiodical to keep teams’ planning updated, according to population needs.  520 \nAmong limitations of the current study, one finds sampling based on 521 \nconvenience. It does not ensure statistical results’ reliability. However, the study was 522 \ncarried out in different socioeconomic, demographic and cultural contexts, since it 523 \nencompassed participants from the five geographic regions in Brazil. Yet, it is important 524 \npointing out the potential of carrying out research in the PHC context in order to allow 525 \nthe participation of people with different demands, needs and life conditions, who seek 526 \ncare in this service. 527 \nHighlights in the present research are data collection by professionals outside the 528 \nassessed services who were trained to carry out the interviews, as well as the use of 529 \nrobust techniques to identify EVFAM-BR validity evidences; among them, CVR 530 \npresents a sophisticated and more adequate method [76] in comparison to the proposed 531 \nalternatives [77]. CVR calculation takes into consideration the number of judges [24,25] 532 \nand it minimizes the increase in random compliance [24], a fact that allows adopting a 533 \nlarge number of judges to judge the instrument. The adoption of a multi-disciplinary 534 \npanel of judges comprising researchers, translators, health professionals, methodology 535 \nexperts and lay people leads to more consistent results from the judges’ panel [77-79]. 536 \nIt is important pinpointing the need of implementing research in order to identify 537 \nthe potential and challenges of using EVFAM-BR in the routine of PCH’s services in 538 \ndifferent Brazilian contexts and, yet, in countries presenting similar health system 539 \n . CC-BY 4.0 International licenseIt is made available under a \n is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review)\nThe copyright holder for this preprint this version posted January 12, 2023. ; https://doi.org/10.1101/2023.01.12.23284419doi: medRxiv preprint \n\n \n40 \n \nfeatures, as well as population socioeconomic, demographic, sanitary and 540 \nepidemiological features.    541 \n 542 \nConclusion     543 \nGiven the set of herein employed techniques, it is possible stating that the set of 544 \ncontent validity and EVFAM-BR internal structure evidences are adequate, consistent, 545 \nreliable and robust, as well as that the cross-validation method ensured model reliability 546 \nand replicability. A synthetic scale was presented, and it is capable of accurately 547 \nmeasuring and differentiating familiar vulnerability. 548 \n    549 \nReferences 550 \n1. Carmo ME, Guizardi FL. O conceito de vulnerabilidade e seus sentidos para as 551 \npolíticas públicas de saúde e assistência social. Cad. 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