Sensitivity and Specificity of a Short Scale for Assessing Psychological Violence in Peruvian Health Professionals

Sensitivity and Specificity of a Short Scale for Assessing Psychological Violence in Peruvian Health Professionals | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research note Sensitivity and Specificity of a Short Scale for Assessing Psychological Violence in Peruvian Health Professionals Luis Fidel Abregú Tueros, Roger dos Santos Rosa This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-646009/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 8 You are reading this latest preprint version Abstract Objective: Psychological violence at work is becoming more acute in the health sector due to the precariousness of psychosocial work conditions at a global scale. To date, there have been no psychometric studies to classify this situation. The objective of the study was to determine the sensitivity and specificity of the psychological violence scale in health professionals (PVS-Health) among the Peruvian population. Results: The study included 188 professionals from ten care centres in Peru. Two groups of 94 subjects were formed: subjects who had experienced psychological violence at work (PVW) and subjects who had not experienced. The average age was 36.8 ± 10.5 years; 59% of the sample were women. The subjects’ work experience ranged between 1 to 35 years. The analysis based on the receiver operating characteristic ( ROC ) curve concludes significantly: a) area under the curve, AUC x 0.974; standard error, SE x 0.10; p < 0.0003 (95% CI – 0.954 – 0.994), showing adequate randomness; b) cut-off point for maximum sensitivity (S x 0.94) and specificity (E x 0.89) was 35 out of 73 as the maximum score; and c) PVS-Health effectively distinguish subjects with PVW from those without PVW (89% with PVW, 94% of those without). Physiology Health Economics & Outcomes Research Workplace violence Utility of scales ROC curve Cut-off point Health professionals Healthcare workers Figures Figure 1 Introduction Psychological violence at work (PVW) is an intentional action through which workers are verbally attacked, threatened, and/or humiliated during their professional practice [ 1 , 2 ]; PVW does not include external violence [ 3 ]. PVW is exacerbated in the health sector due to precarious work conditions, which are common psychosocial risk factors [ 4 – 6 ], and there are no differences in PVW between developed and underdeveloped countries or between different groups of health professionals [ 7 – 10 ]; however, at the individual level, the effects of PVW may vary based on individual resilience [ 6 , 11 ]. At the global level, there are a large variety of instruments to assess and monitor the prevalence of PVW and its impact [ 3 , 10 ]. In Peru, PVW studies conducted by internal agents (i.e., superiors or colleagues) related to interpersonal conflicts or motivational demands are scarce for health professionals [ 9 , 12 ]. This scarcity is due, at least in part, to the fact that some analysis tools (e.g., structured instruments or the Aggressive Behaviour Scale [ 10 , 13 , 14 ]) have been validated for Spain, Mexico, Colombia, Ecuador, Chile, and Bolivia but not for the Peruvian population. In three different Latin American countries, diagnostic scales have been established to validate instruments that measure violence (including external violence) and psychological harassment in service providers and industry, commerce, and education workers [ 15 , 16 ]. A convergent validation was also carried out on the 12-item General Health Questionnaire, but the sensitivity and specificity of the diagnostic scales used were not established. The instruments used in Peru to assess PVW at different levels of health care are limited because they do not assess utility or classification, which hinders the achievement of optimal standards for psychological tests [ 17 , 18 ]. These limitations lead to the necessity of an instrument that exhibits utility, good discriminatory capability, and randomness to classify workers exposed to PVW [ 19 ]. In addition, it is necessary to standardize criteria for the interpretation of results to identify, evaluate, and compare the prevalence of PVW; determine corrective actions; and establish baselines for mental health at work. The lack of tools with baseline references and discriminatory capability makes standardized evaluations of PVW difficult. This report is complementary to the psychological violence scale in health professionals (PVS- Health) instrument, a brief scale to assess psychological violence in health professionals and allows a determination of the best cut-off point of the instrument to classify individuals who have and have not experienced psychological violence. Our objective is to determine the sensitivity and specificity properties of the Peruvian version of the PVS - Health instrument. Methods From a population of 263 health professionals who agreed to participate in the study, a total of 75 professionals were excluded due to their omission of answers in two instruments. A total of 188 health professionals from 10 health centres in different Peruvian cities were finally included in this study, 94 of whom had experienced psychological violence at work (PVW) and 94 of whom had not (NPVW); 59% of the total sample were women (Table 1). The participants’ average age was 36.8 ± 10.5 years, and their work experience ranged from 1–35 years. The predominant occupational group was care providers (80.3% of the total sample), who mainly worked in emergency services (18.6% of the total). The study design was cross-sectional and was based on surveys conducted at two stages: a) first, a classification of groups with and without PVW and assess their job satisfaction (JS) using the Overall Job Satisfaction scale (OJS), which was applied as an external criterion; b) second, an evaluation of the sensitivity and specificity of the PVS-Health in both groups. In terms of the sample size and sampling method, the surveys were conducted with the entire target population between November 2019 and February 2020, with a health care professional being responsible for the survey administration in each health care centre. To be eligible, the participants had to have completed all the answers on both evaluation scales (the PVS-Health and OJS), which took a maximum of nine minutes. Instruments PVS-Health (a brief scale to assess psychological violence in health professionals) The PVS-Health For this study, a scale was developed consisting of 22 items referring to four types of violence in the Peruvian health context (loss of prestige, isolation, repression, and intimidation). Each item corresponds to a 4-point Likert-type scale (ranging from 1, “never”, to 4, “always”) (See Additional file 1). The scale exhibited good reliability and validity in a population of 316 health care professionals, showing the following properties: a) Good content validity, which was evaluated by five experts (doctors, nurses, and teaching psychologists), with a Kendall rank coefficient exceeding the minimum values (W = 0.509; p <0.026) [20]; b) Appropriate construct validity, as shown by the clustering of elements that explained up to 67.4% of the total variance and exceeded the minimum value (40%) [21], confirmatory factors that indicated a need for moderate adjustment ; a root mean square error of approximation and standardized residual of the root mean square that were both over the acceptability limit; acceptable Tuker-Lewis and comparative fit indices (0.60), and the good convergent validity of the PVS-Health with the OJS = (r = -0.769; p <0.0003); c) Good internal consistency reliability, with a global Cronbach's alpha coefficient of α = 0.842 and an item coefficient of α = 0.841 (the acceptable values were α = 0.70–0.80) [18]; d) PVS-Health indices based on percentiles indicating the grouping of the frequency and intensity of PVW into three levels (with low PVW ranging from 22 to 34 points). Overall job satisfaction scale This scale consists of 15 items grouped into two subscales: a) intrinsic satisfaction, linked to factors related to the content of tasks, i.e., recognition, responsibility, and promotion (7 items), and b) extrinsic satisfaction, related to satisfaction within the organization, i.e., schedules, wages and physical work conditions (8 items). Each item corresponds to a 7-point Likert-type scale (where 1 is "very dissatisfied" and 7 is "very satisfied"). The scale exhibited good reliability and validity with 518 Spanish nurses [14]; the global reliability was α = 0.75. This construct reflects experiences and emotional responses at work [15]. Procedure The study subjects were informed about the objectives of the research, and their voluntary participation was recorded through a letter of consent in which the participants’ anonymity and the confidentiality of the data were guaranteed. The simultaneous collection of data was carried out by organizational psychologists and health professionals. Statistic analysis To evaluate the sensitivity and specificity of the PVS-Health instrument in groups with and without PVW, we performed a receiver operating characteristic (ROC) curve analysis; we determined the area under the curve (AUC), the standard error (SE), and the cut-off point indicating the maximum sensitivity and specificity of the instrument [22, 23]. To confirm the agreement between PVW and JS, Cohen's kappa coefficient was calculated. The data were processed in IBM © SPSS © Statistics v26. The datasets generated and analysed during the current study are available in the [Figshare] repository, [ Persistent web link to datasets ], DOI [ 10.6084/m9.figshare.14308937.v1 ] Ethics The study was approved according to resolution 292/2018-D-FCEA of Universidad Nacional Agraria de la Selva (Peru). Informed consent was obtained from all study participants respecting their privacy and free will. Results Sensitivity and specificity The results showed a statistically significant ROC curve, with an AUC = 0.899 (which is higher than the suggested minimum value AUC = 0.70) [ 22 , 23 ] and an SE = 0.02, for p < 0.01 (95% CI = 0.855–0.942); these values demonstrated that individuals can be randomly identified using the PVS-Health scale. The scale exhibited a good ability to discriminate between those with and without PVW: detecting 89% of those with PVW versus 94% of those without (Fig. 1). The cut-off point indicating maximum sensitivity (S = 0.94) and 1 - specificity (E = 0.89) was 35 out of a maximum score of 73 on the scale, which reflected a good position of the predictive coordinates (ROC curve ≥ 0.80) [ 22 ]. The maximum Youden index (J = 0.83) indicated adequate the predictive limit and discriminative capability [ 23 ]. Job satisfaction as an external criterion The magnitude of concordance or reproducibility of JS (generated in categorical scores) regarding the PVW of the health professionals was good (k = -0.7669; “adequate” values are k = 0.61–0.80 (Table 2). Although the normal distribution of scalar scores was limited, the degree of nonparametric negative correlation between PVW and JS was high (ρ = -0.850; p < 0.0001), which confirms that when the PVW levels increase, the perception of JS decreases, and vice versa. Up to 81.7% of the changes in JS were explained by PVW. Discussion This work confirms that the PVS-Health scale shows good randomness for classifying individuals with and without PVW and establishes a cut-off point for maximum sensitivity and specificity (89% and 94%, respectively). We also found that PVW explains up to 81.7% of changes in the "criterion factor" of extrinsic and intrinsic JS. Considering the evidence gaps described above, which are related to the usefulness of the instruments for evaluating PVW in the health sector (which is an area that is as specific as it is contextual [12]), we highlight three indirectly associated topics: a) The PVS-Health scale, which assesses violence perpetrated by internal agents [1-3], differs from the inventory developed by Diaz et al. [16] because the cut-off scores for high violence and psychological harassment are different (45 in their inventory versus 35 in the PVS-Health) and because the inventory by Diaz et al. [16] assessed physical-verbal violence generated by both internal and external agents. In theory, these types of violence are hierarchical violence [2, 3] , horizontal violence (type III), and external violence or “type II” violence [12]. b) The results on ROC curves reported in other studies [3, 19] provide conclusive support for the PVS-Health scale because of the discriminative capability (AUC = 0.89 versus limit AUC > 0.80) [19] and because of the randomness of selection, which are adequate in both studies [3, 19]. c) Compared to a Pakistani stress questionnaire (AUC = 0.64; kappa = 0.84 [6] versus k = -0.766; AUC =0.89), the use of the PVS-Health scale in clinical and legal settings is stronger given the convergence of stress as an underlying factor [6]. Because decreased JS negatively affects organizational commitment [5] and increases levels of stress and exhaustion in health workers [2, 10], PVW often leads to job resignation [12]. To our knowledge, this is the first study to evaluate the practical use and prospects for using the PVS-Health instrument, which classifies PVW based on uniform criteria [3, 4] and allows the establishment of a baseline and the follow-up of responses within the framework of clinical and organizational psychology [3, 6]. Conclusion ROC curve analysis indicates the good randomness of the PVS-Health instrument and establishes that the cut-off point for maximum sensitivity and specificity is 35 (out of a maximum score of 73). The scale can be used in different health centres in the country. The PVS-Health exhibits a good ability to discriminate between individuals with PVW and those without PVW (detecting 89% of those with PVW and 94% of those without PVW). Limitations The limitations of this study are related to the heterogeneity of the distribution of scores of the variables under study; the low level of quality control in the interviewers’ application of the instrument; and the heterogeneity of the sample in terms of the sample size and participants’ origins, occupations, and employment status. The AUC estimation was performed with 94% of the required clinical sample size (n = 188/200) [ 12 ]. However, as our comparison groups had the same sample sizes, the coordinates of the determined ROC curve maintained their current positions [ 12 , 22 ], which increases the usefulness of the PVS-Health scale. Future studies may address the interaction of resilience and perform stratified analysis. Abbreviations EPVS-Health: Scale for assessing psychological violence in healthcare PVW: Psychological violence at work ROC: Receiver operating characteristic AUC: Area under the curve SE: Standard error S: Sensitivity E: Specificity JS: Job satisfaction OJS: Overall job satisfaction scale Declarations Ethics approval and consent to participate The study was approved according to resolution 292/2018-D-FCEA from Universidad Nacional Agraria de la Selva (Perú). Participants gave written informed consent respecting their identity and willingness. Consent for publication Not applicable Availability of data and materials The data set used and/or analysed during the study is available upon reasonable request to the author. Competing interests The author declare that they have no competing interests. Funding This study was self-funded. Authors’ contributions The author conceived the idea, conceptualized the study design, performed and reviewed the statistical analysis, and wrote the manuscript. Acknowledgements Not applicable Authors’ information Grupo de Investigación en Salud en el Trabajo, Universidad Nacional Agraria de la Selva, Perú References Organización Internacional del Trabajo. Consejo Internacional de Enfermeras, Organización Mundial de la Salud. Directrices marco para afrontar la violencia laboral en el sector de la salud. Ginebra: OIT; 2002. Li P, Xing K, Qiao H, Fang H, Ma H, Jiao M, et al. Psychological violence against general practitioners and nurses in Chinese township hospitals: incidence and implications. Health Qual Life Outcomes. 2018;16:117. Schindeler E, Reynald DM. What is the evidence? Preventing psychological violence in the workplace. Aggress Violent Behav. 2017;36:25–33. Hasan MI, Hassan MZ, Bulbul MMI, Joarder T, Chisti MJ. Iceberg of workplace violence in health sector of Bangladesh. BMC Res Notes. 2018;11:702. Vévoda J, Vévodová Š, Nakládalová M. Psychosocial risks in healthcare. Cas Lek Cesk. 2018;157:411–8. Artani A, Kamal AK, Azam SI, Artani M, Bhamani SS, Saif M, et al. Validation of the Recent Life Changes Questionnaire (RLCQ) for stress measurement among adults residing in urban communities in Pakistan. BMC Psychol. 2019;7:66. Schablon A, Wendeler D, Kozak A, Nienhaus A, Steinke S. Prevalence and consequences of aggression and violence towards nursing and care staff in Germany-a survey. Int J Environ Res Public Health. 2018;15:1274. Shea T, Sheehan C, Donohue R, Cooper B, De Cieri H. Occupational violence and aggression experienced by nursing and caring professionals. J Nurs Scholarsh. 2017;49:236–43. Volz NB, Fringer R, Walters B, Kowalenko T. Prevalence of horizontal violence among emergency attending physicians, residents, and physician assistants. West J Emerg Med. 2017;18:213–8. Mento C, Silvestri MC, Bruno A, Muscatello MRA, Cedro C, Pandolfo G, et al. Workplace violence against healthcare professionals: a systematic review. Aggress Violent Behav. 2020;51:101381. Braun-Lewensohn O, Sagy S. Community resilience and sense of coherence as protective factors in explaining stress reactions: comparing cities and rural communities during missiles attacks. Community Ment Health J. 2014;50:229–34. Nowrouzi-Kia B, Isidro R, Chai E, Usuba K, Chen A. Antecedent factors in different types of workplace violence against nurses: a systematic review. Aggress Violent Behav. 2019;44:1–7. Travetto C, Daciuk N, Fernández S, Ortiz P, Mastandueno R, Prats M, et al. Agresiones hacia profesionales en el ámbito de la salud. Rev Panam Salud Publica. 2015;38:307–15. Llor-Esteban B, Sánchez-Muñoz M, Ruiz-Hernández JA, Jiménez-Barbero JA. User violence towards nursing professionals in mental health services and emergency units. Eur J Psychol Appl Leg Context. 2017;9:33–40. Pando M, Aranda C, Preciado L, Franco SA, Salazar JE. Validez y confiabilidad del inventario de violencia y acoso psicológico en el trabajo (IVAPT-Pando). Enseñ Invest Psicol. 2015;11:319–32. Díaz X, Mauro A, Toro JP, Villarroel C, Campos C. Validación del inventario de violencia y acoso psicológico en el trabajo -IVAPT-Pando- en tres ámbitos laborales chilenos. Cienc Trab. 2015;17:7–14. American Educational Research Association, American Psychological Association (APA). National Council on Measurement in Education. Standards for educational and psychological testing. Washington, DC: American Educational Research Association; 2014. Coulacoglou C, Saklofske DH. Psychometrics and psychological assessment: Principles and applications. Chicago: Elsevier Inc.; 2018. Harris AHS. Three critical questions that should be asked before using prediction models for clinical decision support. JAMA Netw Open. 2019;2:e196661. Aravena PC, Moraga J, Cartes-Velásquez R, Manterola C. Validez y confiabilidad en investigación odontológica. Int J Odontostomatol. 2014;8:69–75. Lloret-Segura S, Ferreres-Traver A, Hernández-Baeza A, Tomás-Marco I. Exploratory item factor analysis: a practical guide revised and up-dated. An Psicol. 2014;30:1151–69. Hajian-Tilaki K. Receiver Operating Characteristic (ROC) curve analysis for medical diagnostic test evaluation. Caspian J Intern Med. 2013;4:627–35. Carter JV, Pan J, Rai SN, Galandiuk S. ROC-ing along: evaluation and interpretation of receiver operating characteristic curves. Surgery. 2016;159:1638–45. Tables Due to technical limitations, tables are only available as a download in the Supplemental Files section. Supplementary Files Additionalfile1.PVSHealth.pdf Additional file 1. PVS-Health, a brief scale to assess psychological violence in health professionals that provides socio-occupational information and 22 anonymous responses on psychological violence that occurred during the last six months. Additionalfile2.Datasetonvariables.xlsx TABLES1edited.pdf TABLES2edited.pdf Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Major revision 31 Oct, 2021 Reviewer # 2 agreed at journal 15 Aug, 2021 Review # 1 received at journal 31 Jul, 2021 Reviewers invited by journal 15 Jun, 2021 Reviewer # 1 agreed at journal 15 Jun, 2021 Editor assigned by journal 03 Jun, 2021 Submission checks completed at journal 03 Jun, 2021 Editor invited by journal 03 Jun, 2021 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-646009","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research note","associatedPublications":[],"authors":[{"id":34640188,"identity":"62146b39-af6a-41ad-8854-498edf6b5be6","order_by":0,"name":"Luis Fidel Abregú Tueros","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABAUlEQVRIiWNgGAWjYBACPgbGBiB1AMRmfAAVNMCrhQ1JCzNMKSEtYADWwiZBnBaJ5OYPDDV38vn515hV8+6ws2dgb94mwbjDBo+WxDYJhmPPLGfOeGN2m/dMcmIDz7EyCcYzaXi1AMnDBgY3zgC1tDEnMEjkmEkwth3GpwXosH+HDeyBWop52+rtGeTfgLT8x6elAWSmgQF/jxkzb9thxgYJHpCWA7i18Dxsk0jse2YgcYOtWHJu2/HENp60YovEM8k4tfCzpz/+8OHbHQP+/sMbP7xtq7bnZz+88cbHHXY4tYBBAoiQSIDaCyISG/DrgNqH7HpGorSMglEwCkbBCAEA/SxO3Cgp6dkAAAAASUVORK5CYII=","orcid":"https://orcid.org/0000-0002-0938-5061","institution":"Universidad Nacional Agraria de la Selva","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Luis","middleName":"Fidel Abregú","lastName":"Tueros","suffix":""},{"id":34640189,"identity":"a5c46899-ad7a-41b6-9dce-0f58ffd60c1e","order_by":1,"name":"Roger dos Santos Rosa","email":"","orcid":"","institution":"Universidade Federal do Rio Grande do Sul","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Roger","middleName":"dos Santos","lastName":"Rosa","suffix":""}],"badges":[],"createdAt":"2021-06-21 17:04:18","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-646009/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-646009/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":10751512,"identity":"53389176-dc29-4e48-831d-80919825b647","added_by":"auto","created_at":"2021-06-24 20:19:53","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":111808,"visible":true,"origin":"","legend":"ROC curve for psychological violence at work evaluated using the PVS-Health scale","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-646009/v1/be1f8366cd701c5e64791f98.jpg"},{"id":13700302,"identity":"b82ad53d-4dc8-428a-8aa1-e72fa663d37d","added_by":"auto","created_at":"2021-09-17 13:24:12","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":373735,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-646009/v1/ab11d220-61cd-40b3-8535-77425ad59672.pdf"},{"id":10751891,"identity":"5a472a52-9315-41a6-a98e-167b6176fa33","added_by":"auto","created_at":"2021-06-24 20:22:53","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":94063,"visible":true,"origin":"","legend":"Additional file 1. 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PVW is exacerbated in the health sector due to precarious work conditions, which are common psychosocial risk factors [\u003cspan additionalcitationids=\"CR5\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e], and there are no differences in PVW between developed and underdeveloped countries or between different groups of health professionals [\u003cspan additionalcitationids=\"CR8 CR9\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]; however, at the individual level, the effects of PVW may vary based on individual resilience [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAt the global level, there are a large variety of instruments to assess and monitor the prevalence of PVW and its impact [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. In Peru, PVW studies conducted by internal agents (i.e., superiors or colleagues) related to interpersonal conflicts or motivational demands are scarce for health professionals [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. This scarcity is due, at least in part, to the fact that some analysis tools (e.g., structured instruments or the Aggressive Behaviour Scale [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]) have been validated for Spain, Mexico, Colombia, Ecuador, Chile, and Bolivia but not for the Peruvian population.\u003c/p\u003e \u003cp\u003eIn three different Latin American countries, diagnostic scales have been established to validate instruments that measure violence (including external violence) and psychological harassment in service providers and industry, commerce, and education workers [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. A convergent validation was also carried out on the 12-item General Health Questionnaire, but the sensitivity and specificity of the diagnostic scales used were not established.\u003c/p\u003e \u003cp\u003eThe instruments used in Peru to assess PVW at different levels of health care are limited because they do not assess utility or classification, which hinders the achievement of optimal standards for psychological tests [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThese limitations lead to the necessity of an instrument that exhibits utility, good discriminatory capability, and randomness to classify workers exposed to PVW [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. In addition, it is necessary to standardize criteria for the interpretation of results to identify, evaluate, and compare the prevalence of PVW; determine corrective actions; and establish baselines for mental health at work. The lack of tools with baseline references and discriminatory capability makes standardized evaluations of PVW difficult.\u003c/p\u003e \u003cp\u003eThis report is complementary to the psychological violence scale in health professionals (PVS- Health) instrument, a brief scale to assess psychological violence in health professionals and allows a determination of the best cut-off point of the instrument to classify individuals who have and have not experienced psychological violence. Our objective is to determine the sensitivity and specificity properties of the Peruvian version of the PVS - Health instrument.\u003c/p\u003e "},{"header":"Methods","content":"\u003cp\u003eFrom a population of 263 health professionals who agreed to participate in the study, a total of 75 professionals were excluded due to their omission of answers in two instruments. A total of 188 health professionals from 10 health centres in different Peruvian cities were finally included in this study, 94 of whom had experienced psychological violence at work (PVW) and 94 of whom had not (NPVW); 59% of the total sample were women (Table 1).\u003c/p\u003e\n\u003cp\u003eThe participants\u0026rsquo; average age was 36.8 \u0026plusmn; 10.5 years, and their work experience ranged from 1\u0026ndash;35 years. The predominant occupational group was care providers (80.3% of the total sample), who mainly worked in emergency services (18.6% of the total).\u003c/p\u003e\n\u003cp\u003eThe\u0026nbsp;study design was cross-sectional and was based on surveys conducted at two stages: a) first, a classification of groups with and without PVW and assess their job satisfaction (JS) using the Overall Job Satisfaction scale (OJS),\u0026nbsp;which was applied as an external criterion; b) second, an evaluation of\u0026nbsp;the\u0026nbsp;sensitivity and specificity\u0026nbsp;of\u0026nbsp;the PVS-Health in both groups.\u003c/p\u003e\n\u003cp\u003eIn terms of the sample size and sampling method, the surveys were conducted with the entire target population between November 2019 and February 2020, with a health care professional being responsible for the survey administration in each health care centre.\u0026nbsp;To be\u0026nbsp;eligible, the participants\u0026nbsp;had to\u0026nbsp;have completed all the answers\u0026nbsp;on\u0026nbsp;both evaluation scales (the PVS-Health and OJS), which took a maximum of nine minutes.\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003e\u003cem\u003eInstruments\u003c/em\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/h2\u003e\n\u003ch3\u003e\u003cem\u003ePVS-Health (a brief scale to assess psychological violence in health professionals)\u003c/em\u003e\u003c/h3\u003e\n\u003ch3\u003eThe \u003cem\u003ePVS-Health\u0026nbsp;\u003c/em\u003e\u003c/h3\u003e\n\u003cp\u003eFor this study, a scale was developed consisting of 22\u0026nbsp;items referring to four types of violence in the Peruvian health context (loss of prestige, isolation, repression, and intimidation). Each item corresponds to a 4-point Likert-type scale (ranging from 1, \u0026ldquo;never\u0026rdquo;, to 4, \u0026ldquo;always\u0026rdquo;) (See Additional file 1). The scale exhibited good reliability and validity in a population of 316 health care professionals, showing the following properties:\u003c/p\u003e\n\u003cp\u003ea) Good content validity, which was evaluated by five experts (doctors, nurses, and teaching psychologists), with a Kendall rank coefficient exceeding the minimum values (W = 0.509; p \u0026lt;0.026) \u0026nbsp;[20];\u003c/p\u003e\n\u003cp\u003eb) Appropriate construct validity, as shown by the clustering of elements that explained up to 67.4% of the total variance and\u0026nbsp;exceeded\u0026nbsp;the minimum value (40%) [21], confirmatory factors that indicated a need for moderate adjustment\u0026nbsp;;\u0026nbsp;a root mean square error of approximation and standardized residual of the root mean square that were both over the acceptability limit; acceptable Tuker-Lewis and comparative fit indices (0.60), and the good convergent validity\u0026nbsp;of the PVS-Health with the OJS = (r = -0.769; p \u0026lt;0.0003);\u003c/p\u003e\n\u003cp\u003ec) Good internal consistency reliability, with a\u0026nbsp;global Cronbach\u0026apos;s alpha coefficient of \u0026alpha; = 0.842 and an item coefficient of \u0026alpha; = 0.841 (the acceptable values were \u0026alpha; = 0.70\u0026ndash;0.80) [18];\u003c/p\u003e\n\u003cp\u003ed) PVS-Health indices based on\u0026nbsp;percentiles indicating the grouping of the frequency and intensity of PVW into three levels (with low PVW ranging from 22 to 34 points).\u003c/p\u003e\n\u003ch2\u003e\u003cem\u003eOverall job satisfaction scale\u003c/em\u003e\u003c/h2\u003e\n\u003cp\u003eThis scale consists of 15 items grouped into two subscales: a) intrinsic satisfaction, linked to factors related to the content of tasks, i.e., recognition, responsibility, and promotion (7 items), and b) extrinsic satisfaction, related to satisfaction within the organization, i.e., schedules, wages and physical work conditions (8 items). Each item corresponds to a 7-point Likert-type scale (where 1 is \u0026quot;very dissatisfied\u0026quot; and 7 is \u0026quot;very satisfied\u0026quot;). The scale exhibited good reliability and validity with 518 Spanish nurses [14];\u0026nbsp;the\u0026nbsp;global reliability was \u0026alpha; = 0.75. This construct reflects experiences and emotional responses at work [15].\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003e\u003cem\u003eProcedure\u003c/em\u003e\u003c/h2\u003e\n\u003cp\u003eThe study subjects were informed about the objectives of the research,\u0026nbsp;and their voluntary participation was recorded through a letter of consent in which the participants\u0026rsquo; anonymity and the confidentiality of the data\u0026nbsp;were\u0026nbsp;guaranteed. The simultaneous collection of data was carried out by organizational psychologists and health professionals.\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003e\u003cem\u003eStatistic analysis\u003c/em\u003e\u003c/h2\u003e\n\u003cp\u003eTo evaluate the sensitivity and specificity of the PVS-Health instrument in groups with and without PVW, we\u0026nbsp;performed a receiver operating characteristic (ROC) curve analysis; we determined the area under the curve (AUC), the standard error (SE), and the cut-off point indicating the maximum sensitivity and specificity of the instrument [22, 23]. To confirm the agreement between PVW and JS, Cohen\u0026apos;s kappa coefficient was calculated. The data were processed in IBM \u0026copy; SPSS \u0026copy; Statistics v26.\u003c/p\u003e\n\u003cp\u003eThe datasets generated and analysed during the current study are available in the [Figshare] repository, [\u003ca href=\"https://figshare.com/articles/dataset/Additional_file_1_Data_set_on_variables_of_psychological_violence_at_work_PVW_job_satisfaction_JS_and_socio-occupational_variables_Health_centres_in_Peru_2019-2020/14308937\"\u003ePersistent web link to datasets\u003c/a\u003e], DOI [\u003ca href=\"https://figshare.com/articles/dataset/Additional_file_1_Data_set_on_variables_of_psychological_violence_at_work_PVW_job_satisfaction_JS_and_socio-occupational_variables_Health_centres_in_Peru_2019-2020/14308937/1\"\u003e10.6084/m9.figshare.14308937.v1\u003c/a\u003e]\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003ch2\u003e\u003cem\u003eEthics\u003c/em\u003e\u003c/h2\u003e\n\u003cp\u003eThe study was approved according to resolution 292/2018-D-FCEA of Universidad Nacional Agraria de la Selva (Peru). Informed consent was obtained from all study participants respecting their privacy and free will.\u003c/p\u003e"},{"header":"Results","content":" \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eSensitivity and specificity\u003c/h2\u003e \u003cp\u003eThe results showed a statistically significant ROC curve, with an AUC\u0026thinsp;=\u0026thinsp;0.899 (which is higher than the suggested minimum value AUC\u0026thinsp;=\u0026thinsp;0.70) [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e] and an SE\u0026thinsp;=\u0026thinsp;0.02, for p\u0026thinsp;\u0026lt;\u0026thinsp;0.01 (95% CI\u0026thinsp;=\u0026thinsp;0.855\u0026ndash;0.942); these values demonstrated that individuals can be randomly identified using the PVS-Health scale. The scale exhibited a good ability to discriminate between those with and without PVW: detecting 89% of those with PVW versus 94% of those without (Fig.\u0026nbsp;1). The cut-off point indicating maximum sensitivity (S\u0026thinsp;=\u0026thinsp;0.94) and 1 - specificity (E\u0026thinsp;=\u0026thinsp;0.89) was 35 out of a maximum score of 73 on the scale, which reflected a good position of the predictive coordinates (ROC curve\u0026thinsp;\u0026ge;\u0026thinsp;0.80) [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. The maximum Youden index (J\u0026thinsp;=\u0026thinsp;0.83) indicated adequate the predictive limit and discriminative capability [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e].\u003c/p\u003e \u003cdiv id=\"Sec13\" class=\"Section3\"\u003e \u003ch2\u003eJob satisfaction as an external criterion\u003c/h2\u003e \u003cp\u003eThe magnitude of concordance or reproducibility of JS (generated in categorical scores) regarding the PVW of the health professionals was good (k = -0.7669; \u0026ldquo;adequate\u0026rdquo; values are k\u0026thinsp;=\u0026thinsp;0.61\u0026ndash;0.80 (Table\u0026nbsp;2).\u003c/p\u003e \u003cp\u003eAlthough the normal distribution of scalar scores was limited, the degree of nonparametric negative correlation between PVW and JS was high (ρ = -0.850; p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), which confirms that when the PVW levels increase, the perception of JS decreases, and vice versa. Up to 81.7% of the changes in JS were explained by PVW.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e "},{"header":"Discussion","content":"\u003cp\u003eThis work confirms that the PVS-Health scale shows good randomness for classifying individuals with and without PVW and establishes a cut-off point for maximum sensitivity and specificity (89% and 94%, respectively). We also found that PVW explains up to 81.7% of changes in the \u0026quot;criterion factor\u0026quot; of extrinsic and intrinsic JS.\u003c/p\u003e\n\u003cp\u003eConsidering the evidence gaps described above, which are related to the usefulness of the instruments for evaluating PVW in the health sector (which is an area that is as specific as it is contextual [12]), we highlight three indirectly associated topics:\u003c/p\u003e\n\u003cp\u003ea) The PVS-Health scale, which assesses violence perpetrated by internal agents [1-3], differs from the inventory developed by Diaz et al. [16] because the cut-off scores for high violence and psychological harassment are different (45 in their inventory versus 35 in the PVS-Health) and because the inventory by Diaz et al. [16] assessed physical-verbal violence generated by both internal and external agents. In theory, these types of violence are hierarchical violence [2, 3]\u003cstrong\u003e,\u003c/strong\u003e horizontal violence (type III), and external violence or \u0026ldquo;type II\u0026rdquo; violence [12].\u003c/p\u003e\n\u003cp\u003eb) The results on ROC curves reported in other studies [3, 19] provide conclusive support for the PVS-Health scale because of the discriminative capability (AUC =\u0026nbsp;0.89 versus limit AUC \u0026gt; 0.80) [19] and because of the randomness of selection, which are adequate in both studies [3, 19].\u003c/p\u003e\n\u003cp\u003ec) Compared to a Pakistani stress questionnaire (AUC = 0.64; kappa = 0.84 [6] versus\u0026nbsp;k = -0.766;\u0026nbsp;AUC =0.89), the use of the PVS-Health scale in clinical and legal settings is stronger given the convergence of stress as an underlying factor [6]. Because decreased\u0026nbsp;JS negatively affects organizational commitment [5]\u0026nbsp;and\u0026nbsp;increases levels of stress and exhaustion in health workers [2, 10], PVW often leads to job resignation [12].\u003c/p\u003e\n\u003cp\u003eTo our knowledge, this is the first study to evaluate the practical use and prospects for using the PVS-Health instrument, which classifies PVW based on uniform criteria [3, 4] and allows the establishment of a baseline and the follow-up of responses within the framework of clinical and organizational psychology [3, 6].\u003c/p\u003e"},{"header":"Conclusion","content":" \u003cp\u003eROC curve analysis indicates the good randomness of the PVS-Health instrument and establishes that the cut-off point for maximum sensitivity and specificity is 35 (out of a maximum score of 73). The scale can be used in different health centres in the country. The PVS-Health exhibits a good ability to discriminate between individuals with PVW and those without PVW (detecting 89% of those with PVW and 94% of those without PVW).\u003c/p\u003e "},{"header":"Limitations","content":" \u003cp\u003eThe limitations of this study are related to the heterogeneity of the distribution of scores of the variables under study; the low level of quality control in the interviewers\u0026rsquo; application of the instrument; and the heterogeneity of the sample in terms of the sample size and participants\u0026rsquo; origins, occupations, and employment status. The AUC estimation was performed with 94% of the required clinical sample size (n\u0026thinsp;=\u0026thinsp;188/200) [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. However, as our comparison groups had the same sample sizes, the coordinates of the determined ROC curve maintained their current positions [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e], which increases the usefulness of the PVS-Health scale. Future studies may address the interaction of resilience and perform stratified analysis.\u003c/p\u003e "},{"header":"Abbreviations","content":"\u003cp\u003eEPVS-Health: Scale for assessing psychological violence in healthcare\u003c/p\u003e\n\u003cp\u003ePVW: Psychological violence at work\u003c/p\u003e\n\u003cp\u003eROC: Receiver operating characteristic\u003c/p\u003e\n\u003cp\u003eAUC: Area under the curve\u003c/p\u003e\n\u003cp\u003eSE: Standard error\u003c/p\u003e\n\u003cp\u003eS: Sensitivity\u003c/p\u003e\n\u003cp\u003eE: Specificity\u003c/p\u003e\n\u003cp\u003eJS: Job satisfaction\u003c/p\u003e\n\u003cp\u003eOJS: Overall job satisfaction scale\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003e\u003cem\u003eEthics approval and consent to participate\u003c/em\u003e\u003c/h2\u003e\n\u003cp\u003eThe study was approved according to resolution 292/2018-D-FCEA from Universidad Nacional Agraria de la Selva (Per\u0026uacute;). Participants gave written informed consent respecting their identity and willingness.\u003c/p\u003e\n\u003ch2\u003e\u003cem\u003eConsent for publication\u003c/em\u003e\u003c/h2\u003e\n\u003cp\u003eNot applicable\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003e\u003cem\u003eAvailability of data and materials\u003c/em\u003e\u003c/h2\u003e\n\u003cp\u003eThe data set used and/or analysed during the study is available upon reasonable request to the author.\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003e\u003cem\u003eCompeting interests\u003c/em\u003e\u003c/h2\u003e\n\u003cp\u003eThe author declare that they have no competing interests.\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003e\u003cem\u003eFunding\u003c/em\u003e\u003c/h2\u003e\n\u003cp\u003eThis study was self-funded.\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003e\u003cem\u003eAuthors\u0026rsquo; contributions\u003c/em\u003e\u003c/h2\u003e\n\u003cp\u003eThe author conceived the idea, conceptualized the study design, performed and reviewed the statistical analysis, and wrote the manuscript.\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003e\u003cem\u003eAcknowledgements\u003c/em\u003e\u003c/h2\u003e\n\u003cp\u003eNot applicable\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003e\u003cem\u003eAuthors\u0026rsquo; information\u003c/em\u003e\u003c/h2\u003e\n\u003cp\u003eGrupo de Investigaci\u0026oacute;n en Salud en el Trabajo, Universidad Nacional Agraria de la Selva, Per\u0026uacute;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eOrganizaci\u0026oacute;n Internacional del Trabajo. 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Washington, DC: American Educational Research Association; 2014.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCoulacoglou C, Saklofske DH. Psychometrics and psychological assessment: Principles and applications. Chicago: Elsevier Inc.; 2018.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHarris AHS. Three critical questions that should be asked before using prediction models for clinical decision support. JAMA Netw Open. 2019;2:e196661.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAravena PC, Moraga J, Cartes-Vel\u0026aacute;squez R, Manterola C. Validez y confiabilidad en investigaci\u0026oacute;n odontol\u0026oacute;gica. Int J Odontostomatol. 2014;8:69\u0026ndash;75.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLloret-Segura S, Ferreres-Traver A, Hern\u0026aacute;ndez-Baeza A, Tom\u0026aacute;s-Marco I. Exploratory item factor analysis: a practical guide revised and up-dated. 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Surgery. 2016;159:1638\u0026ndash;45.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eDue to technical limitations, tables are only available as a download in the Supplemental Files section.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-research-notes","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"resn","sideBox":"Learn more about [BMC Research Notes](http://bmcresnotes.biomedcentral.com)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/resn/default.aspx","title":"BMC Research Notes","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Workplace violence, Utility of scales, ROC curve, Cut-off point, Health professionals, Healthcare workers","lastPublishedDoi":"10.21203/rs.3.rs-646009/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-646009/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eObjective: \u003c/strong\u003e\u003c/p\u003e\u003cp\u003ePsychological violence at work is becoming more acute in the health sector due to the precariousness of psychosocial work conditions at a global scale. To date, there have been no psychometric studies to classify this situation. The objective of the study was to determine the sensitivity and specificity of the psychological violence scale in health professionals (PVS-Health) among the Peruvian population.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003eThe study included 188 professionals from ten care centres in Peru. Two groups of 94 subjects were formed: subjects who had experienced psychological violence at work (PVW) and subjects who had not experienced. The average age was 36.8 ± 10.5 years; 59% of the sample were women. The subjects’ work experience ranged between 1 to 35 years. The analysis based on the receiver operating characteristic ( ROC ) curve concludes significantly: a) area under the curve, AUC x 0.974; standard error, SE x 0.10; p \u0026lt; 0.0003 (95% CI – 0.954 – 0.994), showing adequate randomness; b) cut-off point for maximum sensitivity (S x 0.94) and specificity (E x 0.89) was 35 out of 73 as the maximum score; and c) PVS-Health\u0026nbsp;effectively distinguish subjects with PVW from those without PVW (89% with PVW,\u0026nbsp;94% of those without).\u003c/p\u003e","manuscriptTitle":"Sensitivity and Specificity of a Short Scale for Assessing Psychological Violence in Peruvian Health Professionals","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2021-06-24 20:19:52","doi":"10.21203/rs.3.rs-646009/v1","editorialEvents":[{"type":"communityComments","content":7},{"type":"decision","content":"Major revision","date":"2021-11-01T00:00:00+00:00","index":"","fulltext":""},{"type":"reviewerAgreed","content":"","date":"2021-08-16T00:00:00+00:00","index":2,"fulltext":""},{"type":"editorInvitedReview","content":"","date":"2021-08-01T00:00:00+00:00","index":1,"fulltext":"Recommendation: Reviewer's comments unavailable due to the journal's policy.\n"},{"type":"reviewersInvited","content":"","date":"2021-06-16T00:00:00+00:00","index":"","fulltext":""},{"type":"reviewerAgreed","content":"","date":"2021-06-16T00:00:00+00:00","index":1,"fulltext":""},{"type":"editorAssigned","content":"","date":"2021-06-04T00:00:00+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2021-06-03T23:00:00+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2021-06-03T23:00:00+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-research-notes","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"resn","sideBox":"Learn more about [BMC Research Notes](http://bmcresnotes.biomedcentral.com)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/resn/default.aspx","title":"BMC Research Notes","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"6ce14f5f-8eac-4335-a61f-0441874a6739","owner":[],"postedDate":"June 24th, 2021","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":5219011,"name":"Physiology"},{"id":5219012,"name":"Health Economics \u0026 Outcomes Research"}],"tags":[],"updatedAt":"2021-06-24T20:19:52+00:00","versionOfRecord":[],"versionCreatedAt":"2021-06-24 20:19:52","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-646009","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-646009","identity":"rs-646009","version":["v1"]},"buildId":"7rjqhiLT3MXkJMwkYKINL","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}