Abstract The propose was to seek validity evidences of scales based on the model of reactions of higher education professors about the evaluation of graduate programs conducted by the Brazilian Federal Agency for Support and Evaluation of Graduate Education (Capes). The scales of satisfaction, justice perception, utility perception, and accuracy perception were applied on 814 higher education professors, being 50.36% males, with a mean age of 47.66 years (SD = 9.34). Exploratory analysis indicated reliability of the four scales (alphas ranged from .69 to .97 and omegas are from .70). These and other psychometric indicators of the scales indicate that the measures are reliable, and the reaction model was confirmed by the strong correlation between the scales.

CERN-LHC. A measurement of the splitting scales, as defined by the kT clustering algorithm, for final states containg a W boson produced in proton-proton collisions at a centre-of-mass energy 7 TeV. The measurements uses the full 2010 data sample with a total integrated luminsoity of 36 pb-1. The measurements are made separately for W bosons decaying into electron and muuon final states. Details of the splitting scale variable d_k are described in the paper. Data on the four hardest splitting scales d0,d1,d2 and d3 are presented together with their ratios.

Results of the multivariate analysis of variance of the measurement bias for the four kinds of Differential Item Functioning (DIF) studied.

Abstract This study investigated the psychometric properties of a scale for measuring the Perception of Occupational Stressors by Teachers (EPEOP). The scale was applied in a sample of 404 teachers of public schools (state or municipal) of basic education of Mossoró (RN), Brazil. 73.8% were women between 20 to 68 years old. The EPEOP, composed of 22 items, was applied collectively in the participants' schools. The scale reliability was considered high with a Cronbach's alpha of 0.94. The factorial analysis divided the scale into four factors with the following indices: workload (α=0.88), physical and environmental aspects of work (α=0.88), career growth and professional training (α=0.82), and relationships with students and guardians (α=0.79). The EPEOP overall average for the sample was 46.80 points. The instrument presents adequate psychometric characteristics for evaluating teachers' stress and can orient actions aimed at improving the quality of life of these professionals.

Results from the pretreatment habitat factor analysis using the nine local-scale forest structure variables measured at four study sites in Arizona and New Mexico.

Background: Measuring Quality of Life (QoL) in mental health using self-reported items is important for evaluating the quality of service and understanding the person's experience of the care received.Objective: The aim of this research was to develop and validate a self-reported QoL instrument for inpatient and community mental health settings.Methods: Data were collected from diverse research sites in Canada, Belgium, Russia, Finland, Brazil, and Hong Kong, using the 37-item interRAI Quality of Life Survey for Mental Health and Addictions. The survey was administrated to 2,218 participants from inpatient and community mental health settings, assisted living, and the general community. We randomly divided the sample into a training and a test sample (70 and 30%, respectively). We conducted principal component analysis (PCA) and exploratory factor analysis (EFA) using the training sample to identify potential factor structure. Confirmatory factor analysis (CFA) models were then fitted to finalize and externally validate the measurement model using training and test data, respectively.Results: PCA, EFA, and CFA of the training sample collectively suggested a 23-item scale measuring four latent constructs: well-being and hope (8 items), relationship (7 items), support (5 items), and activity (3 items). This model was supported by the CFA of the test sample. The goodness-of-fit statistics root mean square error, comparative fit index and Tucker-Lewis index were 0.03, 1.00, and 0.99, respectively. Estimated Cronbach's alpha based on the test data was 0.92. Raw Cronbach's alpha values for the subscales were 0.86 for well-being and hope, 0.86 for relationship, 0.69 for support, and 0.72 for activity.Conclusions: The interRAI SQoL-MHA scale is a valid instrument to measure QoL in mental health settings. The instrument will support the evaluation of the quality of care and can also be used for future research to produce SQoL-MHA values on a quality adjusted-life-year scale, facilitating the evaluation of various mental health interventions.

The animal's reaction to human handling (i.e., temperament) is critical for work safety, productivity, and welfare. Subjective phenotyping methods have been traditionally used in beef cattle production. Even so, subjective scales rely on the evaluator's knowledge and interpretation of temperament, which may require substantial experience. Selection based on such subjective scores may not precisely change temperament preferences in cattle. The objectives of this study were to investigate the underlying genetic interrelationships among temperament measurements using genetic factor analytic modeling and validate a movement-based objective method (four-platform standing scale, FPSS) as a measure of temperament. Relationships among subjective methods of docility score (DS), temperament score (TS), 12 qualitative behavior assessment (QBA) attributes and objective FPSS including the standard deviation of total weight on FPSS over time (SSD) and coefficient of variation of SSD (CVSSD) were investigated using 1,528 calves at weaning age. An exploratory factor analysis (EFA) identified two latent variables account for TS and 12 QBA attributes, termed difficult and easy from their characteristics. Inclusion of DS in EFA was not a good fit because it was evaluated under restraint and other measures were not. A Bayesian confirmatory factor analysis inferred the difficult and easy scores discovered in EFA. This was followed by fitting a pedigree-based Bayesian multi-trait model to characterize the genetic interrelationships among difficult, easy, DS, SSD, and CVSSD. Estimates of heritability ranged from 0.18 to 0.4 with the posterior standard deviation averaging 0.06. The factors of difficult and easy exhibited a large negative genetic correlation of −0.92. Moderate genetic correlation was found between DS and difficult (0.36), easy (−0.31), SSD (0.42), and CVSSD (0.34) as well as FPSS with difficult (CVSSD: 0.35; SSD: 0.42) and easy (CVSSD: −0.35; SSD: −0.4). Correlation coefficients indicate selection could be performed with either and have similar outcomes. We contend that genetic factor analytic modeling provided a new approach to unravel the complexity of animal behaviors and FPSS-like measures could increase the efficiency of genetic selection by providing automatic, objective, and consistent phenotyping measures that could be an alternative of DS, which has been widely used in beef production.

This dataset comprises contents of major elements phosphorus (P) and calcium (Ca) and trace elements uranium (U), vanadium (V), nickel (Ni), and chromium (Cr) in sedimentary fish scales obtained from four marine sediment cores collected off Namibia. Additionally, bulk sediment contents of V and Cr were analyzed from the same cores. The sediment cores were retrieved during research cruise AHAB04 in March 2004 in the Benguela Upwelling System. Fish scales were hand-picked from the sediment and cleaned with methanol and Milli-Q water. After drying, samples were digested in a 1:1 mixture of concentrated HNO₃ and HCl at 140 °C for 5 minutes. Uranium, Cr, Ni, and V in the fish scale digests were measured using a triple-quadrupole inductively coupled plasma mass spectrometer (iCAP TQ ICP-MS, Thermo Scientific). Calcium and P concentrations were measured via optical emission inductively coupled plasma spectroscopy (iCAP PRO ICP-OES, Thermo Scientific). Bulk sediment contents of V and Cr were determined using wavelength-dispersive X-ray fluorescence (Panalytical Axios Plus).

Abstract

Sustainable Development Goal (SDG) target 2.1 commits countries to end hunger, ensure access by all people to safe, nutritious and sufficient food all year around. Indicator 2.1.2, “Prevalence of moderate or severe food insecurity based on the Food Insecurity Experience Scale (FIES)”, provides internationally-comparable estimates of the proportion of the population facing difficulties in accessing food. More detailed background information is available at http://www.fao.org/in-action/voices-of-the-hungry/fies/en/ .

The FIES-based indicators are compiled using the FIES survey module, containing 8 questions. Two indicators can be computed:
1. The proportion of the population experiencing moderate or severe food insecurity (SDG indicator 2.1.2), 2. The proportion of the population experiencing severe food insecurity.

These data were collected by FAO through the Gallup World Poll. General information on the methodology can be found here: https://www.gallup.com/178667/gallup-world-poll-work.aspx. National institutions can also collect FIES data by including the FIES survey module in nationally representative surveys.

Microdata can be used to calculate the indicator 2.1.2 at national level. Instructions for computing this indicator are described in the methodological document available in the documentations tab. Disaggregating results at sub-national level is not encouraged because estimates will suffer from substantial sampling and measurement error.

Geographic coverage

National

Analysis unit

Individuals

Universe

Individuals of 15 years or older with access to landline and/or mobile phones.

Kind of data

Sample survey data [ssd]

Sampling procedure

NA Exclusions: Due to ongoing conflict and security issues, Tigray, Gambella, Harari regions were excluded. The excluded areas represent approximately 7% of the total population of Ethiopia. Design effect: 1.64

Mode of data collection

Face-to-Face [f2f]

Cleaning operations

Statistical validation assesses the quality of the FIES data collected by testing their consistency with the assumptions of the Rasch model. This analysis involves the interpretation of several statistics that reveal 1) items that do not perform well in a given context, 2) cases with highly erratic response patterns, 3) pairs of items that may be redundant, and 4) the proportion of total variance in the population that is accounted for by the measurement model.

Sampling error estimates

The margin of error is estimated as 4. This is calculated around a proportion at the 95% confidence level. The maximum margin of error was calculated assuming a reported percentage of 50% and takes into account the design effect.

pone.0280035.t001 - Measurement, data analysis and modeling of electromagnetic wave propagation gain in a typical vegetation environment

Abstract This research is about the relationship between the exploitation, exploration, and absorptive capacity of the organizational knowledge. The three themes are of great importance to the sustainable competitive advantage of organizations. In general, although they are inserted in the discussion of organizational learning, they are still in the evolutionary process regarding antecedents, moderators, and outcomes, as can be observed in the theoretical reference. It has not been possible to identify studies with similar characteristics as the one presented here, i.e., studies linking exploration and exploitation with absorptive capacity, particularly in the Brazilian context. The main objective was to evaluate the degree of association between exploration, exploitation, and absorptive capacity. This study used quantitative research in 100 companies operating in commerce and services sectors, all located in the city of Palmas, Tocantins State. The sector was chosen based on the concentration of commercial and services companies in the city. The informants were the managers who worked in these companies. The questionnaire involved the use of two scales: one scale for the measurement of exploration and exploitation, and the other scale for measuring the absorptive capacity, both validated by early studies. The technique involved structural equation modeling using Partial Least Square-Path Modeling (PLS-PM) software was used for the verification of the principal hypothesis. The concepts of exploration and exploitation were based on six dimensions: organizational knowledge practices, innovation practices, strategic orientation, competition, partnerships, and efficiency. The concept of absorptive capacity was based on four dimensions: porosity, routines and structures, public knowledge, and individual abilities. The results showed that companies had exploitation orientation. Regarding the absorptive capacity, companies had a high relationship with the environment, with routines and with procedures, and with public knowledge. The main hypothesis was confirmed, indicating a positive relationship between exploration, exploitation, and absorptive capacity.

Abstract

Sustainable Development Goal (SDG) target 2.1 commits countries to end hunger, ensure access by all people to safe, nutritious and sufficient food all year around. Indicator 2.1.2, “Prevalence of moderate or severe food insecurity based on the Food Insecurity Experience Scale (FIES)”, provides internationally-comparable estimates of the proportion of the population facing difficulties in accessing food. More detailed background information is available at http://www.fao.org/in-action/voices-of-the-hungry/fies/en/ .

The FIES-based indicators are compiled using the FIES survey module, containing 8 questions. Two indicators can be computed:
1. The proportion of the population experiencing moderate or severe food insecurity (SDG indicator 2.1.2), 2. The proportion of the population experiencing severe food insecurity.

These data were collected by FAO through the Gallup World Poll. General information on the methodology can be found here: https://www.gallup.com/178667/gallup-world-poll-work.aspx. National institutions can also collect FIES data by including the FIES survey module in nationally representative surveys.

Microdata can be used to calculate the indicator 2.1.2 at national level. Instructions for computing this indicator are described in the methodological document available in the documentations tab. Disaggregating results at sub-national level is not encouraged because estimates will suffer from substantial sampling and measurement error.

Geographic coverage

National coverage

Analysis unit

Individuals

Universe

Individuals of 15 years or older with access to landline and/or mobile phones.

Kind of data

Sample survey data [ssd]

Sampling procedure

A dual frame (landline and mobile phone frames) was used to complete 1,000 telephone surveys. About 70% of the completes were from the mobile phone sample whereas landline completes accounted for the remaining 30%. Exclusions: NA Design effect: 1.64

Mode of data collection

Computer Assisted Telephone Interview [cati]

Cleaning operations

Statistical validation assesses the quality of the FIES data collected by testing their consistency with the assumptions of the Rasch model. This analysis involves the interpretation of several statistics that reveal 1) items that do not perform well in a given context, 2) cases with highly erratic response patterns, 3) pairs of items that may be redundant, and 4) the proportion of total variance in the population that is accounted for by the measurement model.

Sampling error estimates

The margin of error is estimated as 4. This is calculated around a proportion at the 95% confidence level. The maximum margin of error was calculated assuming a reported percentage of 50% and takes into account the design effect.

Abstract

Sustainable Development Goal (SDG) target 2.1 commits countries to end hunger, ensure access by all people to safe, nutritious and sufficient food all year around. Indicator 2.1.2, “Prevalence of moderate or severe food insecurity based on the Food Insecurity Experience Scale (FIES)”, provides internationally-comparable estimates of the proportion of the population facing difficulties in accessing food. More detailed background information is available at http://www.fao.org/in-action/voices-of-the-hungry/fies/en/ .

The FIES-based indicators are compiled using the FIES survey module, containing 8 questions. Two indicators can be computed: 1. The proportion of the population experiencing moderate or severe food insecurity (SDG indicator 2.1.2), 2. The proportion of the population experiencing severe food insecurity.

These data were collected by FAO through the Gallup World Poll. General information on the methodology can be found here: https://www.gallup.com/178667/gallup-world-poll-work.aspx. National institutions can also collect FIES data by including the FIES survey module in nationally representative surveys.

Microdata can be used to calculate the indicator 2.1.2 at national level. Instructions for computing this indicator are described in the methodological document available under the "DOCUMENTATION" tab above. Disaggregating results at sub-national level is not encouraged because estimates will suffer from substantial sampling and measurement error.

Geographic coverage

National coverage

Analysis unit

Individuals

Universe

Individuals of 15 years or older with access to landline and/or mobile phones.

Kind of data

Sample survey data [ssd]

Sampling procedure

NA Exclusions: NA Design effect: 1.71

Mode of data collection

Computer Assisted Telephone Interview [cati]

Cleaning operations

Statistical validation assesses the quality of the FIES data collected by testing their consistency with the assumptions of the Rasch model. This analysis involves the interpretation of several statistics that reveal 1) items that do not perform well in a given context, 2) cases with highly erratic response patterns, 3) pairs of items that may be redundant, and 4) the proportion of total variance in the population that is accounted for by the measurement model.

Sampling error estimates

The margin of error is estimated as 4.1. This is calculated around a proportion at the 95% confidence level. The maximum margin of error was calculated assuming a reported percentage of 50% and takes into account the design effect.

The Family Planning High Impact Practices (HIP) initiative is a multi-organization effort started in 2010 that aims to highlight evidence-based practices that are vetted by experts against specific criteria, and that, when scaled up, will maximize impact in family planning (FP). HIPs are identified based on demonstrated impact on contraceptive use, scalability, sustainability, cost-effectiveness, and applicability in a wide range of settings. The HIP initiative is supported by more than 30 organizations that play a key role in developing, reviewing, disseminating, and implementing HIPs. The goal of this assessment was two-fold: 1) to generate evidence to help countries reflect on and optimize implementation of HIPs and 2) to inform harmonized, globally and locally relevant measurement standards for HIPs. The approach for measuring scale, reach, quality and cost was replicated in each country. HIPs varied by country and covered immediate postpartum FP (IPPFP), community health workers (CHWs), post-abortion FP (PAFP), pharmacies and drug shops (PDS), and mass media (MM). In Nigeria, the study was conducted in two states – Kadouna and Lagos states and covered four HIPs: IPPFP, PFPA, PDS and MM. This assessment of scale, reach, quality and cost of HIP implementation used a cross-sectional, observational design with the following data sources: 1. Key informant interviews (KIIs) with FP program managers and relevant social and behavioral change (SBC) technical leads within health promotion-focused units in the Ministry of Health (MOH) supplemented with desk review of relevant national level documents (all HIPs). 2. KIIs with program managers at managing authorities and desk review of relevant records or documents (all HIPs). 3. Service statistics (IPPFP, PAFP, PDS). 4. Health facility assessment (IPPFP, PAFP), a survey with FP providers (IPPFP, PAFP) and a survey with PDS. 5. Analysis of SBC strategies/plans and mass media products (MM). 6. Activity-based costing (all HIPs).

The increasing prevalence of childhood overweight and obesity is a major public health concern in the United Kingdom. Parents are critical in shaping their child’s health-related behaviors and are relied upon to recognize healthy weight gain and take necessary action. Despite this, evidence suggests that parental recognition of overweight and obese children is poor and requires improvement. It is crucial that parents are able to recognise child overweight and obese, as measures need to be implemented as obese children and adolescents are five times more likely to be obese in adulthood than those who were not obese.

Given their reliance on visual cues to evaluate weight status, the Map Me intervention developed body image scales of known weight status of 4-5 and 10-11-year-old children, the age groups that are monitored nationally as part of the National Child Measurement Programme (NCMP). The body scales created were the first of known weight status created for 4-5 and 10-11-year-old children based on the UK90 criteria. In a previous study as part of my Ph.D., we found that participants could discriminate the different sizes of these bodies, however, there was some misjudgment at the higher weight categories. By way of explanation for the observed misjudgments, the close positioning of the heavier bodies at the upper end of the BMI range is exacerbated by perceptual biases: Weber’s Law and contraction bias. Weber’s Law means that the BMI spacing in absolute terms between bodies has to increase as the size of the bodies increases for the stimuli to be distinguished. However, as the BMI separation between the bodies within the scales is based on NCMP weight categories, the spacing between the heavier bodies actually gets smaller making it harder to discriminate between these bodies.

Based on these findings, I, therefore, conducted a just noticeable difference (JND) experiment, whereby the JND between the two objects (i.e., the minimum size change necessary for an observer to detect a difference) is a constant proportion of the size of the reference object, and this is called the Weber Fraction. This study determined the minimum size change needed between each of the bodies in our child body scale (a difference of 12 BMI centiles) so that participants can successfully discriminate between the size of the bodies without misjudgment. The aim of this study is therefore to assess the reliability and validity of some new Daz versions of these 3D computer-generated child figure scales that have been created based on the findings from the JND experiment. We aim to validate these scales in a sample of parents of 4-5 and 10-11 year-old parents, which is the ages of the children that the 3D body stimuli represent.

BackgroundIntegrating measures of respectful care is an important priority in family planning programs, aligned with maternal health efforts. Ensuring women can make autonomous reproductive health decisions is an important indicator of respectful care. While scales have been developed and validated in family planning for dimensions of person-centered care, none focus specifically on decision-making autonomy. The Mothers Autonomy in Decision-Making (MADM) scale measures autonomy in decision-making during maternity care. We adapted the MADM scale to measure autonomy surrounding a woman’s decision to use a contraceptive method within the context of contraceptive counselling. This study presents a psychometric validation of the Family Planning Autonomous Decision-Making (FP-ADM) scale using data from Argentina, Ghana, and India.Methods and findingsWe used cross-sectional data from women in four subnational areas in Argentina (n = 890), Ghana (n = 1,114), and India (n = 1,130). In each area, 20 primary sampling units (PSUs) were randomly selected based on probability proportional to size. Households were randomly selected in Ghana and India. In Argentina, all facilities providing reproductive and maternal health services within selected PSUs were included and women were randomly selected upon exiting the facility. Interviews were conducted with a sample of 360 women per district. In total, 890 women completed the FP-ADM in Argentina, 1,114 in Ghana and 1,130 in India. To measure autonomous decision-making within FP service delivery, we adapted the items of the MADM scale to focus on family planning. To assess the scale’s psychometric properties, we first examined the eigenvalues and conducted a parallel analysis to determine the number of factors. We then conducted exploratory factor analysis to determine which items to retain. The resulting factors were then identified based on the corresponding items. Internal consistency reliability was assessed with Cronbach’s alpha. We assessed both convergent and divergent construct validity by examining associations with expected outcomes related to the underlying construct. The Eigenvalues and parallel analysis suggested a two-factor solution. The two underlying dimensions of the construct were identified as “Bidirectional Exchange of Information” (Factor 1) and “Empowered Choice” (Factor 2). Cronbach’s alpha was calculated for the full scale and each subscale. Results suggested good internal consistency of the scale. There was a strong, significant positive association between whether a woman expressed satisfaction with quality of care received from the healthcare provider and her FP-ADM score in all three countries and a significant negative association between a woman’s FP-ADM score and her stated desire to switch contraceptive methods in the future.ConclusionsOur results suggest the FP-ADM is a valid instrument to assess decision-making autonomy in contraceptive counseling and service delivery in diverse low- and middle-income countries. The scale evidenced strong construct, convergent, and divergent validity and high internal consistency reliability. Use of the FP-ADM scale could contribute to improved measurement of person-centered family planning services.

This study examined the factorial validity of the Slovene version of the cultural intelligence scale (CQS) in a representative sample of 1,000 Slovenian participants (49% were female). The results of confirmatory factor analysis supported the factorial validity of the Slovene CQS and the existence of a general (second-order) cultural intelligence factor. The four scales and the overall (general) CQS scale showed satisfactory internal consistency. The results of multiple-group confirmatory factor analyses supported the hypotheses of partial measurement invariance across gender, and full measurement invariance across type of settlement (urban vs. rural).

ObjectiveThis study investigated the relationship between orthopedic pain experienced at rest, and degree of movement asymmetry during trot in horses with induced reversible acute arthritis. Orthopedic pain was assessed with the Horse Grimace Scale (HGS), the Equine Utrecht University Scale of Facial Assessment of Pain (EQUUS-FAP), the Equine Pain Scale (EPS), and the Composite Orthopedic Pain Scale (CPS). Reliability and diagnostic accuracy were evaluated with intraclass correlation coefficients (ICC) and area under the curve (AUC).Study design and animalsEight healthy horses were included in this experimental study, with each horse acting as its own control.MethodsOrthopedic pain was induced by intra-articular lipopolysaccharide (LPS) administration. Serial pain assessments were performed before induction and during pain progression and regression, where three observers independently and simultaneously assessed pain at rest with the four scales. Movement asymmetry was measured once before induction and a minimum of four times after induction, using objective gait analysis.ResultsOn average 6.6 (standard deviation 1.2) objective gait analyses and 12.1 (2.4) pain assessments were performed per horse. The ICC for each scale was 0.75 (CPS), 0.65 (EPS), 0.52 (HGS), and 0.43 (EQUUS-FAP). Total pain scores of all scales were significantly associated with an increase in movement asymmetry (R2 values ranging from −0.0649 to 0.493); with CPS pain scores being most closely associated with movement asymmetry. AUC varied between scales and observers, and CPS was the only scale where all observers had a good diagnostic accuracy (AUC > 0.72).Conclusions and clinical relevanceThis study identified significant associations between pain experienced at rest and degree of movement asymmetry for all scales. Pain scores obtained using CPS were most closely associated with movement asymmetry. CPS was also the most accurate and reliable pain scale. All scales had varying linear and non-linear relations between total pain scores and movement asymmetry, illustrating challenges with orthopedic pain assessment during rest in subtly lame horses since movement asymmetry needs to be rather high before total pain score increase.

Strengths, Opportunities, Aspirations, and Results (SOAR) is a strengths-based framework for strategic thinking, planning, conversations, and leading that focuses on strengths, opportunities, aspirations, and results. The SOAR framework leverages and integrates Appreciative Inquiry (AI) to create a transformation process through generative questions and positive framing. While SOAR has been used by practitioners since 2000 as a framework for generating positive organizational change, its use in empirical research has been limited by the absence of reliable and valid measures. We report on the reliability, construct validity, and measurement invariance of the SOAR Scale, a 12-item self-report survey organized into four first-order factors (Strengths, Opportunities, Aspirations, and Results). Data from a sample of 285 U.S. professionals were analyzed in Mplus using confirmatory factor analysis and exploratory structural equation modeling. The Four-Factor first-order exploratory structure equation modeling (ESEM) had the best model fit. Measurement invariance tests found the scalar invariance of the SOAR Scale across gender and education groups. Implications are discussed for using the SOAR Scale to build resilience at the individual, the team, and the organizational levels.

Abstract This paper aims to assess the use of Exploratory Factor Analysis by Production and Operations researchers, discussing the adequacy of its application. We analyzed 97 papers published between 2010 and 2015 in the Production and Operations area -- of which 61 and 36 were published in international and Brazilian journals, respectively. These papers contain 140 different applications of Factor Analysis. The research shows that confirmatory techniques are prevalent in international papers, as well as exploratory techniques to evaluate the problem of common method bias. Conversely, the papers in Brazilian journals typically use the exploratory technique in more traditional ways, such as to confirm the unidimensionality of the construct, or still to generate scores for use in other statistical techniques. Despite the textbooks for the AFE teaching focus exclusively on the use of AFE in the exploratory mode (to identify the number and meaning of the common factors), this use has been less frequent in published articles, both national and international. Moreover, the research shows that the inappropriate use of exploratory (rather than confirmatory) factor analysis in four Brazilian papers resulted in the “destruction of theory”. These findings suggest that national research have been using exploratory factor analysis in a questionable way; in this sense we propose scholars discuss this topic in order to disseminate the good practices.