Factor Analysis Methods and Validity Evidence

Aim The aim was to explore the psychometric properties with respect to the internal consistency reliability of the subject‐specific questionnaire “Failing to Fail.” Design Cross‐sectional study. Methods Exploratory factor analysis with varimax rotation. A confirmatory factor analysis was used to examine the factor structure of the “Failing to Fail” scale. The sample included 336 Norwegian nurse mentors. Results The confirmatory factor analysis confirmed a five‐factor structure of the “Failing to Fail” scale with adequate model fit. The factors were named as: (a) Insufficient mentoring competence; (b) Insufficient support in the working environment; (c) Emotional process dominates the assessment; (d) Insufficient support from the university; and (e) Decision‐making detached from learning outcomes. The scale proved to be feasible to test whether mentors are Failing to Fail nursing students. The confirmatory factor analysis model supported the predictive validity of the “Failing to Fail” scale.

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“…According to Wetzel (2012), factor analysis methods could explore validity in studies with fewer than 100 respondents.…”

Section: Discussionmentioning

confidence: 99%

Failing to Fail nursing students among mentors: A confirmatory factor analysis of the Failing to Fail scale

et al. 2019

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“…10,11 Removing the global scoring from each skill made the checklist easier to use and required less training for evaluators. 12,13 Students were instructed to ask an evaluator to complete the IV checklist during at least one IV placement attempt in any patient encounter.…”

Section: Methodsmentioning

confidence: 99%

An Intervention to Improve Medical Student Perception of Observation and Feedback During an Anesthesiology Clerkship

Trawicki

Zuegge

Volz

et al. 2018

TOJ

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“…We recruited a convenience sample of 364 patients from three treatment sites (one residential and two outpatient) in KZN ( n = 134) and seven sites (three residential and four outpatient) in the WC ( n = 230) between September 2011 and July 2012. This sample size is adequate for most factor analyses [ 35 ]. Participants were eligible to participate if they were at least 18 years of age, had been receiving substance abuse treatment for at least three weeks, and could read and write English.…”

Section: Methodsmentioning

confidence: 99%

“…Suitability of items for factor analysis was determined using two measures; Bartlett’s Test of Sphericity (significance of p ≤ 0.05) and the Kaiser-Meyer-Olkin (KMO) measure of sampling adequacy (0.70 and above). The EFA was conducted using maximum likelihood estimation (MLE) and oblique minimum rotation to extract and rotate identified factors [ 35 ]. Only factors with an Eigenvalue greater than 1 were selected for consideration [ 36 ].…”

Section: Methodsmentioning

confidence: 99%

Development and psychometric validation of a novel patient survey to assess perceived quality of substance abuse treatment in South Africa

Myers

Govender

Koch

et al. 2015

Subst Abuse Treat Prev Policy

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BackgroundA hybrid performance measurement system that combines patient-reported outcome data with administrative data has been developed for South African substance abuse treatment services. This paper describes the development and psychometric validation of one component of this system, the South African Addiction Treatment Services Assessment (SAATSA).MethodsFirst, a national steering committee identified five domains and corresponding indicators on which treatment quality should be assessed. A decision was made to develop a patient survey to assess several of these indicators. A stakeholder work group sourced survey items and generated additional items where appropriate. The feasibility and face validity of these items were examined during cognitive response testing with 16 patients. This led to the elimination of several items. Next, we conducted an initial psychometric validation of the SAATSA with 364 patients from residential and outpatient services. Exploratory (EFA) and confirmatory factor analyses (CFA) were conducted to assess the latent structure of the SAATSA. Findings highlighted areas where the SAATSA required revision. Following revision, we conducted another psychometric validation with an additional sample of 285 patients. We used EFA and CFA to assess construct validity and we assessed reliability using Cronbach’s measure of internal consistency.ResultsThe final version of the SAATSA comprised 31 items (rated on a four-point response scale) that correspond to six scales. Four of these scales are patient-reported outcome measures (substance use, quality of life, social connectedness and HIV risk outcomes) that together assess the perceived effectiveness of treatment. The remaining two scales assess patients’ perceptions of access to and quality of care. The models for the final revised scales had good fit and the internal reliability of these scales was good to excellent, with Cronbach’s α ranging from 0.72 to 0.89.ConclusionA lack of adequate measurement tools hampers efforts to improve the quality of substance abuse treatment. Our preliminary evidence suggests that the SAATSA, a novel patient survey that assesses patients’ perceptions of the outcomes and quality of substance abuse treatment, is a psychometrically robust tool that can help fill this void.

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Factor Analysis Methods and Validity Evidence

Cited by 54 publications

References 91 publications

Failing to Fail nursing students among mentors: A confirmatory factor analysis of the Failing to Fail scale

Failing to Fail nursing students among mentors: A confirmatory factor analysis of the Failing to Fail scale

An Intervention to Improve Medical Student Perception of Observation and Feedback During an Anesthesiology Clerkship

Development and psychometric validation of a novel patient survey to assess perceived quality of substance abuse treatment in South Africa

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