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. Author manuscript; available in PMC: 2023 Apr 5.
Published in final edited form as: Eur J Cancer Care (Engl). 2022 Sep 15;31(6):e13707. doi: 10.1111/ecc.13707

Development and psychometric evaluation of the Spanish version of the lung cancer screening health belief scale

Lisa Carter-Bawa 1, Elizabeth Schofield 1, Thomas M Atkinson 1, Jamie S Ostroff 1
PMCID: PMC10074415  NIHMSID: NIHMS1879579  PMID: 36109851

Abstract

Objective:

The aim of this study was to describe the translation and psychometric testing of the Lung Cancer Screening Health Belief Scale (LCSHBS) into Spanish.

Methods:

The English version of the LCSHBS was professionally translated in accordance with best practices in the translation of patient-reported outcome tools. The independent certified professional translator completed a forward translation of the LCSHBS from English to Spanish, followed by a review of the translated questionnaire by a certified Memorial Sloan Kettering Cancer Center Spanish-English bicultural expert, who reviewed the scale for accuracy.

Results:

Initial testing of the scales is valid and reliable, and supports the Spanish version of the LCSHBS (LCSHBS-S). Internal consistency reliability of the scales was supported with Cronbach’s ranging from 0.81 to 0.96. Construct validity was established with confirmatory factor analysis and testing for differences between individuals who have and have not screened in theoretically proposed directions. These newly translated scales can help investigators expand this research into the large Spanish-speaking lung screening-eligible population as they develop and test critical behavioural interventions to increase lung cancer screening in the at-risk population.

Conclusions:

Development of effective interventions to enhance shared decision-making about lung cancer screening between patients and providers must first identify factors influencing the individual’s screening participation. Future efforts facilitating patient–provider conversations are better informed by understanding the perspective of the individual making the decision.

Keywords: cancer screening, health belief model, lung, patient reported outcome measures, psychometrics, psycho-oncology

1 |. INTRODUCTION

Lung cancer remains the leading cause of cancer death worldwide, largely explained by the majority of lung cancer cases being diagnosed at an advanced stage contributing to the low survival rates (American Cancer Society, 2022). In what is considered a breakthrough in reducing lung cancer-related mortality, the National Lung Screening Trial in the United States found that lung cancer screening with low-dose computed tomography (LDCT) of the chest in individuals who have a long-term smoking history has been shown to decrease relative lung cancer-related mortality by approximately 20% (National Lung Screening Trial Research Team et al., 2011). In response to these findings, the United States Preventive Services Task Force (USPSTF) issued guidelines in 2013 recommending annual screening with an LDCT of the chest for individuals aged 55–80 years with a 30 pack-year smoking history who either currently smoke or quit within the past 15 years (USPSTF, 2022a). In 2021, the USPSTF updated the eligibility criteria by decreasing the age of eligibility to 50 years and lowering the pack-year history to 20 which subsequently increased the number of eligible individuals in the United States (USPSTF, 2022b) Despite the change in eligibility criteria and its intent to be more inclusive, lung cancer screening uptake remains abysmally low, particularly among individuals from an African and Latinx background (National Cancer Institute Cancer Trends Progress Report, 2022). While overall screening uptake in the United States is around 5%, uptake among African Americans and Latinx are only 1.7% and 0.7%, respectively (National Cancer Institute Cancer Trends Progress Report, 2022).

Since the release of the 2013 USPSTF recommendation for lung cancer screening, research has been focused on understanding and intervening with individuals at risk for lung cancer by addressing knowledge, awareness and other key variables (Carter-Harris et al., 2017; Carter-Harris, Comer, et al., 2020; Carter-Harris, Slaven, et al., 2020; Lu et al., 2018; Sharma et al., 2019). Prior research has shown that individual health beliefs about lung cancer screening are critical components for guiding patient–provider discussions about lung cancer screening participation and screening uptake (Carter-Harris et al., 2017; Carter-Harris, Comer, et al., 2020; Carter-Harris, Slaven, et al., 2020; Lu et al., 2018; Sharma et al., 2019). Key constructs that have been supported as drivers of health behaviour include health beliefs such as perceived risk, perceived benefits, perceived barriers and self-efficacy (Carter-Harris et al., 2016).

The Lung Cancer Screening Health Belief Scale (LCSHBS) consists of four subscales: (1) Perceived risk of lung cancer; (2) perceived benefits of lung cancer screening; (3) perceived barriers to lung cancer screening; and (4) self-efficacy for lung cancer screening (Carter-Harris et al., 2017). The LCSHBS was developed and psychometrically validated in an English-speaking US population and has been used successfully in the United States and other English-speaking populations to better understand individual decision-making about lung cancer screening uptake (Carter-Harris et al., 2016, 2017; Carter-Harris, Comer, et al., 2020; Carter-Harris, Slaven, et al., 2020; Lu et al., 2018; Sharma et al., 2019). However, approximately 12% of the screening-eligible individuals living in the United States identify as being from a Latinx background (Pinsky et al., 2021); there are an estimated 17.5 million Spanish-speaking individuals in the United States at risk for the development of lung cancer based upon the updated USPSTF lung cancer screening criteria of May 2021 (Pinsky et al., 2021; USPSTF, 2022b). For researchers to make better use of the LCSHBS to better understand screening uptake among the Spanish-speaking population, the LCSHBS needs to be translated and validated in Spanish.

1.1 |. Purpose

The purpose of this paper is to describe the translation of the original LCSHBS into Spanish and the psychometric testing of the Spanish version of the LCSHBS in a Spanish-speaking screening-eligible population in the United States. Many studies in lung and other types of cancer screening have demonstrated the ability of theory-based interventions to successfully increase screening rates (Carter-Harris, Comer, et al., 2020; Carter-Harris, Slaven, et al., 2020; Juárez-García et al., 2021; Lei et al., 2021; Taş et al., 2019). Therefore, establishing valid and reliable measures in Spanish will allow researchers to facilitate a better understanding of the influence of perceptions of risk, benefits, barriers and self-efficacy to understand which, if any, are potentially modifiable targets that can be used in interventions to increase lung cancer screening in high-risk individuals.

To evaluate the psychometric properties of the LCSHBS–Spanish Version (LCSHBS-S) consistent with best practices in the development of patient-reported outcome instruments (Reeve et al., 2013; US Department of Health and Human Services, 2009), we tested the following hypotheses: (1) each subscale will demonstrate adequate internal consistency reliability with Cronbach’s α ≥ 0.70; (2) individuals who have been screened will exhibit higher perceived risk of lung cancer, higher perceived benefits of, lower perceived barriers to and higher self-efficacy for lung cancer screening; and (3) a 4-factor (perceived risk of lung cancer, perceived benefits of, perceived barriers to and self-efficacy for lung cancer screening) model will be consistent with observed data, and individual LCSHBS-S items will demonstrate loadings ≥0.40 on the corresponding latent factors.

2 |. METHODS

2.1 |. Participants and methods

The study protocol and the informed consent form, both in English and in Spanish, were approved by the Institutional Review Board at Memorial Sloan Kettering Cancer Center in New York.

2.2 |. Translation of the LCSHBS

The English version of the LCSHBS was professionally translated in accordance with best practices in the translation of patient-reported outcome tools (Eremenco et al., 2017). An independent certified professional translator through the services of Memorial Sloan Kettering Cancer Center completed a forward translation of the LCSHBS from English to Spanish, followed by a review of the translated questionnaire by a certified Spanish–English bicultural expert at Memorial Sloan Kettering Cancer Center, who reviewed the scale for accuracy and reconciled with a second independent certified professional translator.

2.3 |. Psychometric validation

2.3.1 |. Design

A descriptive, cross-sectional study was conducted to test the hypotheses related to internal consistency reliability and construct validity of the four translated subscales.

2.3.2 |. Sample

Inclusion criteria included individuals living in the United States who (1) are Spanish-speakers, (2) are aged 45 to 80 years, (3) have a minimum 20 pack-year tobacco smoking history, (4) are individuals who either currently smoke or quit within the past 15 years and (5) have not been diagnosed with lung cancer. Participants were recruited using Facebook targeted advertisement. Power analysis indicated that 300 participants were needed to detect a 0.20 correlation between scores on each of the four subscales and lung cancer screening uptake.

2.3.3 |. Recruitment

Facebook targeted advertisement was chosen as the venue for recruitment to mirror the original psychometric study (Carter-Harris et al., 2017). Facebook has the ability to ‘target’ an advertisement by demographics and keywords listed in each individual user’s profile or interest list. The Facebook user’s interest list includes a wide range of details a user can indicate when setting up and/or maintaining their profile that they have an interest in such as groups, hobbies, lifestyle choices, behaviours, points of view, specific organisations and preferred language. By setting the following as the specific targeting variables within our Facebook advertisement, this allowed us to purposively sample people who were aged 45–80, preferred language was Spanish, indicated smoking as an interest and resided in the United States.

Cognizant of the potential risks inherent in online research, we followed the methodological and ethical considerations for recruitment and intervention delivery published by Arigo and colleagues (Arigo et al., 2018). We also followed the formal safety and monitoring guidelines for researchers using social media outlined by Russomanno et al. (2019) through protocol development defining our Facebook page administration, notification settings and monitoring, recruitment cycle duration, inclusion and exclusion terms and public page settings and moderation (Russomanno et al., 2019). In addition, we included various mechanisms within the Research Electronic Data Capture (REDCap) screening survey to decrease the likelihood of fraudulent responses such as requiring respondents to pass a completely automated public Turing test to tell computers and humans apart (CAPTCHA). Using Facebook targeted advertisement, we were able to decrease the likelihood of promoting the study to ineligible respondents and limited visibility of study-related social media profiles to audiences in the target geographic regions with the specified targeting criteria. In addition, we monitored the REDCap database and Facebook targeted advertisement analytics multiple times daily to monitor frequency and content of responses for suspicious patterns.

2.3.4 |. Data collection

Data were collected via a one-time, web-based survey using the RED-Cap system. REDCap is a secure web-based application for building and managing online surveys and databases. Figure 1 presents the CONSORT flow diagram to test the psychometric properties of the Spanish version of the instrument.

FIGURE1.

FIGURE1

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CONSORT for Spanish Lung Cancer Screening Health Belief Psychometric Study

2.3.5 |. Measures

The English version of the LCSHBS consists of four subscales to measure perceived risk of lung cancer, perceived benefits of, perceived barriers to and self-efficacy for lung cancer screening (Carter-Harris et al., 2017). The perceived risk, perceived benefits, perceived barriers and self-efficacy subscales are comprised of 3, 6, 17 and 9 items, respectively. The perceived risk, perceived benefits and perceived barriers subscales use 4-point Likert-style responses from strongly agree to strongly disagree, whereas the self-efficacy subscale utilises 4-point Likert-style responses with items ranging from very confident to not at all confident. Sociodemographic information was also collected including participant age, marital status, educational level, income, gender, insurance status, smoking status (current and former), family history of lung cancer, provider recommendation and lung cancer screening uptake status (screened and unscreened).

2.3.6 |. Data analyses

Data were entered into SPSS Version 25.0 (IBM Corp, 2017) and cleaned by examining frequencies and identifying outliers. Data were evaluated for normal distributions and no outliers were noted. Neither the four subscales, nor any individual item of the four scales had more than 5% missing data. Each scale was summed to create a total scale score for the analyses. Patient demographic and health care factors are described overall and by screening status. Internal consistency reliability was tested using Cronbach’s α (i.e., values ≥ 0.70). Construct validity was evaluated using confirmatory factor analysis because each subscale was developed to be unidimensional. This analytic model was chosen to demonstrate the discriminant validity of the four LCSHBS-S subscales. Factorial invariance of the confirmatory factor analysis models was evaluated through subscale comparisons with screened and unscreened participants. Subscale scores are compared between screening groups using a series of Wilcoxon tests for unadjusted associations, and then a series of logistic regression models fitted using backwards selection to adjust for potential sociodemographic and health care covariates. For the adjusted models, all potential covariates significantly associated with screening were initially entered into a model for the specific subscale, and then covariates were removed sequentially unless each remained significant at the 0.10 level. Finally, confirmatory factor analysis models were compared based on the following fit indices: Standardised root mean square residual, root mean squared error of approximation (RMSEA), comparative fit index (CFI), normative fit index (NFI) and Tucker Lewis Index (TLI). Standardised root mean square residual is the standardised difference between the observed correlation and the predicted correlation; a value of less than 0.08 is considered good fit. The RMSEA is related to the residual of the model, with values ranging from 0 to 1; smaller numbers indicate a better fit. An RMSEA of 0.06 or less is considered good fit. CFI, NFI and TLI are all indicative of good fit if they exceed 0.9. All analyses were conducted using α = 0.05 as the significance level.

3 |. RESULTS

Participants (N = 335) were fairly, evenly distributed by gender. The majority (65.7%, n = 220) reported they currently smoke cigarettes. The average pack-year history was 32 (SD = 17) across both smoking statuses. Ages ranged from 45 to 80 years (M = 58.6, SD = 7.3). Participants were well educated, with 77% having some college or higher. See Table 1 for a complete list of participant sociodemographic characteristics.

TABLE 1.

Participant sociodemographic characteristics

Variable Overall (N = 334) n (%) Screened (n = 74) n (%) Unscreened (n = 260) n (%) p value
Education
 Less than high school 12 (3.6%) 4 (5.4%) 8 (3.1%) 0.87
 High school graduate 65 (19.5%) 9 (12.2%) 56 (21.5%)
 Some college 109 (32.6%) 32 (43.2%) 77 (29.6%)
 College graduate or higher 148 (44.3%) 29 (39.2%) 119 (45.8%)
Annual income
 Less than $25,000 104 (31.1%) 12 (16.2%) 92 (35.4%) 0.01
 $25,000 to $50,000 129 (38.6%) 36 (48.7%) 93 (35.8%)
 Greater than $50,000 101 (30.2%) 26 (35.1%) 75 (28.9%)
Insurance
 Government-sponsored insurance 91 (27.3%) 11 (14.9%) 80 (30.8%) 0.01
 Private health insurance 82 (24.6%) 18 (24.3%) 64 (24.6%)
 Uninsured 161 (48.2%) 45 (60.8%) 116 (44.6%)
Smoking status
 Currently smokes 114 (34.1%) 18 (24.3%) 96 (36.9%) 0.04
 Formerly smoked 220 (65.9%) 56 (75.7%) 164 (63.1%)
Family history of lung cancer
 Yes 101 (30.2%) 45 (60.8%) 56 (21.5%) <0.001
Provider recommendation for LCS
 Yes 106 (31.7%) 58 (78.4%) 48 (18.5%) <0.001
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3.1 |. Hypothesis 1. Internal consistency reliability

All Cronbach’s α values exceeded the a priori 0.70 level; 0.88 for the perceived risk subscale, 0.81 for the perceived benefits subscale, 0.89 for the perceived barriers subscale and 0.96 for the self-efficacy subscale.

3.2. |. Hypothesis 2. Mean differences on scale scores between screened and unscreened individuals

Most (78%) participants were unscreened. In Wilcoxon tests of location, there were no significant differences between screeners and nonscreeners for any of the four LCSHBS-S subscales. Although there were differences noted between groups for total perceived risk, total perceived benefits and total perceived barriers scores in the hypothesized theoretical directions, they were not statistically significant (Table 2). Total self-efficacy scores were similar for screeners and nonscreeners. In logistic regression models adjusted for significant covariates, only total perceived barriers were associated with screening. After adjustment for family history and provider recommendation, a 1-point increase in perceived barriers was associated with lower odds of screening (OR = 0.94; 95% CI = 0.92–0.97).

TABLE 2.

Subscale means examining differences between participants who have screened for lung cancer and unscreened participants

Subscale range Overall (N = 334) X¯ (SD) Screened (n = 74) X¯(SD) Unscreened (n = 260) X¯(SD) p value
Total perceived risk 3–12 7.31 (3.02) 7.66 (3.00) 7.22 (3.02) 0.30
Total perceived benefits 6–24 19.55 (3.38) 19.59 (3.63) 19.54 (3.31) 0.52
Total perceived barriers 17–68 39.13 (14.38) 37.18 (12.64) 39.69 (14.81) 0.26
Total self-efficacy 9–36 29.30 (4.87) 28.91 (4.35) 29.41 (5.01) 0.12
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Note: Values are mean (standard deviation); p values are from Wilcoxon nonparametric test.

3.3. |. Hypothesis 3. Confirmatory factor analysis

A 4-factor confirmatory factor analysis representing the theoretical model (perceived risk, perceived benefits, perceived barriers and self-efficacy) was performed. Fit statistics showed the data fitting the 4-factor model reasonably well, with a standardised root mean square residual value of 0.064. The confirmatory factor analysis had a RMSEA of 0.065, showing moderate fit. CFI was 0.89, NFI was 0.82 and TLI was 0.88. These fit statistics were all much better than those for a single factor confirmatory factor analysis assessed for comparison; RMSEA, CFI, NFI and TLI were 0.11, 0.66, 0.61 and 0.63, respectively. Total perceived risk and total perceived barriers were most strongly correlated (r = 0.56, p < 0.001), followed by total perceived benefits and total self-efficacy (r = 0.33, p < 0.001). Subscale means for screened and unscreened participants did not statistically differ, providing evidence of factorial invariance for the 4-factor confirmatory factor analysis model (Table 2).

4 |. DISCUSSION

This paper details the psychometric testing of the LCSHBS-S. Development of a Spanish version of this scale adds to the current state of the science by providing psychometrically valid and reliable, theoretically grounded measures of individual health beliefs related to lung cancer screening. This patient-reported outcome survey can be used in future research to assess individual health beliefs in the Spanish-speaking screening-eligible population and provide a means of identifying potentially modifiable intervention targets for lung cancer screening (Gany et al., 2014; Glickman et al., 2011; Muthukumar et al., 2021; Smith et al., 2018; Squires et al., 2020; Staples et al., 2018). Theoretically based patient-reported outcome questionnaires provide evidence that health belief model constructs are relevant to Spanish-speaking at-risk individuals and can be validly and reliably measured in the context of lung cancer screening participation.

4.1 |. Study limitations

Although the LCSHBS-S shows promising results, this study is not without limitations. The study is limited by the availability of individuals who have completed lung cancer screening, likely related to low rates of awareness among the screening-eligible public of the option to screen, or not, for lung cancer. It will be important to continue to test relationships between health belief model constructs and lung cancer screening participation in the Spanish-speaking screening-eligible population to understand screening behaviour more robustly. In addition, most participants (68.8%; n = 230) were from less deprived socio-economic groups. It is important to recognise the heterogeneity of the Spanish-speaking community and recognise this component and its importance moving forward. This new measurement tool will enable future work with Spanish-speaking lung screening-eligible individuals from all socio-economic backgrounds so that scientists are able to determine potentially modifiable intervention targets that are not only language appropriate but culturally relevant and meaningful.

4.2 |. Clinical implications

Although lung cancer screening participation is influenced by many factors at multiple levels, including individual, provider and system, it is essential to understand these factors from the perspective of the individual making the decision to screen, or not, for lung cancer. Understanding an individuals’ health beliefs has been supported as an influential variable in lung cancer screening behaviour among those at risk and is a critical component of future efforts to facilitate patient–provider discussions about lung cancer screening. With an estimated 17.5 million screening-eligible individuals in the United States who report Spanish as their first language (Pinsky et al., 2021; USPSTF, 2022b), it is important that researchers seeking to design interventions to better support patients and providers in this decision have psychometrically validated scales in Spanish. In addition, as with the original English version of the LCSHBS, future research is needed on health belief model constructs in the context of lung cancer screening including examination of other key variables that may be important in a Spanish-speaking population. In addition, research examining the possible mediation effect of key psychological variables (such as stigma, mistrust, fatalism, fear and worry on lung cancer screening health beliefs) in a Spanish-speaking population is a critical next step. Further, research examining who may or may not be more likely to screen will be useful for researchers interested in developing tailored interventions. Ultimately, viewing lung cancer screening as a process and tailoring interventions to an individuals’ readiness for that information may be well-received by the patient.

5 |. CONCLUSION

These findings contribute to the evidence of reliability and validity of the LCSHBS-S for Spanish speakers; all four subscales performed satisfactorily in a Spanish-speaking sample. The perceived risk of lung cancer, perceived benefits of, perceived barriers to and self-efficacy for lung cancer screening subscales are easy to use and offer researchers the opportunity to assess lung cancer screening health beliefs in populations at risk for the development of lung cancer whose primary language is Spanish. In addition, the LCSHBS-S has value for evaluating the effectiveness of much-needed interventions to change health beliefs in the context of lung cancer screening to promote screening uptake as one component of an effective cancer prevention and control programme focused on decreasing lung cancer-related mortality.

Supplementary Material

Supporting Information

Funding information

This work was supported in part by funding from the National Cancer Institute (P30CA008748). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

Footnotes

CONFLICTS OF INTEREST

There are no conflicts of interest for any of the authors.

SUPPORTING INFORMATION

Additional supporting information can be found online in the Supporting Information section at the end of this article.

DATA AVAILABILITY STATEMENT

The datasets generated and analysed during the current study are available from the corresponding author on reasonable request.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supporting Information
NIHMS1879579-supplement-Supporting_Information.pdf (139.2KB, pdf)

Data Availability Statement

The datasets generated and analysed during the current study are available from the corresponding author on reasonable request.

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