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Replication Data for Unlocking the Power of Inclusive Leadership: Enhancing...
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Updated May 1, 2025
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EmailClick to copy linkLink copiedCiteScott Phillips (2025). Replication Data for Unlocking the Power of Inclusive Leadership: Enhancing job satisfaction and elevating perceived patient care through cultural competence [Dataset]. http://doi.org/10.7910/DVN/BWMCIBCroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.Unique identifierhttps://doi.org/10.7910/DVN/BWMCIBDataset updatedMay 1, 2025Dataset provided byHarvard DataverseAuthorsScott PhillipsLicenseCC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
License information was derived automaticallyDescription- Purpose and provenance The file contains the anonymized, raw responses to the cross-sectional survey that underpins “Unlocking the Power of Inclusive Leadership: Enhancing Job Satisfaction and Elevating Perceived Patient Care Through Cultural Competence”. Data were collected between June and November 2024 from healthcare professionals in multiple U.S. institutions after University of New Orleans IRB approval (Protocol 04Apr24). Participants gave electronic informed consent before answering. 2. File structure Row(s) Contents Notes 1 Human-readable column labels Full question text or variable title as exported by Qualtrics. 2 Qualtrics metadata (ImportId, time-zone, etc.) Preserves original item IDs for reproducibility. 3 – 219 Individual response records (n = 217) Each row = one respondent. Two system rows above must be removed or skipped when importing to most statistical packages. Key system columns include StartDate, EndDate, ResponseId, Progress, Finished, and fraud-detection flags (e.g., Q_RelevantIDFraudScore). 3. Sample overview Total raw records: 217 Finished = 1 (completed): 154 Analytic sample used in the manuscript: 142 (filtered for completion, ≥80 % item response, and role eligibility). Demographic variables (Q1–Q7 plus ZIP code) capture practice setting, professional role, gender (0 = No, 1 = Yes for female, consistent with manuscript coding), race/ethnicity, education, income (text stripped of “or more”), and age category. 4. Survey blocks and variable prefixes Construct / scale Prefix & item count Response scale (all 5-point unless noted) Inclusive Leadership (Carmeli et al.) Inclusive Leadership_1 – _9 1 = Not at all → 5 = To a large extent Cultural Competence (Balcázar et al.) Cultural Competence_1…28† 5 = Strongly agree → 1 = Strongly disagree Climate for Inclusion (Nishii) CiD1.1…CiD3.3 (15 items) 5 = Strongly agree → 1 = Strongly disagree Short Index of Job Satisfaction SIJS1…SIJS5 5 = Strongly agree → 1 = Strongly disagree Healthcare Quality Perception HQP1…HQP35 5 = Strongly agree → 1 = Strongly disagree Social Desirability (SDRS-5) SDRS1…SDRS5 1 = Definitely True → 5 = Definitely False †Only 18 of the original 28 CCAI items met inclusion after pilot testing (see manuscript Appendix A). Reverse-worded items are retained as exported; users should recode before computing scale scores (see codebook in Appendix B of the manuscript). 5. Data quality flags and recommended filters Finished = 1 and Progress ≥ 80 % identify complete surveys. Blank cells represent unanswered items; Qualtrics exports them as empty strings, which most software reads as NA. The file keeps partial and screened-out cases to allow alternative inclusion criteria; replicate the manuscript analyses by selecting the 142-case subset described above. 6. Usage notes Format: UTF-8, comma-separated. Compatible with R, Python (pandas), SPSS, and Stata (skip first two rows or use read_spss() with header rows ignored). Anonymity: No direct identifiers; ZIP code is the most granular geographic field and may be removed for secondary sharing if desired. Reliability diagnostics: Cronbach’s α for each construct, as reported in the article (α = 0.95 for IL, etc.), can be replicated with the raw columns once reverse coding is applied. 7. Citation When using the dataset, please cite the parent article and include a data statement such as: “Survey data are available in Supplementary File 1 (‘Inclusive_Leadership_in_Healthcare_Management_Survey_Raw.csv’). See Phillips et al. (2025) for instrument details and variable coding.”
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Scott Phillips (2025). Replication Data for Unlocking the Power of Inclusive Leadership: Enhancing job satisfaction and elevating perceived patient care through cultural competence [Dataset]. http://doi.org/10.7910/DVN/BWMCIB
Replication Data for Unlocking the Power of Inclusive Leadership: Enhancing job satisfaction and elevating perceived patient care through cultural competence
CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
Unique identifier
https://doi.org/10.7910/DVN/BWMCIBDataset updated
May 1, 2025Dataset provided by
Harvard DataverseAuthors
Scott Phillips License
CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
License information was derived automatically
Description
- Purpose and provenance The file contains the anonymized, raw responses to the cross-sectional survey that underpins “Unlocking the Power of Inclusive Leadership: Enhancing Job Satisfaction and Elevating Perceived Patient Care Through Cultural Competence”. Data were collected between June and November 2024 from healthcare professionals in multiple U.S. institutions after University of New Orleans IRB approval (Protocol 04Apr24). Participants gave electronic informed consent before answering. 2. File structure Row(s) Contents Notes 1 Human-readable column labels Full question text or variable title as exported by Qualtrics. 2 Qualtrics metadata (ImportId, time-zone, etc.) Preserves original item IDs for reproducibility. 3 – 219 Individual response records (n = 217) Each row = one respondent. Two system rows above must be removed or skipped when importing to most statistical packages. Key system columns include StartDate, EndDate, ResponseId, Progress, Finished, and fraud-detection flags (e.g., Q_RelevantIDFraudScore). 3. Sample overview Total raw records: 217 Finished = 1 (completed): 154 Analytic sample used in the manuscript: 142 (filtered for completion, ≥80 % item response, and role eligibility). Demographic variables (Q1–Q7 plus ZIP code) capture practice setting, professional role, gender (0 = No, 1 = Yes for female, consistent with manuscript coding), race/ethnicity, education, income (text stripped of “or more”), and age category. 4. Survey blocks and variable prefixes Construct / scale Prefix & item count Response scale (all 5-point unless noted) Inclusive Leadership (Carmeli et al.) Inclusive Leadership_1 – _9 1 = Not at all → 5 = To a large extent Cultural Competence (Balcázar et al.) Cultural Competence_1…28† 5 = Strongly agree → 1 = Strongly disagree Climate for Inclusion (Nishii) CiD1.1…CiD3.3 (15 items) 5 = Strongly agree → 1 = Strongly disagree Short Index of Job Satisfaction SIJS1…SIJS5 5 = Strongly agree → 1 = Strongly disagree Healthcare Quality Perception HQP1…HQP35 5 = Strongly agree → 1 = Strongly disagree Social Desirability (SDRS-5) SDRS1…SDRS5 1 = Definitely True → 5 = Definitely False †Only 18 of the original 28 CCAI items met inclusion after pilot testing (see manuscript Appendix A). Reverse-worded items are retained as exported; users should recode before computing scale scores (see codebook in Appendix B of the manuscript). 5. Data quality flags and recommended filters Finished = 1 and Progress ≥ 80 % identify complete surveys. Blank cells represent unanswered items; Qualtrics exports them as empty strings, which most software reads as NA. The file keeps partial and screened-out cases to allow alternative inclusion criteria; replicate the manuscript analyses by selecting the 142-case subset described above. 6. Usage notes Format: UTF-8, comma-separated. Compatible with R, Python (pandas), SPSS, and Stata (skip first two rows or use read_spss() with header rows ignored). Anonymity: No direct identifiers; ZIP code is the most granular geographic field and may be removed for secondary sharing if desired. Reliability diagnostics: Cronbach’s α for each construct, as reported in the article (α = 0.95 for IL, etc.), can be replicated with the raw columns once reverse coding is applied. 7. Citation When using the dataset, please cite the parent article and include a data statement such as: “Survey data are available in Supplementary File 1 (‘Inclusive_Leadership_in_Healthcare_Management_Survey_Raw.csv’). See Phillips et al. (2025) for instrument details and variable coding.”