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Validation of the French version of the Hospital Survey on Patient Safety Culture questionnaire

P. Occelli, J-L. Quenon, M. Kret, S. Domecq, F. Delaperche, O. Claverie, B. Castets-Fontaine, R. Amalberti, Y. Auroy, P. Parneix, P. Michel
DOI: http://dx.doi.org/10.1093/intqhc/mzt047 459-468 First published online: 5 July 2013


Objective To assess the psychometric properties of the French version of the Hospital Survey on Patient Safety Culture questionnaire (HSOPSC) and study the hierarchical structure of the measured dimensions.

Design Cross-sectional survey of the safety culture.

Setting 18 acute care units of seven hospitals in South-western France.

Participants Full- and part-time healthcare providers who worked in the units.

Interventions None.

Main outcome measures Item responses measured with 5-point agreement or frequency scales.

Data analyses A principal component analysis was used to identify the emerging components. Two structural equation modeling methods [LInear Structural RELations (LISREL) and Partial Least Square (PLS)] were used to verify the model and to study the relative importance of the dimensions. Internal consistency of the retained dimensions was studied. A test–retest was performed to assess reproducibility of the items.

Results Overall response rate was 77% (n = 401). A structure in 40 items grouped in 10 dimensions was proposed. The LISREL approach showed acceptable data fit of the proposed structure. The PLS approach indicated that three dimensions had the most impact on the safety culture: ‘Supervisor/manager expectations & actions promoting safety’ ‘Organizational learning—continuous improvement’ and ‘Overall perceptions of safety’. Internal consistency was above 0.70 for six dimensions. Reproducibility was considered good for four items.

Conclusions The French HSOPSC questionnaire showed acceptable psychometric properties. Classification of the dimensions should guide future development of safety culture improving action plans.

  • safety culture
  • safety climate
  • safety management
  • validation studies
  • psychometrics


In France, as in other Western countries, adverse events are frequent, serious and preventable in more than one-third of cases [1]. These events have their roots in system failures, care processes and working conditions that do not promote safety [2]. Developing a ‘safety culture’ based on a systemic view of the determinants of safety could be a leverage to improve patient safety in health care [3].

There are many definitions of the safety culture [4]. One definition comes from the nuclear power industry and has been adapted to healthcare: ‘the safety culture of an organization is the product of individual and group values, attitudes, perceptions, competencies, and patterns of behavior that determine the commitment to, and the style and proficiency of’ a healthcare organization to manage safety [5].

Safety culture measurement relies on a combination of quantitative (individual and self-administered questionnaires) and qualitative (interviews, on-site observations, focus groups) methods. For feasibility reasons, individual and self-administered questionnaires are mostly used in health care [69]. These questionnaires are distributed to a group of healthcare providers in order to measure their shared perceptions about safety, also called ‘safety climate’. Data collected from individuals are aggregated to represent safety climate at the unit level. Few studies combined the use of a quantitative questionnaire with another source of information such as qualitative measures [10, 11].

The Hospital Survey on Patient Safety Culture (HSOPSC) is a self-administered questionnaire funded by the Agency for Healthcare Research and Quality [12]. It measures 12 dimensions of the safety culture through 42 items and can be used across disciplines. It is widely used in the USA as well as in European countries [1317]. The study of the psychometric properties of the different HSOPSC versions showed that the structure of the original one was partially replicated but that some adaptations were needed (dimensions were merged together, items were deleted or replaced in another dimension). However, these studies had some limitations. The reproducibility of the measured items has not been studied despite the fact that such surveys are used to monitor safety culture over time. Other dimensions that could be relevant in healthcare have only been tested in one study [16]. The first objective of the described study was to assess the psychometric properties of the French version in order to propose a validated tool to French hospitals. The second objective was to study the hierarchical structure of the measured dimensions in order to identify relevant area for future research on safety culture.


French version of the hospital survey on patient safety culture

The HSOPSC was translated into French by a group of French researchers in epidemiology, sociology, ergonomics, anesthesiology and management who work in patient safety. It was pretested among healthcare providers [18]. No back translation was done but the questionnaire translation was compared with another translation independently performed by another group of French researchers.

The French HSOPSC was identical to the American one except for three items that were added. These items sought to account for the influence of peers in the acquisition of a safety culture, an aspect that was not measured in the original questionnaire. They were a priori grouped into a new dimension labeled ‘Training and organizational learning’: (1) patient safety issues were addressed during my education, (2) in contact with our co-workers, we improve our practices in term of safety, (3) when someone does not respect patient safety because of a difficult or complex situation, the ward staff does not react. Additionally, respondents' background information was collected.

Item responses were measured with 5-point agreement (from 1 = strongly disagree to 5 = strongly agree) or frequency (from 1 = never to 5 = always) scales. For each item, the percentage of positive responses (pointing to a developed safety culture) was calculated. For positively worded items, responses 4 and 5 corresponded to positive answers. Inversely, for negatively worded items, responses 1 and 2 corresponded to positive answers. Each dimension was measured through three to four items. For each dimension, a score was calculated. It was the mean of the percentages of positive answers to the dimension's respective items.

Data collection

The survey was conducted in January 2009 in seven hospitals in South-western France. Hospitals were randomly selected according to their status and number of beds. Eighteen acute care units of the selected hospitals voluntarily participated in the survey: 10 medical (dermatology, endocrinology, pneumology, rheumatology, neurology, internal medicine, gastroenterology and three cardiology units) and 8 surgical (cardiac and general surgery, urology, pediatrics, gynecology, neurosurgery, and two orthopedic units) units. Full- and part-time healthcare providers who worked in the unit for at least one month prior the administration of the questionnaire were included in the survey.

Quality and risk management assistants coordinated the distribution and collection of the questionnaires in each hospital. Head nurses were in charge to identify and to distribute a questionnaire to each eligible healthcare provider. The recommended survey completion period was one week. Completion was voluntary and anonymous. A deposit box was used for collection.

Statistical analysis

Exploratory analyses

Items were described calculating response rates and percentage of responses in each category. Intercorrelations among items and dimensions were calculated using the non-parametric Spearman test as it is adapted to qualitative ordinal variables. High correlation above 0.80 indicated that two items were redundant, and some items could be deleted. Low correlation under 0.20 indicated that two items were weakly related, and some items were misplaced or could be deleted.

Internal consistency of the questionnaire and its dimensions was measured by Cronbach's alpha coefficient. The consistency of each dimension was also measured after dropping items. Homogeneity was considered good if alpha was greater than 0.70 [19, 20].

A principal component analysis (PCA) was used to reduce the number of variables and to identify the emerging components, with no a priori on the number of components and their underlying causal structure [20]. First, the items' loadings on the first component were studied to confirm the unidimensionality of the questionnaire. Then, as dimensions were correlated (correlation above 0.30), the oblimin rotation method was used. The Kaiser's rule, the scree test and the Horn's parallel analysis, along with the subjective interpretation of the retained components, were used in order to determine the number of components. For an item to be considered as being adequately represented by a particular component, the square of its cosine should be 0.30 or greater [21]. For an item to be considered as having an adequate contribution to a particular component, its loading should be 0.40 or greater [20]. A PCA with an oblimin rotation was finally performed on the final French version of the questionnaire, and internal consistency of its dimensions was measured.

Confirmatory analyses

A structural equation modeling method (SEM) was used to verify the model hypothesized from the exploratory analyses and to determine how well it fits the data [22, 23]. The SEM consisted in an external model representing the relationships between the latent (the dimensions) and manifest variables (their items); as well as an internal model representing the relationships between the latent variables.

Two complementary approaches were used in parallel: (1) the LInear Structural RELations (LISREL) approach in order to study the extent to which the data fits the hypothesized model [24] and (2) the Partial Least Square (PLS) approach in order to estimate the individual scores of the latent variables [25]. Using the LISREL approach, the best fit model was assessed with the Comparative Fit Index (CFI), and the Root Mean Square Error Approximation (RMSEA). CFI value above 0.90 and RMSEA value under 0.08 indicate a good fit model, CFI value above 0.95 and RMSEA value under 0.05 indicate an excellent fit model [26, 27]. The jöreskog chi-square test was used to compare the original structure in 12 dimensions with the hypothesized model. The best model had the lowest chi-square [28].

Using the PLS approach, the internal and external model's parameters were estimated. For the external model, normalized external weights were calculated: they quantify the impact of each item on its dimension (with percentage of relative importance of an item's effect on its dimension). For the internal model, structural coefficients were calculated: they represent the impact of each dimension on the safety culture, without quantifying it. Homogeneity of the dimensions was measured using Dillon–Goldstein's rho coefficient.


To assess the reproducibility, a test–retest was conducted in another hospital. Forty-five randomly selected healthcare providers were asked to answer the questionnaire twice with a 2-week interval between the test and the retest. The retest was sent out once the test questionnaire had been collected. Internal hospitals' mailing facilities were used for distribution and collection.

Test–retest reliability of the 42 items of the original version of the questionnaire was assessed by the one-way intra-class correlation coefficient (ICC type (1, 1) [29]. Reliability was considered good if ICC was greater than 0.70 [30].



Overall response rate to the survey was 76.5% (n = 401). It varied across units from 42.3 to 100%. Most respondents were nurses (45.8%, n = 181). Among respondents, 190 (48.1%) had worked for 11 years or more in their specialty, 208 (52.8%) had worked for six years or more in their hospital, and 141 (35.5%) had worked for six years or more in their unit (Table 1).

View this table:
Table 1

Characteristics of the responders (n = 401)

Staff position395
 Auxiliary nurse12932.7
Number of years in specialty395
 <1 year389.6
 1 to 5 years9524.1
 6 to 10 years7218.2
 11 to 15 years369.1
 16 to 20 years5012.7
 ≥21 years10426.3
Number of years in hospital394
 <1 year6316.0
 1 to 2 years358.9
 2 to 5 years8822.3
 ≥6 years20852.8
Number of years in clinical unit397
 <1 year8421.2
 1 to 2 years4210.6
 2 to 5 years13032.7
 ≥6 years14135.5
Working time in clinical unit397
 Between 50 and 100%37193.5
Participation in risk management committees or structures397

Validation of a French version of the hospital survey on patient safety culture

Exploratory analyses

Item response rate ranged from 94.8 to 99.8% (Table 2). Four items (A7, A11, F6 and F11) had low correlations with two or more items of their dimension (Table 2); no items had high correlations, above 0.80, with other items of their dimension. Cronbach's alpha was of 0.88 for the questionnaire and ranged from 0.46 to 0.84 for dimensions. Three dimensions had an alpha above 0.70. The dimensions ‘Staffing’ and ‘Training and organizational learning’ had the lowest coefficients.

View this table:
Table 2

Exploratory factor analysis: response rates, intercorrelations, PCA components, internal consistency and reproducibility of the 45 items and 13 dimensions measured with the French version of the HSOPSC questionnaire

Dimensions and itemsResponse rateIntercorrelation between items of the same dimensionPCACronbach's alphaICC
1. Overall perceptions of safety95.50.67
 A15 Patient safety is never sacrificed to get more work done.98.8A10F70.53
 A18 Our procedures and systems are good at preventing errors from happening.99.0F70.50
 A10 It is just by chance that more serious mistakes do not happen around here.98.8A15F70.50
 A17 We have patient safety problems in this unit.98.5F70.74
2. Frequency of event reporting94.80.84
 D1 When a mistake is made, but is caught and corrected before affecting the patient, how often is this reported?96.0D2F20.37
 D2 When a mistake is made, but has no potential to harm the patient, how often is this reported?95.5D1, D3F20.24
 D3 When a mistake is made that could harm the patient, but does not, how often is this reported?94.8D2F20.60
3. Supervisor/manager expectations & actions promoting safety97.80.83
 B1 My supervisor/manager says a good word when he/she sees a job done according to established patient safety procedures.99.5F10.76
 B2 My supervisor/manager seriously considers staff suggestions for improving patient safety.98.5F10.70
 B3 Whenever pressure builds up, my supervisor/manager wants us to work faster, even if it means taking shortcuts.98.8B4F10.66
 B4 My supervisor/manager overlooks patient safety problems that happen over and over.98.8B3F10.51
4. Organizational learning—continuous improvement97.30.59
 A13 After we make changes to improve patient safety, we evaluate their effectiveness.99.0F60.60
 A6 We are actively doing things to improve patient safety.99.3F60.57
 A9 Mistakes have led to positive changes here.98.5F60.55
5. Teamwork within hospital units98.30.63
 A1 People support one another in this unit.99.5A11A4F30.62
 A11 When one area in this unit gets really busy, others help out.99.3A1, A4F110.59
 A3 When a lot of work needs to be done quickly, we work together as a team to get the work done.99.5F30.67
 A4 In this unit, people treat each other with respect.99.5A11A1F30.70
6. Communication openness96.80.62
 C2 Staff will freely speak up if they see something that may negatively affect patient care.99.50.32
 C4 Staff feel free to question the decisions or actions of those with more authority.97.50.50
 C6 Staff are afraid to ask questions when something does not seem right.98.8F50.53
7. Feedback and communication about error95.50.64
 C1 We are given feedback about changes put into place based on event reports.98.3F80.64
 C3 We are informed about errors that happen in this unit.97.8F100.11
 C5 In this unit, we discuss ways to prevent errors from happening again.98.0F60.57
8. Non-punitive response to error97.50.57
 A12 When an event is reported, it feels like the person is being written up, not the problem.98.80.63
 A16 Staff worry that mistakes they make are kept in their personnel file.99.3A8F120.49
 A8 Staff feel like their mistakes are held against them.99.0A160.50
9. Staffing96.30.46
 A2 We have enough staff to handle the workload.99.0A7F90.77
 A14 We work in ‘crisis mode’, trying to do too much, too quickly.99.8A7F90.63
 A5 Staff in this unit work longer hours than is best for patient care.99.3A7F90.69
 A7 We use more agency/temporary staff than is best for patient care.98.3A2, A14, A5F100.64
10. Hospital management support for patient safety95.50.73
 F1 Hospital management provides a work climate that promotes patient safety.97.0F80.53
 F8 The actions of hospital management show that patient safety is a top priority.96.8F80.63
 F9 Hospital management seems interested in patient safety only after an adverse event happens.97.5F80.53
11. Teamwork across hospital units96.80.59
 F10 Hospital units work well together to provide the best care for patients.98.0F6F80.33
 F4 There is good cooperation among hospital units that need to work together.97.8F40.38
 F6 It is often unpleasant to work with staff from other hospital units.98.3F10, F20.62
 F2 Hospital units do not coordinate well with each other.97.3F6F40.55
12. Hospital handoffs and transitions95.50.66
 F11 Shift changes are problematic for patients in this hospital.97.8F3, F7F50.71
 F3 Things ‘fall between the cracks’ when transferring patients from one unit to another.97.5F11F40.49
 F5 Important patient care information is often lost during shift changes.97.3F4. F50.65
 F7 Problems often occur in the exchange of information across hospital units.97.3F11F40.26
13. Training and organizational learninga0.46
 H1 Patient safety issues were addressed during my education95.5H3F11
 H2 In contact with our co-workers, we improve our practices in term of safety97.0F3
 H3 When someone does not respect patient safety because of a difficult or complex situation, the ward staff does not react.96.8H1F11
  • PCA, principal component analysis; ICC, intra-class correlation coefficient.

  • In the column entitled PCA, F7 is the factor to which the item had an adequate contribution (factor loading ≥ 0.40). A bold entry correspond to a factor that adequately represents the item (square of the cosine ≥ 0.30). In the column entitled Cronbach's alpha, ‘↓’ indicates that the alpha of the dimension was higher after dropping the corresponding item.

  • aAdded dimension to the original questionnaire.

The results of the exploratory analyses and a first PCA (components loadings of the items are shown in Supplementary material, Appendix) lead to hypothesize a structure in 10 dimensions and 40 items: three items from the original version were dropped (A7, A11 and F11) and one added item was kept (Table 3). Two items were reworded (F6 and A5).

View this table:
Table 3

Dimensions and items of the French version of the HSOPSC questionnaire, before and after exploratory analyses

French structure before exploratory analysesFrench structure after exploratory analyses
1. Overall perceptions of safetyA10, A15, A17, A181. Overall perceptions of safetyA10, A15, A17, A18
2. Frequency of event reportingD1, D2, D32. Frequency of event reportingD1, D2, D3
3. Supervisor/manager expectations & actions promoting safetyB1, B2, B3, B43. Supervisor/manager expectations & actions promoting safetyB1, B2, B3, B4
4. Organizational learning—continuous improvementA6, A9, A134 + 7. Organizational learning—continuous improvementA6, A9, A13, C1, C3, C5
5. Teamwork within hospital unitsA1, A3, A4, A115. Teamwork within hospital unitsA1, A3, A4, H2, (A11)
6. Communication opennessC2, C4, C66. Communication opennessC2, C4, C6
7. Feedback and communication about errorC1, C3, C5
8. Non-punitive response to errorA8, A12, A168. Non-punitive response to errorA8, A12, A16
9. StaffingA2, A5, A7, A149. StaffingA2, A5, A14, (A7)
10. Hospital management support for patient safetyF1, F8, F910. Hospital management support for patient safetyF1, F8, F9, F10
11. Teamwork across hospital unitsF2, F4, F6, F1011 + 12. Teamwork across hospital unitsF2, F4, F6, F3, F5, F7, (F11)
12. Hospital handoffs and transitionsF3, F5, F7, F11
13. Training and organizational learningH1, H2, H3
  • 4 + 7: two dimensions grouped into a single dimension. A bold and underlined entry correspond to an added item. An italic entry correspond to a removed item.

A second PCA was performed on the hypothesized structure. Before rotation, the study of the first component confirmed the unidimensionality of the questionnaire. After rotation, the Kaiser's rule indicated a solution in 10 components accounting for 58% of the total variance. The Horn's parallel analysis indicated a solution in nine components. No solution could be retained from the scree test as there was no obvious break in the scree plot.

The internal consistency measured on the structure in 10 dimensions showed that Cronbach's alpha was above 0.70 for six dimensions (dimensions number 2 to 5, 10 and 11 + 12) and ranged from 0.55 to 0.67 for the other four.

Confirmatory analyses

Using the LISREL approach, the original structure in 12 dimensions and 42 items was tested (chi-square = 1308.4, df = 741) and showed an acceptable fit to the data (CFI = 0.848; RMSEA = 0.050). The hypothesized model in 10 dimensions and 40 items was tested (chi-square = 1199.4, df = 685) and showed an acceptable fit (CFI = 0.855; RMSEA = 0.049). Results of the chi-square test indicated that the hypothesized model fitted the data better.

The PLS model was conducted on the 10-dimension structure. The homogeneity of the 10 dimensions was good with rho coefficients from 0.77 to 0.91. External model parameters showed that the effect of items on their dimension differed (Fig. 1), e.g. one item of dimension 8 and two items of dimension 9 had more effect on their dimension than other items. Internal model parameters showed that the impact on the safety culture of the dimensions differed. The five dimensions with the most impact were ‘3: Supervisor/manager expectations & actions promoting safety’ (structural coefficient = 0.226) had the most impact, followed by ‘4 + 7: Organizational learning—continuous improvement’ (0.218), ‘1: Overall perceptions of safety’ (0.205), ‘10: Hospital management support for patient safety’ (0.179), ‘11 + 12: Teamwork across hospital units’ (0.170).

Figure 1

Confirmatory factor analysis of the hypothesized structure of the French version of the HSOPSC questionnaire: impact of the manifest variables on the latent variables and of the latent variables on the safety culture. Rectangles represent items or manifest variables; circles represent the dimensions (dim) and the safety culture, or latent variables. ‘W(Nor)’ is the normalized external weight of each item on its dimension. ‘Reg’ is the structural coefficient of each dimension on the safety culture. The dark variation shows which dimensions have the most impact on the safety culture.


Forty-five providers answered twice to the questionnaire. For the 42 items of the original version, ICC ranged from 0.11 to 0.77 (Table 2). Four items had an ICC above 0.70, 25 items had an ICC between 0.50 and 0.70 and 13 items had an ICC of 0.50 or under.

Perceptions of safety across the 18 care units

Health care workers' perceptions on the 10 dimensions of safety culture were studied. It showed that five dimensions had a score of 50% or under in more than half of the 18 care units, pointing to poorly developed dimensions (Table 4). They were as follows: ‘1: Overall perceptions of safety’ (score range, 25.0–71.8%), ‘8: Non-punitive response to error’ (3.5–47.1%), ‘9: Staffing’ (15.0–58.3%), ‘10: Hospital management support for patient safety’ (15.4–58.8%) and ‘11 + 12: Teamwork across hospital units' (24.6–66.7%).

View this table:
Table 4

Scoresa of the 10 dimensions measured with the validated French version of the HSOPSC questionnaire

Dimensions of safety cultureABCDEFG
1. Overall perceptions of safety53.251.037.571.844.760.750.063.925.038.234.455.040.240.850.026.167.636.8
2. Frequency of event reporting68.873.170.858.878.965.260.055.673.350.072.773.850.753.761.449.347.175.9
3. Supervisor/manager expectations & actions promoting safety73.457.148.167.681.377.367.163.655.664.758.358.362.072.571.120.563.27.4
4 + 7. Organizational learning—continuous improvement45.
5. Teamwork within hospital units87.566.372.878.079.261.455.952.362.092.661.560.072.773.886.876.189.773.6
6. Communication openness61.556.
8. Non-punitive response to error42.731.024.420.636.836.226.33.717.919.624.642.243.529.829.824.647.13.5
9. Staffing29.229.821.
10. Hospital management support for patient safety19.515.427.023.419.732.127.919.439.833.837.533.929.540.056.629.358.822.4
11 + 12. Teamwork across hospital units36.730.834.033.836.134.128.735.239.531.431.338.944.947.548.024.666.736.0
  • A is a university hospital; B is a public hospital with 300 beds or more; C is a hospital with less than 300 beds; D to G are private hospitals with 200 beds or more. Unit number 1 and 2 are medical units and 3 and 4 are surgical units.

  • aThe score of a dimension is the mean of the percentages of positive answers (indicating a developed safety culture) on its items.


The French version of the HSOPSC questionnaire explores the same constructs as the original version does; however, some adjustments were required to fit the French context: two dimensions were merged into one, three items were removed and one was added in the revised version. The final structure in 10 dimensions and 40 items performed better than the original one in the sample of the seven French hospitals.

The French version of the questionnaire has shown acceptable psychometric properties. It has shown a good feasibility and acceptability of a single survey with high response rates. The internal consistency of the final structure was above 0.70 for six dimensions. After exploratory analyses, only one out of the three new items was kept and added to the dimension ‘Teamwork within units’. This indicates that the content of the dimensions could be improved. The HSOPSC questionnaire has been translated in several European (Belgium, Netherlands, UK and German-speaking Switzerland) and non-European countries (Taiwan, Japan) [1316, 31, 32]. Even though other translation validation results converge with ours, the final structure of the tools does differ. This corroborates the need to adapt the tool to each country according to local ways of being, thinking, behaving and communicating. For international comparison purposes, a core set of dimensions consistently assessed as valid should be defined and measured in all countries.

The study has some limitations. First, selection bias might have existed as units were selected on a voluntary basis and as head nurses were responsible for distributing the questionnaires. One dimension measures the perceptions of workers on the supervisor actions for safety in the unit (including the head nurse's actions). Hence, it is possible that head nurses chose not to include some healthcare providers eligible. For future surveys, list of eligible providers should be collected independently from the management of the surveyed unit. Besides, as most of the respondents are nurses, the final structure probably reflects their perceptions of safety. The survey is best fitted for examining patient safety climate from a hospital staff unit perspective. Second, the drafting up and validation of the French version were based on the PCA and MES studies carried out on the same data set. The small size of the sample did not allow us to split in half the sample as in a typical cross-validation study. The MES studies conducted on the same data confirmed the hypothesized model, but this need to be confirmed on different data. Finally, the items could require some fine-tuning. The results of our exploratory analyses showed that the items of the dimension ‘Communication openness’ would not measure this construct precisely enough in the French version. The reproducibility of 26 of the final 40 items was found to be average (ICC > 0.50). As back translation has not been performed, it cannot be ruled out that the measurement structure has been changed through translation. But, the low reliability also points out the instability of the aspects measured by the questionnaire, which are based on professionals' perceptions of safety (themselves linked to safety circumstances at a given time, and inherently instable and subject to change). If culture does not change so rapidly, perceptions do. These results show that test–retest reliability should be assessed in studies about psychometric properties of safety climate questionnaires. Future research should also evaluate the impact of response rates on safety climate measurements, define a threshold for which safety climate can be considered developed and compare safety climate measurements with results of ethnographic studies and with the evolution of patient safety process or outcomes.

The LISREL and the PLS techniques were both used. These methods are complementary rather than being competitive. The LISREL approach allowed us to validate the structure emerging from the exploratory analysis, but no scores could be calculated. The PLS approach made it possible to rank the dimensions according to their impact on safety culture and to calculate the weight of each item on its dimension. The calculation of scores showed that the dimension ‘Supervisor/manager expectations & actions promoting safety’ turned out to have the most impact. A finding, which was previously reported by a Norwegian study aimed at validating a short version of the HSOPSC questionnaire [33]. Actions aiming at improving safety culture are currently being defined and tested in health care [34, 35]. Culture being a multidimensional concept, it seems important to target the dimensions that have the most impact. In the literature, developing a non-punitive response to errors is described as an important area to focus on [4]. However, according to our ranking, it does not appear to be one of the most important dimensions, in spite of its being poorly developed in the surveyed units. In our study, three of the five considered dimensions that are perceived as being poorly developed have an important impact on safety culture. Dimensions to focus on in priority should be ‘Overall perceptions of safety’, ‘Hospital management support for patient safety’ and ‘Teamwork across hospital units'. Finally, the effect of items on their respective dimensions was quantified. A short version of the French HSOPSC questionnaire could be drawn up, by including the most important items only.

As a conclusion, a French language safety culture measuring tool has been tested. It has similar psychometrics properties as compared with those of other translation of the HSOPSC questionnaire. Since 2010, safety culture evaluation is one of the requirements of the French hospitals' accreditation program. In addition, the Ministry of health and the Haute Autorité de Santé (High Authority for Health) launched a research program to draw indicators from this questionnaire for accountability and public diffusion.

Confirmatory analyses showed that the dimensions measured by the French HSOPSC questionnaire do not all have the same impact on the safety culture of health care units. This finding is important for future research: it should guide the study of relationships between measured dimensions, safety culture and patient safety as well as help drawing up relevant interventions aiming at improving safety culture.

Supplementary material

Supplementary material is available at INTQHC online.


This work was supported by the Haute Autorité de Santé (National Authority for Health) [grant number CSR – PR n07–34]


Sandrine BERTHELOT, Hospital Nursing Administrator, Polyclinique de Bordeaux Tondu; Sophie ZAMARON, Director, Quality and Patient Safety Department, CHU de Bordeaux; Chantal PETIT, Quality and Patient Safety Manager, CHU de Bordeaux; Maryse LABEYRIE, Quality and Patient Safety Manager, Clinique Esquirol St Hilaire d'Agen; Catherine DELHAIE, Quality and Patient Safety Manager, Polyclinique de Navarre à Pau; Stéphanie CAZENAVE, Quality and Patient Safety Assistant Manager, Polyclinique de Navarre à Pau; Marie-Odile CAULIER, Hospital Nursing Administrator, CH d'Orthez; Véronique NOIRET, Quality and Patient Safety Manager, CH d'Orthez; Elisabeth ETCHEBERRY, Head Nurse, Polyclinique Aguiléra; Violaine LAPORTE, Quality and Patient Safety Assistant Manager, Polyclinique Aguiléra; Christine CADOT, Quality and Patient Safety Manager, CH d'Agen; Audrey LARRIVE, Quality and Patient Safety Secretary, CH d'Agen; Maryse PISCAREL, Secretary, CCECQA; Teachers of the Institute of Public Health, Epidemiology and Development (ISPED), Université Bordeaux 2.


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