Abstract
Background
In the international literature, several questionnaires measuring everyday activities are known with the aim of examining patients' quality of life. In the Hungarian language, few validated questionnaires focus on daily activities, examining both basic and moderately difficult physical activity, as well as mental health.
Objective
Our goal was to translate the Functional Status Questionnaire (FSQ) into Hungarian and examine its reliability and validity.
The validation of the questionnaire into Hungarian followed the six-step principle formulated in 2000. In our cross-sectional study, 376 participants took part. For convergent validity, we used the 36-Item Short Form Survey (SF-36) and the Functional Independence Measure (FIM) questionnaires. The examination of internal consistency was performed through Cronbach's alpha calculations. Test-retest reliability within the class was assessed with the intraclass correlation coefficient (ICC). We conducted discriminant validity for pain and general health.
Results
Internal consistency values demonstrated reliability. Participants' demographic data showed that the majority live in cities and have secondary education. The individuals included in the study exhibited unusually high levels of sports activity compared to the Hungarian average. Convergent validity examinations revealed significant relationships between dimensions of health-related quality of life of the different measurement tools.
Conclusions
The validated Hungarian questionnaire is valid and reliable. Similar to the original questionnaire, it is quickly and easily completed, allowing healthcare professionals in clinical settings to assess the patient's functional status before initiating examinations.
Introduction
The assessment of functional status and quality of life is a crucial factor in modern health science and clinical practice. Through the integration of objective and subjective measurement methods, researchers and healthcare professionals have the opportunity to conduct a detailed examination of their patients' physical, psychosocial, and cognitive status. The goal of these assessments is not only to document the current condition of patients but also to support the effectiveness of therapeutic interventions and patient-centered thinking [1]. Questionnaires measuring functional status play an important role in monitoring the effectiveness of therapeutic interventions. These tools allow clinicians to assess patients' abilities and limitations, thereby contributing to the development of personalized and effective treatments. Additionally, they provide opportunities for patients to actively participate in therapeutic processes and decision-making [2]. The assessment of quality of life adds another dimension to the evaluation of health status. Quality of life questionnaires not only capture patients' subjective experiences but also extend the evaluation of the functional status to various areas of life. Through this, researchers and professionals can better understand the daily life circumstances of patients, which can be crucial information in shaping healthcare policies and distributing healthcare resources more efficiently.
Nelson and colleagues demonstrated that patients and primary care physicians may perceive the patient's functional limitations differently [3].
In international practice, there are numerous questionnaires adapted into the Hungarian language for assessing functional status, physical activity, and related diseases, such as the Short Form 36 (SF-36) or the Rapid Assessment of Physical Activity (RAPA). However, there is a demand for further cultural and linguistic adaptation of questionnaires approaching the topic from different perspectives [4, 5].
The FSQ questionnaire was published in 1986 by Alan Jette and colleagues in the Journal of General Internal Medicine. The authors aimed to provide clinicians with a tool to easily and quickly recognize patients' non-obvious functional impairments. The validation was conducted at Boston and Los Angeles institutions, with a total of 1,153 participants. The questionnaire consists of several major units, each intended to assess the disability in a specific area related to functional status [6].
The FSQ measures physical activity, mental and social status, as well as the quality of individual social relationships, making it applicable in various fields. Besides its practical use, the questionnaire has been utilized in multiple research studies since its inception. Almost every year, studies are published where the FSQ is employed. Its versatility allows for application in research areas such as workplace productivity, targeted industry-specific functional status measurement, predicting future cognitive decline, or measuring the effectiveness of social support [7–10].
Saldanha and colleagues used the FSQ to examine the prevalence and functional status of individuals living with depression. The goal of the research was to provide professionals with a tool to easily screen individuals with mental illnesses, as depression is a significant public health issue. However, early detection of the condition reduces disability. The FSQ was applied as a screening tool alongside the Mini Mental State Examination (MMSE), which enabled them to filter out those 13% of the 2000 subjects in the study who required psychiatric treatment [7].
Hebling and colleagues used the FSQ with the aim of conducting a predictive analysis of cognitive decline. The study utilized brain data and clinical scores in the analysis, with one of the clinical scores being the FSQ result [8].
Fisher and colleagues employed the FSQ with cancer patients, alongside the Brief Pain Inventory test. The FSQ was used to screen participants based on their functional and mental abilities in a study that tested a model examining the relationship between social support and depressive symptoms through the mediating effects of fatigue and pain in women with breast cancer [9].
In addition to the above, almost every year, studies are published where the FSQ is employed. Its versatility allows for application in research areas such as workplace productivity, targeted industry-specific functional status measurement, predicting future cognitive decline, or measuring the effectiveness of social support [10].
The original English-language study included 1,153 participants from two locations in the United States. The questionnaire includes sub-scales for “basic activities of daily living,” “instrumental activities of daily living,” “mental health,” “physical functions,” and “quality of social interactions.” Reliability was measured through internal consistency analysis. The Cronbach's alpha values for the individual sub-scales were as follows: basic activities of daily living: 0.79; instrumental activities of daily living: 0.82; mental health: 0.81; physical functions: 0.65; quality of social interactions: 0.64.
Two methods were used to assess the validity of the FSQ: content validity and construct validity. Content validity is based on expert opinions, which determine how well the measurement reflects the content related to each functional dimension. For construct validation, Pearson product-moment correlation coefficients were used to evaluate univariate relationships between each FSQ scale score and seven variables that were shown or hypothesized to be related to function: age, number of bedridden days, number of days with limited activity, health satisfaction, role limitations, number of close friends, and frequency of social interactions. The measurements of bedridden days and days with limited activity were sourced from the National Health Interview Survey. The questions on role limitations were adapted from tools used in the Rand Health Insurance Study [6].
Our goal was to provide a valid and reliable Hungarian-language questionnaire for clinicians, therefore we conducted the adaptation and validation of the FSQ questionnaire from English to Hungarian.
Materials and methods
Participant selection and sample characteristics
Participants were recruited through non-random sampling. Inclusion criteria were as follows: 18 years or older, capacity to act, ability to perform daily activities without musculoskeletal limitations, voluntary participation, Hungarian native speakers, and involvement in primary care. A total of 369 individuals completed the questionnaire; however, we had to invalidate 2 responses as they were so incomplete that we could not use them in the statistical calculations. Therefore, our final sample size consisted of 367 completed questionnaires. Some participants completed the survey online, whereas approximately two-thirds were provided with on-site completion opportunities. It is important to note that for these invitations, we clearly communicated the inclusion criteria and requested that only those who met the criteria attend the completion sessions. This method proved to be successful, as no individuals who did not meet the inclusion criteria showed up during the three completion sessions. When determining the sample size, we adhered to the rule of 10 participants per item for exploratory analysis. The questionnaire was made available electronically, and navigation among participants was designed to minimize dropout rates [11, 12].
Validation process
The validation of the FSQ questionnaire was conducted following the six-step principle formulated by Beaton and colleagues. The procedure involved translation, synthesis, back-translation, pretesting, reliability testing, feedback, and finalization [13]. After obtaining approval from the original authors for translation and validation, two independent Hungarian translations were produced. One translator held a degree in English education and curriculum development (MA), whereas the other was a health science translator-interpreter with an MSc and a physiotherapist with a BSc. Twenty-six discrepancies were identified between the two translations, including cases of synonymous words and structural differences. A three-member committee reviewed all 26 differences and determined which translations would be included in the synthesis. The committee members include: 1 physical therapist, 1 PhD student working in the field of biomechanics, and 1 health science translator-interpreter with an MSc degree.
Translation discrepancies were typically limited to individual words, which were synonyms of one another, therefore in these cases, we chose the word that better fit the context. In some cases, differences in meaning arose during the translation process. We examined the original author's intent behind the question and selected the expression that better conveyed that intent. In cases where the discrepancies involved synonyms, but beyond fitting into the context, it was also important to consider which term would be better understood or accepted by native Hungarian patients, we made our decisions by analyzing the wording of various Hungarian-language or Hungarian-validated questionnaires. During the translation process, we did not encounter any expressions that were incomprehensible in Hungarian or within Hungarian culture.
Pretesting involved 30 individuals aged 18 and above. The questionnaire was completed in electronic form. For displaying the questions and answer options, we used the same approach that was later applied in the final version of the questionnaire. After reading the information and accepting the data handling policies, participants were able to begin filling out the questionnaire. Since only one formal suggestion was made during pretesting, and participants did not otherwise propose changes, the questionnaire as configured during this phase became the final version.
Ethical considerations of the research
The description of the validation of the questionnaire's validity and reliability was conducted based on the COSMIN guidelines [14]. Prior to completing the questionnaire, participants received detailed information about the process of filling it out and data handling, and gave their consent to the processing of the data they provided. The study was approved by the Regional Research Ethics Committee of the University of Pécs, Faculty of Health Sciences, and was registered under file number 9114-PTE 2022.
Introduction of measurement instruments
Our questionnaire consisted of four main parts. The self-designed basic data questionnaire collected demographic information, including gender, age, type of residence, sports activities, height, weight, current or past illnesses, surgeries, and medication.
Functional status questionnaire (FSQ) questionnaire
In the second part, participants completed the FSQ questionnaire translated by us. Following the translation, we retained the original English structure of the questionnaire. Thus, the questionnaire consists of five major units, each measuring the disability in a specific area related to functional status. The response options are diversified, and the scoring is not straightforward. At the end of the questionnaire, participants receive six scores for the six question groups, classifying the individual areas into the “warning zone” or “appropriate result” categories along different thresholds. Scores for individual areas can range from 0 to 100. The entire questionnaire comprises 34 questions and can be completed in 15 min. The questionnaire includes sub-scales for “basic activities of daily living,” “instrumental activities of daily living,” “mental health,” “psychical functions,” and “quality of social interactions” [6].
Functional Independence Measure (FIM) questionnaire
In the third part, participants were required to complete the FIM questionnaire as the first external validation questionnaire. The Functional Independence Measure is an assessment tool developed to measure patients' functional independence. The FIM was developed between 1984 and 1987 by a national task force sponsored by the American Academy of Physical Medicine and Rehabilitation and the American Congress of Rehabilitation Medicine, and it was published by Keith, Granger, Hamilton, and Sherwin in 1987. The FIM questionnaire assesses patients' performance in various areas such as self-care, mobility, and social skills. The scale comprises 18 different items, each related to a specific functional area. Based on the responses, patients receive a score reflecting the degree of their independence. The FIM is widely used in the field of rehabilitation and has undergone multiple validation studies to ensure its reliability and validity. The questionnaire has been translated into multiple languages, making it suitable for international research [15].
SF-36 questionnaire
The final part involved completing the second external validation questionnaire, the SF-36. The SF-36 (Short Form 36) is a self-report questionnaire developed to measure patients' quality of life and health status. The questionnaire was developed by the RAND Corporation, a nonprofit research institute, in the 1980s. Due to its popularity and widespread use, the SF-36 is available in multiple translations in many countries. The questionnaire consists of 36 questions related to various health-related dimensions, such as physical functional capacity, pain, mental health, and social roles. Based on the responses, the SF-36 generates various indices, providing a comprehensive overview of the patient's quality of life. The SF-36 is widely used in clinical research, healthcare assessment, and health policy planning. It has undergone multiple validation studies to ensure its reliability and validity. Its goal is to measure patients' health status in a standardized and reliable manner, contributing to the evaluation of the effectiveness of therapies [16, 17].
Statistical analysis
Data were compiled using Mac Excel 2019 and IBM SPSS 28.0 software, and statistical analyses were conducted using the same software. To test the adequacy of sample size for factor analysis, the Kaiser–Meyer Olkin (KMO) (recommended KMO≥0.60) coefficient was calculated, and the Bartlett test of sphericity (significance level lower than P < 0.05) was added to ascertain whether the items complied the prerequisites for factor analysis were correlated. Factor analysis was based on principal component analysis with the varimax rotation method [18].
We performed internal consistency assessment using Cronbach's alpha value, considering results above 0.7 as acceptable. Tukey's test of additivity was significant (P < 0.001).
Content validity was tested using Davis's CVI indexes (item and scale level content validity). In general, the content validity of a scale is considered good when S-CVI/Ave ≥ 0.90 and I-CVI ≥ 0.78. All three experts evaluated the questionnaire items between scores of 1–4 (1 = item is irrelevant; 4 item is efficient) [19].
In the latter case, based on Czimbalmos et al.'s study, we divided the total sample into two subsamples concerning general health and pain [5]. Mann-Whitney U test, Wilcoxon W test, and Z-test were employed for both variables. Results were considered significant at P < 0.05. A retest was conducted with 30 individuals one month after the initial completion for test-retest reliability, and intraclass correlation coefficient (ICC) was calculated within the sample.
Results
Regarding demographic data, nearly two-thirds of respondents were male, and over 95% resided in urban areas. The majority had completed secondary education. We examined data related to their sports activities, revealing that participants engaged in significantly more sports compared to the Hungarian average. According to 2019 Hungarian Central Statistical Office (KSH) data, 59% of the Hungarian population does not engage in any sports during their leisure time, whereas only 7.4% of questionnaire respondents stated no physical activity [20]. The average age of respondents was 42.5 years. Specific values for demographic data are illustrated in Table 1. Internal consistency, as measured by Cronbach's alpha, ranged from 0.786 to 0.958, indicating strong reliability. Detailed data on internal consistency and test-retest reliability are presented in Table 2. Table 3 demonstrates convergent validity among various dimensions of life quality assessed by the SF-36 questionnaire. The general statistical data are summarized in Table 4.
Results of demographic data collection
| n | % | |
| Sex | ||
| Female: n, % | 234 | 63.8 |
| Residence | ||
| Capital | 69 | 18.9 |
| County seat | 126 | 34.4 |
| Other city | 156 | 42.6 |
| Other Municipality | 15 | 4.1 |
| Physical Activity | ||
| Professional Athlete | 44 | 12.1 |
| Amateur Athlete | 110 | 30.1 |
| Actively Engaged in Sports - at least 4 times a week, more than 1 h each time | 107 | 29.3 |
| Infrequently Engaged in Sports - 1–3 times a week, about 1 h each time | 77 | 21.1 |
| Sedentary Lifestyle | 19 | 5.2 |
| Sedentary Lifestyle Due to Health Reasons | 8 | 2.2 |
| Highest Level of Education | ||
| Less than 8th grade | 9 | 2.5 |
| 8th grade | 45 | 12.3 |
| Secondary school without graduation, vocational certificate | 41 | 11.2 |
| Secondary school with graduation | 126 | 34.4 |
| Vocational graduation | 49 | 13.4 |
| Secondary vocational qualification based on graduation | 11 | 3.0 |
| Higher vocational qualification | 62 | 16.9 |
| University, graduate education (MA/MSc) | 22 | 6.0 |
| Doctoral (PhD or DLA) degree | 1 | 0.3 |
Results of internal consistency testing and test-retest examination
| Group of questions | Cronbach's Alpha | Hotelling T2 | Tukey's test for no additivity (F, P) | N of items | ICC average measures | IC 95% | |
| BADL | 0.942 | 0.003 | 17.315 | <0.001 | 3 | 1.000 | – |
| IADL | 0.911 | ≤0.001 | 11.858 | <0.001 | 6 | 1.000 | – |
| Mental health | 0.786 | ≤0.001 | 0.568 | 0.451 | 3 | 0.993 | 0.985–0.997 |
| Psychical functions | 0.958 | ≤0.001 | 1.793 | 0.181 | 6 | 0.996 | 0.992–0.998 |
| Social activities | 0.853 | ≤0.001 | 52.087 | <0.001 | 3 | 0.952 | 0.894–0.978 |
| Quality of social interactions | 0.790 | ≤0.001 | 0.763 | 0.383 | 3 | 0.952 | 0.878–0.979 |
Results of convergent validity
| BADL | IADL | MH | PF | SA | QofSI | ||
| Physical function | r | 0.614 | 0.596 | 0.156 | 0.107 | 0.552 | 0.315 |
| P | <0.001 | <0.001 | 0.001 | 0.034 | <0.001 | <0.001 | |
| Role limitations due to physical health | r | 0.007 | 0.136 | 0.082 | 0.341 | 0.087 | 0.087 |
| P | 0.889 | 0.005 | 0.091 | <0.001 | 0.073 | 0.073 | |
| Role limitations due to emotional problems | r | −0.119 | −0.036 | 0.135 | 0.251 | −0.024 | 0.069 |
| P | 0.014 | 0.464 | 0.005 | <0.001 | 0.629 | 0.153 | |
| Energy/fatigue | r | 0.049 | 0.029 | 0.745 | 0.166 | 0.100 | 0.520 |
| P | 0.317 | 0.551 | <0.001 | 0.001 | 0.040 | <0.001 | |
| Emotional well-being | r | 0.037 | 0.039 | 0.788 | 0.164 | 0.086 | 0.550 |
| P | 0.446 | 0.428 | <0.001 | 0.001 | 0.077 | <0.001 | |
| Social functioning | r | −0.069 | 0.035 | 0.200 | 0.105 | −0.039 | 0.076 |
| P | 0.160 | 0.477 | <0.001 | 0.037 | 0.423 | 0.118 | |
| Pain | r | 0.010 | 0.146 | 0.167 | 0.087 | 0.141 | 0.035 |
| P | 0.842 | 0.003 | 0.001 | 0.085 | 0.004 | 0.474 | |
| General health | r | 0.335 | 0.366 | 0.228 | 0.127 | 0.270 | 0.360 |
| P | <0.001 | <0.001 | <0.001 | 0.011 | <0.001 | <0.001 | |
| FIM | r | −0.051 | 0.016 | 0.042 | 0.062 | −0.002 | −0.017 |
| P | 0.329 | 0.765 | 0.426 | 0.257 | 0.974 | 0.742 |
General statistical results
| Mean | Median | SD | Percentiles 25 | Percentiles 75 | Skewness | Kurtosis | |
| BASIC ADL | 92.76 | 100.00 | 16.65 | 100.00 | 100.00 | −2.48 | 5.40 |
| IADL | 88.82 | 100.00 | 18.90 | 88.89 | 100.00 | −1.85 | 2.41 |
| MH | 62.43 | 73.33 | 23.43 | 46.67 | 80.00 | −1.14 | 0.59 |
| PF | 79.41 | 83.33 | 23.00 | 66.67 | 100.00 | −1.54 | 2.39 |
| SA | 91.08 | 100.00 | 17.54 | 88.89 | 100.00 | −1.20 | 3.17 |
| QofSI | 70.20 | 80.00 | 24.51 | 66.67 | 86.67 | −1.38 | 1.50 |
| Mean | Median | SD | Percentiles 25 | Percentiles 75 | Skewness | Kurtosis | |
| BASIC ADL | 92.76 | 100.00 | 16.65 | 100.00 | 100.00 | −2.48 | 5.40 |
| IADL | 88.82 | 100.00 | 18.90 | 88.89 | 100.00 | −1.85 | 2.41 |
| MH | 62.43 | 73.33 | 23.43 | 46.67 | 80.00 | −1.14 | 0.59 |
| PF | 79.41 | 83.33 | 23.00 | 66.67 | 100.00 | −1.54 | 2.39 |
| SA | 91.08 | 100.00 | 17.54 | 88.89 | 100.00 | −1.20 | 3.17 |
| QofSI | 70.20 | 80.00 | 24.51 | 66.67 | 86.67 | −1.38 | 1.50 |
Structural validity was measured by factor analysis, where the KMO value and Barlett's test of sphericity of (P < 0.001) showed that the sample is adequate for factor analysis.
Structural validity was analysed using two dimensions and 11 entries of the original scale, with a scale KMO value of 0.848 and Bartlett's test of sphericity of P < 0.001. The cumulative variance contribution is 82.388% (factor 1 = 28.915%, factor 2 = 20.420%, factor 3 = 14.932%, factor 4 = 8.545, factor 5 = 6.392). The communalities of the items were between 0.607 and 0.889.
Correlations between SF-36 Physical Function and FSQ basic activities of daily living (BADL), instrumental activities of daily living (IADL), mental health (MH), social activity (SA), quality of social interactions (QofSI), and psychical functions (PF) dimensions are significant (0.107 ≤ r ≤ 0.614), generally exhibiting higher values, except for the MH and PF dimensions, where the correlation is lower. Significant correlations are observed between Role Limitations due to Physical Health and IADL, PF, and QofSI dimensions (0.087 ≤ r ≤ 0.341), with lower correlation values. Emotional Problems and BADL, MH, and PF dimensions exhibit significant correlations (0.119 ≤ r ≤ 0.251), with lower correlation values. Energy/Fatigue and MH, PF, SA, and QofSI dimensions show significant correlations (0.1 ≤ r ≤ 0.745), with higher values in MH and QofSI dimensions. Emotional Well-being and MH, PF, and QofSI dimensions display significant correlations (0.164 ≤ r ≤ 0.788), with higher values in MH and QofSI dimensions. Social Functioning and MH, PF dimensions have significant correlations (0.105 ≤ r ≤ 0.200). Pain and IADL, MH, and SA dimensions show significant correlations (0.141 ≤ r ≤ 0.167). General Health exhibits significant correlations with all dimensions (0.127 ≤ r ≤ 0.366).
For the FIM, no significant relationship was observed with the FSQ questionnaire for any dimension: P > 0.05. Tables 5–6 reflects discriminant validity among dimensions assessing life quality. Notable differences exist between the presence of pain and dimensions of life quality. Based on statistically significant results, the group without pain consistently exhibits higher average values in every life quality dimension. The absence of pain is significantly correlated with various aspects of life quality, supported by the higher average values in both groups. Therefore, the impact of pain on different dimensions of life quality may be substantial, as confirmed by statistically validated results.
Discriminant validity regarding pain
| pain | BADL | IADL | MH | PF | SA | QofSI | |
| be unwell | Mean | 91.88 | 85.97 | 58.38 | 79.31 | 87.28 | 69.92 |
| N | 115.00 | 115.00 | 119.00 | 110.00 | 114.00 | 119.00 | |
| Std. Deviation | 18.40 | 20.55 | 22.35 | 20.20 | 20.07 | 23.92 | |
| feel good | Mean | 93.09 | 89.89 | 64.00 | 79.45 | 92.49 | 70.31 |
| N | 307.00 | 307.00 | 307.00 | 286.00 | 307.00 | 307.00 | |
| Std. Deviation | 15.97 | 18.16 | 23.68 | 24.02 | 16.31 | 24.78 | |
| Total | Mean | 92.76 | 88.82 | 62.43 | 79.41 | 91.08 | 70.20 |
| N | 422.00 | 422.00 | 426.00 | 396.00 | 421.00 | 426.00 | |
| Std. Deviation | 16.65 | 18.90 | 23.43 | 23.00 | 17.54 | 24.51 | |
| P | 0.495 | 0.001 | 0.001 | 0.254 | 0.003 | 0.600 | |
Discriminant validity regarding general health
| general health | BADL | IADL | MH | PF | SA | QofSI | |
| 0.00 | Mean | 88.37 | 83.08 | 57.39 | 77.22 | 86.24 | 63.40 |
| N | 193.00 | 193.00 | 194.00 | 185.00 | 191.00 | 194.00 | |
| Std. Deviation | 20.17 | 22.25 | 25.43 | 24.58 | 20.89 | 26.15 | |
| 1.00 | Mean | 96.46 | 93.66 | 66.64 | 81.33 | 95.10 | 75.89 |
| N | 229.00 | 229.00 | 232.00 | 211.00 | 230.00 | 232.00 | |
| Std. Deviation | 11.81 | 13.84 | 20.75 | 21.40 | 12.91 | 21.52 | |
| Total | Mean | 92.76 | 88.82 | 62.43 | 79.41 | 91.08 | 70.20 |
| N | 422.00 | 422.00 | 426.00 | 396.00 | 421.00 | 426.00 | |
| Std. Deviation | 16.65 | 18.90 | 23.43 | 23.00 | 17.54 | 24.51 | |
| P | <0.001 | <0.001 | <0.001 | 0.211 | <0.001 | <0.001 | |
Table 5 illustrates discriminant validity between dimensions assessing life quality and overall health status. Changes in overall health significantly affect various dimensions of life quality. When the “generalhealth” variable is 0, the BADL, IADL, MH, PF, SA, and QofSI dimensions show significantly lower average values, contrasting with the “generalhealth” value of 1, where average scores are higher. The data statistically support that improvements in overall health are closely associated with more positive life quality across all assessment dimensions. The “generalhealth” variable significantly influences overall life quality, providing substantive information about the depth of the relationship between overall health status and life quality. Based on quantified results, positive changes in overall health are clearly linked to positive changes in various life quality dimensions.
Discussion
In our study, we were able to examine 367 valid responses, compared to the original English-language study, which analysed data from 1,153 participants—significantly more than the number we produced. However, we adhered to the rule of 10 participants per item for exploratory analysis. The original questionnaire's respondents ranged in age from 19 to 96, with 60% of them being 60 years old or older. Approximately 75% of them were women. About 11% had completed a maximum of 8 years of elementary school, whereas 30% had attended college. The original questionnaire also inquired about marital status, with 45% of the respondents being married. During the Hungarian-language validation, we considered participants' attitudes toward sports to be important, as the questionnaire also asks about daily activity patterns.
The aim of the study was to perform the Hungarian adaptation and validation of the FSQ questionnaire originally in English. The questionnaire had been translated into several languages before, and validation had also been conducted [21]. To develop the Hungarian version, 367 individuals were involved. The results of the questionnaire indicated adequate internal consistency, and convergent validity showed significant associations between dimensions assessing life quality. Positive changes in overall health were closely related to more positive life quality in every dimension. These results support the reliability and validity of the examined tool, emphasizing the importance of relationships between life quality and functional states in health science research and clinical practice.
We endeavoured to compose a sample with a similar composition to that of the original English questionnaire respondents. The English version presented the population in a summary manner, and accordingly, we attempted to include participants. The authors note that 60% of English questionnaire respondents were over 60 years old, and 75% were female. Our respondents had a lower average age, 42.47 years, with a standard deviation of 18.16. The gender distribution was also slightly lower for females, at 63.8%. Regarding education, we obtained similar results. In the English version, 11% reported completing a maximum of 8 years of elementary school, while in our case, this was 14.7%. Hungarian participants reported fewer individuals with higher education, only 23.2%, compared to the 30% indicated in the English version, although the English version does not distinguish between participation in college education and its completion. The original questionnaire's internal consistency reliability ranged between 0.64 and 0.82; in our case, it was 0.78–0.95.
In the original English-language questionnaire, only the sub-scales for basic activities of daily living (0.79), instrumental activities of daily living (0.82), and mental health (0.81) showed such high internal consistency. For the psychical functions and quality of social interactions sub-scales, the Cronbach's alpha values were 0.65 and 0.64, respectively.
In the study by Saldanha and colleagues, where the FSQ was also utilized, the average age was 34.35 years, and the population studied had nearly twice as many men as women. This study focused on patients suffering from depression, making it understandable that the majority of the population fell into the warning zone. In the BADL and IADL categories, 99.4%, in the psychological category, 81.6%, in the role category, 95.8%, and in the social category, 95% of participants were in the warning zone. The data on physical activity are surprising, although the study does not elaborate on the physical condition of the individuals. Regarding the statistical data related to the measurement tools, it was concluded that Spearman's rho showed a positive correlation between age and AEQ, PHQ, the physical category, the psychological category, and the MMSE, and a negative correlation with the role and social categories. Additionally, the Mann–Whitney U-test revealed significant differences in all variables (AEQ, FSQ scores, and MMSE) when comparing patients without depression and those with mild depression [7].
In the 2023 study by Merwin and Brotto, a single patient was examined in relation to the psychological treatment of genitopelvic dysesthesia. The patient was a 58-year-old woman who sought medical attention due to experiencing nervous system symptoms during the COVID-19 pandemic. During the treatment, the patient completed self-report questionnaires that measured depressive and anxiety symptoms, and she also filled out the FSQ to assess her quality of life. She completed the questionnaire three times during the treatment, in the 8th, 10th, and 13th weeks. The treatment consisted of 11 sessions, which used cognitive and dialectical behavior therapy, as well as exercises for anxiety tolerance and emotion regulation skills. By the end of the treatment, improvements or stagnation were observed across all FSQ subscales, with a significant improvement in the patient's IADL Mental Health score. Meanwhile, her scores on the Beck Depression Inventory and Beck Anxiety Inventory, which measure depressive and anxiety symptoms, continuously decreased, indicating a reduction in symptoms. This study illustrates well how the FSQ can be used in conjunction with other tests as a means of reinforcement [22].
In the 2022 study by Du and colleagues, an exercise program was developed for older Latino individuals that combined physical and mental exercise. Thirteen participants were involved in the study, with an average age of 76.4 years and a female proportion of 92%. These figures differ significantly from our sample, but the goal of this study was to examine elderly individuals. To measure the effectiveness of the program, several instrumental assessments and questionnaires were used, including the FSQ. No significant improvement was observed in FSQ scores. At the start of the study, the average FSQ total score was 29.31, the midtest average was 30.23, and the posttest average was 29.58. In contrast, based on instrumental assessments, the researchers concluded that the exercise program was useful in promoting physical activity. The values from the Exercise-Induced Feeling Inventory test increased, and the participants' physical endurance improved. The fact that FSQ scores did not show a significant increase highlights that the FSQ is a complex questionnaire that measures not only self-assessed physical activity but also the overall functional status of individuals [23].
Limitations of the study
It is important to note that the original questionnaire's results were published in 1986, indicating that the surveys were conducted in that year or the preceding one. Therefore, in the more than 35 years since then, numerous factors have influenced people's daily lives, impacting healthcare practices, health consciousness, rehabilitation, and other areas determining people's life quality. Changes during this period may contribute to differences between the results of the two test versions.
Since our goal was not to study the population but to adapt, validate, and assess the reliability of the FSQ in Hungarian, we paid less attention to sample heterogeneity and instead focused on analyzing statistically significant results relevant to validation. As the main task was to test the measurement tool rather than to track patient progress, the interval between the test and retest was only 30 days. This interval was determined after analyzing other Hungarian studies related to validation. A longer interval between the test and retest would likely have resulted in worse ICC values.
Additionally, it should be noted that the sample predominantly consisted of men (63.8%) and individuals living in urban areas, which may not fully reflect the diversity of the Hungarian population. A more balanced sample in terms of gender and residence type would have strengthened the external validity of the results. The non-random sampling and high proportion of physically active urban participants could limit the generalizability of the findings.
Conclusions
The Hungarian version of the questionnaire is suitable for serving the purpose of the original English version's authors, quickly and reliably assessing a patient's physical functional and mental state, even before the first personal consultation. It is important to highlight that the questionnaire distinguishes whether the patient cannot perform an action due to health reasons or other reasons, a distinction not made by questionnaires such as SF-36 or EQ-5D.
Conflict of interest statement
Mr. Zsenák reports grants from Hungarian National Research, Development and Innovation Office, during the conduct of the study; grants from Hungarian National Research, Development and Innovation Office, outside the submitted work. Dr. Járomi reports grants from Hungarian National Research, Development and Innovation Office, during the conduct of the study; grants from Hungarian National Research, Development and Innovation Office, outside the submitted work. Dr. Makai has nothing to disclose.
Acknowledgement
The research was conducted within the framework of the KDP2020 (Hungarian National Research, Development and Innovation Office) grant.
References
- 1.↑
Safdar N, Abbo LM, Knobloch MJ, Seo SK. Research methods in healthcare epidemiology: survey and qualitative research. Infect Control Hosp Epidemiol 2016; 37(11): 1272–7. https://doi.org/10.1017/ice.2016.171.
- 2.↑
Grotle M, Brox JI, Vøllestad NK. Functional status and disability questionnaires: what do they assess? A systematic review of back-specific outcome questionnaires. Spine (Phila Pa 1976) 2005; 30(1): 130–40. https://doi.org/10.1097/01.brs.0000149184.16509.73.
- 3.↑
Nelson E, Conger B, Douglass R, Gephart D, Kirk J, Page R, et al. Functional health status levels of primary care patients. JAMA 1983; 249(24): 3331–8. https://doi.org/10.1001/jama.1983.03330480037027.
- 4.↑
Miszory EV, Makai A, Pakai A, Jaromi M. Cross-cultural adaptation and validation of the rapid assessment of physical activity questionnaire (RAPA) in Hungarian elderly over 50 years. BMC Sports Sci Med Rehabil 2022; 14(1): 131. https://doi.org/10.1186/s13102-022-00512-3.
- 5.↑
Czimbalmos Á, Nagy Z, Varga Z, Husztik P. Patient satisfaction survey using the SF-36 questionnaire and determination of normal values in Hungary [Hungarian]. Népegészségügy 1999; 80(1): 4–19.
- 6.↑
Jette AM, Davies AR, Cleary PD, Calkins DR, Rubenstein LV, Fink A, et al. The functional status questionnaire: reliability and validity when used in primary care. J Gen Intern Med 1986; 1(3): 143–9. https://doi.org/10.1007/BF02602324.
- 7.↑
Saldanha D, Mujawar S, Chaudhury S, Banerjee A. A community-based study of prevalence and functional status of major depressive disorder in an industrial area. Ind Psychiatry J 2021; 30(1): 96–101. https://doi.org/10.4103/ipj.ipj_2_21.
- 8.↑
Hebling Vieira B, Liem F, Dadi K, Engemann DA, Gramfort A, Bellec P, et al. Predicting future cognitive decline from non-brain and multimodal brain imaging data in healthy and pathological aging. Neurobiol Aging 2022; 118: 55–65. https://doi.org/10.1016/j.neurobiolaging.2022.06.008.
- 9.↑
Fisher HM, Winger JG, Miller SN, Wright AN, Plumb Vilardaga JC, Majestic C, et al. Relationship between social support, physical symptoms, and depression in women with breast cancer and pain. Support Care Cancer 2021; 29(9): 5513–21. https://doi.org/10.1007/s00520-021-06136-6.
- 10.↑
de Oliveira C, Saka M, Bone L, Jacobs R. The role of mental health on workplace productivity: a critical review of the literature. Appl Health Econ Health Policy 2023; 21(2): 167–93. https://doi.org/10.1007/s40258-022-00761-w.
- 11.↑
Edwards PJ, Roberts I, Clarke MJ, Diguiseppi C, Wentz R, Kwan I, et al. Methods to increase response to postal and electronic questionnaires. Cochrane Database Syst Rev 2009; 2009(3): MR000008. https://doi.org/10.1002/14651858.MR000008.pub4.
- 12.↑
Edwards P. Questionnaires in clinical trials: guidelines for optimal design and administration. Trials 2010; 11: 2. https://doi.org/10.1186/1745-6215-11-2.
- 13.↑
Beaton DE, Bombardier C, Guillemin F, Ferraz MB. Guidelines for the process of cross-cultural adaptation of self-report measures. Spine (Phila Pa 1976) 2000; 25(24): 3186–91. https://doi.org/10.1097/00007632-200012150-00014.
- 14.↑
Mokkink LB, Terwee CB, Patrick DL, Alonso J, Stratford PW, Knol DL, et al. The COSMIN checklist for assessing the methodological quality of studies on measurement properties of health status measurement instruments: an international Delphi study. Qual Life Res 2010; 19(4): 539–49. https://doi.org/10.1007/s11136-010-9606-8.
- 15.↑
Keith RA, Granger CV, Hamilton BB, Sherwin FS. The functional independence measure: a new tool for rehabilitation. Adv Clin Rehabil 1987; 1: 6–18.
- 16.↑
Hays RD, Sherbourne CD, Mazel RM. The RAND 36-item health survey 1.0. Health Econ 1993; 2(3): 217–27. https://doi.org/10.1002/hec.4730020305.
- 17.↑
Rannou F, Poiraudeau S, Berezne A, Baubet T, Le-Guern V, Cabane J, et al. Assessing disability and quality of life in systemic sclerosis: construct validities of the Cochin hand function scale, health assessment questionnaire (HAQ), systemic sclerosis HAQ, and medical outcomes study 36-item short form health survey. Arthritis Rheum 2007; 57(1): 94–102. https://doi.org/10.1002/art.22468.
- 18.↑
Nájera P, Abad FJ, Sorrel MA. Is exploratory factor analysis always to be preferred? A systematic comparison of factor analytic techniques throughout the confirmatory-exploratory continuum. Psychol Methods 2023. Advance online publication. https://doi.org/10.1037/met0000579.
- 19.↑
Crestani AH, Moraes AB, Souza APR. Content validation: clarity/relevance, reliability and internal consistency of enunciative signs of language acquisition. Codas 2017; 29(4): e20160180. https://doi.org/10.1590/2317-1782/201720160180.
- 20.↑
Hungarian Central Statistical Office. Exercise [Hungarian]; 2019 [cited 2024. 01.10.]. Available from: https://www.ksh.hu/docs/hun/xftp/idoszaki/elef/testmozgas_2019/index.html#footnote-1.
- 21.↑
Riphah International University. Cross cultural adaptation of functional status questionnaire in Urdu language in CABG patients; 2022. [updated 2022. 04.21.; cited 2024. 01.10.]. Available from: https://ichgcp.net/clinical-trials-registry/NCT05023083.
- 22.↑
Merwin KE, Brotto LA. Psychological treatment of persistent genital arousal disorder/genitopelvic dysesthesia using an integrative approach. Arch Sex Behav 2023; 52(5): 2249–60. https://doi.org/10.1007/s10508-023-02617-3.
- 23.↑
Du Y, Patel N, Hernandez A, Zamudio-Samano M, Li S, Zhang T, et al. Examining the delivery of a tailored Chinese mind-body exercise to low-income community-dwelling older Latino individuals for healthy aging: feasibility and acceptability study. JMIR Form Res 2022; 6(9): e40046. https://doi.org/10.2196/40046.
