Abstract
Objective
Hair plays multiple biological, psychosocial, and cultural roles, impacting psychological well-being and contributing to a rapidly expanding hair care market. This study aimed to validate a questionnaire assessing hair health and care (HHCQ) among young adults.
Results
A total of 200 participants completed the questionnaire (mean age = 20.75 years). Item screening and content validation reduced the initial 46 items to 32. No items were removed following face validation, which relied on a qualitative pilot study. Exploratory factor analysis yielded two factors for knowledge (knowledge about routine hair hygiene and care, and knowledge about hair products and procedures) and one factor for attitudes (attitudes toward hair care). The knowledge and attitude factors accounted for 50.3% and 50.6% of the explained variance, respectively. Confirmatory factor analysis revealed that the model was acceptable (CFI = 0.955, TLI = 0.991, RMSEA = 0.077, and SRMR = 0.060). Test-retest reliability showed excellent Intraclass Correlation Coefficients, and Cronbach’s alpha coefficients were acceptable. Practice items were treated as a formative index, obviating the need for factor or internal consistency analyses. While the 32-item HHCQ showed basic evidence of validation and reliability, it should be culturally adapted to different settings with additional validation. The questionnaire can be used to guide public health campaigns, policymaking, and clinical practice.
Supplementary Information
The online version contains supplementary material available at https://doi.org/10.1186/s13104-026-07944-x.
Keywords: Hair, Hair growth, Hair treatment, Hair care, Scalp, Trichology
Introduction
As part of the integumentary system, hair has thermoregulatory, protective, tactile, and sensory functions, and contributes to the dispersion of sebum, sweat, and pheromones [1, 2]. Additionally, it plays an essential psychosocial role due to its aesthetic value, influencing notions of attractiveness, self-esteem, and body image [3]. Because of this influence, hair carries cultural implications, especially since it can be manipulated to accommodate prevailing cultural and fashion ideals [4]. These values have created an enormous market for hair care products and services.
The appearance and health of hair are affected by a variety of genetic, epigenetic, biological, environmental, and behavioral factors [5–8]. Poor hair care practices and lifestyle habits can lead to hair damage, loss, and diseases [9]. Clinically, hair care is essential for maintaining patient hygiene, improving self-esteem, and preventing relevant complications [10].
However, the few studies that have assessed knowledge, attitudes, and practices (KAP) related to hair care developed and used questionnaires without validation. This might have introduced considerable methodological limitations that challenge their academic utility and wider application [11–16]. This study aimed to develop and validate a questionnaire assessing KAP regarding hair care among Arabic-speaking young adults.
Methods
Study design and sampling
This validation study was conducted from March to September 2024 in the Palestinian West Bank. The development and validation of the Hair Health and Care Questionnaire (HHCQ) included item generation and screening; assessment of content, face, and construct validity; and internal consistency and test-retest reliability (Fig. 1). All university students aged 17 years or older were eligible to participate and were sampled using convenience sampling. A sample size of 200 was selected for validation, as determined by Guilford [17]. The development and validation were guided by the consensus-based standards for the selection of health measurement instruments (COSMIN) [18].
Fig. 1.
Flowchart illustrating the phases of questionnaire development and validation
Item generation
A literature review was conducted to gather evidence-based information and explore related questionnaires. The search strategy incorporated the following major keywords and their equivalences: hair, shampoo, conditioner, knowledge, literacy, understanding, attitude, perception, belief, practice, and behavior. After duplicate removal and abstract and full-text screening, 10 out of 338 relevant articles were retrieved (Supplementary File 1). These questionnaires were nonvalidated, culture-specific, or relied on anecdotal evidence, with methodological limitations in item phrasing or development, or a narrow focus on a particular topic, such as hair styling [11–16, 19–22]. A framework of the three domains (hair washing; hair products and procedures; and general hair care) was developed based on expert interviews and a literature review.
The knowledge section was structured using a true-or-false format, with scores calculated by assigning one point for each correct answer and summing the total points. The attitudes section comprised items with evaluative and affective components, measured on a three-point scale: agree, disagree, or neutral. To capture the full range of responses, a score of 3 was given to ‘agree’ responses, 2 to ‘neutral,’ and 1 to ‘disagree.’ Total attitude scores were calculated by summing the scores of individual items [23]. Practice items were conceptualized as a formative index using the same framework-based categories. Each practice item represents an independent action in real life, contributing separately to adherence to hair care practices [24–27]. For example, a participant may engage in frequent hair washing without necessarily adopting other practices such as using suitable hair care products. Therefore, factor analysis is not methodologically appropriate because such formative items are composite actions that collectively define the construct, unlike reflective items, which are caused by a latent construct and expected to correlate. Based on evidence-based guidelines, practice items were scored on a scale from 0 to 2 points, where higher scores indicate superior practice, except for one item that was assigned a score of either 1 or 2. Two items related to using home remedies were collected for descriptive purposes. The final score is calculated by summing the scores of the 11 items and ranges from 1 to 22. More details on the scoring rubrics are provided in Supplementary File 2.
Content and face validity
Content validity was assessed by eight experts in dermatology, cosmetology, and clinical pharmacy using a content validity form that evaluated the relevance of each item to its corresponding domain [28]. The items were rated on a 4-point scale (1 as irrelevant to 4 as highly relevant), with a low validity score (1–2) reported as 0 and an acceptable validity score (3–4) reported as 1 [29, 30]. The content validity index for an item (I-CVI) was calculated as the proportion of experts assigning an acceptable score to each item, with a minimal acceptable value of 0.83 [30]. The scale CVI (S-CVI/average) was calculated as the arithmetic mean of the I-CVI values across all the items, with a minimal acceptable value of 0.8 [31]. Then, face validity was evaluated through a pilot study with 35 participants [32].
Construct validity
Factor analyses were applied to knowledge and attitudes scales. However, the practices section was excluded as its items are formative, composite indicators that lack item correlation and do not theoretically represent a single latent construct [33, 34]. An exploratory factor analysis (EFA) with principal axis factoring and varimax rotation were conducted. Kaiser–Meyer–Olkin (KMO) (> 0.6) and Bartlett’s test of sphericity (p < 0.001) were used to confirm sampling adequacy [35, 36]. The number of meaningful factors and the eigenvalues were determined via latent root criterion and visual inspection of the Cattell’s scree plot [37, 38]. Items with factor loadings less than 0.3 were removed [39]. Oblique Promax rotation was first conducted to attain a simpler structure. If the factor correlation was 0.32 or greater, oblique Promax rotation is warranted. Otherwise, the lack of adequate interfactor overlap justifies the use of orthogonal varimax rotation [40]. Confirmatory factor analysis (CFA) was subsequently performed, with the following thresholds of the fit indices: Comparative Fit Index (CFI) ≥ 0.9; Tucker Lewis Index (TLI) ≥ 0.9; Root Mean Square Error of Approximation (RMSEA) ≤ 0.08; and Standardized Root Mean Square Residual (SRMR) ≤ 0.09 [40–42].
Reliability
Internal consistency was tested via Cronbach’s alpha coefficient for the reflective subscales of knowledge and attitudes, with a score of ≥ 0.6 and ≥ 0.8 indicating acceptable and high reliability, respectively [43, 44]. As practice items were conceptualized as a formative index, internal consistency was not calculated because inter-item correlations are not expected [33, 34]. Test-retest reliability was assessed by asking 30 participants to complete the questionnaire again after two weeks, and was analyzed via Intraclass Correlation Coefficients (ICCs) for the three sections [45].
Data analysis
Descriptive statistics, reliability analysis, and EFA were performed via IBM SPSS Statistics (version 23). Normality was checked via the Shapiro–Wilk test (p < 0.05 indicating nonnormal distribution). CFA was performed via RStudio for macOS using the lavaan package Version 0.6-21. The Weighted Least Squares Mean and Variance-adjusted (WLSMV) was used as an estimator, which is suitable for categorical and ordinal data [46, 47]. Complete-case analysis was used to handle missing data.
Ethical consideration
The Institutional Review Board office at An-Najah National University granted approval for this study. Written informed consent was obtained from all respondents after adequate explanations of the study objectives were provided.
Results
Participant characteristics
The average time to complete the final questionnaire was eight minutes, with a total of 200 participants included in the final analysis (response rate = 95.2%). The mean age was 20.75 years (SD = 1.82), with 66.5% being female and 33.5% being male. An exact half resided in rural areas (50.0%), whereas the other half either resided in an urban area (45.5%) or a camp (4.5%) (Table 1). Most participants reported that they live with their family (76.5%).
Table 1.
Sociodemographic characteristics of the participants
| Variable | Frequency (%) |
|---|---|
| n = 200 | |
| Age mean (± SD) | 20.75 (1.82) |
| Gender | |
| Male | 67 (33.5) |
| Female | 133 (66.5) |
| Residency | |
| City | 91 (45.5) |
| Town | 100 (50.0) |
| Palestinian refugee camps | 9 (4.5) |
| Living status | |
| In a family accommodation | 153 (76.5) |
| Not in a family accommodation | 47 (23.5) |
| Year of study | |
| First | 32 (16.0) |
| Second | 38 (19.0) |
| Third | 41 (20.5) |
| Fourth | 47 (23.5) |
| Fifth | 31 (15.5) |
| Sixth or more | 11 (5.5) |
Item generation
In addition to the sociodemographic questions, item screening resulted in the removal of 12 items from the initial pool of 46 items (Fig. 1). The initial set of items was reduced from 18, 12, and 16 to 13, 8, and 13 for the knowledge, attitudes, and practices sections, respectively. A set of 34 items remained after item screening, covering hair washing (K1-3, A1-2, P1-4), hair products and procedures (K4-8, A3-6, P5-10), and general hair care (K9-13, A7-8, P11-13).
Content and face validity
Only two items measuring satisfaction were removed from the attitudes section (A7-8) following content validity evaluation, reducing the total number of items from 34 to 32 (Fig. 1). Content validity testing revealed an acceptable S-CVI/average of 0.949, with I-CVIs ranging between 0.875 and 1 (Table 2). The main feedback included improving the accuracy of some items (e.g., specifying heat-based procedures in K8 and A6), using more affective wording in the attitudes section, and correcting language and technical mistakes. Face validity was tested with 35 participants, who commented on some technical words and complex structures, without removing any item.
Table 2.
Findings of the content validity analysis using the content validity indices
| E1 | E2 | E3 | E4 | E5 | E6 | E7 | E8 | Expert in agreement | I-CVI | |
|---|---|---|---|---|---|---|---|---|---|---|
| K1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 8 | 1 |
| K2 | 1 | 1 | 1 | 0 | 1 | 1 | 1 | 1 | 7 | 0.875 |
| K3 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 8 | 1 |
| K4 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 8 | 1 |
| K5 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 8 | 1 |
| K6 | 1 | 1 | 1 | 1 | 1 | 0 | 1 | 1 | 7 | 0.875 |
| K7 | 1 | 1 | 1 | 1 | 1 | 0 | 1 | 1 | 7 | 0.875 |
| K8 | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 7 | 0.875 |
| K9 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 8 | 1 |
| K10 | 1 | 1 | 1 | 1 | 1 | 0 | 1 | 1 | 7 | 0.875 |
| K11 | 1 | 1 | 0 | 1 | 1 | 1 | 1 | 1 | 7 | 0.875 |
| K12 | 1 | 1 | 1 | 1 | 1 | 0 | 1 | 1 | 7 | 0.875 |
| K13 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 8 | 1 |
| A1 | 1 | 1 | 1 | 0 | 1 | 1 | 1 | 1 | 7 | 0.875 |
| A2 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 8 | 1 |
| A3 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 8 | 1 |
| A4 | 1 | 1 | 1 | 0 | 1 | 1 | 1 | 1 | 7 | 0.875 |
| A5 | 1 | 1 | 1 | 1 | 1 | 0 | 1 | 1 | 7 | 0.875 |
| A6 | 1 | 1 | 1 | 0 | 1 | 1 | 1 | 1 | 7 | 0.875 |
| A7 | 1 | 1 | 0 | 1 | 1 | 0 | 1 | 1 | 6 | 0.750 |
| A8 | 1 | 1 | 0 | 1 | 1 | 0 | 1 | 1 | 6 | 0.750 |
| P1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 8 | 1 |
| P2 | 1 | 1 | 1 | 1 | 1 | 0 | 1 | 1 | 7 | 0.875 |
| P3 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 8 | 1 |
| P4 | 1 | 1 | 1 | 1 | 1 | 0 | 1 | 1 | 7 | 0.875 |
| P5 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 8 | 1 |
| P6 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 8 | 1 |
| P7 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 8 | 1 |
| P8 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 8 | 1 |
| P9 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 8 | 1 |
| P10 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 8 | 1 |
| P11 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 8 | 1 |
| P12 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 8 | 1 |
| P13 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 8 | 1 |
| S-CVI/Ave = 0.949 (with excluded items: 9.375) | ||||||||||
E expert, I-CVI content validity index for item, S-CVI/ave scale-content validity index/average
For the purpose of CVI calculation, the item scores were reported on the basis of recategorization of those scores filled by experts, where a low validity score of 1 or 2 was reported as 0 and an acceptable validity score of 3 or 4 was reported as 1. The CVI for item (I-CVI) is calculated by summing the number of experts providing a high CVI for each item. The scale CVI (S-CVI/average) was reported by calculating the average I-CVI across all the items
Construct validity
Knowledge section
The KMO value (0.863) and Bartlett’s test of sphericity (χ² = 1105.8, df = 78, p < 0.001) demonstrated sample suitability for EFA. Oblique Promax rotation was first conducted and yielded a factor correlation matrix with correlation coefficients less than 0.32, which warranted the use of orthogonal varimax rotation. Principal axis factoring with varimax rotation was performed. Based on latent root criterion and scree plot, two factors were extracted, explaining 50.3% of the variance. No items were removed because all the items had loadings higher than 0.3 (Table 3). The items that loaded on the first factor were K1-3 and K9-13; and those that loaded on the second factor were K4-8 (Fig. 2). CFA revealed that the model was acceptable (CFI = 0.943, TLI = 0.930, RMSEA = 0.067, and SRMR = 0.055).
Table 3.
Factor loading matrix of the questionnaire via exploratory factor analysis
| Item | Factor 1—Knowledge about routine hair hygiene and care | Factor 2—Knowledge about hair products and procedures | Factor 3—Attitudes toward hair care |
|---|---|---|---|
| K1 | 0.647 | − 0.143- | |
| K2 | 0.688 | − 0.200- | |
| K3 | 0.724 | − 0.003- | |
| K4 | − 0.023- | 0.732 | |
| K5 | − 0.117- | 0.833 | |
| K6 | − 0.175- | 0.708 | |
| K7 | − 0.112- | 0.751 | |
| K8 | − 0.072- | 0.708 | |
| K9 | 0.621 | − 0.088- | |
| K10 | 0.652 | − 0.075- | |
| K11 | 0.691 | − 0.033- | |
| K12 | 0.685 | − 0.132- | |
| K13 | 0.641 | − 0.060- | |
| A1 | 0.346 | ||
| A2 | 0.385 | ||
| A3 | 0.351 | ||
| A4 | 0.382 | ||
| A5 | 0.503 | ||
| A6 | 0.346 |
Boldface indicates the highest factor loading for each item
The KMO value (0.863 and 0.786 for the knowledge and attitudes section, respectively) and Bartlett’s test of sphericity for both (p < 0.001)
Extraction Method: Principal Axis Factoring
Rotation method: Varimax rotation
Fig. 2.
Factor analysis of the Hair Health and Care Questionnaire (HHCQ). K knowledge item, A attitude item, F factor. The depicted numbers indicate factor loadings of items
Attitudes section
The KMO value (0.786) and Bartlett’s test of sphericity (χ² = 355.5, df = 15, p < 0.001) demonstrated sample suitability for EFA. Principal axis factoring with varimax rotation was performed, and one factor was extracted, explaining 50.6% of the variance. All attitude items loaded on the single factor and no items were removed because all the items had loadings higher than 0.3 (Table 3; Fig. 2). CFA revealed that the model was acceptable (CFI = 0.955, TLI = 0.991, RMSEA = 0.077, and SRMR = 0.060).
Reliability
A test-retest reliability analysis was conducted with 30 participants and revealed excellent ICCs for knowledge (0.977), attitudes (0.987), and practices (0.942). The Cronbach’s alpha coefficient was 0.813, 0.869, and 0.801 for Factors 1, 2, and the single attitude factor, respectively. The final HHCQ consists of 32 items: 13 items assessing knowledge, 6 assessing attitudes, and 13 assessing practices (Supplementary File 3 for the Arabic version and Supplementary File 4 for the English version).
Discussion
Published KAP questionnaires assessing hair care are few, nonvalidated, or have methodological limitations [11–16, 19–22], probably because hair care is deprioritized as an aesthetic issue amid overriding health needs. This study developed a questionnaire comprising 13 knowledge, 6 attitude, and 13 practice items, following content, face, and construct validation, as well as internal consistency and test-retest reliability assessment. The HHCQ represents a standardized, accessible, reliable tool that can be used in regional and global trichology research and facilitate comparisons across settings. However, its external validity requires replication among demographically and culturally diverse samples, with integration of local cultural practices.
Importantly, the study addressed a gap in content validity noticed in previous questionnaires by creating a framework to guide item generation. The approach to ensure content validity addressed coverage, whereby every aspect of the topic is covered by the included items, and relevance, whereby items irrelevant to the measured concepts are omitted. To establish construct validity, the number of extracted factors was determined via latent root criterion and visual inspection of the Cattell’s scree plot. As no single method is absolutely best for determining the number of factors, the integration of multiple criteria is recommended in methodological literature, particularly when supported by acceptable variance and theoretical interpretability [44, 48].
The two knowledge and the single attitude factors accounted for 50.3% and 50.6% of the total explained variance, which are acceptable values in social and health sciences. This is particularly relevant for complex, heterogeneous behavioral constructs that are influenced by daily habits, cultural norms, and personal experiences. This is further supported by theoretical interpretability and acceptable item loadings. For knowledge, Factor 1 (Routine Hair Hygiene and Care) includes items on daily hair hygiene, washing, and manual handling, while Factor 2 addresses specialized application of hair products and procedures. Notably, two of the three pre-validation theoretical domains were merged into a single factor, aligning with Clark and Watson’s emphasis on the centrality of an initial articulated theory to construct validity. They, however, noted that such theory is amenable to change and mainly aims to increase the likelihood of contribution to the literature [48, 49]. Similarly, all attitude items converged into a single factor. This reflects a theoretically reasonable and practically advantageous perception whereby young adults integrate different tools and practices into a cohesive attitude toward hair health.
The HHCQ is a versatile tool that can be adapted for different purposes and settings. Poor hair care practices and the wide availability of hair care products and procedures can lead to hair problems, such as scalp infections, dandruff, and hair loss. These problems often require medical treatment and consistent product use, both of which are associated with considerable economic burdens. The HHCQ can be used to gather baseline data to inform public health campaigns, particularly among young adults, who are more likely to adopt poor hair care practices, such as misuse of chemical and heat-based styling procedures. The HHCQ's utility also extends to informing clinical practice. Identifying common behaviors, misconceptions, and knowledge gaps can shape recommendations and guide personalized patient counselling. In addition, this can guide clinicians in designing brief in-service trainings or demonstrations that help increase patient self-efficacy and prevent complications. Indeed, hair care improves self-esteem, maintains hygiene, increases patient control over their own health, and prevents complications such as knot formation [10].
While the sample size was determined based on a methodological reference, it may be considered modest for conducting factor analyses. Accordingly, the extracted factor solution and model fit indices should be interpreted with caution, as small samples may produce less stable factor structures and loadings, limiting their replicability in other samples. Using such a sample size may also yield a structure whose construct validity may be influenced by sampling variability. Importantly, however, modern psychometric literature does not label one rule as universal for sample-size adequacy, highlighting the impact of item content, communalities, and factor structure [50]. Additionally, the sample size adopted in this study should be evaluated against the 32-item tool on which factor analysis was applied, as the initial 46 items were reduced following validation phases and prior to data collection. This yields a participant-to-item ratio of 6.25:1, slightly exceeding the minimum threshold of 5:1 [44]. Nonetheless, future validation studies should employ more recent methodological references and use a larger sample size to confirm model stability and validity [51].
Limitations
This validation study has several limitations. While the HHCQ can serve as a model that can be adapted for and validated in different contexts, its validation relied on a convenience sampling technique within a single-country setting and was validated among a population with specific characteristics, such as being native Arabic-speaking university students. These methods and settings limit the generalizability of the findings to other demographic groups or diverse cultural contexts across the region. Therefore, future research is recommended to externally validate the questionnaire among more diverse populations, including different countries, cultures, clinical settings, and educational backgrounds. Second, the questionnaire should be replicated in larger, separate samples, as both EFA and CFA were conducted on the same sample, whose size may be considered modest [50]. Additionally, the absence of convergent, discriminant, or criterion validation is a methodological limitation that should be addressed in future validation research. However, the sample was diversified by including participants studying several majors other than health sciences to mitigate the effect of health-conscious behavior prevalent among health science students. Furthermore, the questionnaire lacks coverage of specific domains, such as hair loss, which might undermine its content validity. Excluding some domains, however, serves the purpose of creating a short, general questionnaire addressing daily hair care practices and avoids the complexity required to include detailed and complicated clinical issues. Creating a respondent-friendly questionnaire entails minimizing the number of items within each domain. Otherwise, long questionnaires can be cumbersome to fill, potentially introducing information biases by increasing the rates of missing and erroneous data. To the best of the authors’ knowledge, this study introduces a validated questionnaire assessing hair care to help inform health interventions and guide clinical practice. This also enriches the research practices in dermatology and cosmetology, which has long been neglected in the region.
Supplementary Information
Below is the link to the electronic supplementary material.
Acknowledgements
The authors thank An-Najah National University for all the administrative assistance offered for the writing of paper.
Abbreviations
- KAP
Knowledge, attitudes, and practices
- CVI
Content validity index
- I-CVI
Content validity index for item
- S-CVI
Scale content validity index
- EFA
Exploratory factor analysis
- KMO
Kaiser‒Meyer‒Olkin
- CFI
Comparative Fit Index
- TLI
Tucker Lewis Index
- RMSEA
Root mean square error of approximation
- SRMR
Standardized root mean square residual
- ICC
Intraclass correlation coefficient
- IRB
Institutional review board
Author contributions
ST and SHZ designed, conceptualized, and supervised the study. ST, DD, HD, HT, HH, RA, and AR performed the literature review. DD, HD, HT, HH, and RA collected the data. ST, SHZ, and AA analyzed the data. ST conducted factor analyses (EFA and CFA) and designed the figures. ST, AR, AA, and HH wrote the initial draft of the manuscript. ST wrote the final draft of the manuscript, which was approved by all authors.
Data availability
The data are available from the corresponding author upon reasonable request.
Declarations
Competing interests
The authors declare no competing interests.
Footnotes
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Contributor Information
Sari Taha, Email: saritaha1993@gmail.com, Email: sari.taha@najah.edu.
Abdulsalam Alkaiyat, Email: a.khayyat@najah.edu.
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Data Availability Statement
The data are available from the corresponding author upon reasonable request.