Table of Contents
Abstract
The perceived access to Health Care Questionnaire is a multidimensional psychometric instrument designed to evaluate how individuals subjectively experience and navigate barriers to medical services. While traditional public health metrics often rely on objective indicators—such as the geographic distance to a clinic or the ratio of hospital beds to citizens—this tool pivots toward the psychological reality of the patient. It operates on the premise that objective availability does not guarantee actual utilization; rather, a patient's personal perception of accessibility, affordability, and cultural acceptability ultimately dictates their healthcare-seeking behavior.
Developed by synthesizing Penchansky and Thomas's foundational five-dimension model of access with Saurman's later addition of 'awareness', the instrument captures a holistic picture of healthcare barriers. It bridges the gap between spatial limitations, economic constraints, organizational hurdles, and health literacy. By quantifying these subjective experiences, the questionnaire provides researchers and policymakers with actionable data to identify hidden inequities in healthcare systems, particularly those that persist despite adequate physical infrastructure.
📊 Psychometric Scorecard
30
Multidimensional
0.86
📍 Iran
Authors
Purpose
In the realm of health services research, there is a historical overreliance on objective, market-driven metrics to define healthcare access. However, these metrics frequently fail to explain why certain populations—despite living near well-funded facilities—continue to underutilize medical care. The perceived access to Health Care Questionnaire was developed to address this critical measurement gap. It shifts the analytical focus from the structural capacity of the health system to the lived experience of the consumer.
For clinicians and public health researchers, this scale is invaluable because it operationalizes the psychological and cultural dimensions of access. Existing tools tend to be fragmented, focusing on single dimensions like cost or geographic distance. By offering a unified, standardized measure of perceived access across six distinct domains, this instrument allows researchers to pinpoint exactly where the breakdown in healthcare delivery occurs, facilitating highly targeted interventions to improve health equity.
Construct
The psychological construct of 'perceived access' measured by this scale is grounded in a comprehensive, six-factor theoretical framework. The first two dimensions are spatial: 'Availability' evaluates the perceived adequacy of healthcare resources and personnel, while 'Accessibility' captures the subjective burden of travel time and geographic distance. The subsequent three dimensions are non-spatial, focusing on the socio-economic and cultural interface between patient and provider. 'Affordability' assesses the individual's perceived financial capacity to bear healthcare costs, 'Accommodation' measures how well the organization of services aligns with patient needs and schedules, and 'Acceptability' gauges the cultural and interpersonal comfort between patients and medical staff.
The final dimension, 'Awareness', represents a vital cognitive component added to modern access models. It encompasses health literacy and the patient's ability to identify their own medical needs, understand what services exist, and navigate the system to utilize them. Together, these six dimensions form a cohesive construct reflecting the complex, multifaceted nature of healthcare access as a subjective human experience rather than a mere logistical reality.
Validity
The development of the questionnaire involved rigorous validation protocols to ensure psychometric soundness. Content validity was established through both qualitative expert review and quantitative metrics. A panel of specialists evaluated the initial 31 items, resulting in excellent Content Validity Ratio (CVR) scores exceeding 0.78 for 30 items, leading to the elimination of one underperforming item. The Content Validity Index (CVI) further supported the item pool, with 29 items scoring above the strict 0.79 threshold and one requiring minor revisions.
Face validity was confirmed quantitatively, with all retained items achieving an impact score greater than 1.5, indicating high relevance and clarity as judged by both experts and the target demographic. Construct validity was subsequently evaluated using Confirmatory Factor Analysis (CFA) on a sample of 300 Adults. The CFA successfully validated the theoretical six-factor structure, demonstrating that the empirical data aligned well with the a priori dimensions of availability, accessibility, affordability, accommodation, acceptability, and awareness.
Reliability
The instrument demonstrates robust reliability, making it a dependable tool for both cross-sectional and longitudinal research. Internal consistency for the overall 30-item scale is strong, yielding a Cronbach's alpha of 0.86. When examining the individual subscales, the alpha coefficients range from 0.60 to 0.80 (specifically: acceptability at 0.80, accessibility and awareness at 0.76, affordability at 0.66, availability at 0.61, and accommodation at 0.60). While some subscale values are modest, they remain within acceptable psychometric boundaries for multidimensional constructs with relatively few items per factor.
Temporal stability was also rigorously tested. A two-week test-retest reliability analysis utilizing the two-way mixed absolute agreement method produced an Intraclass Correlation Coefficient (ICC) of 0.94. This exceptionally high ICC value indicates that the questionnaire is highly stable over time, ensuring that any changes detected in longitudinal studies are likely due to true shifts in perceived access rather than measurement error.
Factor Analysis
To verify the underlying structure of the questionnaire, the researchers employed Confirmatory Factor Analysis (CFA) using the lavaan package in R. Unlike exploratory approaches, CFA requires the researchers to specify the exact factor structure beforehand based on theory—in this case, the six-dimensional model of access.
The analysis evaluated how well the 30 items mapped onto their respective latent variables (availability, accessibility, affordability, accommodation, acceptability, and awareness). The researchers established stringent a priori fit criteria, including a Tucker Lewis Index (TLI) and Goodness of Fit (GFI) of 0.95 or higher, and a Root Mean Square Error of Approximation (RMSEA) below 0.05. The results confirmed that the six-factor model provided an appropriate and statistically sound fit for the empirical data, validating the multidimensional nature of perceived healthcare access.
Subscales
| Subscale | Items | Description |
|---|---|---|
| Availability | Measures the perceived physical availability and capacity of healthcare resources. | |
| Accessibility | Measures the perceived burden of geographic distance and commuting time to healthcare facilities. | |
| Affordability | Measures the perceived economic capacity to pay for healthcare services and insurance. | |
| Accommodation | Measures perceptions of how well healthcare services are organized to meet patient needs and schedules. | |
| Acceptability | Measures the perceived cultural and interpersonal comfort between patients and healthcare providers. | |
| Awareness | Measures health literacy and the ability to identify needs and navigate the healthcare system. |
Instrument
| Test Type | Self-report questionnaire |
| Format | 30 items, 5-point Likert scale (strongly agree to strongly disagree) |
| Language | Persian |
| Population | Adults, Medical patients |
| Age Group | 20-60 years |
| Administration | Interview-administered |
Perceived Access to Health Care Questionnaire Items
Items are currently not available
The individual items of this scale are not publicly available. Researchers interested in using this instrument should contact the original authors directly to request the scale materials.
Sample
300 adult patients (aged 20 to 60 years) who were citizens and residents of Iran, referred to healthcare centers in south Tehran. Participants were selected using a multi-stage sampling method, excluding those with severe cognitive impairments or specific chronic diseases.
Cite This Paper
Sara-Sadat Hoseini-Esfidarjani, Reza Negarandeh, Farzaneh Delavar, Leila Janani (2021). perceived access to Health Care Questionnaire. BMC Health Services Research. https://doi.org/10.1186/s12913-021-06655-2
References
40 references
- Saurman E. Improving access: modifying Penchansky and Thomas’s theory of access. J Health Serv Res Policy. 2016;21(1):36–9. https://doi.org/10.1177/1355819615600001. 🔗 https://doi.org/10.1177/1355819615600001
- Levesque J-F, Harris Mark F, Grant R. Patient-centred access to health care: conceptualising access at the interface of health systems and populations. Int J Equity Health. 2013;12(1):18. https://doi.org/10.1186/1475-9276-12-18. 🔗 https://doi.org/10.1186/1475-9276-12-18
- Zandam HU, Hanafiah JM, Hayati KS, et al. Development and validation of perceived access to health care measurement instrument. Int J Public Health Clin Sci. 2017;4(5):158–71. Retrieved from http://www.publichealthmy.org/ejournal/ojs2/index.php/ijphcs/article/view/494.
- Negarandeh R, Haydeh N, Maryam HP. Evaluating the perception of martyrs’ parents of access to the services of health monitoring plan provided by Foundation of Martyrs and Veterans Affair of 10 and 11 districts of Tehran in 2014. Nurs Pract Today. 2016;3(3):99–106. Retrieved from https://npt.tums.ac.ir/index.php/npt/article/view/165.
- World Health Organization. Expanding access to health services with self-care interventions. 2019. Retrieved from: https://www.who.int/reproductivehealth/self-care-interventions/access-health-services/en/.
- Eide AH, Hasheem M, Mustafa K, et al. Perceived barriers for accessing health services among individuals with disability in four African countries. PLoS One. 2015;10(5):e0125915. https://doi.org/10.1371/journal.pone.0125915. 🔗 https://doi.org/10.1371/journal.pone.0125915
- Cylus J, Irene P. An analysis of perceived access to health care in Europe: how universal is universal coverage? Health Policy. 2015;119(9):1133–44. https://doi.org/10.1016/j.healthpol.2015.07.004. 🔗 https://doi.org/10.1016/j.healthpol.2015.07.004
- Wang F. Measurement, optimization, and impact of health care accessibility: a methodological review. Ann Assoc Am Geogr. 2012;102(5):1104–12. https://doi.org/10.1080/00045608.2012.657146. 🔗 https://doi.org/10.1080/00045608.2012.657146
- Mary Brown Walker. A phenomenological study on perceptions of health care access for African Americans and Latino Americans: University of Phoenix; 2015. retrieved from https://search.proquest.com/openview/1a3a9625e12ff18eaca682c914da265e/1?pq-origsite=gscholar&cbl=18750&diss=y.
- Terry D, Kaye E, Alan C, et al. Heterogeneity of rural consumer perceptions of health service access across four regions of Victoria. J Rural Soc Sci. 2017;32(2):6. retrieved from https://egrove.olemiss.edu/jrss/vol32/iss2/6/.
- Julián Alfredo Fernández-Niño, Chavarro Lud Magdy, Vásquez-Rodríguez Ana Beatriz, et al. Perception of effective access to health services in Territorial Spaces for Training and Reincorporation, one year after the peace accords in Colombia: a cross-sectional study. F1000Research. 2019;8:2140. https://doi.org/10.12688/f1000research.21375.2 🔗 https://doi.org/10.12688/f1000research.21375.2
- Thiede M, Patricia A, Di MI, et al. Exploring the dimensions of access. In: McIntyre D, Mooney G, editors. The economics of health equity. Cambridge: Cambridge University Press; 2007. p. 103–23. https://doi.org/10.1017/CBO9780511544460.007. 🔗 https://doi.org/10.1017/CBO9780511544460.007
- Kyriopoulos I-I, Dimitris Z, Anastasis S, et al. Barriers in access to healthcare services for chronic patients in times of austerity: an empirical approach in Greece. Int J Equity Health. 2014;13(1):54. https://doi.org/10.1186/1475-9276-13-54. 🔗 https://doi.org/10.1186/1475-9276-13-54
- Shrestha J. Evaluation of access to primary healthcare: a case study of Yogyakarta, Indonesia: [MSc thesis on the internet] University of Twente Faculty of geo-information and earth observation (ITC); 2010.
- Jeannie L. Haggerty, & Levesque Jean-Frédéric. Validation of a new measure of availability and accommodation of health care that is valid for rural and urban contexts. Health Expect. 2017;20(2):321–34. https://doi.org/10.1111/hex.12461. 🔗 https://doi.org/10.1111/hex.12461
- Bath B, Megan J, Darren M, et al. Factors associated with reduced perceived access to physiotherapy services among people with low back disorders. Physiother Can. 2016;68(3):260–6. https://doi.org/10.3138/ptc.2015-50. 🔗 https://doi.org/10.3138/ptc.2015-50
- Onyeneho NG, Amazigo Uche V, Njepuome Ngozi A, et al. Perception and utilization of public health services in Southeast Nigeria: implication for health care in communities with different degrees of urbanization. Int J Equity Health. 2016;15(1):12. https://doi.org/10.1186/s12939-016-0294-z. 🔗 https://doi.org/10.1186/s12939-016-0294-z
- Weber M, Lisa T, Schmiege Sarah J, et al. Perception of access to health care by homeless individuals seeking services at a day shelter. Arch Psychiatr Nurs. 2013;27(4):179–84. https://doi.org/10.1016/j.apnu.2013.05.001. 🔗 https://doi.org/10.1016/j.apnu.2013.05.001
- Allin S, Cristina M, Corinna S, et al. Measuring inequalities in access to health care: a review of the indices. Belgium: European Commission Brussels; 2007. retrieved from: https://scholar.google.com/scholar?hl=en&as_sdt=0%2C5&q=%22Measuring+inequalities+in+access+to+health+care.+A+review+of+the+indices%22&btnG.
- Fitzpatrick AL, Powe Neil R, Cooper Lawton S, et al. Barriers to health care access among the elderly and who perceives them. Am J Public Health. 2004;94(10):1788–94. https://doi.org/10.2105/ajph.94.10.1788. 🔗 https://doi.org/10.2105/ajph.94.10.1788
- Quinn M, Claire R, Jane F, et al. Survey instruments to assess patient experiences with access and coordination across healthcare settings: available and needed measures. Med Care. 2017;55(Suppl 7 1):S84. 🔗 https://doi.org/10.1097/MLR.0000000000000730
- Myers ND, Soyeon A, Ying J. Sample size and power estimates for a confirmatory factor analytic model in exercise and sport: a Monte Carlo approach. Res Q Exerc Sport. 2011;82(3):412–23. retrieved from:. https://doi.org/10.1080/02701367.2011.10599773. 🔗 https://doi.org/10.1080/02701367.2011.10599773
- Shi G, Jun W, Xu X, et al. Culture-related grief beliefs of Chinese Shidu parents: development and psychometric properties of a new scale. Eur J Psychotraumatol. 2019;10(1):1626075. https://doi.org/10.1080/20008198.2019.1626075. 🔗 https://doi.org/10.1080/20008198.2019.1626075
- S Parry. Fit indices commonly reported for CFA and SEM. Cornell Statistical Unit. 2020. retrieved from: https://www.cscu.cornell.edu/news…
- Mohamad Adam Bujang, & Baharum Nurakmal. A simplified guide to determination of sample size requirements for estimating the value of intraclass correlation coefficient: a review. Arch Orofac Sci. 2017;12(1). retrieved from: https://scholar.google.com/scholar?hl=en&as_sdt=0%2C5&q=%22A+simplified+guide+to+determination+of+sample+size+requirements+for+estimating+the+value+of+intraclass+correlation+coefficient%3A+a+review%22&btnG=.
- Koo TK, Li Mae Y. A guideline of selecting and reporting intraclass correlation coefficients for reliability research. J Chiropract Med. 2016;15(2):155–63. https://doi.org/10.1016/j.jcm.2016.02.012. 🔗 https://doi.org/10.1016/j.jcm.2016.02.012
- Daud KAM, Zulkarnaen KN, Rasdan IA, et al. Validity and reliability of instrument to measure social media skills among small and medium entrepreneurs at Pengkalan Datu River. Int J Dev Sustain. 2018;7(3):1026–37.
- Martin CR, Emily S-MG. A ‘good practice’guide for the reporting of design and analysis for psychometric evaluation. J Reprod Infant Psychol. 2013;31(5):449–55. 🔗 https://doi.org/10.1080/02646838.2013.835036
- Yakob B, Purity NB. Correlates of perceived access and implications for health system strengthening–lessons from HIV/AIDS treatment and care services in Ethiopia. PLoS One. 2016;11(8):e0161553. https://doi.org/10.1371/journal.pone.0161553. 🔗 https://doi.org/10.1371/journal.pone.0161553
- William D Savedoff. A moving target: universal access to healthcare services in Latin America and the Caribbean. Working Paper; 2009. https://www.econstor.eu/handle/10419/51524. 🔗 https://doi.org/10.18235/0011233
- Bezem J, Debbie H, Ria R, et al. Improving access to school health services as perceived by school professionals. BMC Health Serv Res. 2017;17(1):743. https://doi.org/10.1186/s12913-017-2711-4. 🔗 https://doi.org/10.1186/s12913-017-2711-4
- Tanner EC, Vann Richard J, Elvira K. Consumer-level perceived access to health services and its effects on vulnerability and health outcomes. J Public Policy Mark. 2020;39(2):240–55. https://doi.org/10.1177/0743915620903299. 🔗 https://doi.org/10.1177/0743915620903299
- Pyne JM, Adam KP, Fischer Ellen P, et al. Development of the perceived access Inventory: A patient-centered measure of access to mental health care. Psychol Serv. 2020;17(1):13. https://doi.org/10.1037/ser0000235. 🔗 https://doi.org/10.1037/ser0000235
- Otieno PO, Achach WEO, Mohamed Shukri M, et al. Access to primary healthcare services and associated factors in urban slums in Nairobi-Kenya. BMC Public Health. 2020;20:981. https://doi.org/10.1186/s12889-020-09106-5. 🔗 https://doi.org/10.1186/s12889-020-09106-5
- Gendall P. A framework for questionnaire design: Labaw revisited. Marketing bulletin-department of marketing massey university. 1998;9:28–39. https://scholar.google.com/scholar?hl=en&as_sdt=0%2C5&q=%22A+Framework+for+Questionnaire+Design%3A+Labaw+Revisited%22&btnG.
- Jenn NC. Designing a questionnaire. Malaysian Fam Phys. 2006;1(1):32. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4797036/.
- Orcan F. Exploratory and confirmatory factor analysis: which one to use first. J Measurement Eval Educ Psychol. 2018;9(4):414–21. retrieved from: https://scholar.google.com/scholar?hl=en&as_sdt=0%2C5&q=%22Exploratory+and+Confirmatory+Factor+Analysis%3A+Which+One+to+Use+First%3F%22&btnG.
- Tavakol M, Reg D. Making sense of Cronbach’s alpha. Int J Med Educ. 2011;2:53–5. https://doi.org/10.5116/ijme.4dfb.8dfd. 🔗 https://doi.org/10.5116/ijme.4dfb.8dfd
- Jih-Yuan Chen. Stimulate reflection and foster critical thinking in nursing education. Int J Curr Res. 2017;9(7):55089–55093. retrived from: http://www.journalcra.com.
- Mehdi H, Rajabi G. Health Care Services Utilization in Iran. Iran J Public Health. 2017;46(6):863-4. retrieved from: https://scholar.google.com/scholar?hl=en&as_sdt=0%2C5&q=%22Health+Care+Services+Utilization+in+Iran%22&btnG=
Cite this article
Mohammed looti (2026). Perceived Access to Health Care Questionnaire. PSYCHOLOGICAL SCALES. Retrieved from https://scales.arabpsychology.com/s/perceived-access-to-health-care-questionnaire/
Mohammed looti. "Perceived Access to Health Care Questionnaire." PSYCHOLOGICAL SCALES, 12 Aug. 2026, https://scales.arabpsychology.com/s/perceived-access-to-health-care-questionnaire/.
Mohammed looti. "Perceived Access to Health Care Questionnaire." PSYCHOLOGICAL SCALES, 2026. https://scales.arabpsychology.com/s/perceived-access-to-health-care-questionnaire/.
Mohammed looti (2026) 'Perceived Access to Health Care Questionnaire', PSYCHOLOGICAL SCALES. Available at: https://scales.arabpsychology.com/s/perceived-access-to-health-care-questionnaire/.
[1] Mohammed looti, "Perceived Access to Health Care Questionnaire," PSYCHOLOGICAL SCALES, vol. X, no. Y, ص Z-Z, August, 2026.
Mohammed looti. Perceived Access to Health Care Questionnaire. PSYCHOLOGICAL SCALES. 2026;vol(issue):pages.