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Health service utilization, Health service use, Determinant, Systematic review, What&,rsquo s Known Over one billion people around the world, mostly in countries with low or average income, do not have access to healthcare services. Andersen&,rsquo s behavioral model provides a useful framework for informing the analysis of the contributing factors to health service utilization. What&,rsquo s New Structural-level factors such as residential stability, distance to healthcare delivery centers, travel time to the nearest health center, density of health service providers and health centers, population size of municipalities, and the state-level income play an important role in health service utilization. IntroductionThe underutilization of health services has become an essential concern of public health and policy issues worldwide. 1, Various countries, especially in the developing world, seek to improve health service utilization (HSU) and equitable access to healthcare. 1,- 4, Over one billion people around the world, mostly in countries with low or average income, do not have access to healthcare services, 2,, 4, which stems from a complex set of interactive factors. In fact, decision making of individuals to use healthcare services depends on a host of interacting factors relevant to health and self-reported health situation as well as the availability of health services. 5, There have been a lot of studies probing into why HSU patterns are different from one individual to another. Concerning HSU, various theoretical models have been developed with the purpose of perceiving and exploring a multitude of factors governing it and the extent they vary based on economic, psychological, behavioral, and epidemiological veiwpoints. 6, HSU is defined as obtaining healthcare provided by healthcare services in the form of healthcare contacts. 6, In other words, HSU refers to the point in health systems in which the needs of the patients are met on the part of health professionals. In order to explain this process, most studies have used the Behavioral Model of Health Services Utilization (BM), 7,- 13, which was developed in 1968 by the American medical sociologist and health services researcher, Ronald M Andersen. The BM is a multilevel model that incorporates both individual and contextual determinants of HSU. 6,, 10,, 12,, 14,, 15, Individual characteristics are evaluated at the individual level, whereas contextual characteristics such as families, communities, and national healthcare systems are measured at an aggregate level. 7,, 11,, 12,, 14,, 15, The BM provides a useful framework for informing the analysis of contributing factors to HSU, 7,, 11,, 16,, 17, and it is built upon three components, which are presumably associated with HSU and could be applied as predictors of utilization, as follows, 14,, 15, Predisposing factors are comprised of the sociodemographic characteristics that create the condition to increase the probability of HSU. At the individual level, these factors include age, sex, marital status, and ethnicity, along with attitudes, beliefs, values, and knowledge vis-&,agrave -vis health and health services. The contextual factors that predispose individuals to HSU encompass the demographic and social composition of communities and their collective and organizational values, as well as cultural norms. 9,, 10,, 12,, 14,, 17,, 18, Enabling factors are considered those that can hinder or facilitate HSU. At the individual level, these factors include income, wealth, health insurance status, and regular sources of care. At the contextual level, the enabling factors consist of per capita community income the rate of health insurance coverage the amount, variety, location, structure, and distribution of health service facilities and personnel provider-related factors physician and hospital density distance from healthcare services 8, the availability of transportation 4,, 10, the quality of healthcare and health policies. 1,, 2,, 4,, 9,, 12, Need factors are understood as variables concerning the perception of a change in individuals&,rsquo health status. At the individual level, these factors encompass both the perceived need for health services and the evaluated need. At the contextual level, the need factors comprise not only environmental need features, namely occupational and traffic- and crime-based accidents and death rates but also health indices including the epidemiological indicators of mortality, morbidity, and disability. 8,, 12,, 19, The evaluation of HSU patterns is useful for identifying the subgroups of patients who are either under- or overutilizing services. 12, Service underutilization has consequences for patients. By way of example, patients who are not fully engaged in care are liable to have poorer outcomes. 18, Furthermore, understanding the factors that facilitate and inhibit HSU is essential for enhancing HSU, which explains why to ensure fair access to healthcare services, policymakers need to identify the factors that influence HSU. 4, Previous studies have examined the role of different factors in determining HSU, including age, 4,, 12,, 20,- 22, gender, 8,, 9, the education level, 8,, 21, socioeconomic status, 10,, 11,, 13, race/ethnicity, 8,, 13,, 14, employment status, 1,, 9,, 11,, 21, marital status, 4,, 23,, 24, income, 1,, 3,, 4,, 12,, 21,, 25, and health insurance, 22,, 26,- 30, along with cultural beliefs and perceptions. 8,, 10, Moreover, other studies have focused on factors such as family size, 4,, 13,, 31, the cost/price of health services, 12, perceived need and self-assessed health status, 1,, 14,, 17, the urban/rural regions of residence, 1,, 2,, 9,, 10,, 22,, 23, the characteristics of the healthcare delivery system, 8,, 14, and accessibility of healthcare services. 1,, 2,, 8,, 14, Although some systematic reviews are available on specific populations 15,, 32,- 34, or specific types of HSU, 18,, 19,, 35, to the best of our knowledge, no comprehensive review has so far been undertaken regarding the factors associated with HSU in the general adult population. Furthermore, all the numerous quantitative studies on the factors influencing HSU in recent years have addressed only one or some factors in preliminary investigations unsystematically and ambiguously. Additionally, there is a gap in the relevant literature regarding the overall association and direction of the relationship between the determinants and HSU. Accordingly, the current study is aimed to review all studies on outpatient HSU both in order to identify factors contributing to HSU among the general population based on Andersen&,rsquo s BM of HSU in observational, population-based studies and in order to provide a comprehensive and up-to-date overview of these determinants.Materials and MethodsStudy Design This systematic scoping review reviewed all available studies examined the factors of HSU in the general population. The study was approved by University of Social Welfare and Rehabilitation Sciences (IR.USWR.REC.1397.029). Search StrategyThis review was conducted between January 2008 and July 2018 and followed the PRISMA guidelines to identify published articles on factors related to HSU. Quantitative studies were searched from the most comprehensive related databases of Web of Science, MEDLINE (PubMed), and Scopus. Similarly, additional records were identified through a manual search of the reference lists of the included studies. In addition, two key concepts, namely determinants (factors) and HSU were combined using the keywords and titles in the respective databases. The search terms related to HSU (i.e. &,ldquo Health service utilization&,rdquo OR &,ldquo Health care utilization&,rdquo OR &,ldquo Health service use&,rdquo OR &,ldquo Health care use&,rdquo OR &,ldquo service utilization&,rdquo OR &,ldquo service use&,rdquo OR &,ldquo Health care utili*&,rdquo , OR &,ldquo Health service utili*&,rdquo ) were combined with those terms for factors (i.e. &,ldquo Determinant&,rdquo OR &,ldquo factor&,rdquo , OR &,ldquo predictor&,rdquo ). In order to have a more comprehensive search, we drew upon the entree of SCOPUS and the medical subject headings (MeSH) including the entry terms of PubMed as well.Inclusion CriteriaOnly quantitative, observational, cross-sectional, and secondary analysis studies, along with longitudinal surveys that predicted HSU by the adult population, were included in the study. Further, the outcome measure of this study was outpatient HSU such as any contact with formal HSU including private, public, and general practitioners, together with specialist physicians, for health need reasons by adults aged 15 and older. The study specifically focused on the use of services as a binary outcome (i.e. any use vs. no use). To be eligible for inclusion, the selected study must have assessed the association between HSU and any other factors (determinants). This study encompassed only original peer-reviewed research published in scientific journals in 2008 or afterwards. This cut-off point was chosen for reviewing more recent studies that were published in the last decade, with no restrictions on the geographic area of publication. Only papers published in the English language were included in the present review. Exclusion CriteriaStudies examining the use of informal health services (e.g. friends, family, and religious support) or complementary/alternative treatments (i.e. those provided outside the formal health sector or traditional medicine) were excluded from this review. Considering that the interest population of this study was the general adult population, the studies that only focused on specific subpopulations such as children, elderly, veterans, military forces, prisoners, immigrants, and those which involved participants not living in community settings (e.g. prisoners, inpatients, and the residents of elderly care homes) or were defined by their occupation (e.g. doctors, police officers, military forces, and students) were excluded from this review. Moreover, studies of HSU in special diseases whose participants&,rsquo experiences represented no wider population as well as those in which participants received specific types of HSU (e.g. maternal, mental HSU, or inpatient HSU) were not included in the current investigation. Additionally, these, reviews, letters to the editors, non-English articles, interventional or theoretical studies, irrelevant studies in terms of design and subject, studies with insufficient information or results, studies with data similar to or overlapping with those in other articles, studies with results that did not address outpatient HSU, and studies with retrospective data extracted from medical service center records were removed from the study.Study SelectionThrough the database search, we found 2530 papers. Further, we could identify another set of studies (i.e. 13) by carrying out a manual search in the relevant reference lists. After removing the duplicates, we reached 1813 articles, leading us to the title- and abstract-screening stage. The selection process was carried out in two phases. Following database search, the first (NS) and second (SEK) authors screened the identical 1813 titles/abstracts independently. Afterwards, they developed and adapted an eligibility assessment with reference to the initially specified features (refer to eligibility criteria). Later, the abstracts which remained were split into two groups and screened separately by each author. In cases of discord on the scope of the inclusion criteria, the researchers consulted the senior author (SHMK) to reach consensus. Following this procedure, 1667 studies were excluded at this phase of data selection. Moreover, from the remaining 146 studies, NS and SHMK assessed full-text papers independently to arrive at the final set of the most eligible studies. Meanwhile, they continued their discussions to resolve possible cases of disagreement under the supervision of the senior author (ASF). On the whole, 109 studies failed to satisfy the defined eligibility criteria, and thus they were excluded from further investigation. Therefore, merely 37 studies were found to be eligible for inclusion. The full procedure for study selection was conducted in line with PRISMA guidelines (figure 1,).Figure 1. PRISMA flowchart shows the selection of studies.The findings based on Anderson&,rsquo s behavioral model are described below.Quality AssessmentThe quality of the selected studies was evaluated by using the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) checklist. In other words, the quality assessment scale for cross-sectional studies was applied to assess the risk of bias in the included studies. 36,, 37, Qualitative assessments were independently conducted by two reviewers (NS and SK), and in the case of disagreement, the samples were referred to a third reviewer (SHMK). For simplicity, the study was considered to be of good or satisfactory quality if it achieved a score higher than 16 on the STROBE statement. No study turned out to be poor in terms of quality. Expressed differently, eight papers were classified as fair (11&,le score&,le 16), and the remaining 29 papers were considered good (score&,gt 16). Data ExtractionA predefined Excel spreadsheet was applied to extract data from the included studies. The extracted data pertained to date, type, design, and the context of the study, as well as the date of publication, sample size, participants, data source, data-collection times, HSU outcomes, and factors associated with HSU. Data AnalysisOwing to the special type of this scoping review examining the factors of HSU, a narrative synthesis was deemed the most appropriate method of data analysis.ResultsStudy Characteristics Overall, this review included 37 articles with samples from the general population. The total number of participants ranged from 200 to 327076. Most frequently, it included routine National HSU data or household survey databases. Sixteen (43.2%), six (16.2%), two (5.4%), four (10.8%), three (8.1%), three (8.1%), and two (5.4%) studies reported data from Asia, Europe, North America, South America, Africa, and the United States of America, along with international data from across world regions, respectively. Furthermore, one (2.7%) study reported data from Australasia and another (2.7%) from Central America.In general, the participants comprised both men and women aged 15 and over. Most studies (n=34) used retrospective data obtained from self-report measures. Furthermore, the articles included 34 cross-sectional and three longitudinal studies that recruited participants from the general population. Moreover, most studies de&,#64257 ned HSU as a dichotomous dependent variable. Thus, 30 days or 12 months were used as HSU indices prior to data collection (the interview) whether there was a self-reported need for outpatient care services, including primary or secondary health services, and whether the respondents had contacts with (visit) healthcare professionals (e.g. general practitioners and specialists) and received medication in the preceding two weeks. A summary of the results of the included studies is presented in table 1,.No.ArticleLocation (Country)Sample SizeDesign/ApproachParticipantsData SourceFactors (Determinants) of Health Service UtilizationQuality Assessment Score1Economou and others38,Belgium, Denmark, Greece, Ireland, Italy, Netherlands, Portugal, Spain, and the United KingdomN=327076Cross-sectional, secondary analysis, retrospective cohort Individuals &,gt 18 years oldEight Waves of the European Community Household Panel (ECHP) surveyUnemployment, income level, education level, age, marital status, being a member of any kind of social club, being out of the labor force, self-assessed health status, working hours per week212Gonz&,aacute lez &,Aacute lvarez and Barranquero39,SpainN=7500 Longitudinal Households and individuals &,ge 16 years oldEuropean Community Household Panel (ECHP) from 1994 to 2001Self-assessed health status, type of illness (e.g., chronic vs acute), need, education level, additional private health insurance, activity status (e.g., retiree or housewife), region of residence, doubled coverage versus publicly insured, sex, income213Krishnaswamy, Saroja, and others1,MalaysiaN=2202Cross-sectional, secondary analysis Malaysian citizens &,ge 16 years oldMalaysian Mental Health Survey (MMHS) Health complications, having disabilities, age, presence of chronic illnesses, non-Chinese ethnicities, lacking health facilities near the home, having little family support during illnesses204Lemstra and others40,Saskatoon, CanadaN=3433Cross-sectional (2000-2001-2003-2005) secondary analysisCanadian Community Health Survey (CCHS)Presence (prevalence) of heart disease, hypertension, diabetes,lower self-report health, higher age, low income135L&,oacute pez-Cevallos and Chi41,Ecuador28908 households and 33387 individualsCross-sectional, secondary analysisENDEMAIN 2004 surveyed households (individuals &,ge 12 years old)National Demographic and Maternal and Child Health Survey, 2004Ethnicity and race (mestizo), sex (male), age (aged 35), marital status (married), region of residence (urban), belonging to the highest household economic status and consuming quintiles (belongs to the highest assets and consumption quintile categories), education level (college), education level of the household head, health insurance, health problems during the previous 30 days, number of health problems206L&,oacute pez-Cevallos and Chi42,Ecuador10985 households and 46497 individualsCross-sectional, secondary analysisENDEMAIN 2004 surveyed households (individuals &,ge 12 years old)National Demographic and Maternal and Child Health Survey, 2004Density of public practice health personnel, density of service providers, density of health services per 10 000 inhabitants, socioeconomic status of households (assets and consumption quintiles), household wealth, density of private practice physicians, region of residence (rural), number of health problems, health insurance217Morera Salas and Aparicio Llanos43,Costa RicaN=4892Cross-sectional, secondary analysis Adults &,ge 15 years oldNational Survey of Health for Costa Rica (ENSA), 2006Education level, perceived health status, type of illness (chronic), geographical region of residence178&,#350 enol 44,Kayseri, Turkey1880 household members living in 576 householdsCross-sectional Household membersSeven Public Health Centers (PHCs) from 21 PHCs in the center of Kayseri between 2005 and 2006Marital status (married), sex (male), social insurance coverage, sufficient monthly income, proximity (&,amp lt 500 meters), poor perception of health, type of disease (chronic)189 Girma and others21,Jimma Zone, southwest Ethiopia836 householdsCross-sectional Household members (randomly selected one individual from each of the samples households)January 30 to February 08, 2007, in Jimma ZoneSex (male), marital status (married), household income (above the poverty line), socioeconomic status, presence of disabling health problems, presence of an illness episode in the previous 12 months, perceived transport costs, perceived treatment costs, distance to the nearest health center or hospital1710Lahana and others45,Thessaly, GreeceN=1372 (1042 Greeks and 330 Albanians)Cross-sectional Individuals &,ge 18 years oldCross-sectional study in 2006 in ThessalyHealthcare needs, self-perceived health, education level, income, age, ethnicity1811Tountas Lahana and others46,GreeceN=1005Cross-sectional, secondary analysis Adult population (individuals &,ge 18 years old)Nationwide Household Survey Hellas Health I, 2006Presence of a family doctor, social class (higher), region of residence, having private health insurance, education level, level of health needs (i.e., chronic illnesses), self-assessed, general health (low), sex (female)1812Afzal Mahmood and others47,AustraliaN=12914Cross-sectional, secondary analysis English-speaking persons aged between18 and 65 yearsAustralian Bureau of Statistics&,rsquo National Health Survey, 2001Household composition, living arrangements, age, sex (male), remoteness, socioeconomic status, body mass index, the status of heart condition, social support1813Hansen and others48,Troms&,oslash , NorwayN=12982Cross-sectional, secondary analysis Persons aged between 30 and 87 yearsThird Nord-Tr&,oslash ndelag Health Survey (HUNT 3) of 2006&,ndash 2008 (Household incomes and levels of education were appended from the national register data from Statistics Norway [SSB].)Self-rated health, income, education level1714Jahangeer49,PakistanN=1407 Cross-sectional, secondary analysis Individuals belonging to 855 urban householdsPakistan Socioeconomic Survey (PSES)Distance to a provider, household economic status and wealth (rich), duration of illness1215Nguyen50,VietnamN=16685Cross-sectional, secondary analysis Two most recent VHLSSs, conducted by the General StatisticalOffice of Vietnam (GSO), with technical support from the World Bank (WB) in the years 2004 and 2006Having voluntary health insurance1116Vikum and others51,NorwayN=44775 (24147 women and 20608 men)Cross-sectional, secondary analysis Women and men &,ge 20 years oldThird Nord-Tr&,oslash ndelag Health Survey (HUNT 3) of 2006&,ndash 2008 (Household incomes and levels of education were appended from the national register data from Statistics Norway [SSB].)High-income population, poor health, functional impairment and morbidity, living in the largest municipalities, age, sex, education level, the population size of the municipalities2017Barraza-Llor&,eacute ns and others52,MexicoN=234609 (110460 NHS 2000 and +124 149 NHNS 2006)Cross-sectional, secondary analysis Individuals &,ge 18 years oldNational Health Survey (NHS) 2000 and National Health and Nutrition Survey (NHNS), 2006Income (higher-income), living standards (3 standard-of-living measures, household income, wealth, and expenditure), health insurance status, education level, health need, poor self-assessed health status2118Gan-Yadam and others4,Ulaanbaatar, MongoliaN=500(465)Community-based, cross-sectionalAdults &,gt 18 years oldUrban and suburban residents of UlaanbaatarHousehold size ( &,gt 5), residential stability, attention to health checkups, having periodic dental and physical examinations, participating in group support activities, poor self-assessed health status, self-assessed long-standing illnesses, satisfaction with health services, income (low), sex (female), age, marital status (married), the stability of life, non-hospitalization during the preceding 3 years, proper documentation, having health insurance, unwillingness to obtain information about food and nutrition, having no concerns about food and nutrition, self-treatment over the preceding 12 months, willingness to receive treatment abroad1919Hassanzadeh and others31,Iran, MarkaziN=2711 Cross-sectional, secondary analysis All individuals &,ge 15 years old (2131)HCU survey (from 16 February to 1 March 2008)Sex (female), having a higher household wealth index, having inpatient need for healthcare, education level, income level (higher level), having insurance1720Mohammadbeigi and others53,Iran, MarkaziN=2711 Cross-sectional, secondary analysis All individuals &,ge 15 years old (2131)HCU survey (from 16 February to 1 March 2008)Region of residence, education level, disease severity (requiring hospitalization), sex (female), household expenditure index quintile (lowest), employment (being a housewife/retiree)1821Vikum and others54,Nord-Tr&,oslash ndelag, NorwayN=97251 (1 [n=48414], 2 [n=28167], or 3 [n=20670])Cross-sectional, secondary analysis (longitudinal)All individuals &,ge 18 years old Nord-Tr&,oslash ndelag Health Study (HUNT), HUNT1 (1984&,ndash 86), HUNT2 (1995&,ndash 97), and HUNT3 (2006&,ndash 08) + Statistics Norway (SSB) (Personal incomes and education data were appended from the national register data from Statistics Norway [SSB].)Income level (higher), education level (higher), socioeconomic status (higher), sex (female)1922Ownby and others55,United StatesN=475Cross-sectionalSpanish- and English-speaking participants &,ge 18 years oldHealth literacy (lower levels), number of health conditions, number of physical symptoms1223Chiavegatto Filho and others56,S&,atilde o Paulo, BrazilN=3588Cross-sectional, secondary analysis Residents &,ge 18 years oldThe Brazilian version of the World Mental Health Survey (between May 2005 and May 2007), plus data from the Brazilian Institute of Geography and Statistics (IBGE) in the 2010 censusSex (female), age (&,gt 60 years old), health insurance, education level (higher), income level (higher), having chronic illnesses, presence of mental illnesses in the preceding 12 months, living in areas (regions) with high median incomes and low violence levels2024Fields and others27,United States N=61039Cross-sectionalAdults aged between 18 and 64 years2006 to 2010 Medical Expenditure Panel Survey Household Component (MEPS HC)Health insurance continuity, the region of residence (residents of metropolitan areas), discontinuously insurance (gaps in insurance coverage)1925Nouraei Motlagh and others57,Tehran, Iran118000 individuals (34700 households)Cross-sectional, secondary analysis Residents aged between 15 and 64 years in 22 districts of TehranTehran Urban HEART Population-Based Survey, 2011Having members with chronic illnesses, income level, income deciles (upper-income groups), having insurance (insured individuals), age (households with members aged &,gt 65 years or &,amp lt 5 years) increases the likelihood of HSU, sex (female), education level (Higher Education), employment (number of employees [more] in the household), household size (Larger), homeownership (living in rental houses) decreases the likelihood of HSU2126Zhang and others58,China N=143212Cross-sectional, secondary analysis Adults &,ge 15 years old Fourth National Health Services Survey, 2008Household income (high-income groups), presence of chronic illnesses, type of insurance schemes, education level (higher), health insurance coverage/scheme, the shortest distance to health facilities, time to reach the nearest medical institution, need, health status (limitations of daily activities)2127Duckett and others59,ChinaN=3680Cross-sectional, secondary analysis (between 1 November 2012 and 17 January 2013)Mainland Chinese citizens aged between 18 and 70 yearsResearch Centre for Contemporary China (RCCC)Levels of distrust in clinics1728Kim and Lee60,KoreaN=13734Cross-sectional, secondary analysis Household membersSource data of the Korea Health Panel (jointly collected by the consortium of the National Health Insurance Service and the Korea Institute for Health and Social Affairs), between the years 2010 and 2012Sex (female), marital status (married), having chronic-illnesses as a need factor, age1529Kim and Casado61,Chicago, Illinois, United StatesN=212Cross-sectional, secondary analysis Adults &,ge 18 years old Survey of the Korean American Community in Chicago, Illinois, metropolitan area (between February and May 2012 )Age (older adults), having health insurance, citizenship, income level (high-income earners), sex, family networks, perceived health1730Sozmen and Unal62,TurkeyN=14655 individuals from 5668 households Cross-sectional, secondary analysis Adults &,ge 15 years old Turkish Health Survey, 2008Sex (female), having poor self-rated health, chronic illnesses (need factor), income level (lowest income quintile), education level, region of residence (rural), marital status1931Tran and others63,VietnamN=200Cross-sectionalFamily head or any other person at home to participate in the surveyAvailability of health services, number of health problems, perceived quality of health services, healthcare costs and expenditure, economic status, distance to community health centers, satisfaction with the availability of services, ethnicity (ethnic majority), the severity of health problems, distance (long-distance &,gt 2 km ) to healthcare facilities, unaffordability1232Abera Abaerei and others2,Gauteng Province, South AfricaN=27490Cross-sectional, secondary analysis Residents &,ge 18 years old Quality of Life Survey, 2013Sex (female), ethnicity (being white vs being African), having medical insurance, age (increasing), immigration status, employment status, quality of care in public healthcare services2133Bazie and Adimassie64,Dessie, EthiopiaN=420Community-based cross-sectional (January to March 2015)All adults &,gt 18 years old living in Dessie Town for 12 month preceding the study (the head of the household)All adults &,gt 18 years old and a member of that household for at least 12 months prior to the data collection periodSex (female), annual income greater than the poverty line, perception of health status (poor), perceived severity of illnesses (severe), number of acute illnesses in the preceding 12 months, having chronic health problems, community-level variables, time to arrive at the nearest modern healthcare center (access factors), perceived transportation costs, distance to healthcare delivery centers1734Fujita and others65,Chiba City, JapanN=166966Retrospective cohort Adults aged between 40 and 47 yearsRetrospective cohort study, conducted between April 2012 and March 2013 (Demographic data for each region were obtained from the 2010 Japanese census data.)Income level ( higher), age (elderly), sex (female), shorter travel time to the nearest facility, the density of healthcare facilities (higher), larger enhanced 2-step floating catchment area (E2SFCA) with slow decay, geographical access variables, travel time to the nearest health center, the density of health centers (number of health centers within 30 minutes&,rsquo walking distance of one&,rsquo s residence), supply-to-demand ratio1735Lostao and others66,Germany and SpainCross-sectional, (nationwide longitudinal survey) secondary analysisIn Germany, all adults &,ge 16 years old within each householdIn Spain, Spanish non-institutionalized adults aged between 16 and 75 yearsData from the 2006 and 2011 Socio-Economic Panel (SOEP), carried out in Germany, plus data from the 2006 and 2011 National Health Surveys, carried out in SpainIncome level (lower), education level1736Mojumdar 3,IndiaCross-sectional, secondary analysis Household members24th (1986&,ndash 1987) and 60th (2004&,ndash 2005) NSS dataAge (&,lt 5 years), the gender of the household head (female), household head&,rsquo s education level, marital status (married), household size, economic condition of households, monthly per capita consumption expenditure, occupational category of the household head, belonging to regular-income groups, the ratio of (percentage) earning members in the household, social class of households (belonging to the Scheduled Caste), town size (smaller town size), state-level income (low-income states per capita income, net state domestic product, type of ailment (duration of the illness/ having chronic ailment), the gender of ailing individuals (female), age of ailing individuals (children and aged members), the incidence of morbidity (higher)1437Ranjbar Ezzatabadi67,Iran, Isfahan1037 householdsCross-sectional in 2014Household membersResidents living in Isfahan ProvinceEconomic status (high), level of education, insurance coverage, gender of the head of household (male), type of illness (contagious/ non-contagious), presence of self-medication patterns12Table 1. Summary of the results of the included studiesQuality of Studies The quality of the included studies was assessed using the STROBE checklist. The outcomes of the quality ratings in the assessment checklist are pre-de&,#64257 ned as &,ldquo good&,rdquo (score&,gt 16), &,ldquo fair&,rdquo (11&,le score&,le 16), or &,ldquo poor&,rdquo (score&,lt 11). After assessing all the studies (n=37) with the 22-item checklist, 8 studies 3,, 40,, 49,, 50,, 55,, 60,, 63,, 67, achieved the fair scores (11&,le score&,le 16), while the remaining 29 studies received a &,ldquo good&,rdquo rating, 1,, 2,, 4,, 21,, 27,, 31,, 38,, 39,, 41,- 48,, 51,- 54,, 56,- 59,, 61,, 62,, 64,- 66, and no studies were excluded because of poor quality rating. Expressed differently, the study quality was rated as &,ldquo good&,rdquo (78.37%) for more than half of the studies, &,ldquo fair&,rdquo for 21.62% of the studies, and &,ldquo poor&,rdquo for no study.The aforementioned scoring procedure was not meant to assess the quality of the studies considering their own primary aims. As a matter of fact, this rating system was intended to assess the quality of the evidence pertinent to this review. As the majority of the scores for the quality assessment were ranked as &,ldquo good&,rdquo and a few with &,ldquo fair&,rdquo quality, all 37 studies were included in the results section, and the results were extracted. The results of the quality rating of the studies can be seen in table 1,.Factors Associated with Outpatient Health Service UtilizationAnderson&,rsquo s behavioral model of HSU was employed as a framework to classify the findings (Table 2,) of this review into predisposing, enabling, and need factors. 7,, 12,, 17, Variables and the Studies Researching Each VariableNumber of StudiesPredisposing Factors |