Development of the Rural Perception Scale (RPS-18)

Abstract

Background:

People living in rural areas often experience limited access to health resources, slow knowledge diffusion, and geographical isolation, and tend to be at higher risk for poor physical and mental health outcomes compared with nonrural populations. It is unclear, yet, how the concept of “rural” shapes observed differences from nonrural populations. We aim to develop a psychometrically sound scale to assess key dimensions that constitute individual-level perceived rurality.

Methods:

We first conducted a broad literature review to identify a priori concepts related to rurality and adapted survey items measuring relevant constructs, such as loneliness, attitudes toward people living in rural areas, and perceived social membership. We used these conceptual constructs and measures to develop a survey questionnaire focused on rural perceptions. We recruit residents in 3 rural states: Kentucky, New Hampshire, and Vermont. Using the explorative factor analysis and second-order measurement model in the structural equation model framework, we developed a rural perception scale consisting of 18 items.

Results:

We recruited 1,384 participants (n = 686 from KY; n = 698 from NH/VT) using Amazon Mechanical Turk (n = 897, 64.8%) and social media paid ads (n = 487, 35.2%). The average age of participants was 41 years old (SD = 15); 54.7% of respondents had less than college graduate education, and 94.2% reported their race as non-Hispanic White. Majority of the participants were from Rural Urban Commuting Area (RUCA)-designated urban areas (n = 798, 57.7%), followed by RUCA-designated large rural areas (257, 18.6%), RUCA-designated rural areas (n = 174, 12.6%) and RUCA-designated isolated areas (n = 133, 9.6%). Our final model revealed 4 latent constructs: “belonging” (Cronbach’s α = 0.896), “attitudes toward rural life” (Cronbach’s α = 0.807), “loneliness” (Cronbach’s α = 0.898), and “community social ties to people in their community” (Cronbach’s α = 0.846).

Conclusions:

We identified 4 subfactors of the umbrella concept of rurality that explain how people in rural regions may perceive being in rural environments and having rural lifestyles.

INTRODUCTION

Increasing research has called attention to enhancing health equity for people living in rural areas, where there is often poor access to resources, slow knowledge diffusion, and geographical isolation. Rural populations experience many health disparities, including some related to cancer. For example, rural residents are less physically active; less likely to be up-to-date with cancer screenings; have higher rates of smoking; and are diagnosed with colorectal, cervical, and lung cancers at higher rates than nonrural residents.^1,2 Further, rural residents have poorer access to most specialized health services and are significantly less likely to receive guideline-concordant care for certain conditions, including cancer.^3–5

Measures of rural health, such as these disparities, are reported by first applying a definition of “rural” and determining the prevalence of the health behavior or outcome for all individuals living within a specified geographic unit (eg, ZIP code or county) that is classified as “rural.” Policy and research experts acknowledge that defining rurality is complex and that no single definition of rurality can be consistently applied.⁶ This heterogeneity in definitions reflects geographic, economic, cultural, demographic, and policy dimensions. Common definitions are based on classification systems, such as the Rural-Urban Continuum Codes (RUCC), Rural Urban Commuting Area codes (RUCA), and Frontier and Remote Area codes—none of which were developed for health-related research.

Little is understood about the contextual factors inherent in the concept of rurality and whether these contextual factors influence observed patterns of health disparities for rural populations. Further, because the concept of “rurality” is not measured at an individual-level by taking psychological aspects (eg, perceived rurality) into consideration—rather attributed to an area-level geographic characteristic (eg, RUCA)—the extent to which any causal effects of geographically defined rurality can be linked to individual factors is not known. Few factors or perceptions that may shape behaviors and outcomes of rural residents at an individual-level have been examined, yet these factors may be important mechanisms by which the construct of “rural” influences observed patterns for rural populations. At the same time, when examining the influence of rurality on health-related measures, misclassification and erroneous associations may arise by using only a group-level rural classification based on geographic location.⁷ Onega et al. found that there are discrepancies between the geographically defined rurality and the perceived rurality.⁷ That is, residents in New Hampshire living in an urban area that is defined by the RUCC may still view themselves living in a rural area.

Although there is growing research attention on how rural research is lacking a scale that measures individual-level rurality in terms of potential mechanistic components that comprise the concept of “rural” to date, no comprehensive theoretical model or population-level data phenotyping perceived rurality exists. A psychometrically sound survey instrument measuring perceived rurality may explain health behaviors among rural populations and inform interventions to promote rural health equity.⁸ There is a critical need to identify factors that help to understand individuals’ perceptions of rurality first to develop a reliable assessment. Given the lack of a comprehensive questionnaire to assess how people perceive rurality, we aimed to develop a psychometrically sound survey instrument that captures conceptual mapping for how individuals perceive rural life, rural communities, and people living in rural areas—rural perceptions.

METHODS MEASURES

Demographic information and health characteristics

We measured sociodemographic characteristics (eg, age, sex, race/ethnicity, education, and income) and health status characteristics (eg, smoking, height/weight, and food security). The broader study also examined cancer-related characteristics, such as cancer communication patterns, cancer screening behaviors, cancer histories, and human papillomavirus (HPV) vaccine knowledge, as well as substance use characteristics. In this study, given our primary research goal of developing a rural perception scale, we focus on demographic and geographic characteristics in regard to factors that may contribute to rural perception.

Item generation for rural perception

Following standard scale development and report guidelines (eg, Refs. 9-11, see Table 1), we first defined the concept of rurality and conducted a literature review with target keywords (eg, rural perceptions and rurality scale) to identify conceptually relevant constructs that may constitute the umbrella concept of rurality. We expanded to include relevant search terms, such as “isolation” and “loneliness” as the literature suggests these constructs were closely related and manifested concepts among people living in RUCA-identified rural areas (eg, Refs. 12 and 13). Based on the search results, we pulled validated survey items that were conceptually related to these constructs, and complied a preliminary pool of 97 survey items. The constructs measured attitudes and perceptions related to rural residents, living in a rural area, and rural communities/towns. More specifically, we adapted survey items from the Texas Rural Survey,¹⁴ the Sense of Community Index 2 (SCI-2),¹⁵ the Three-Item Loneliness Scale,¹⁶ the Social Capital Scale,¹⁷ the Neighborhood Social Cohesion Instrument,¹⁸ the Semantic Differential Attitude Scale,¹⁹ and the Community Identify and Rural Identify Survey.²⁰ We conceptualized that constructs assessed in these questionnaires are critical in describing people’s views and perceptions about rurality.⁹ Both positively and negatively worded items were included to reduce potential response bias.²¹ Throughout an iterative review process at an item-level, we slightly modified the wording of items, when needed, to fit the context of the study, added leading statements prior to the survey items for ease of understanding, and reviewed survey items for item-level face validity. For example, the items from the Perceptions of Rural and Urban Living questionnaire borrowed from the 2013 Texas Rural Survey,³ which assesses positive and negative images of rurality and perceptions of urban living, were presented with the following leading statement: “Read each statement carefully and select the response that best describes your feeling and opinion. There is no right or wrong answer.” Appendix 1 presents how survey blocks were organized, the process of item-level modification, and leading statements for survey blocks. The entire procedure and strategy of developing the scale is described in Table 1.

TABLE 1.

A strategy and process to develop the scale and its outcomes.

Scale development procedure	Outcomes
1. Define the target construct	The target construct is Rural Perception. Rural Perception is an umbrella concept concerning how individuals perceive, characterize, and think of rural lifestyles, rural towns, and residents and people living in rural communities and towns.
2. Justify the need for the new measure	Little is understood about the contextual factors inherent in the concept of rurality and whether these contextual factors influence observed patterns of health disparities for rural populations. A psychometrically sound survey instrument measuring perceived rurality may explain health behaviors among rural populations and inform interventions to promote rural health equity. The proposed scale can enhance the knowledge base and health care practices pertinent to understanding how rurality is perceived and how that perceptions are related to rural health and rural populations.
3. Conduct literature review and define relevant subconcepts under the umbrella concept of “rural perception” to develop a preliminary pool of survey items	Based on the subconcepts relevant to rurality found in the literature review, we generated an initial pool of items and performed internal expert review for content validity. A total of 97 items were included in the preliminary pool. When needed, wording of the items and leading statements in the survey instruments were modified. See Appendix 1 for the modifications applied.
4. Describe sampling strategy and provide all dates of data collection	Multimodal online surveys were deployed in the Fall of 2017. We used Amazon Mechanical Turk (MTurk) and Facebook Ads to recruit adult residents in New Hampshire, Vermont, and Kentucky.
5. Run exploratory factor analysis (EFA)	We conducted EFAs to examine the underlying factor structure and refine the item pool. EFA results are presented in Table 2.
6. Discuss methodological limitations and directions for future research	We discussed how methodological limitations (eg, suboptimal sampling) may have influenced findings and psychometric properties. We also discussed future research directions (eg, testing the scale for measurement validation on different populations).

Recruitment

We recruited participants through the process of geo-targeting features of a market-leading crowdsourcing platform (Amazon Mechanical Turk [MTurk]) and social media paid advertisements (ie, Facebook/Instagram Ads, Twitter Ads, and Google Ads) to recruit residents in 3 largely rural states: Kentucky, New Hampshire, and Vermont in the Fall of 2017. We focused on these states due to the broader research focus of conducting a population health needs assessment to inform cancer centers’ cancer control efforts, using predefined cancer center catchment areas.²² We used state-level geotargeting features on social media platforms and MTurk to recruit survey participants in these 3 states. To prevent potential deception during online survey participation (eg, misrepresenting their information to become eligible for the survey), we embedded tactics, such as presenting randomly ordered decoy questions during eligibility screening, establishing double-verification procedures, and requesting participants’ residential ZIP codes and states.^23–26 To be eligible, participants had to be at least 18 years old and older and be current full-time residents of New Hampshire, Vermont, or Kentucky. We compensated participants from MTurk with USD $5/person for their time. Participants recruited from social media advertisements who provided their email addresses at the end of the survey to enter a raffle were compensated with a $15 e-gift card (n = 25 randomly selected).

Rural definition and source population

To develop this rural perception questionnaire among residents in rural states, we tested its dimensionality and association with geographically identified subgroups by RUCA codes. The RUCA categorization metric is based on population density, urbanization, and commuting patterns at the census tract by ZIP Code levels. We used a 4-tier RUCA classification scheme (urban, large rural, small rural, and isolated) to attribute an individual’s self-reported residential ZIP code to a rural-urban context. The ZIP code-level RUCA classification scheme is one of the most commonly used rural classification systems in health-related studies because individuals know their ZIP code of residence and they are readily linked to individual residential locations, patient addresses, and health care facilities. Other commonly used rural-urban classification systems, such as the RUCC, are not as geographically granular, being at the county level. RUCA codes are available at the census tract level, which are more uniform in population and geographic size than ZIP codes, but are not readily usable as most individuals do not know their census tract of residence; thus, we used ZIP code-level RUCA categories, which are predominant in health studies.

Data analysis and item selection

Prior to factor analysis, several items were reverse-coded to indicate higher values being positive perceptions toward rurality. We performed a series of explorative factor analyses (EFAs) to determine the number of latent constructs that explain the correlations among a set of manifest variables and to reduce items.²⁷ Exploratory factor analyses were repeated, stratified by RUCA designation to determine if the item loadings were similar by RUCA designation (urban vs rural groups). A series of factor analyses was performed to examine construct validity prior to finalizing the factor structure. A sensitivity analysis was conducted between 2 subsamples of NH/VT residents and Kentucky residents to compare final items across the 2 subsamples to check for consistency. The identical sensitive analysis procedure was also repeated between rural and urban subsamples. Starting with a preliminary pool of 97 items, we proceeded with item selection and removal based on face validity, item-level relevancy, the Kaiser-Mayer-Olkin (KMO) indicators for the suitability of the items for factor analysis, theoretical justification, and a consensus between expert reviews (eg, Refs. 28 and 29). For example, in addition to evaluating factor loading coefficients and KMO indicators, we removed items that were considered less theoretically relevant, or conceptually overlapping with other items to develop a parsimonious set of survey items.

Based on the final set of items, we examined the relationships among subfactors, the relationships among items, and the relationships between subfactors and items in a single set of multivariate regression equations.²⁷ Analyses were conducted using MPlus version 7.4 and SPSS version 22.^27,30

RESULTS

We recruited 1,384 participants from the 3 states (KY = 682, 49.3%; NH = 435, 31.4%; VT = 267, 19.3%). The majority of the sample were females (n = 973, 70.3%). Participants reported an average age of 40.68 years old (minimum = 18, maximum = 90, median = 37, SD = 14.99), 54.7% of respondents had less than college graduate education, and 94.2% reported their race as non-Hispanic White. Annual income less than $50,000 per year was reported by 60.8% (n = 829) of the 1,364 participants. More than one-third of the participants (n = 473, 34.2%) indicated having Medicare (n = 178, 12.9%) or Medicaid or another state program (n = 295, 21.3%) as their primary insurance coverage. The majority of the participants were from RUCA-designated urban areas (n = 798, 57.7%).

Preliminary analyses

The response distributions of all individual items were examined. The values for skewness and kurtosis of all the items were between −2 and +2, which is the acceptable skewed or kurtotic range^31,32; as such, no items were removed from the analyses based on their distributions.

Exploratory factor analysis

KMO assessment supports the use of factor analysis that the items are grouped in a set of underlying factors (KMO = 0.96). The item reduction process was performed using a maximum likelihood (ML) extraction with a rotation method of promax.³³ Items with communality extract coefficients lower than 0.50 and those less relevant to the conceptual definitions of the target concept (rurality) were not included in further analysis,³³ leading to 68 items. A second round of KMO assessment was performed on the reduced set of items and those with communalities greater than 0.50 were retained for further analysis, leading to a set of 61 items in total (Appendix 2). Data were divided into 2 groups (Urban group vs Rural group) based on zip code alignment with RUCA categorization of urban, large rural, small rural, and isolated. Given the distribution and conceptual agreement, we aggregated participants with RUCA urban designation (57.7%) as the Urban group and those with RUCA’s large rural, small rural, and isolated designations as the Rural group (40.8%). KMO scores were examined for Urban versus Rural groups separately and comparatively. To be included in further analysis, items with extraction communalities had to be greater than 0.50 in both groups, and the value had to be greater in the Rural group compared to the value in the Urban group. Extraction communalities are estimates of the variance in each item accounted for in the factor solution. Low values (< 0.3) indicate that the item does not represent well with the other variables.^34,35 Based on these item-inclusion criteria as well as the theoretical evaluation of each item, a set of 29 items were retained (Appendix 3). A final EFA using ML extraction with promax was performed with the reduced set of 29 items. Items with factor loading scores greater than 0.50 and good discriminant validity with no cross-loading across factors were remained for subsequent modeling (Appendix 3), leading to 25 items. The loneliness factor had 2 items; given that the loneliness scale isfrom a previously validated 3-item scale, we included the left-out item, ID #96 “How often do you feel left out?” and removed the item with low factor loading value and conceptual relevancy, ID #84 “The people I interact with in my community would help me fight an injustice” (see Table 2 for 25 items).

TABLE 2.

Four-factor structure and item loading coefficients.

Item ID #	Survey items	1 (α = 0.92)	2 (α = 0.85)	3 (α = 0.90)	4 (α = 0.82)
63	Fitting into this community is important to me.	0.79
73	I feel hopeful about the future of this community.	0.75
68	This community has good leaders.	0.74
90	Interacting with people in my community makes me feel connected to the bigger picture. [R]	0.74
89	Interacting with people in my community makes me feel like part of a larger community. [R]	0.74
65	I care about what other community members think of me.	0.63
54	Being a member of this community makes me feel good.	0.73
51	I get important needs of mine met because I am part of this community.	0.68
62	Being a member of this community is a part of my identity.	0.66
52	Community members and I value the same things.	0.65
74	Members of this community care about each other.	0.64
43	I would say, living in a rural area is… Unpleasant: Pleasant		0.89
41	I would say, living in a rural area is… Bad: Good		0.88
42	I would say, living in a rural area is… Harmful: Beneficial		0.87
50	I would say, living in a rural area is… Preferred: Not preferred [R]		0.79
48	I would say, living in a rural area is… Acceptable: Unacceptable [R]		0.74
45	I would say, living in a rural area is… Boring: Stimulating		0.73
96	How often do you feel left out?			0.90
97	How often do you feel isolated from others?			0.90
95	How often do you feel that you lack companionship?			0.88
16	Most of the people in my community know me.				0.89
15	I know most of the people who live around me.				0.82
58	I can recognize most of the members of this community.				0.77
80	The people I interact with in my community would put their reputation on the line for me.*
82	The people I interact with in my community would share their last dollar with me.*

Note: An item with an asterisk character was dropped due to a relatively low factor loading coefficient. R: Reverse-coded items. 1 = Belonging; 2 = Attitudes; 3 = Loneliness; 4 = Community Social Ties.

Factor analysis with reduced items

We examined item-level factor loading scores in the measurement models. For item-level convergent validity, items with factor loading greater than 0.60 were included, and items with weak discriminant validity were excluded for further analysis. The 25-item measurement model explained 63.18% of the total variance in the data. Based on the latent construct structure and item loading coefficients, we examined whether the content of items within each subfactor conceptually fit to the target subfactor as well as the broader umbrella concept of rural perception (see Table 2 for factor loadings).

Factor structure

Parallel analysis, the Monte Carlo simulation approach, was used to determine the number of factors that had statistically significant eigenvalues.^36,37 Based on the results from parallel analysis with permutations of the raw data set, we retained 4 subfactors. The 4 subfactors explained 61.9% of the total variance in the data. The first factor relates to a sense of community membership; the second factor focuses on positive and negative attitudes toward living in a rural area; the third factor is concerned with loneliness; and the fourth factor includes survey items regarding perceived closeness to people (Table 2). Each factor was labeled as Belonging (Cronbach’s α = 0.92), Attitudes (Cronbach’s α = 0.85), Loneliness (Cronbach’s α = −0.90), and Community Social Ties (Cronbach’s α = 0.82), respectively.

Item-level sensitivity by subgroups

A series of factor analysis was performed among 23 items among overall sample and between 2 subsamples of NH/VT residents and Kentucky residents to compare factor loadings across groups. For consistency, differences of item loading across overall, NH/VT, and KY groups had to be less than 0.15, and factor loadings with smaller than 0.60 in any groups were removed, leading to 21 items (Figure 1).

FIGURE 1.

Factor loading scores for 4 rural perception factors by overall, New Hampshire/Vermont, and Kentucky. Note: Items with an asterisk character were removed for further analysis. [R] = reverse-coded items.

Bivariate associations between covariances and rural perception subconstructs

Demographic characteristics and geographic characteristics of residential areas were used to see if there are any subgroup differences in rural perceptions. We examined bivariate associations between covariances and 4 of the rural perception subconstructs. We found that age was related to positive attitudes toward living in a rural area, and older people tend to have a greater sense of closeness and social ties to people in the rural community. The more educated, the more likely people felt a sense of belonging to the community and expressed a greater sense of social ties with people in the community. People who reported a difficulty in securing income were more likely to have a decreased sense of belonging and greater loneliness. People who perceived their community to be more rural than in actuality (based on their zip code’s alignment with RUCA 4 categorization) expressed positive attitudes toward living in rural areas, felt less lonely, and reported a greater sense of social ties and connectedness with people around them (Table 3).

TABLE 3.

Bivariate associations between covariates and rural perception subconstructs.

	1	2	3	4
2	0.37**	.	.	.
3	−0.35**	−0.17**	.	.
4.	0.46**	0.21**	−0.28**	.
Age	–	0.15**	–	0.13**
Sex	–	−0.09**	–	–
Education	0.07*	–	–	−0.11**
Income	–	–	−0.19**	–
Financial satisfaction	−0.10**	–	0.28**	–
Rural perception congruency	–	0.11**	−0.06*	0.06*
RUCA 4				0.17**

Note: 1 = belonging: sense of community membership; 2 = attitudes: a greater value indicates positive attitudes toward living in a rural area; 3 = loneliness: a greater value indicates more loneliness; 4 = connectedness: a sense of connectedness to people in the community. Sex 0 = Female and 1 = Male. For the education variable, the greater the value, the longer years of education (1 = less than 12 years [did not graduate]; and 6 = postgraduate). Financial satisfaction the lowest value indicates living comfortably on present income and the highest value indicates “finding it very difficult on present income.” The rural congruency score ranged between −3 and 3: a greater value indicates perceiving their community more rural/isolated than their zip code-based RUCA category. RUCA 4 Categories and perceived RUCA (1 = urban, 2 = large rural, 3 = small rural, 4 = isolated). All denoted values are Pearson’s correlation coefficients significant, and nonsignificant correlation coefficients are left blank.

^*P < .05.

^**P < .01.

Exploratory measurement model

MPlus was used to examine measurement models in the structural equation framework. The initial measurement model structure was estimated with each of the 21 items loading onto the latent factor. A total of 21 items were fit to the data with 4 first-order latent constructs (belonging, attitudes, isolation, and community social ties) and 1 second-order factor (rural perception). Based on the path coefficients, 2 items with negative values were removed from the initial model. The modified model had an improved model fit, CFI = 0.851, RMSEA = 0.085, SRMR = 0.077. Based on the conceptual links and modification indices, 3 correlated error terms were included between items within the latent factor. The model fit improved, CFI = 0.93, RMSEA = 0.07, SRMR = 0.06.

Based on the standardized path coefficients, an item that does not add substantial information in explaining variances of the latent factor was dropped. The item was “living in a rural area is Bad- Good” (0.43). An additional correlated error term was included in the model. The revised second-order measurement model with a reduced set of 18 items had CFI = 0.94, RMSEA = 0.065, SRMR = 0.065, indicating a good model fit (Figure 2).

FIGURE 2.

The second-order measurement model with latent constructs and 18 items. Note: CFI=0.94, RMSEA=0.065,SRMR=0.065. All path coefficients are significant. Numbers in the boxes indicate item ID numbers listed in Appendix 1. Items in the model include:

Belonging (Cronbach’s α = 0.896)

63 Fitting into this community is important to me.

73 I feel hopeful about the future of this community.

68 This community has good leaders.

54 Being a member of this community makes me feel good.

62 Being a member of this community is a part of my identity.

52 Community members and I value the same things.

74 Members of this community care about each other.

Attitudes (Cronbach’s α = 0.807)

43 I would say, living in a rural area is… Unpleasant: Pleasant

42 I would say, living in a rural area is… Harmful: Beneficial

50 I would say, living in a rural area is… Preferred: Not preferred [R]

48 I would say, living in a rural area is… Acceptable: Unacceptable [R]

45 I would say, living in a rural area is… Boring: Stimulating

Loneliness (Cronbach’s α = 0.898)

95 How often do you feel that you lack companionship?

96 How often do you feel left out?

97 How often do you feel isolated from others?

Community Social Ties (Cronbach’s α = 0.846)

16 Most of the people in my community know me.

15 I know most of the people who live around me.

58 I can recognize most of the members of this community. Use of a 5-point or 7-point likert scale is recommended for response options.

DISCUSSION

This study is the first, to our knowledge, that provides a comprehensive and methodologically sound scale for a novel measure of rural perceptions; namely, the Rural Perception Scale 18 (RPS-18). The scale is designed to assess perceptions toward people residing in rural America, rural lives, and rural communities through 4 dimensions (ie, a sense of belongingness, attitudes toward living in a rural area, loneliness, and closeness to community/social ties). We anticipated that these dimensions should manifest more strongly among individuals living in rural areas than those living in urban areas. Unlike other measures of rurality, which attribute rurality to population-based geographic locations, this scale measures individual-level components related to the concept of rurality that may be causal factors in the contextual influence of rurality on health measures.

In this work, we developed the scale based on a 97-item preliminary survey pool that was administered to individuals via a multimode survey method. In developing the RPS-18,4 dominant domains emerged: Belonging, Attitudes, Loneliness, and Community Social Ties. These 4 factors explained most of the variance for questions related to the overarching concept of rural perception. We examined the RPS-18 in relation to sociodemographic characteristics, and to residential-based rurality. The 4 subfactors of the RPS-18 were related to demographic characteristics, such as a greater sense of social ties was correlated with older age and higher education. People with greater financial satisfaction reported a lower sense of belongingness and community membership than people with lower financial satisfaction. The development of the RPS-18 offers a complementary approach to measuring rural perceptions, in addition to residential-based classifications, which may capture inherent, contributing factors of rural health and rural well-being. Subsequent work should validate and relate the RPS-18 to individual-level health measures (eg, cancer screening, obesity, and mental health).

The 4 subfactors of the RPS-18 scale–belonging, attitudes, loneliness, and social ties–are not typically reported in health or health behavior assessments. However, some of these factors have been identified in sociological studies as important to the concept of rurality. For example, belonging–which we found to be a strong subfactor in the concept of rurality–has been previously described in ethnography as a cultural structure of rural communities that mediates the association between the individual and the community.³⁸ Belonging for rural individuals has been defined as a social association within a locality, and takes on various forms, such as kinship, neighborhood, class, trade/labor group, sect, and ethnicity.³⁸ A sense of closeness with people in the community (community social ties) is related to belongingness, but it refers more distinctly to close psychological distance with people and social ties within a locality and/or community. The subconcept of community social ties can be thought of as the inverse of social isolation, which has been examined in a recent health-related study. As in our study, which found greater social ties with people in the community associated with a perception of more rural, that study found less social isolation for rural individuals.¹³ Further, that study found a mixed effect of loneliness, depending on the degree of rurality. Individuals in noncore rural areas had the greatest loneliness reported, but micropolitan rural less so. Our study found less loneliness associated with rurality. In the Henning-Smith et al. study,¹³ individuals were classified a priori, based on the RUCA of residence, and the factors were then summarized within those residence-based rural categories. Thus, the development of a rural perception scale allowed salient factors to arise from within the data, agnostic of geographical rural classification.

Other rural scales have been developed to try to capture elements of rurality within the contextual geographic unit. For example, Doogan et al. developed a geographic isolation scale as a continuous measure from the perspective of access to resources for rural health disparities.¹² Similar to the RPS-18, that measure showed good construct validity. Unlike our measure, however, it was based on residential location as the premise for defining the key parameters. In another study by Oser et al.,⁸ authors have developed and validated a single-factor scale containing 15 items with a factor loading of 0.40 or greater (Cronbach’s α = 0.83). Distinct from ours, Oser et al.’ Rural Identify Scale items focus on the day-to-day lived experiences of rural residents and include items reflective of activities and events common in rural life (eg, preserving vegetables, fruits, and/or herbs, and going to county festival/fair attendance) and also the historical connection to their community (eg, familial roots). Although none of the items in this scale overlaps with ours, both the Rural Identify Scale and the Rural Perception Scale are designed to measure how individuals are connected to and perceive their rural communities and lives, and how this perceived identify or perception might impact health and well-being of the individuals.

Examining the 4 factors of the RPS-18 in relation to RUCA category of residence reveals strong congruency of rural perception with rural residence for belonging, but perceiving one’s rurality greater than that of the actual RUCA of residence is correlated with more positive attitudes about rural locales, stronger perceived social ties, and less loneliness.³⁹ Thus, the RPS-18, as a validated measure of rural perception, seems to capture individual-level perceived rurality distinctly from the residence-based attribution of rurality. Including the individual-level perception of rurality when considering the influence of rurality on health and health measures seems likely to be an important adjunct to geographic-unit-based attribution of rurality, which may be coarse, and also does not capture potential mechanistic influences.

Limitations

This study offers novel findings, but has some limitations imposed by study designs. First, although we benefited from our multimode recruitment strategies, online sampling is yet considered as nonprobability sampling. Note that in our data there were more Whites (White in the NH/VT sample = 95.9%; White in the KY sample = 93.4%) and females (69.9% in the NH/VT sample; 70.7% in the KY sample) compared to the state populations (Whites: 86.9% ~ 93.8% Females: 50.0% ~ 50.3%). There is no standard operation of accomplishing random sampling through social media or crowdsourcing platforms. We argue that it will be worthwhile to establish online-based probability sampling methods as online platforms are becoming ubiquitous and pervasive recruitment tools more so than traditional sampling methods using mail and telephone. Second, this study introduces the development of the scale, but to establish a strong validity, the scale needs to be replicated and validated across heterogeneous samples. In this study, we used 1 data set and conducted exploratory analyses to develop a scale, while combining data from multimodes. It is strongly recommended that a separate data set be used to validate the scale. Neither did we have a capacity to administer the survey with a new sample nor split the data into 2 groups for a development data set and a validation data set, respectively. We instead used the entire data set to explore factor structure and perform factor analysis and item reduction. We suggest future research validate the proposed factor structure and replicate construct validity tests. Lastly, it should be noted that this scale was only administered in 3 rural states (ie, New Hampshire, Vermont, and Kentucky). The factor structure and item loadings of the scale may fit very differently if data from other rural regions of the United States (eg, Mississippi Delta, rural Southwest) were used. Future study should test the scale and further validate by using heterogeneous rural populations.

CONCLUSIONS

We explored and developed the Rural Perception Scale, a survey instrument that will help researchers assess the social, psychological, and culture dimensions of rural perception. The scale consists of 4 key subfactors of the umbrella concept of rurality, including belongingness, attitudes toward rural lives, loneliness, and perceived closeness to social ties in rural communities. The scale reflects how people in rural regions may perceive being in rural environments and having rural lifestyles. Although further validation research on the scale is necessary to further define its psychometric properties across heterogeneous rural populations and rural regions in the United States, this scale can be used to capture individual-level perceptions about rural lives, rural communities, and rural people which may explain rural health disparities.

APPENDIX 1:

RESOURCES, CONSTRUCTS, AND ADJUSTMENTS OF A PRELIMINARY POOL OF 97 SURVEY ITEMS

Resources and instructions	Constructs	Item No.	Items
Five items from the neighborhood social cohesion scale18 were borrowed, and presented with this leading statement: “For the next set of questions, think about the community where you currently live. Please indicate how much you agree or disagree with the following statements.” Original item of #5 was “People in this neighborhood or community do not share the same values.”	Capital efficiency	1	People around here are willing to help their neighbors.
		2	This is a close-knit neighborhood or community.
		3	People in this neighborhood or community can be trusted.
		4	People in this neighborhood or community generally do not get along with each other.
		5	People in this neighborhood or community do not share the same values as I do.
Six items from Ref. 20 were adapted and slightly modified as follows: Item #6 was “How much do you see yourself belonging to a rural community?” Item #7 was “How much is being from a rural community a part of who you are?” Item #8 was “How much do you identify with people who live in rural communities?” Rural identify items were presented with this leading statement: “Please indicate how much each of the following statements describes you.”	Rural identity	6	To what extent do you see yourself belonging to a rural community.
		7	To what extent is being from a rural community a part of who you are.
		8	To what extent do you identify with people who live in rural communities.
		9	To what extent do you feel your general attitudes and opinions are similar to people who live in rural communities.
		10	To what extent do you feel that you are typical of people who live in rural communities.
		11	To what extent do you consider yourself a city person.
Six items from Ref. 20 were borrowed and presented with the following leading statement: “The following items ask your opinions about the place where you currently live. Please indicate how much you agree or disagree with each statement below by filling in one choice on each line.”	Community identity	12	I want to live in my community for a long time.
		13	I feel at home in my community.
		14	I feel a sense of loyalty to my community.
		15	I know most of the people who live around me.
		16	Most of the people in my community know me.
		17	I feel a sense of connection with other people in my community.
We borrowed the Perceptions of Rural and Urban Living questionnaire from the 2013 Texas Rural Survey,14 which assesses positive and negative images of rurality and perceptions of urban living. Items were presented with the following leading statement: “Read each statement carefully and select the response that best describes your feeling and opinion. There is no right or wrong answer.”	Positive images of rurality	18	Rural areas have more peace and quiet than do other areas.
		19	Rural life brings out the best in people.
		20	Rural families are more close-knit and enduring than are other families.
		21	Neighborliness and friendliness are more characteristic of rural communities than other areas.
		22	Rural communities are the most satisfying of all places to live, work, and play.
		23	Rural life is closer to nature, and it is more wholesome.
		24	Life in rural communities is less stressful than life elsewhere.
		25	There is less crime and violence in rural areas than in other areas.
		26	Rural people are more likely than other people to accept you as you are.
	Negative images of rurality	27	Rural people are crude and uncultured in their talk, actions, and dress.
		28	Rural life is monotonous and boring.
		29	Living in rural areas means doing without the good things in modern society.
		30	Rural people are suspicious and prejudiced toward anyone not like themselves.
		31	Rural communities provide few opportunities for the individual to get ahead in life.
		32	Rural people are closed-minded in their thinking.
		33	Rural communities provide few opportunities for new experiences.
	Perceptions of urban living	34	Urban life is complex, fast-paced, and stressful.
		35	Political corruption is a fact of life in the urban areas of my state.
		36	Crime and violence characterize life in the urban areas of my state.
		37	The relationships among people in urban areas are impersonal and uncaring.
		38	Urban areas are artificial settings that separate people from nature.
		39	Urban areas are crowded, dirty, and noisy environments in which to live.
		40	Urban life is too centered on the quest for money.
We adapted the Semantic Differential Attitude scale from Ref. 19 and modified by replacing [smoking cigarettes] with [living in a rural area]. For example, the original Item #41 was “I would say smoking cigarettes is bad: good.” The 10 items assessing semantic differential attitudes toward living in a rural area were presented with the following leading statement. “Please indicate how you feel about living in the community where you live.”	Semantic Differential Rural Attitude scale	41	I would say, living in a rural area is Bad: Good
		42	I would say, living in a rural area is Harmful: Beneficial
		43	I would say, living in a rural area is Unpleasant: Pleasant
		44	I would say, living in a rural area is Dull: Interesting
		45	I would say, living in a rural area is Boring: Stimulating
		46	I would say, living in a rural area is Desirable: Undesirable [R]
		47	I would say, living in a rural area is Appealing: Unappealing [R]
		48	I would say, living in a rural area is Acceptable: Unacceptable [R]
		49	I would say, living in a rural area is Limiting: Not limiting
		50	I would say, living in a rural area is Preferred: Not preferred [R]
24 items from the Sense of Community Index-2 (SCI-2) by Chavis et al.15 were borrowed. These items were presented with the following leading statement: “Please indicate how well each of the following statements represent how you feel about the community where you live.”	Subscale Reinforcement of needs	51	I get important needs of mine met because I am part of this community.
		52	Community members and I value the same things.
		53	This community has been successful in getting the needs of its members met.
		54	Being a member of this community makes me feel good.
		55	When I have a problem, I can talk about it with members of this community.
		56	People in this community have similar needs, priorities, and goals.
	Membership	57	I can trust people in this community.
		58	I can recognize most of the members of this community.
		59	Most community members know me.
		60	This community has symbols and expressions of membership such as clothes, signs, art, architecture, logos, landmarks, and flags that people can recognize.
		61	I put a lot of time and effort into being part of this community.
		62	Being a member of this community is a part of my identity.
	Influence	63	Fitting into this community is important to me.
		64	This community can influence other communities.
		65	I care about what other community members think of me.
		66	I have influence over what this community is like.
		67	If there is a problem in this community, members can get it solved.
		68	This community has good leaders.
	Shared emotional connection	69	It is very important to me to be a part of this community.
		70	I am with other community members a lot and enjoy being with them.
		71	I expect to be a part of this community for a long time.
		72	Members of this community have shared important events together, such as holidays, celebrations, or disasters.
		73	I feel hopeful about the future of this community.
		74	Members of this community care about each other.
20 items were adapted from Ref. 15, modified by replacing [online/offline] with [in my community]. For example, the original item of the Item #75 was “There are several people online/offline I trust to help solve my problems.” The 20 items measured 2 subscales: Bonding and Bridging.	Bonding	75	There are several people in my community I trust to help solve my problems.
		76	There is someone in my community I can turn to for advice about making very important decisions.
		77	There is no one in my community who I feel comfortable talking to about intimate personal problems.
		78	When I feel lonely, there are several people in my community I can talk to.
		79	If I needed an emergency loan of $500, I know someone in my community I can turn to.
		80	The people I interact with in my community would put their reputation on the line for me.
		81	The people I interact with in my community would be good job references for me.
		82	The people I interact with in my community would share their last dollar with me.
		83	I do not know people in my community well enough to get them to do anything important.
		84	The people I interact with in my community would help me fight an injustice.
Items under the Bridging subscale was modified as those in the Bonding subscale. For example, the original statement of Item #85 was “Interacting with people online/offline makes me interested in things that happen outside of my town.” For items under the Bridging subscale, we adapted items from Ref. 17 and modified by replacing [online/offline] with [in my community]	Bridging	85	Interacting with people in my community makes me interested in things that happen outside of my community.
		86	Interacting with people in my community makes me want to try new things.
		87	Interacting with people in my community makes me interested in what people unlike me are thinking.
		88	Talking with people in my community makes me curious about other places in the world.
		89	Interacting with people in my community makes me feel like part of a larger community.
		90	Interacting with people in my community makes me feel connected to the bigger picture.
		91	Interacting with people in my community reminds me that everyone in the world is connected.
		92	I am willing to spend time to support general community activities.
		93	Interacting with people in my community gives me new people to talk to.
		94	In my community, I come in contact with new people all the time.
The Three-Item Loneliness Scale was borrowed16 to measure loneliness. These 3 items were presented with the following leading statement was: “The next questions are about how you feel about different aspects of your life in your community. For each one, indicate how often you feel that way about living in your community.”	Loneliness	95	How often do you feel that you lack companionship?
		96	How often do you feel left out?
		97	How often do you feel isolated from others?

APPENDIX 2:

RURAL PERCEPTION SURVEY ITEMS (97 ITEMS)

Constructs	Item No.	Items	Inter-item reliability (α)	First round: KMO >0.50	Second round: KMO >0.50
Capital efficiency	1	People around here are willing to help their neighbors.	0.74	x	x
	2	This is a close-knit neighborhood or community.		x
	3	People in this neighborhood or community can be trusted.		x	x
	4	People in this neighborhood or community generally do not get along with each other.
	5	People in this neighborhood or community do not share the same values as I do.
Rural identity	6	To what extent do you see yourself belonging to a rural community.	0.87	x	x
	7	To what extent is being from a rural community a part of who you are.		x	x
	8	To what extent do you identify with people who live in rural communities.		x	x
	9	To what extent do you feel your general attitudes and opinions are similar to people who live in rural communities.		x	x
	10	To what extent do you feel that you are typical of people who live in rural communities.		x	x
	11	To what extent do you consider yourself a city person.
Community identity	12	I want to live in my community for a long time.	0.88	x	x
	13	I feel at home in my community.		x	x
	14	I feel a sense of loyalty to my community.		x	x
	15	I know most of the people who live around me.		x	x
	16	Most of the people in my community know me.		x	x
	17	I feel a sense of connection with other people in my community.		x	x
Positive images of rurality	18	Rural areas have more peace and quiet than do other areas.	0.85
rurality	19	Rural life brings out the best in people.		x
	20	Rural families are more close-knit and enduring than are other families.
	21	Neighborliness and friendliness are more characteristic of rural communities than other areas.
	22	Rural communities are the most satisfying of all places to live, work, and play.		x	x
	23	Rural life is closer to nature, and it is more wholesome.
	24	Life in rural communities is less stressful than life elsewhere.
	25	There is less crime and violence in rural areas than in other areas.
	26	Rural people are more likely than other people to accept you as you are.
Negative images of rurality	27	Rural people are crude and uncultured in their talk, actions, and dress.	0.84
	28	Rural life is monotonous and boring.		x
	29	Living in rural areas means doing without the good things in modern society.
	30	Rural people are suspicious and prejudiced toward anyone not like themselves.	x	x
	31	Rural communities provide few opportunities for the individual to get ahead in life.		x	x
	32	Rural people are closed-minded in their thinking.		x	x
	33	Rural communities provide few opportunities for new experiences.		x	x
Perceptions of urban living	34	Urban life is complex, fast-paced, and stressful.	0.83
	35	Political corruption is a fact of life in the urban areas of my state.
	36	Crime and violence characterize life in the urban areas of my state.
	37	The relationships among people in urban areas are impersonal and uncaring.		x
	38	Urban areas are artificial settings that separate people from nature.		x
	39	Urban areas are crowded, dirty, and noisy environments in which to live.
	40	Urban life is too centered on the quest for money.		x
Semantic Differential Rural Attitude scale	41	I would say, living in a rural area is Bad: Good	0.92	x	x
	42	I would say, living in a rural area is Harmful: Beneficial		x	x
	43	I would say, living in a rural area is Unpleasant: Pleasant		x	x
	44	I would say, living in a rural area is Dull: Interesting		x	x
	45	I would say, living in a rural area is Boring: Stimulating		x	x
	46	I would say, living in a rural area is Desirable: Undesirable [R]		x	x
	47	I would say, living in a rural area is Appealing: Unappealing [R]		x	x
	48	I would say, living in a rural area is Acceptable: Unacceptable [R]		x	x
	49	I would say, living in a rural area is Limiting: Not limiting
	50	I would say, living in a rural area is Preferred: Not preferred [R]		x	x
Subscale Reinforcement of needs	51	I get important needs of mine met because I am part of this community.	0.91	x	x
	52	Community members and I value the same things.		x	x
	53	This community has been successful in getting the needs of its members met.		x	x
	54	Being a member of this community makes me feel good.		x	x
	55	When I have a problem, I can talk about it with members of this community.		x	x
	56	People in this community have similar needs, priorities, and goals.
Membership	57	I can trust people in this community.	0.92	x	x
	58	I can recognize most of the members of this community.		x	x
	59	Most community members know me.		x	x
	60	This community has symbols and expressions of membership such as clothes, signs, art, architecture, logos, landmarks, and flags that people can recognize.
	61	I put a lot of time and effort into being part of this community.		x	x
	62	Being a member of this community is a part of my identity.		x	x
Influence	63	Fitting into this community is important to me.	0.85	x	x
	64	This community can influence other communities.
	65	I care about what other community members think of me.		x	x
	66	I have influence over what this community is like.
	67	If there is a problem in this community, members can get it solved.		x	x
	68	This community has good leaders.		x	x
Shared emotional connection	69	It is very important to me to be a part of this community.	0.87	x	x
	70	I am with other community members a lot and enjoy being with them.		x	x
	71	I expect to be a part of this community for a long time.		x	x
	72	Members of this community have shared important events together, such as holidays, celebrations, or disasters.
	73	I feel hopeful about the future of this community.		x	x
	74	Members of this community care about each other.		x	x
Bonding	75	There are several people in my community I trust to help solve my problems.	0.72	x	x
	76	There is someone in my community I can turn to for advice about making very important decisions.		x	x
	77	There is no one in my community who I feel comfortable talking to about intimate personal problems.
	78	When I feel lonely, there are several people in my community I can talk to.		x	x
	79	If I needed an emergency loan of $500, I know someone in my community I can turn to.		x	x
	80	The people I interact with in my community would put their reputation on the line for me.		x	x
	81	The people I interact with in my community would be good job references for me.
	82	The people I interact with in my community would share their last dollar with me.		x	x
	83	I do not know people in my community well enough to get them to do anything important.
	84	The people I interact with in my community would help me fight an injustice.		x	x
Bridging	85	Interacting with people in my community makes me interested in things that happen outside of my community.	0.9	x
	86	Interacting with people in my community makes me want to try new things.		x	x
	87	Interacting with people in my community makes me interested in what people unlike me are thinking.		x	x
	88	Talking with people in my community makes me curious about other places in the world.
	89	Interacting with people in my community makes me feel like part of a larger community.		x	x
	90	Interacting with people in my community makes me feel connected to the bigger picture.		x	x
	91	Interacting with people in my community reminds me that everyone in the world is connected.		x	x
	92	I am willing to spend time to support general community activities.
	93	Interacting with people in my community gives me new people to talk to.
	94	In my community, I come in contact with new people all the time.
Loneliness	95	The next questions are about how you feel about different aspects of your life in local region/town. For each statement, indicate how often you feel that way for living in your community. How often do you feel that you lack companionship?	0.9	x	x
	96	How often do you feel left out?		x	x
	97	How often do you feel isolated from others?		x	x

APPENDIX 3:

RURAL PERCEPTION SURVEY ITEMS (61 ITEMS)

Item No.	Items	KMO in the Urban group	KMO in the Rural group	Included (29 items)
9	To what extent do you feel your general attitudes and opinions are similar to people who live in rural communities.* [R]	0.58	0.61	x
14	I feel a sense of loyalty to my community.* [R]	0.67	0.74	x
15	I know most of the people who live around me. [R]	0.67	0.69	x
16	Most of the people in my community know me. [R]	0.81	0.83	x
17	I feel a sense of connection with other people in my community.* [R]	0.66	0.69	x
31	Rural communities provide few opportunities for the individual to get ahead in life*.	0.44	0.61	x
41	I would say living in a rural area is Bad: Good	0.60	0.82	x
42	I would say living in a rural area is Harmful: Beneficial	0.59	0.77	x
43	I would say living in a rural area is Unpleasant: Pleasant	0.62	0.84	x
45	I would say living in a rural area is Boring: Stimulating	0.87	0.89	x
48	I would say living in a rural area is Acceptable: Unacceptable [R]	0.69	0.74	x
50	I would say living in a rural area is Preferred: Not preferred [R]	0.70	0.74	x
51	I get important needs of mine met because I am part of this community.	0.53	0.64	x
52	Community members and I value the same things.	0.53	0.54	x
54	Being a member of this community makes me feel good.	0.72	0.74	x
58	I can recognize most of the members of this community.	0.60	0.64	x
62	Being a member of this community is a part of my identity.	0.65	0.65	x
63	Fitting into this community is important to me.	0.68	0.71	x
65	I care about what other community members think of me.	0.50	0.55	x
68	This community has good leaders.	0.55	0.56	x
73	I feel hopeful about the future of this community.	0.56	0.61	x
74	Members of this community care about each other.	0.60	0.61	x
80	The people I interact with in my community would put their reputation on the line for me.	0.59	0.59	x
82	The people I interact with in my community would share their last dollar with me.	0.51	0.57	x
84	The people I interact with in my community would help me fight an injustice.	0.52	0.55	x
89	Interacting with people in my community makes me feel like part of a larger community. [R]	0.69	0.71	x
90	Interacting with people in my community makes me feel connected to the bigger picture. [R]	0.74	0.76	x
95	How often do you feel that you lack companionship?	0.63	0.76	x
97	How often do you feel isolated from others?	0.79	0.86	x
8	To what extent do you identify with people who live in rural communities. [R]	0.62	0.61
12	I want to live in my community for a long time. [R]	0.79	0.72
13	I feel at home in my community [R]	0.70	0.70
33	Rural communities provide few opportunities for new experiences.	0.48	0.61
61	I put a lot of time and effort into being part of this community.	0.67	0.58
1	People around here are willing to help their neighbors. [R]	0.50	0.41
3	People in this neighborhood or community can be trusted. [R]	0.50	0.41
6	To what extent do you see yourself belonging to a rural community. [R]	0.67	0.56
7	To what extent is being from a rural community a part of who you are. [R]	0.56	0.53
10	To what extent do you feel that you are typical of people who live in rural communities. [R]	0.65	0.57
22	Rural communities are the most satisfying of all places to live, work, and play. [R]	0.52	0.46
30	Rural people are suspicious and prejudiced toward anyone not like themselves.	0.61	0.53
32	Rural people are closed-minded in their thinking.	0.73	0.67
44	I would say living in a rural area is Dull: Interesting	0.91	0.90
46	I would say living in a rural area is Desirable: Undesirable [R]	0.80	0.76
47	I would say living in a rural area is Appealing: Unappealing [R]	0.90	0.87
53	This community has been successful in getting the needs of its members met.	0.52	0.51
55	When I have a problem, I can talk about it with members of this community.	0.65	0.61
57	I can trust people in this community.	0.61	0.55
59	Most community members know me.	0.76	0.75
67	If there is a problem in this community members can get it solved.	0.55	0.54
69	It is very important to me to be a part of this community.	0.72	0.71
70	I am with other community members a lot and enjoy being with them.	0.65	0.65
71	I expect to be a part of this community for a long time.	0.70	0.61
75	There are several people in my community I trust to help solve my problems.	0.73	0.72
76	There is someone in my community I can turn to for advice about making very important decisions.	0.70	0.61
78	When I feel lonely, there are several people in my community I can talk to.	0.71	0.67
79	If I needed an emergency loan of $500, I know someone in my community I can turn to.	0.56	0.48
86	Interacting with people in my community makes me want to try new things.	0.52	0.49
87	Interacting with people in my community makes me interested in what people unlike me are thinking.	0.54	0.44
91	Interacting with people in my community reminds me that everyone in the world is connected.	0.61	0.58
96	How often do you feel left out?	0.78	0.70

Note: Four items with * were not included in the 25 items in Table 2.