Falling for It: Is Trust a Direct Effect of Perceived Risk?

7/30/2019 Falling for It: Is Trust a Direct Effect of Perceived Risk?

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Falling For It: Is Trust an Effect of Perceived Risk?

Jessica Deitzer

The Pennsylvania State University



Deitzer 2 Abstract

Past research has used questions on fear of walking home alone at night, such as the

question from the General Social Survey (GSS), as a measure of fear of crime. Calling into the

question the validity of this variable, researchers have proposed it more accurately represents

perceived risk and that studies should look to other measures, one of which is trust, for the study

on fear of crime. This study looks at the effect of many demographic variables, perceived risk,

and attitudinal measures reflecting beliefs about other people on the GSS variable on trust. Our

findings reflect that trust is directly impacted by demographics and beliefs about other people,

but not perceived risk. Future research should examine what measures are more representative of

the authentic experience of fear of crime.



Deitzer 3 Introduction

The General Social Survey (GSS), begun in 1972, launched a plethora of scientific

research on fear of crime due to its consistent inclusion of questions designed to assess fear of

crime. Soon thereafter, researchers recognized the great difference between the pulse-pounding

adrenaline rush of fear and a written or spoken answer to a survey question (Ferraro &

LaGrange, 1987). While the respondent is in no immediate danger, the validity of their answers

to questions on “fear” is questionable. Research has thus found it very difficult to conceptualize

fear of crime (Walklate, 1998; Ferraro & LaGrange, 1987) and the broad questions used in the

General Social Survey (GSS) became the subject of great criticism. A commonly used GSS

question on fear of crime is “Is there anywhere around here – that is, within a mile – where you

would be afraid to walk alone at night?” Albeit this measure being called both vague and invalid

in past research, it is still widely used (Ferraro & LaGrange, 1987).

The weakness of the past research on fear of crime lies in the conflicting opinions on

measuring the construct of “fear.” The research on “fear of crime” is subject to arbitrary and

irregular levels of measurement. Many studies have used questions such as the above measure of

fear of walking alone at night from the GSS, also examined in this study, without addressing

whether answering “yes” to a question such as this implies a true fear of crime or fear of

victimization instead of simply acknowledging the risk in their surrounding neighborhoods. As

Ferraro & LaGrange (1987) described in their paper on “The Measurement of Fear of Crime”:

Consider the following question: “How safe would you feel walking alone at

night in your neighborhood?” While such a question has been used to measure fear of

crime (e.g., Baker et al. 1983), it more accurately measures the risk to self of walking

alone at night in one’s neighborhood. This is not an emotional reaction to crime, but



Deitzer 4 rather a judgment about the likelihood of criminal victimization for the individual. A

person who says he or she would not feel very safe may not be afraid at all, but simply

aware of the relative risk.

Likewise, other measures that may be simply calculated judgments may need to be excluded as a

dependent variable supposing to represent the construct of “fear.” Ferraro & LaGrange (1987) go

on to suggest that any valid measures should separate judgments and simple risk assessments

from emotional reactions. That doesn’t exclude these questions; on the contrary, it requires

empirical research to clarify what exactly they measure.

Walklate (1998) presented a hypothesis that fear can be studied through trust. Assuming

fear affects one’s worldview and one’s worldview in turn affects fear, it is hypothesized fear will

negatively impact trust. Logically, the presence of trust implies a decrease of fear of those

around you, and, as that trust of others falls, fear will then rise. This paper investigates this

premise, determining whether “fear of crime” as studied by the GSS mediates trust. It also

examines whether one’s attitude towards others instead mediates trust or if demographic factors

have a direct impact on trust of others, considering all alternatives in an attempt to find the true

link between the General Social Survey’s “fear of crime” construct and its measure of trust. This

study presents an innovative look at the measurement of fear of crime and proposes a new

construct for further study—trust—by exploring the frequently used data from the General Social

Survey (GSS). It also explores various demographic factors commonly associated with fear of

crime such as age, income, and socioeconomic status, focusing on the construct of trust instead

of the current unreliable measures of fear of crime.

Measuring Fear of Crime



Deitzer 5 A question asking if a respondent “would be afraid to walk alone at night” often ask the

participants to judge has been shown to more accurately reflect a risk assessment—hereafter

referred to as the respondent’s perceived risk of crime. A great debate exists over the differences

between the actual and perceived risk from crime, and the effect that has on fear (Walklate,

1998). Many continue using this question as if no true difference exists. However, discrepancies

between actual likelihood of victimization and the respondent’s perception of risk point to the

difference between actual and perceived risk. Studies have shown that correlations between

perceived risk and objective risk assessments of the community in question are only moderately

related at best (Ferraro & LaGrange, 1987). Clearly, one’s actual risk is not an accurate predictor

of the amount of reported fear, and one’s perceptions of risk do not predict one’s actual risk. The

question remains how the difference between actual and perceived risk relates to fear of crime.

Research suggests perceived risk still has an impact on the “irrational” construct of fear.

For instance, women consistently report more fear than men, no matter the age or socioeconomic

status, despite the fact men are more likely to be victimized by all crimes besides sexual assault

(Ferraro, 1996). These results occur independent of what research methods of measurement are

used. This exhibits “irrational” fear as a measure of crime, supporting the discrepancy between

actual and perceived risk as a valid measure. For the present research, this seems to validate the

use of perceived risk as a valid measure of fear.

Walklate (1996) recognized an issue with fear as irrational when he took to defining the

construct of “fear” with other measures. Fear as “other” represents past forays into fear of crime

as an “us versus them” paradigm, specifically focusing on divisions of race. Fear as “anxiety”

places emphases on levels of psychoanalytic and other types of measurement relating global

anxiety to fear of crime. Fear as safety attempts to explain fear by attempts to avoid risk, such as



Deitzer 6 avoiding walking in one’s neighborhood at night, much like the “rape schedule” or “ordinary

fear” scholarly literature has commonly attributed to women. Lastly, fear as “reason” focuses on

both rational and irrational fear of crime (Walklate, 1996).

Fear as reason, rational or irrational, actual or perceived, is the type of crime surveys

have typically measured, using questions relating to participant’s fear of crime and then their

estimations of the incidence of that particular crime in the area. In this way, participants’ answers

determine whether their fear is rational or irrational. Many studies then go on to describe the fear

of certain groups, essentially women or the elderly, as “irrational.” Walklate (1998) argues that

the principal reliance on calculating perceived or actual risk does not truly reflect the authentic

fear of crime. We do not simply calculate our chances of being victimized and then decide our

course of action; there is far more to our fear than that.

Overall, research on fear and the measurement of fear has suggested the importance of

differentiating the emotional response from the objective analysis of risk. Perceived risk or

“irrational” fear is commonly measured by survey questions in social science research. Yet,

measuring actual vs. perceived “irrational” risk assessments far from encompass the true

experience of fear and may be missing the bigger picture. Our current methods assume this type

of fear as measureable, despite the fact the majority of fear is experienced in the direct threat of

physical victimization or otherwise stressful environments by mental, emotional, and

physiological arousal (i.e. “fight or flight” tendencies) and therefore may not be measurable at all

(Waldlate, 1998). Reforms such as including “how afraid” or making a point to mention crime

have been encouraged to try to make the emotional response of fear of crime more salient

(Ferraro & LaGrange, 1996); however, this is largely untestable. Although science would ideally

be able to measure the response when faced directly with victimization, this is not the case. In



Deitzer 7 fact, by this reasoning, “fear” may not be a measurable, emotional construct at all but rather left

as a calculated perception of risk.

The Place of Trust

Walklate (1998) emphasizes the consequences of fear of crime rather than its theoretical

underpinnings in a “fear as praxis” section. Focusing on trust as a measure of fear of crime

avoids the faults associated with each of the other models. Trust of others inarguably plays a role

in fear of crime, and vice versa; however, trust remains currently understudied in social science,

especially pertaining to fear of crime.

The trust construct represents not only the potential victimization by strangers (i.e.

“stranger rape”), but also the risk of victimization by people as a whole. Described another way,

trust encompasses both the people a woman knows or is familiar with and the strangers or

“others” she encounters. This is in line with the reality of victimization, with crime against

women most often perpetrated by familiar males (Walklate, 1998) and the “ordinary fear”

experienced by women in their typical routines. Thus, the study of trust may have previously

untold implications for the examination of gender differences in fear of crime and the study of

crime itself.

Trust has garnered a lot of attention in recent economic and social theories. It is often

measured by games, such as one in which participants must decide whether to accept a sure thing

small payment from the researcher or trust another participant who they only had minimal

information about to allocate a larger sum, and has shown that there are differences in trust of

others between genders, with men more trusting than women, although women are considered

more trustworthy (Maddux & Brewer, 2005). Additionally, attitudinal questions have been used



Deitzer 8 to measure the general belief in the trustworthiness of other people. Although questioned about

their validity in extension to real-life scenarios, research has found favorable evidence that

attitudinal measures of trust extend to trustworthiness and trust in others (Capra, Lanier, & Meer,

2008).

Current Research

In order to avoid the invalid measure of fear of walking alone at night, this study strove to

examine this new construct that may be directly related to widespread levels of fear. By focusing

on trust of others as a valid, emotional measure, this study attempted to avoid the ambiguity and

contradictory evidence among the measurement of fear of crime. We sought to examine the

relationship between a typical measure of fear (i.e. the GSS question “Is there anywhere around

here – that is, within a mile – where you would be afraid to walk alone at night?”) and the broad

rating of trust. Controlling for other factors, we wished to examine whether fear—in this case, of

walking in their neighborhood alone at night—had a direct effect on their trust of others.

The present study strives to explain trust as a sign of vulnerability by a variety of factors

that have been proven or speculated to be involved in the fear of crime. This multi-factorial

approach includes typical predictors of fear of crime, such as sex, race, age, and socioeconomic

status. Additionally, this study wished to include other attitudinal factors in order to search for an

additional effect or to rule out the effect of attitudes about people affecting trust. To the author’s

knowledge, no study to date has examined trust by these factors, especially with a focal point on

fear of crime. This study strives to explain trust by three different hypothesized models.

In accordance with the literature, this study hypothesizes that divisions in sex, race, age,

and socioeconomic status will be significantly related to trust. The first model posits that such



Deitzer 9 demographic factors will have a direct effect on trust, even whilst controlling for other factors,

such as fear of walking alone at night. The second model, however, predicts that between

demographic factors and trust, our variable measuring fear will be a mediating factor. The third

model replaces fear with general attitudes towards others, seeking to discover if negative

attitudes towards others determines trust.

Data and Methods

The data for this study was collected from the General Social Survey (GSS) conducted in

2010. The GSS is the most widely analyzed dataset in the social sciences, excepting the U.S.

Census, funded by the National Science Foundation. Tracking social trends since 1972, the GSS

It consists of 90 minute in-person interviews administered to a representative sample of the

American public with response rates exceeding 70%. These interviews consist of many

demographic and attitudinal questions, allowing the study to take many dependent and

independent variables into consideration in producing our results. For the 2010 survey, the GSS

included 4,901 respondents. For the purposes of ensuring each respondent answered all the

interview items in question, the number of cases was limited to 519.

The question, “Generally speaking, would you say that most people can be trusted or that

you can't be too careful in life?” was used to study trust. This measure of trust was our main

dependent variable. Also used as a dependent variable, our other attitudinal variables on the

helpfulness and fairness of people were treated similarly to trust. For “trust,” “helpful,” and

“fair,” the responses were recoded, with “1” signifying a negative view and “3” signifying the

presence of positive attitudes towards other people. The question used as a measure of belief in

helpfulness of others was “Would you say that most of the time people try to be helpful, or that



Deitzer 10 they are mostly just looking out for themselves?” For a measure of belief in the fairness of

others, the question “Do you think most people would try to take advantage of you if they got a

chance, or would they try to be fair?” was utilized. Belief in the trustworthiness, fairness, and

helpfulness of others were each examined through bivariate and multivariate regressions

including each of the independent variables. The measures were also independent variables in

regressions involving the opposite measures in order to examine the effect these attitudes hold on

trust and vice versa.

Generally, “fear of crime” has been studied with the GSS using questions such as “Is

there any area right around here -- that is, within a mile -- where you would be afraid to walk

alone at night?” In this study, this variable was used as an independent variable. Not to be

confused with the accurate portrayal of “fear of crime,” as discussed earlier, this variable was

labeled “fear of walking alone at night,” also referred to in our study as “perceived risk.” The

variable cannot be referred to as “fear of crime” due to methodological limitations. This variable

was recoded in order to make it useful for regression, with those who answered “yes” to the

above question coded as 1 and those who answered “no” coded as 0. Therefore, a higher number

represented more fear.

Our other independent variables were demographic measures believed to influence belief

in trustworthiness, helpfulness, and fairness of others and/or fear of walking alone at night in

one’s own neighborhood. Sex was used as an independent variable of particular interest, as well

as age and race. Sex was dummy coded into “male,” with females coded as zero. Age was kept

as the appropriate numerical value, and race was dummy coded into “black,” “other,” and

“white,” with “white” as a reference category. The question “Are there any whites/blacks



Deitzer 11 (opposite race) living in this neighborhood now?,” was used as a measure named “Opposite Race

Neighbors,” with 1 representing yes and 0 representing no.

Class status and family dynamics could also hold particular influence trust, attitudes of

others, and fear. Family income, occupational prestige, and years of education were used as

measures of class. Occupational prestige and years of education were kept as is—according to an

ordinal, ranked scale of prestige and numerically coded by number of years. Family income was

divided by $1,000 in order to scale down the output. Number of children, age of children, and

marital status represented the influence of the family. Number of children was kept as a

numerical value as it is coded in the GSS dataset, but the age of youngest child was calculated by

computing the respondent’s answers to babies (number of family members under six years of

age) preteens (number of members six to twelve years), and teenagers (number of members

thirteen to seventeen), dummy coding the youngest child into “young child,” “preteen,” and

“teen,” accordingly, with no children as a reference category. Marital status was also dummy

coded, with new variables “widowed,” “divorced” (also including separated), and “never

married,” compared with the reference category, “married.” Religious affiliation was recoded in

ascending order of strength of the religious affiliation, ranging from “no affiliation” to “strong

affiliation,” with the strongest reports as higher numbers.

Locational variables were hypothesized to have an impact on attitudes towards others,

trust, and fear. Each was dummy coded in order to measure the effects of differing regions and

residential areas. Type of residence was grouped into central city, other urban, suburbs, and rural

residences, with central city as a reference category because this encompassed the most

respondents and was the most interesting to compare all others to. These dummy codes were

gleaned from the GSS variable “SRC Belt Code,” which groups places according to size and



Deitzer 12 type. Likewise, one’s region was grouped into south, north, pacific, mountain, and mid-atlantic

regions, with south as a reference category.

Our variables were examined using frequencies, correlations, crosstabulation, and

multiple regression. Frequencies and crosstabulations between genders were run for each

variable used as a dependent variable in the course of the study (belief in trustworthiness,

helpfulness, and fairness) as well as fear of walking home alone at night. Correlations were run

for trust, helpful, fairness, and fear of walking home alone at night. The researcher conducted

bivariate regressions, including measures of fairness and helpfulness in our regressions

predicting trust. Belief in fairness and helpfulness and then trustworthiness were also, in turn,

regressed on each independent variable. Multivariate regressions, encompassing each

independent variable together, were conducted for each dependent variable.

Results

Table 1 shows a gender difference in fear of walking home alone at night. Women report

there is an area in their own neighborhood they are afraid to walk alone at night almost twice as

often (45.2%) as the men (23.5%) with a highly significant p-value. Likewise, the variable

“trust” breaks down differently by gender, with 63.0% of women reporting people cannot be

trusted while 52.6% of men report this lack of trust. For the variables of helpfulness and fairness,

there was no significant difference by gender, reflecting that the answers are indications of that

respondent’s attitudes about people and not their attitudes as shaped by their experiences as men

or women. This warrants further study on what variables influences belief in fairness,

helpfulness, and trustworthiness of others and whether another variable controls for this

difference.



Deitzer 13 In Table 2, we see in models of correlation, but not causation, what has an impact. There

was a strong correlation between those who believed in the helpfulness and fairness of others and

those who believed in the trustworthiness of others. Belief in helpfulness (.330) and fairness

(.435) have strong positive correlations with belief in trustworthiness of others. Likewise, belief

in helpfulness and fairness are strongly positively correlated with each other (.426). Fear of

walking alone at night holds a slight negative correlation with belief in the trustworthiness of

others (-.089), which is significant, but its negative correlations with belief in helpfulness and

fairness of others are not significant. Overall, this shows the presence of positive attitudes about

people is associated with more trust in others, while fear as perceived risk is associated with less

trust. Although seemingly intuitive, these results support our hypothesis and justify taking a

closer look at what best predicts trust.

Belief in the Helpfulness and Fairness of Others

Starting with belief in the helpfulness of others as our dependent variable, Table 3 shows

both bivariate and multivariate regressions for the total respondents. Considering only the

statistically significant results, the table points out some interesting effects. The bivariate models

find having a preteen, in comparison to no children, to have a negative impact on belief in the

helpfulness of others of -.275. Being a member of the African American race also had a negative

effect of -.470 as compared to white respondents.

Conversely, age, income, occupational prestige, education, and living in the Pacific

region had a positive impact on belief in helpfulness. With each year of increasing age, there was

an average increase in belief of helpfulness of .008 and with each increase of $1,000, there was

an average increase of .004. Occupational prestige (.007) and education (.052) also held yearly



Deitzer 14 increases. Living in the Pacific (.299) held a significant increase as compared to the south, while

all other regions had a positive yet insignificant relationship. Trust in others was associated with

a positive increase in belief in other’s helpfulness, with an average increase in .345 with each

increase in trust. Overall, those with higher age, income, prestige, and education, those from the

Pacific region, and those who were more trusting had a higher belief in the helpfulness of others.

In the multivariate model, being a member of the African American race kept its negative

impact on belief in helpfulness even after controlling for many other variables, although

decreasing to -.294, while having a preteen child lost its significance altogether. Being male,

which was not significant in the bivariate model, became borderline significant with a negative

impact of -.149 on belief of the helpfulness of others. Income, occupational prestige, and

education also lost their significance once many other variables became part of the analysis. Age

kept its significance, with an average increase in belief in helpfulness of .006 per year of age, and

so did trust, with an increase of .272 for each degree of trust. Residing in the Pacific region also

continued having a significant, positive impact on belief in helpfulness, only slightly decreasing

to a value of .271. Thereby, with all the independent variables taken into account, being male and

being black was associated with a decrease in belief of the helpfulness of others whereas

increased age, residing in the Pacific, and holding a belief that others are more trustworthy

generally increased this belief in other’s helpfulness.

The disappearance of significant effects for income, occupational prestige, and education

are primarily interesting. Also noteworthy is the sudden significance of gender. It seems when

controlling for age, race, and gender, other demographic variables don’t retain their significance

on belief in the helpfulness of others, excepting residing in the Pacfic, which keeps its positive

effect nonetheless. Also, men are less likely to belief in the helpfulness of others instead of more



Deitzer 15 likely, contradictory to what the researchers might expect from viewing the opposite trend in the

frequencies and crosstabulations on trust and fear of walking alone at night presented in Table 1.

Trust stays important in the analyses, implying its significant relationship to attitudes about

others as a whole.

Belief in the fairness of others presented very similar effects, at least inside the bivariate

model. An unusual result included the negative impact of being divorced (-.175) and never

married (-.248) to have a negative impact on belief in the fairness of others, in comparison to

those who are married. Being a member of a minority race (black, other) had negative effects of -

.445 and -.434, respectively, as compared to white respondents. Age (.010), income (.004),

occupational prestige (.008), and years of education (.060) again had positive impacts on the

respondents’ attitudes, this time regarding fairness of others. Living in the North (.216) held a

significant increase as compared to the south, while all other regions again had a positive yet

insignificant relationship. Trust in others was associated with a positive increase in belief in

other’s fairness, with an average increase in .415 with each increase in trust. Overall, minority

respondents and those who were newly or continuously single were found to have less belief in

the fairness of other people. Those with higher age, income, prestige, and education, those from

the North, and those who were more trusting had a higher belief in the fairness of others.

In the multivariate model, differences revealed themselves. Age again kept its

significance, with an average increase in belief in fairness of .008 per year of age, as well as

trust, with an only slightly lessened increase of .374 for each degree of trust. Education remained

borderline significant, with an average increase of .027 for each year of education. Race, income,

occupational prestige, marital status, and region all became insignificant in the process of

controlling for all other variables. Like in belief in helpfulness of others, age and trust in others



Deitzer 16 mattered. However, in belief in fairness, education remained significant, whilst for helpfulness, it

didn’t. Also, the effects of sex, race, and region were eliminated.

Belief in the Trustworthiness of Others

The regression of the same demographic variables and including attitudes towards other

people on belief in the trustworthiness of others produced very different results. As shown in

Table 4, this study regressed the same independent variables with the addition of the former

dependent variables on trust. Starting with the bivariate models, fear of walking alone at night

was associated with a negative effect of -.178 on trust of others. Likewise, being a minority

(black, other) was also associated with even greater negative effects of -.597 and -.396,

respectively, as compared to whites. Other significant negative effects include having a young or

preteen child (-.335 and -.277, respectively), as opposed to no children, and being single (-.363),

as opposed to married.

Trust increased with belief in the helpfulness (.331) and fairness (.439) of others, as did

being male, with a positive coefficient of .201. Age (.013), income (.008), occupational prestige

(.013) and years of education (.084) also tend to increase trust in others. Also, residing in the

North (.197) or Mid Atlantic (.351) regions increased trust as compared to residing in the South.

Overall, belief in the helpfulness or fairness of others, being male, being older, higher family

income, more occupational prestige, more education, and residing in the North increased trust

while fear of walking alone at night, being a minority, having young or preteen children, and

being single decreased trust in others. As predicted, the attitudinal variables had an impact on

trust. Also, several variables involved in socioeconomic status played an important role in trust.



Deitzer 17 This study included three multivariate models, once leaving out the attitudinal and fear

variables, one leaving out only fear of walking alone at night, and one including all independent

variables. The differences between the regressions were small; therefore, for the purpose of

concise results, only the last multivariate equation will be discussed. In this multivariate model,

being a minority in the “other” category, having children, being single, occupational prestige,

and residing in the North became insignificant. Particularly noteworthy is fear of walking alone

at night, which stayed negative, but lost its significance.

Belief in the helpfulness (.133) and fairness (.287) of others continued to have a positive

impact on trust. Men also reported increased trust by an average of .131. Age (.007), income

(.003), and years of education (.041) significantly increased belief in the trustworthiness of

others, as well. Surprisingly, residing in the Mid Atlantic kept a significant positive effect,

although it decreased to .183. The negative effect of being black decreased to -.245 and stayed

significant. A particularly interesting effect involved the strength of religiosity, with no

significant effect in the bivariate model, but a borderline significant negative effect on trust of

others. Overall, belief in helpfulness and fairness of others, being male, higher age, income, and

years of education, and residing in the Mid Atlantic increased belief in the trustworthiness of

others, while being black or religious decreased this trust.

Discussion

Overall, demographic factors influenced belief in the helpfulness and fairness of others,

which in turn impacted trust, as one of the three hypothetical models suggested. This model did

not fully explain our results. Several demographic factors predicted trust even when controlling

for other attitudinal variables. Men are more likely to be trusting than females. An older age, a



Deitzer 18 higher income, and more education also suggest a higher degree of trust, regardless of the other

attitudes those respondents hold about other people. Likewise, being a member of the African

American race has a negative effect on trust. This suggests the more historically advantaged

respondents are also the most trusting, unexplained by their attitudes about the fairness and

helpfulness of other people.

Beliefs about fairness and helpfulness are also associated with an increase in trust for

both bivariate and multivariate models. They cannot be explained by our other demographic

independent variables, suggesting the importance of these attitudes apart from the situations that

may have formed them. Several demographic variables have similar results for trust and the

other attitudinal variables. For example, age and years of education held similar significant

effects on belief in helpfulness and/or fairness of others as on trust. This is not true for every

demographic variable. Interestingly, men reported decreased belief in the helpfulness of others,

yet increased trust in others, despite the fact that belief in the helpfulness of others positively

predicted trust. Further research should determine what causes men’s attitudes.

Other variables produced unexpected results. One such variable was region of residence.

Residing in the Pacific region had a positive impact on belief of the helpfulness of others. For

belief in the trustworthiness of others, residing in the Mid Atlantic region held a positive impact.

Even after controlling for numerous demographic and attitudinal factors, these two regions were

important. Although only present in the bivariate model, residing in the North increased belief in

the fairness of others and also impacted trust. It could be that people in the Pacific are more

helpful, or people in the Mid Atlantic states are more worthy of trust. However, this study cannot

determine what causes these consistent effects.



Deitzer 19 Strength of religiosity was also one such variable. Strength of religiosity held no

significant effects for belief in helpfulness or fairness of others. Likewise, it held no significant

effect in the bivariate regressions predicting trust. Only in the multivariate models did strength of

religiosity gain borderline significance, suggesting those with a stronger religious affiliation have

less trust in other people. An interesting find, this suggests those who report themselves as

strongly religious may hold negative views on the trustworthiness of others.

Although fear of walking alone at night was shown to hold gender differences and a

negative correlation with trust, it did not have a significant impact on belief in the helpfulness,

fairness, or trustworthiness of others. It can be rightly assumed that perceived risk is not a good

predictor of trust or attitudes about others as a whole. Therefore, the model hypothesizing fear

will mediate demographic variable’s impact on trust can be safely eliminated. These results

suggest that attitudinal and demographic variables play a far larger role. Trust and fear,

moreover, do not have a strong relationship. Future research should conversely determine the

effect of the same demographics on fear and the effect of trust and other attitudinal variables on

fear. However, this requires a more accurate measure of “fear” in order to conduct scientifically

sound analyses.

In conclusion, our model positing demographic factors impact trust and our model

predicting belief in the helpfulness and fairness of others as mediating variables were supported

in the data analyses. Although demographic factors such as sex, race, age, income, and education

directly impact trust, attitudes about others did as well. Fear, studied as respondent’s “perceived

risk,” had no impact on trust or other attitudes about people. Future research should examine the

effect of perceived risk on trust and strive to improve the measurements of fear. This study built

on past research to determine what impacts trust, and what simply doesn’t—and as for perceived



Deitzer 20 risk, although there are certainly more trends and relationships for future discover, any question

of its effect on trust can be safely forsaken.



Deitzer 21 References

Capra, C. M., K. Lanier, S. Meer. 2007. Attitudinal and behavioral measures of trust: A new

comparison. Working paper, Emory University, Atlanta.

Ferraro, K. F. (1996). Women's fear of victimization: Shadow of sexual assault?. Social Forces,

75(2), 667-690.

Ferraro, K. F., & LaGrange, R. (1987). The measurement of fear of crime. Sociological Inquiry,

57 (1), 70-97.

Fisher, B. S., & Sloan, J. J. (2003). Unraveling the fear of victimization among college women:

Is the "shadow of sexual assault hypothesis" supported?. Justice Quarterly, 20(3), 633-

659.

Franklin, C. A., & Franklin, T. W. (n.d.). Predicting fear of crime: Considering differences

across gender. (2009). Feminist Criminology, 4(1), 83-106.

Glaeser, E. L., Laibson, D. I., Scheinkman, J. A., & Soutter, C. L. (2000). Measuring trust. The

Quartly Journal of Economics, 115(3), 811-846.

Halpern, D. (2001). Moral values, social trust and inequality. British Journal of Criminology, 41,

236-251.

Killias, M., & Clerici, C. (n.d.). Different measures of vulnerability in their relation to different

dimensions of fear of crime. (2000). British Journal of Criminology, 40(3), 437-450.

Maddux, W. W., & Brewer, M. B. (2005). Gender differences in the relational and collective

bases for trust. Group Processes & Intergroup Relations, 8(2), 159-171.

May, D. C., Rader, N. E., & Goodrum, S. (2009). A gendered assessment of the . Criminal

Justice Review, 35(2), 159-182.



Deitzer 22 Meyer, E., & Post, L. A. (2006). Alone at night: A feminist ecological model of community

violence. Feminist Criminology, 1, 207-227.

Morgan, R. (1989). The demon lover . London: Mandarin.

Walklate, S. (1998). Excavating the fear of crime: Fear, anxiety, or trust?. Theoretical

Criminology, 2(403).



*p<.10, **p<.05, ***p<.01

Table 1. Frequencies: Dependent Variables

Total Sample Sex

%

Male

%

Female

%

Fear Walking at Night

Yes 35.3 23.5 45.2

No 64.7 76.5 54.8

!"#$#"%&'%(((#

Trust

People can be trusted 37.7 42.9 33.2

Depends 4.1 4.5 3.8

Can’t be too careful 58.3 52.6 63.0

!"#$)&*%(#

Helpful

People try to be helpful 43.2 41.7 44.5

Depends 9.1 8.5 9.6

Look out for themselves 47.7 49.8 45.9

!"#$&+,*#

Fair

People try to be fair 50.8 52.2 49.7

Depends 8.9 8.1 9.6

Try to take advantage 40.3 39.7 40.8

!"#$&),%#

N 539 247 292





Table 2. Correlation Matrix

Trust Helpful Fair Fear

Trust 1.0

Helpful .330*** 1.0

Fair .435*** .426*** 1.0

Fear ‐.089** ‐.055 ‐.058 1.0

*p<.10, **p<.05, ***p<.01



Table 3. Regressions: Predicting Belief in the Helpfulness and Fairness of Others

Helpfulness Fairness

Bivariate Multivariate Bivariate Multivariate

b b b b

Trust .345*** .272*** .415*** .374***

Fear Walking at Night ‐.110 ‐.069 ‐.115 ‐.023

Male ‐.067 ‐.149* .036 ‐.061

Age .008*** .006* .010*** .008**

Race

White ‐‐ ‐‐ ‐‐ ‐‐

Black ‐.470*** ‐.294** ‐.445*** ‐.172

Other ‐.224 ‐.129 ‐.434*** ‐.201

Opp. Race Neighbors .039 .045 ‐.028 ‐.040

Family Income .004*** .002 .004*** .000

Occupational Prestige .007*** ‐.001 .008*** ‐.001Years of Education .052*** .022 .060*** .027*

# of children .000 .010 ‐.004 ‐.019

Age of youngest child

No child ‐‐ ‐‐ ‐‐ ‐‐

Young Child ‐.055 .134 ‐.153 .106

Preteen ‐.275* ‐.158 ‐.173 .028

Teen ‐.071 ‐.010 ‐.101 .002

Marital Status

Married ‐‐ ‐‐ ‐‐ ‐‐

Widowed .162 .030 ‐.093 ‐.250Divorced ‐.072 ‐.001 ‐.175* ‐.139

Never Married ‐.086 .187 ‐.248** ‐.013

Type of Residence

Rural ‐.024 .150 ‐.106 ‐.046

Suburbs .128 .121 ‐.038 ‐.053

Other Urban .044 .086 ‐.076 ‐.109

Central City ‐‐ ‐‐ ‐‐ ‐‐

Strength of Religiosity .044 .048 .036 .042

Region

South ‐‐ ‐‐ ‐‐ ‐‐

North .141 .032 .216** .104

Pacific .299** .271** .044 ‐.005

Mountain .032 .004 .100 .080

Mid Atlantic .174 .006 .169 ‐.050

N =539; *p<.10, **p<.05, ***p<.01



Table 4. Regressions: Predicting Trust

Bivariate Multivariate

(1) (2) (3) (4)

b b b b

Fear Walking at Night ‐.178** ‐.091

Belief in Other’s Helpfulness .331*** .135*** .133***

Belief in Other’s Fairness .439*** .288*** .287***

Male .201** .137* .151** .131*

Age .013*** .012*** .007** .007**

Race

White ‐‐ ‐‐ ‐‐ ‐‐

Black ‐.597*** ‐.381*** ‐.238** ‐.245**

Other ‐.396*** ‐.113 ‐.020 ‐.008

Opp. Race Neighbors .373 .105 .098 .112

Family Income .008*** .003** .003* .003*

Occupational Prestige .013*** .002 .002 .002

Years of Education .084*** .060*** .041*** .041***

# of children ‐.010 ‐.014 ‐.007 ‐.006

Age of youngest child

No Child ‐‐ ‐‐ ‐‐ ‐‐

Young Child ‐.335*** ‐.064 ‐.104 ‐.110

Preteen ‐.277* ‐.084 ‐.061 ‐.071

Teen ‐.083 ‐.049 ‐.044 ‐.057

Marital Status

Married ‐‐ ‐‐ ‐‐ ‐‐

Widowed ‐.043 ‐.146 ‐.057 ‐.058

Divorced ‐.090 ‐.019 ‐.024 .027

Never Married ‐.363*** ‐.105 ‐.112 ‐.116

Type of Residence

Rural ‐.247 ‐.097 ‐.094 ‐.112

Suburbs .032 .036 .027 .012

Other Urban .033 .054 .064 .054

Central City ‐‐ ‐‐ ‐‐ ‐‐

Strength of Religiosity ‐.042 ‐.056 ‐.067* ‐.069*

Region

South ‐‐ ‐‐ ‐‐ ‐‐

North .197* .101 .052 .048

Pacific .126 ‐.020 ‐.054 ‐.059

Mountain .061 .026 ‐.005 ‐.026

Mid Atlantic .351*** .198* .183* .183*

N =539; *p<.10, **p<.05, ***p<.01

Documents

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