Hello Beautiful? The Effect of Interviewer Physical Attractiveness on Cooperation Rates and Survey Responses

Abstract

This article analyzes the effect of interviewers’ physical attractiveness on cooperation rates in face-to-face interviews and survey responses (self-reports on physical appearance, weight, and health). This article includes four aspects of physical attractiveness (facial attractiveness, voice attractiveness, body mass index [BMI], and height) and reports that (1) interviewers with more attractive faces and lower BMI have higher cooperation rates, (2) differences in interviewers’ personality (Big Five, Rosenberg self-esteem) account for about one third of the total effect of facial attractiveness on cooperation rates, and (3) being interviewed by a more attractive interviewer leads to more positive self-reports on physical appearance, weight, and health (but does not affect self-reports unrelated to physical appearance).

Keywords

interviewer effect physical attractiveness response rate survey response personality social desirability

Survey methodologists have long studied the impact of interviewer characteristics on response rates and survey responses. Results from this research suggest that interviewer characteristics affect both response rates and survey responses, although in different ways (Groves and Cooper 1998; Schaeffer, Dykema, and Maynard 2010). Interviewer characteristics such as race (Anderson, Silver, and Abrahamson 1988; Hatchett and Schuman 1975; Hill 2002), sex (Catania et al. 1996; Dykema et al. 2012; Flores-Macias and Lawson 2008), and experience (Davis et al. 2010; Freeman and Butler 1976) have been found to affect response rates. For example, female and more experienced interviewers tend to have higher response rates than male and less experienced interviewers (Fowler and Mangione 1990; Lievesley 1986). Moreover, interviewer characteristics have been found to affect survey responses. In particular, research shows that interviewer characteristics tend to affect survey responses when an interviewer characteristic is related to the content of a question (e.g., race or sex; Davis et al. 2010; Krysan and Couper 2003; O’Muircheartaigh and Campianelli 1998).

This article focuses on an interviewer characteristic that has received little attention in the literature: physical attractiveness. It analyzes the effect of interviewers’ physical attractiveness on cooperation rates in face-to-face interviews and, given that an interview has been completed, on survey responses relating to physical appearance, weight, and health. This article is motivated by research in other fields that documents positive effects of physical attractiveness on, for example, success in politics (Berggren, Jordahl, and Poutvaara 2010; Rosar, Klein, and Becker 2008), the labor market (Frieze, Olson, and Russell 1991; Hamermesh and Biddle 1994), and in family and social relations (Langlois et al. 2000). Based on these findings, this article argues that interviewers’ physical attractiveness might affect both cooperation rates and survey responses via different mechanisms.

First, interviewers’ physical attractiveness might affect cooperation rates via two mechanisms. Similar to interviewers’ race and sex, physical attractiveness is immediately visible at the doorstep. Given that the first face-to-face contact between interviewers and respondents usually lasts less than five minutes (Groves and Cooper 1998), and moreover that research shows that individuals quickly form opinions about others based on their physical appearance (Langlois et al. 2000), physically attractive interviewers may have higher cooperation rates than less attractive ones because they are perceived more favorably by respondents (e.g., as being warmer and friendlier). Moreover, physically attractive interviewers may develop certain personality traits, for example, self-confidence and extroversion (Eagly et al. 1991), which are beneficial when attempting to recruit respondents. As a consequence, physically attractive interviewers may have a double advantage during the first face-to-face contact since respondents ascribe positive qualities onto them and they possess personality traits that reinforce this impression.

Interviewers’ physical attractiveness might also affect survey responses. Research shows that interviewer characteristics affect survey responses when a question relates to the interviewer characteristic (e.g., race or sex; Groves and Cooper 1998; Schaeffer et al. 2010). Social desirability, that is, respondents consciously or unconsciously modifying responses to present themselves in a favorable manner or to gain the approval of the interviewer, is one plausible explanation of this effect (Davis 1997; King and Bruner 2000). For example, existing research shows that interviewers’ body mass index (BMI) affects survey responses to health-related behaviors (Eisinga et al. 2011, 2012). Building on existing research on interviewer effects and physical attractiveness, this article provides a comprehensive analysis of the effect of interviewer attractiveness on survey outcomes, which makes four contributions to existing research.

First, previous studies use the interviewer’s BMI as the only measure of physical attractiveness (Eisinga et al. 2011; McKenzie et al. 2002). This article includes four aspects of physical attractiveness: facial attractiveness, voice attractiveness, BMI, and height. All four aspects have been shown to independently affect social and socioeconomic outcomes (Eagly et al. 1991; Langlois et al. 2000), and they might also affect cooperation rates and survey responses. As explained below, interviewers’ facial and voice attractiveness were rated by a panel of 10 raters on the basis of photographs and voice recordings, while information on interviewers’ BMI and height was collected through self-reports.

Second, in addition to establishing if physical attractiveness affects cooperation rates, this article seeks to explain what makes attractive interviewers more successful at the doorstep. Specifically, the article analyzes if differences between interviewers in their personality (measured by the Big Five Inventory and the Rosenberg Self-esteem Scale) explain why more attractive interviewers have higher cooperation rates. Previous research suggests that interviewers’ personality (Groves and Cooper 1998; Jäckle et al. 2013) and attitudes (Blom, De Leeuw, and Hox 2011; Durrant et al. 2010) have a direct effect on cooperation rates, but it has not addressed the extent to which differences in personality mediate the effect of physical attractiveness on cooperation rates.

Third, the design of the survey used in this article, the Danish Longitudinal Survey of Youth–Children (DLSY-C), makes it particularly suited for analyzing the effect of interviewer physical attractiveness. The DLSY-C used face-to-face interviews and implemented a strict protocol describing how interviewers were allowed to approach respondents. This protocol stipulated that, after sending out an invitation letter to the respondent, interviewers had to make first contact by physically going to respondents’ homes (first contact by telephone or e-mail was not allowed). Moreover, interviewers had to go to the respondent’s home at least four times (also on evenings or weekends) over a period of no less than two months before the respondent could be written off as a noncontact. Consequently, the design of the DLSY-C means that all interviewers were forced to make a physical first impression.

Fourth, this article analyzes if social desirability (rather than some other explanation) is the mechanism through which interviewers’ physical attractiveness affects survey responses. Respondents in the DLSY-C were asked to rate their own physical appearance, weight level (BMI categories), and subjective health. If social desirability affects survey responses, respondents should rate themselves as more physically attractive (i.e., more attractive, lighter, and in better health) if they are interviewed by a more attractive interviewer compared to interviewed by a less attractive one. This article tests this hypothesis. Moreover, it tests if the effect of social desirability is domain-specific, that is, applying only to survey responses in the domain related to the interviewer characteristic in question (in this case physical attractiveness). Specifically, this article analyzes if interviewers’ attractiveness affects survey responses to a range of other self-reports in the DLSY-C which are unrelated to physical appearance, for example, happiness, psychological self-assessments, and risk attitudes.

The empirical analysis shows that physically attractive interviewers, and specifically those with more attractive faces, have higher cooperation rates than less attractive interviewers. Holding other factors constant, an increase in facial attractiveness of one standard deviation (SD; which is equivalent to an increase of approximately one unit on a 1 to 10 scale) increases the probability that a respondent agrees to give an interview by 1.7 percentage points. Results also show that differences in interviewers’ personality account for about one third of the total effect of facial attractiveness on cooperation rates and, specifically, that higher self-esteem and openness help to explain why more attractive interviewers have higher cooperation rates. Finally, results suggest that interviewer attractiveness affects survey responses related to physical appearance but not responses in other domains. Respondents interviewed by a more attractive interviewer (one who has a more attractive face, lower BMI, and who is taller) rate themselves as being more attractive, in a lower BMI category, and healthier than those interviewed by a less attractive interviewer. Moreover, since interviewer attractiveness has no effect on self-reports in other domains, the evidence suggests that the impact of social desirability is domain-specific.

Why Does Physical Attractiveness Matter?

This section draws on theories in evolutionary and social psychology to motivate why more physically attractive interviewers have higher cooperation rates than less attractive ones and, moreover, how physical attractiveness affects survey responses in face-to-face interviews. Figure 1 summarizes the different mechanisms through which physical attractiveness is expected to affect cooperation rates and survey responses.

Figure 1.

Analytical model.

Evolutionary Psychology

Evolutionary psychologists argue that the development of the human brain was principally driven by the recurrent challenges early humans faced in ancestral environments (Buss 2008; Tooby and Cosmides 2005). In these environments, certain physical traits, for example, strength and reproductive quality, were instrumental for survival and humans developed information processing circuits in the brain, which instinctively recognized manifestations of these traits as attractive (Thornhill and Gangestad 1994). Thus, traits that are regarded as physically attractive are those that signal (re)productive skills, and even today, these traits help to explain psychological and social diversity in human populations. Empirical research supports the basic hypotheses in evolutionary psychology. There is only little variation between individuals in their rating of others’ physical attractiveness (Berscheid and Walster 1974; Feingold 1992a) and only little cross-cultural variation in perceptions of which facial characteristics are considered attractive (Langlois et al. 2000; Perrett, May, and Yoshikawa 1994). Already as infants individuals prefer physically attractive faces to less attractive ones (Etcoff 1999; Langlois et al. 1991), and the evaluation of physical attractiveness has been shown to be instantaneous and without any conscious deliberation (Senior 2003).

Social Psychology

Social psychologists have identified a range of qualities that people associate with physical attractiveness. They argue that a “what is beautiful is good” stereotype exists which implies that physically attractive individuals are ascribed a range of positive qualities such as likability, social competence, friendliness, leadership skills, and intelligence, while unattractive ones are ascribed negative qualities (Berscheid and Walster 1974; Dion, Berscheid, and Walster 1972; Eagly et al. 1991; Feingold 1992b; Langlois et al. 2000; Mobius and Rosenblat 2006). These qualities may originate in evolutionary processes, and they mean that, in addition to recognizing interviewers’ physical attractiveness, respondents unconsciously form positive opinions about attractive interviewers during their first encounter (e.g., they are friendly and likable).

Figure 1 illustrates the proposed links between interviewer attractiveness, survey cooperation, and survey response. The arrow going from interviewer physical attractiveness to survey cooperation captures the expected positive effect of the what is beautiful is good stereotype. Respondents ascribe positive qualities onto physically attractive interviewers (and negative qualities onto less attractive ones) that should have a positive influence on the likelihood of cooperation. Interviewer personality might mediate this relationship as explained in the next section.

Attractiveness and Personality

In addition to being perceived as friendly and likable, physically attractive interviewers might have personality traits that make them more successful in recruiting respondents. Research in social psychology shows that physically attractive individuals gradually internalize outsiders’ judgments and acquire self-views and behaviors that are consistent with the what is beautiful is good stereotype (Darley and Fazio 1980; Eagly et al. 1991). For example, physically attractive interviewers may develop higher confidence or may become more extroverted than less attractive ones (Mathes and Kahn 1975; Thornton and Ryckman 1991), and Figure 1 captures this mechanism by the arrow going from interviewer attractiveness to interviewer personality. Moreover, interviewers may modify other aspects of their appearance, for example, their voices, to match their physical appearance. Research shows that physical attractiveness and voice attractiveness are positively correlated (Feinberg et al. 2008; Hughes, Harrison, and Gallup, Jr. 2002), and furthermore that individuals with attractive voices are judged to have desirable personality traits and to be warmer and more likable than those with less attractive voices (Berry 1990; Zuckerman, Hidgins, and Miyake 1990). If true, this would suggest that interviewers’ personality—and its manifestation in behaviors at the doorstep—mediates some of the positive effect of physical attractiveness on survey cooperation. This mediating effect is illustrated in Figure 1 by the arrow going from interviewer personality to the arrow which captures the effect of interviewer attractiveness on survey cooperation.

To summarize, the positive effect of interviewer physical attractiveness on survey cooperation operates via two channels: attractive interviewers being ascribed positive qualities by respondents (i.e., a “demand” for attractiveness) and attractive interviewers having personality traits that increase the likelihood of cooperation (i.e., a “supply” of attractiveness). As explained below, this article distinguishes between these two channels by including direct empirical measures of interviewer attractiveness and personality.

Social Desirability and Survey Responses

In addition to being more successful at recruiting respondents, physically attractive interviewers may affect survey responses by virtue of their appearance. Research suggests that interviewer characteristics are more likely to affect survey responses when questions relate to the interviewer characteristic, for example, race and sex (Groves and Cooper 1998; Schaeffer et al. 2010). Similarly, Eisinga et al. (2011, 2012) found that higher interviewer BMI was associated with more frequent reporting of eating restraint and less calorie intake. As explained above, social desirability is a potential explanation of why interviewer characteristics affect survey responses (Davis 1997; King and Bruner 2000). In the context of this article, social desirability bias would manifest in respondents reporting looking better and being lighter and healthier if interviewed by a more attractive interviewer than if interviewed by a less attractive one. Figure 1 illustrates this mechanism by the arrows going from interviewer attractiveness to survey responses. In addition to a general effect of social desirability on survey responses, this article tests whether the effect of social desirability is domain-specific. If this is the case, interviewer attractiveness should affect respondents’ self-reported physical attractiveness but not self-reports in other domains. Figure 1 illustrates this hypothesis via the solid arrow going from interviewer attractiveness to respondents’ self-reported physical attractiveness and the dotted arrows (indicating no effect) going from interviewer attractiveness to survey responses in other domains. Operationally, this article tests this hypothesis by analyzing whether the effect of interviewer attractiveness on survey responses is restricted to self-reports on physical appearance or whether it also applies to self-reports that are unrelated to physical appearance (self-reported happiness, psychological self-assessments, and risk attitudes [degree to which respondent considers herself a risk-taker]).

Data

This article combines data from three sources: The DSLY-C (respondents), an interviewer questionnaire, and assessments of interviewers’ physical attractiveness carried out by a panel of raters.

DLSY-C

The principal data source is the DLSY-C. The DLSY-C includes all children born to participants in a long-running cohort study, the DLSY. The DLSY includes a nationally representative sample of 3,151 Danes who were all born in or around 1954 and who have been interviewed regularly since 1968 (interviews have been carried out in 1968, 1970, 1971, 1973, 1976, 1992, 2001, and 2004). The DLSY is similar to other cohort studies such as the National Longitudinal Surveys of Youth in the United States and the National Child Development Study in the United Kingdom.

The DLSY-C samples all children born to the 3,151 respondents who participated in the DLSY. Children were linked to parents on the basis of administrative registers run by Statistics Denmark, the national data authority. Denmark has operated a central person register (CPR) since 1968, in which all inhabitants are assigned a unique CPR number upon birth or migration. This CPR number is used almost universally in transactions with (and between) public authorities (e.g., tax, social security, or health authorities). The CPR number can also be used by researchers to link family members such as parents and children, siblings, and spouses. A search in the CPR registers in January 2010 showed that the DLSY participants had a total of 5,468 children, which amounts to 1.74 children per respondent.¹

Table 1 summarizes interview status for the total population of 5,468 respondents in the DLSY-C, as reported by the survey agency that collected the data. The table shows that 3,515 respondents completed an interview (three partial interviews were also carried out), while 508 or 9.3 percent of the respondents refused to participate when approached by an interviewer. The remaining 1,442 respondents were not interviewed either because no contact was made (e.g., respondents were out of town, had moved abroad, or were covered by research protection) or because respondents were ineligible for an interview (e.g., respondents were too young). The response rate in the DLSY-C is 67.6 percent (American Association of Public Opinion Research [AAPOR] RR2).²

Table 1.

Interview Status of the Danish Longitudinal Survey of Youth–Children Population.

	Interview	Percent	N	Response Category
1	Completed interview	64.4	3,515	I
2	Partial interview	0.1	3	P
	No interview. Reason:
3	Refused	9.3	508	R
4	Out of town	0.7	37	NC
5	Moved abroad	0.4	22	NC
6	Research protection	13.7	747	NC
7	Lives in Greenland	0.3	16	NC
8	Ill	0.3	17	O
9	Disabled	0.4	20	O
10	Deceased	1.5	83	O
11	Not met	3.3	181	UO
12	Moved to unknown location	0.8	42	UO
13	Other reason	0.3	15	UO
14	Too young	2.3	128	NE
15	Missing	0	1	NE
16	Emigrated	2.4	133	NE
Total		100.0	5,468

Note: I = completed interview; P = partial interview; R = refusal and break off; NC = No contact; O = other; UO = unknown other, noninterview; NE = not eligible for interview.

Respondents assigned as “covered by research protection” in Table 1 (code 6) were eligible for an interview but could not be contacted directly for legal reasons. In the period 2000 to 2006, it was possible in Denmark to be “protected” from being contacted by researchers. Research protection means that a person is flagged in the CPR register as not being available for research and, consequently, this person must not be contacted with the objective of being included in surveys. A person would get covered by research protection by “ticking off” a box on the official form which everyone must fill out and submit to their local municipality when registering a change of residence. Once registered, a person remains protected from research until he or she actively takes action to change this status. Research shows that those who were most likely to get protection from research were young people who move a lot and, as a consequence, who often fill out the form required to register a change of residence (Statistics Denmark 2008).

Rather than completely writing off DLSY-C respondents registered as protected from research, the survey agency that collected the data contacted the parent of the DLSY-C respondent, that is, the original DLSY participant, and enquired whether this parent would ask the DLSY-C respondent for permission to contact him or her (DLSY participants were contacted by phone. Protocol stipulated that up to six attempts to make contact with the DLSY participant were required before he or she could be registered as a noncontact). If permission was granted, the research protected respondent was included in the DLSY-C sample and was contacted by an interviewer. In the DLSY-C, 1,127 respondents, or about one fifth of the total population, were registered as protected from research (this figure is identical to national figures for similarly aged cohorts; Statistics Denmark 2008). The 747 respondents listed in Table 1 as protected from research are those for whom permission to make contact was not obtained or where parents could not be contacted. Consequently, the relevant sample in the DLSY-C with regard to survey cooperation is the sample that was approached by an interviewer and that either completed an interview (codes 1 and 2 in Table 1) or that refused to give an interview (code 3). The sample is further restricted to DLSY-C respondents aged 18 or older, which leaves a total of 3,809 respondents.

It should be noted that the DLSY-C sample analyzed in this article cannot be treated as a random sample because, even though it includes the children of a sample that is nationally representative, DLSY-C respondents grew up in families in which one parent is a long-term participant in an existing cohort study. The consequences of this design for the external validity of the empirical findings are discussed in the Conclusion.

Interviewer Data

The survey agency that collected the DLSY-C data used a team of 93 interviewers. These interviewers were typically semiprofessional (most have additional means of income) and carry out interviews in the region of Denmark in which they live. Denmark is a geographically small country (its land mass is approximately 0.5 percent of that of the United States) and is characterized by a high population density, a high level of socioeconomic equality, and low levels of residential and ethnic segregation. For the DLSY-C, interviewers received a list of names and addresses of the respondents who were assigned to them. Thus, while interviewers were not randomly assigned to respondents via an experiment, they had in effect no control over which respondents were assigned to them.³ This means that the assignment of interviewers to respondents can be regarded as plausibly exogenous with regard to interviewers’ physical attractiveness. Table 2 shows descriptive statistics for the interviewer data. Information on interviewers was obtained from two sources: a questionnaire administered during a series of interview training sessions and a set of physical attractiveness ratings carried out by a panel of raters on the basis of a photograph taken of each interviewer and a recording of each interviewer’s voice.

Table 2.

Descriptive Statistics: Means, Standard Deviations, and Variable Ranges.

	Mean	SD	Min	Max
Interviewers (N = 93)
Physical appearance
Facial attractiveness	4.54	1.03	2.6	7.7
Voice attractiveness	0	0.97	−2.2	1.9
Body mass index	25.50	3.52	18.1	37.2
Height (inches)	68.16	3.34	60.3	77.2
Personality
Self-esteem	24.23	3.46	15	30
Extroversion	8.10	1.86	4	12
Agreeableness	8.23	1.45	4	10
Conscientiousness	7.37	1.78	4	10
Neuroticism	4.06	1.54	2	9
Openness	7.28	2.11	2	10
Controls
Sex (= woman)	0.48	0.50
Age	62.76	9.18	24.0	80
Experience (years)	6.03	6.65	0	40
Education	4.62	1.15	1	6.0
Respondents (N = 3,518)^a
Self-reports
Physical appearance	3.28	0.54	1	5
Weight category	2.41	0.79	1	5
Health	4.37	0.76	1	5
Happiness	7.91	1.48	0	10
Self-esteem	22.64	3.89	4	30
Locus of control	1.28	1.09	0	4
Risk attitudes	5.79	2.01	1	10
Controls
Sex (= woman)	0.52	0.50	0	1
Age	27.80	5.09	18	42

^a N is the total number of respondents interviewed (codes 1 and 2 in Table 1).

Variables

Dependent Variables

This article includes two sets of dependent variables. The first set includes one dummy variable that takes the value 1 if the DLSY-C respondent completed an interview (codes 1 and 2 in Table 1) and 0 if the respondent was approached by an interviewer but refused to give an interview (code 3 in Table 1). This variable captures survey cooperation.

The second set of dependent variables includes seven variables for respondents who completed an interview. These variables include three self-reports that relate to physical appearance and four self-reports that do not. The first three items capture self-reported appearance, weight level, and health. Respondents were asked, “How would you rate your physical appearance compared to others of similar age?” Respondents answered this question using a 1 to 5 scale (with the response categories 1 = much worse, 2 = worse, 3 = about the same, 4 = better, and 5 = much better). They were also asked, “How would you rate your own weight level? Do you consider yourself to be…” (with the response categories 1 = obese, 2 = overweight, 3 = slightly overweight, 4 = normal weight, and 5 = underweight). Finally, they were asked, “How would you rate your health at the moment?” (with the response categories 1 = very poor, 2 = poor, 3 = fair, 4 = good, and 5 = excellent). This article also includes four self-reports that are unrelated to respondents’ physical appearance. The first variable is self-assessed happiness on a 0 to 10 scale (where 0 signifies very unhappy and 10 very happy), the second is the respondent’s score on the Rosenberg Self-esteem Scale (which includes 10 items that capture self-assessed psychological attributes relating to self-esteem; Rosenberg 1965), the third is the respondent’s summary score on four items from the Rotter Locus of Control Scale (which captures the extent to which the respondent believes she can affect events happening to her; Rotter 1966), and the final indicator captures the extent to which the respondent thinks of herself as a risk-taker (a 1 to 10 scale, where 1 signifies I avoid risks and 10 I do not mind taking risks).⁴

Physical Attractiveness

This article includes four aspects of interviewers’ physical attractiveness: facial attractiveness, voice attractiveness, BMI, and height.

Facial attractiveness

A panel of 10 raters (aged approximately 20 to 65 and consisting of both men and women) evaluated each interviewer’s facial attractiveness on the basis of a photograph taken during an interviewer training session. The members of the rating panel all worked in two large research institutions in Denmark (some in administrative jobs and some in research) and were recruited via an e-mail invitation. During the rating sessions (three in total), raters filled out independent assessments and did not know the other raters’ assessments. As in previous research (Biddle and Hamermesh 1998; Langlois et al. 2000; Mobius and Rosenblat 2006), raters used a scale from 1 to 10 to evaluate facial attractiveness, with 1 signifying very unattractive and 10 very attractive. The variable used in the empirical analysis summarizes the mean rating of facial attractiveness across all 10 raters. Interrater reliability for this variable is .88 (as measured by Cronbach’s α) and is similar to that reported in previous research.

Voice attractiveness

The panel that evaluated facial attractiveness also evaluated the attractiveness of interviewers’ voices based on a recording of each interviewer reading out a passage from Hans Christian Andersen’s fairy tale, the Tinderbox.⁵ Voice recordings and photographs were presented to the panel in random order (and in separate sessions), which means that raters were unable to link a photograph to a voice and vice versa. Raters were asked to judge the interviewers’ personality and physical appearance solely on the basis of their voice. Specifically, raters were asked to express the extent to which they thought the interviewer was pleasant, competent, physically attractive, trustworthy, extroverted, and confident (Oksenberg and Cannell 1988; van der Vaart et al. 2005; Zuckerman and Miyake 1993). For each dimension, raters used a 1 to 7 scale, with higher values indicating a higher rating of that dimension. As with facial attractiveness, variables capturing voice attractiveness were calculated as the mean rating for each dimension across the 10 raters. Rather than including all six variables in the analysis, the variables were included in a factor analysis to estimate overall voice attractiveness. A single latent factor accounts for 90 percent of the covariance between the six items (factor loadings for the six items lie in the 0.70 to 0.88 range, and interrater reliabilities for the six voice attractiveness ratings lie in the range .72 to .82). This variable was used in the empirical analysis to capture voice attractiveness. The correlation between interviewers’ facial and voice attractiveness is .43 (p < .001).

BMI was calculated on the basis of self-reported height and weight.

Height (in inches) was reported by the interviewers in the interviewer questionnaire. Since men and women are of different height, the height variable was standardized within sexes and measures each interviewer’s height relative to other interviewers of the same sex. This article includes both BMI and height because previous research shows that, although they are related, these different aspects of physical attractiveness have separate effects on a range of economic and social outcomes (Eagly et al. 1991; Langlois et al. 2000).

All measures of physical attractiveness are standardized in the empirical analyses to facilitate interpretation.

Personality

The analysis includes six variables to capture interviewers’ personality: self-esteem and the five dimensions of the Big Five Inventory (Groves and Cooper 1998; Jäckle et al. 2013). The measure of self-esteem is the Rosenberg Self-esteem Scale, which is based on a battery of 10 questions from the interviewer questionnaire and where higher scores indicate higher self-esteem (Rosenberg 1965). The Big Five Inventory is a widely used instrument that captures the following five aspects of personality (descriptive adjectives in parenthesis): extroversion (talkative, assertive, and energetic), agreeableness (good natured, cooperative, and trustful), conscientiousness (orderly, responsible, and dependable), neuroticism (anxious, hostile, and easily upset), and openness (imaginative, excitable, and curious; John and Srivastava 1999). The interviewer questionnaire includes a 10-item short version of the Big Five Inventory proposed by Rammstedt and John (2007), which has been shown to have high reliability. Table A1 summarizes correlations between the different measures of physical attractiveness, personality, and other interviewer characteristics.

Control Variables

In addition to physical attractiveness and personality, the analysis includes a range of interviewer characteristics that have been linked to cooperation rates and survey responses (Groves and Cooper 1998; Schaeffer et al. 2010). These characteristics include the interviewer’s sex (dummy variable for women), age (in years), experience (number of years up to the start of the DLSY-C; Olson and Bilgen 2011), and highest level of education (six ordered categories ranging from no education beyond compulsory school to college degree). Since all interviewers were white, it was not possible to include race as an explanatory variable.

The analysis also includes controls for the respondent’s sex (dummy variable for women) and age in years. These variables were the only ones available for respondents who were not interviewed. Table 2 provides descriptive statistics.

Methods

The objective of the empirical analysis is to estimate the effect of interviewer physical attractiveness on the likelihood that a respondent agrees to give an interview and, given that the respondent gives an interview, the effect on three self-reports on physical appearance and four self-reports that are unrelated to physical appearance.

This article uses binary probit models to estimate the probability of cooperation as a function of interviewer physical attractiveness and the control variables (i.e., a model for the probability of observing a code 1 or 2 vs. a code 3 in Table 1). Among those interviewed, the article uses ordinary least squares (OLS) regression models to estimate the effect of interviewer physical attractiveness on respondents’ self-reported physical appearance, weight, health, and on the four other self-reports.⁶ Since the data have a multilevel structure with respondents nested within interviewers, all standard errors reported adjust for clustering of respondents within interviewers.

In addition to estimating the effect of physical attractiveness on cooperation rates, this article analyzes the extent to which differences in interviewers’ personality mediate the effect of interviewer attractiveness. Specifically, this article estimates the binary probit models described above with and without the personality variables and uses standard decomposition methods for nonlinear models to determine the extent to which personality traits mediate the effect of physical attractiveness on cooperation rates (Karlson, Holm, and Breen 2012).

Results

The presentation of the empirical results is divided into two sections. The first section presents results on the effect of interviewers’ physical attractiveness on cooperation rates and the extent to which these are mediated by personality. The second section presents results on the effect of physical attractiveness on survey responses, including analyses of the extent to which these effects are attributable to social desirability.

The top panel in Table 3 shows results from binary probit models which estimate the effects of the four aspects of physical attractiveness on the likelihood that the respondent cooperates when approached by an interviewer. The lower panel shows results from decomposition analyses of the effect of physical attractiveness, which are discussed below. The probit models include the standardized indicators of interviewers’ physical attractiveness individually due to the low number of effective observations for each variable (N is between 85 and 89) and in order to assess their individual effect on the likelihood of obtaining an interview.

Table 3.

Summary of Binary Probit Regressions of Cooperation Rates and Nonlinear Decompositions.

Model	1	2	3	4	5
Facial attractiveness	0.082 (.032)* [.017]				0.069 (.036)† [.014]
Voice attractiveness		0.028 (.033) [.006]			0.002 (.036) [.0005]
BMI			−0.062 (.033)† [−.013]		−0.051 (.032) [−.010]
Height				0.029 (0.035) [0.001]	0.013 (.031) [.003]
Log likelihood	−1,347	−1,350	−1,306	−1,361	−1,291
Pseudo R ²	0.005	0.002	0.004	0.002	0.006
N (respondents)	3,563	3,563	3,510	3,605	3,468
N (interviewers)	87	87	87	89	85
Decomposition
Percentage of effect of physical attractiveness explained by personality	33.0	—	1.1	—	—
Contribution of different aspects of personality:^a
Self-esteem	62.0		325.3
Extroversion	−4.2		−150.7
Agreeableness	−1.3		39.4
Conscientiousness	−8.9		−186.2
Neuroticism	10.5		–1,399.9
Openness	42.0		1,472.0

Note: Parameter estimates, standard errors in parentheses, and average marginal effects are given in brackets. BMI = body mass index.

^aThe contributions sum to 100. Standard errors adjusted for clustering of respondents within interviewers. Models also include interviewer’s sex, age, experience, and education.

†p < .10. *p < .05. **p < .01. ***p < .001.

Table 3 shows that, net of the control variables, both interviewers’ facial attractiveness (p < .05) and their BMI (p = .062) affect the likelihood that the respondent agrees to give an interview. For facial attractiveness, the average marginal effect of an increase in facial attractiveness by 1 SD (which is approximately the same as an increase of one point on the 1 to 10 scale; SD = 1.03) is a 1.7 percentage point increase in the likelihood of obtaining an interview. These results thus suggest that interviewers with more attractive faces are more successful in recruiting respondents than their colleagues with less attractive faces.⁷ Similarly, interviewers with higher BMI have a lower likelihood of obtaining an interview (although this effect is only marginally significant). The average marginal effect indicates that increasing BMI by 1 SD leads to an 1.3 percentage point decrease in the likelihood of obtaining an interview. This effect, and the effect of facial attractiveness, is consistent with the idea that respondents instantaneously recognize (lack of) physical attractiveness in interviewers and infer about interviewers’ personal qualities based on their appearance. Table 3 also shows that, although the sign of the regression coefficients is in the expected direction, there are no effects of voice attractiveness and height on the probability of obtaining an interview. (Additional models were estimated which included interaction effects between (1) interviewer physical attractiveness and interviewer sex/age and (2) interviewer sex/age and respondent sex/age and (3) the difference in age between the interviewer and the respondent. None of these interaction effects were significant.)

The lower panel in Table 3 summarizes results from decomposition analyses of the extent to which the positive effect of interviewers’ physical attractiveness on cooperation rates is mediated via personality. Since facial attractiveness and BMI were the only indicators of physical attractiveness that had a statistically significant effect on cooperation rates, the analyses are restricted to these two indicators. The decomposition analyses are based on two binary probit models predicting the probability that the respondent agrees to give an interview. The first model includes the same variables as in the top panel in Table 3, while the second adds the six personality variables (self-esteem and the Big Five Inventory). The decomposition analysis uses the normalization procedure proposed by Karlson et al. (2012).

The decomposition analysis shows that the personality variables account for one third of the total effect of facial attractiveness on cooperation rates (the personality variables account for only 1.1 percent of the total effect of interviewer BMI on cooperation rates, and their mediating effect will not be discussed further). Moreover, Table 3 shows that when decomposing the effect of facial attractiveness that is attributable to different aspects of personality, the most important aspects that account for the attractiveness advantage are self-esteem (62.0) and openness (42.0). Consequently, some of the reasons why interviewers with attractive faces have higher cooperation rates than those with less attractive faces are that they are more confident, engaging, and open when interacting with respondents. This result suggests that both explanations outlined in Figure 1 matter: Respondents ascribe positive qualities onto physically attractive interviewers and attractive interviewers act in ways that reinforce that impression.

The second part of the empirical analysis addresses the effect of physical attractiveness on survey responses. Building on previous research, the main hypothesis is that social desirability is the mechanism through which interviewer attractiveness might affect survey responses. In the present analysis, bias from social desirability would manifest in respondents providing more positive self-reports on physical appearance, weight, and health when interviewed by an attractive interviewer than if interviewed by a less attractive interviewer.

Table 4 summarizes results from regressions of self-reported appearance, weight category, and health on physical attractiveness and controls. The table shows that all aspects of interviewer attractiveness except voice attractiveness affect respondents’ self-reported appearance, weight, and health. Holding other factors constant, respondents interviewed by an interviewer with a more attractive face report being more attractive themselves and lighter compared to those interviewed by an interviewer with a less attractive face. Similarly, those interviewed by a heavier interviewer report being less attractive and heavier, and those interviewed by a taller interviewer also report being in better health. Together, these findings are consistent with the hypothesis that interviewer’s physical attractiveness affects survey responses related to physical appearance.

Table 4.

Summary of Ordinary Least Squares Regressions of Self-reported Appearance, Weight Category, and Health.

Model	1	2	3	4	5
Self-reported appearance (higher values = more attractive)
Facial attractiveness	0.042 (.011)***				0.034 (.014)*
Voice attractiveness		0.017 (.014)			0.002 (.015)
BMI			−0.026 (.013)*		−0.019 (.012)
Height				0.026 (.001)**	0.018 (.010)†
N (respondents)	3,108	3,108	3,073	3,147	3,034
Self-reported weight category (higher values = lighter)
Facial attractiveness	0.036 (.016)*				0.038 (.019)
Voice attractiveness		0.002 (.020)			−0.016 (.022)
BMI			−0.063 (.013)***		−0.059 (.013)***
Height				−0.007 (.021)	−0.018 (.020)
N (respondents)	3,110	3,110	3,075	3,149	3,036
Self-reported health (higher values = better health)
Facial attractiveness	0.013 (.019)				0.005 (.019)
Voice attractiveness		0.004 (.023)			−0.002 (.025)
BMI			−0.029 (.020)		−0.027 (.019)
Height				0.032 (.016)*	0.029 (.014)*
N (respondents)	3,113	3,113	3,078	3,152	3,039

Note: Parameter estimates with standard errors are given in parentheses. Standard errors adjusted for clustering of respondents within interviewers. Models also include interviewer’s sex, age, experience, and education and respondent’s sex and age. BMI = body mass index.

†p < .10. *p < .05. **p < .01. ***p < .001.

The last part of the empirical analysis addresses the question of whether the effect of interviewer attractiveness on survey responses is domain-specific. If indeed the effect is domain-specific (as suggested in previous research), the expectation is that interviewer attractiveness affects survey responses related to physical appearance but not those in other domains. Alternatively, it may be that interviewer attractiveness affects survey responses in several domains. To test this hypothesis, this article analyzes whether interviewer attractiveness affects responses to questions in the DLSY-C that are unrelated to physical appearance (but that nonetheless capture self-reports of personal traits). The alternative self-reports available in the DLSY-C include self-reported happiness, self-esteem, locus of control, and risk attitudes, and Table 5 presents results from OLS regressions of these alternative self-reports on interviewer attractiveness and controls. Interestingly, Table 5 shows that interviewer physical attractiveness is unrelated to all of these survey responses. Consistent with research on other interviewer characteristics, this evidence suggests that social desirability is a likely explanation of why interviewer attractiveness affects survey responses, and moreover, it suggests that the effect of social desirability is domain-specific.

Table 5.

Summary of Ordinary Least Squares Regressions of Self-reported Happiness, Self-esteem, Locus of Control, and Risk Attitudes.

Model	1	2	3	4	5
Happiness
Facial attractiveness	−.037 (.030)				−.028 (.033)
Voice attractiveness		−.029 (.032)			−.022 (.033)
BMI			.025 (.038)		.021 (.036)
Height				.028 (.027)	.035 (.026)
Self-esteem
Facial attractiveness	.075 (.084)				.098 (.093)
Voice attractiveness		−.099 (.106)			−.144 (.124)
BMI			−.128 (.098)		−.121 (.094)
Height				.071 (.080)	.047 (.080)
Locus of control
Facial attractiveness	−.037 (.023)				−.026 (.029)
Voice attractiveness		−.020 (.023)			−.010 (.024)
BMI			.029 (.023)		.025 (.023)
Height				−.011 (.017)	−.004 (.021)
Risk attitudes
Facial attractiveness	−.116 (.071)				−.074 (.074)
Voice attractiveness		−.102 (.061)			−.080 (.055)
BMI			−.024 (.079)		−.045 (.075)
Height				−.072 (.059)	−.057 (.055)

Note: Parameter estimates with standard errors in Parentheses. Standard errors adjusted for clustering of respondents within interviewers. Models also include interviewer’s sex, age, experience, and education and respondent’s sex and age. BMI = body mass index.

†p < .10. *p < .05. **p < .01. ***p < .001.

Conclusion

The objective of this article was to analyze the effect of interviewers’ physical attractiveness on survey cooperation and responses. This article argues that interviewer attractiveness might affect both survey cooperation and responses, although via different mechanisms. Physically attractive interviewers might have higher cooperation rates than less attractive ones because they are perceived more favorably by respondents at the doorstep and because they have personality traits that reinforce that impression. Moreover, physically attractive interviewers might affect survey responses because social desirability bias induces respondents to modify responses to conform to norms that they ascribe to the interviewer. Results from the empirical analyses are largely consistent with these ideas. First, physically attractive interviewers (and in particular those with more attractive faces) have higher cooperation rates than less attractive ones, and differences in personality traits (especially self-esteem and openness) account for one third of the total effect of interviewer attractiveness on cooperation rates. Second, interviewer physical attractiveness affects survey responses related to physical appearance but not responses unrelated to physical appearance. This suggests that social desirability matters but also that its effect is domain-specific.

The results presented in this article contribute to existing research on interviewer effects by demonstrating the relevance of an interviewer characteristic that has not previously been addressed. The remainder of this article discusses the implications of the empirical findings for research on interviewer effects and highlights several limitations in the present analysis.

First, the empirical findings suggest that a paradox exists: One the one hand, physically attractive interviewers have higher cooperation rates than their less attractive colleagues but, on the other hand, their attractiveness leads to bias in survey responses (at least in survey responses relating to physical appearance). Consequently, there may be a trade-off between a high cooperation rate and less reliable survey responses (Grover and Cooper 1998). One way of addressing this trade-off in face-to-face interviews would be to change the mode of data collection, when respondents are asked to report on physical appearance and related issues, for example, via a web survey or some other form of self-administration where the interviewer is not present. Alternatively, information on interviewer physical appearance could be collected routinely to allow researchers to address bias arising from this interviewer characteristic.

Second, the empirical findings have potential ethical implications. If indeed physically attractive interviewers are more effective than less attractive ones at recruiting respondents, should survey agencies seek to only hire good-looking interviewers or pay good-looking interviewers more? Unlike other aspects of interviewer behavior that can be improved via training (Groves and Cooper 1998; Schaeffer et al. 2010), physical appearance is difficult to change and has far-reaching consequences. And although legislation to prevent discrimination based on physical appearance exists in some countries, the fact that others’ response to physical attractiveness is instantaneous makes it difficult to prevent discrimination.

Finally, several empirical limitations in the present analysis should be mentioned. The first is that the DLSY-C includes a comparatively small number of interviewers (N = 93). This design limits variation at the level of interviewers and thus statistical power. The second limitation concerns bounds on effect sizes. The interviewers in the DLSY-C (mean age 62.8) are on average much older than the respondents whom they interview (mean age 27.8). This means that the estimated effect of physical attractiveness on cooperation rates and survey responses should be considered lower bound estimates since, arguably, they would have been higher if interviewers and respondents were of similar age. The third limitation concerns measurement of physical attractiveness. Although the method of using a panel of raters to assess facial (and voice) attractiveness is standard, it introduces measurement error that might affect results (Hamermesh and Abrevaya 2013). Similarly, since interviewers’ BMI and height are based on self-reports, they also contain measurement error (Gorber et al. 2007). Unfortunately, no alternative measures are available, so these limitations cannot be addressed in the present analysis. Finally, it must be kept in mind that the participants in the DLSY-C do not comprise a random sample of the Danish population because they are children of participants in a long-running cohort study. This design limits the extent to which empirical results can be generalized, but it also means that the estimated effects of physical attractiveness on cooperation rates and survey responses probably would be stronger in a random sample in which respondents had less experience with interviewers. Despite these limitations, the contributions of this article are to demonstrate that interviewer physical attractiveness affects both cooperation rates and survey responses and to identify some of the mechanisms though which physical attractiveness operates.

Supplemental Material

Supplemental Material, Appendix_Table_A1 - Hello Beautiful? The Effect of Interviewer Physical Attractiveness on Cooperation Rates and Survey Responses

Supplemental Material, Appendix_Table_A1 for Hello Beautiful? The Effect of Interviewer Physical Attractiveness on Cooperation Rates and Survey Responses by Mads Meier Jæger in Sociological Methods & Research

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

Supplemental Material

Supplemental material for this article is available online.

Notes

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