STEVEN D. BROWN
Loyola University Chicago, Chicago, IL
Many people around the world search for jobs each year and, for a sizable number of them, the process can be arduous and physically and emotionally draining. This chapter will review research on the job search process and on interventions that have been developed to facilitate job search success. Tremendous progress has been made over the past 20–25 years in understanding the job search process, defining what constitutes a successful job search, and delineating potential outcomes associated with active engagement in the process. Research on job search interventions has recently begun to home in on what might be termed critical intervention ingredients; that is, professionally designed job search activities that are reliably associated with increased outcome effect sizes (Liu, Huang, & Wang, 2014).
A number of excellent quantitative (e.g., Kanfer, Wanberg, & Kantrowitz, 2001; Paul & Moser, 2009; Wanberg, Kanfer, Hamann, & Zhang, 2016) and narrative (e.g., Wanberg, 2013; Wanberg, Ali, & Csillag, in press) reviews of job search research have appeared in recent years. The narrative reviews typically provide extensive and in‐depth coverage of research on the job search process, factors that are predictive of employment success, and how success is defined in the literature. However, they typically provide limited coverage of the job search intervention literature and do little to integrate the process and intervention literatures. These limitations sometimes make it difficult to apply the research findings to practice with job seekers.
To help bridge this research–practice gap, this chapter will focus on the job search intervention literature. Specifically, I will start by discussing definitions of job search success and identifying variables that have been suggested as critical indicators of a successful job search. The bulk of the chapter will then be devoted to two primary topics. First, I will discuss critical intervention components that have been identified through meta‐analysis. In doing so, I will review research from the broader job search literature that can further elucidate the ingredients and suggest how they might be implemented in practice. Second, I will review contextual (e.g., social capital) and individual difference (e.g., age, race, personal capital, personality) variables that can be used to identify individuals who might particularly benefit from a job search intervention or who might require special attention within an intervention. I will also provide a brief discussion of two extant job finding interventions (JOBS and the Job Club) that have garnered substantial research support. The chapter concludes with a set of take‐home messages for practitioners interested in working with persons seeking work.
It is important to note that people engage in job searches for a variety of reasons. For example, some are first‐time job seekers who are about to graduate from high school or college. Or they may be persons seeking to change jobs for better opportunities or because they feel overqualified in a present job. Others have become unemployed after having been fired or laid off. Still others may be searching for paid work after having been engaged in other roles or settings outside of the formal job market (e.g., re‐entry caregivers, military personnel, ex‐offenders). Finally, in today's labor market, some people may be on the job market to move from gig to more stable employment or from one gig job to another. Recent immigrants also represent a growing segment of job seeking population.
The job search process may be more arduous, challenging, and stressful for some persons (e.g., unemployed) than for others (e.g., employed job seekers), and their reasons for seeking work may present some unique challenges and issues. However, since all job seekers are looking for work, there are some basic elements of the job search process that they all share. This chapter will first focus on these common elements and later consider contextual and individual difference variables associated with job search success (e.g., age, gender, race/ethnicity, and personal and social capital of the job seeker) that have implications for the delivery of job search interventions. Allan and Kim (Chapter 24, this volume) provide an in‐depth discussion of the behavioral, emotional, psychological, social, and financial challenges associated with underemployment and unemployment that need to be considered in interventions for unemployed job seekers. The discussion later in this chapter of contextual and individual difference variables associated with job search success will offer suggestions concerning unique job search intervention needs associated with the age, gender, race/ethnicity, and the personal and social capital of the job seeker.
Research on the job search process and intervention effectiveness has defined job search success in many ways. The two most common and widely used indices focus on employment status and speed to employment—does the job search result in a job, and how quickly was the job attained? When considered in tandem, these are clearly reasonable indices of job search success and are useful in evaluating intervention effectiveness. For example, all else being equal, interventions associated with faster versus slower times to employment would be preferable. Other investigators (e.g., Saks, 2006) have pointed out that the job search is an unfolding process whereby job search behaviors lead to interviews, interviews lead to job offers, and job offers lead to employment. Thus, numbers of interviews and job offers have also been used to operationalize job search success and to evaluate intervention effectiveness.
Still others (e.g., Saks & Ashforth, 2002; Wanberg, et al., 2016) have suggested that the quality of jobs found as a result of the job search represents another critical way to assess intervention effectiveness and provides a more comprehensive way to study the job search process. A number of indices of employment quality have appeared in the literature. For example, Bae and Mowbray (2019) measured employment quality in terms of pay, amount of paid vacation, working hours (part‐time versus full‐time), work schedule (regular versus irregular), and union contract. Wanberg et al. (2016) suggested that indices of job quality cluster into three major dimensions: (a) type of job (full‐time versus part‐time, temporary, or contract), (b) extrinsic rewards (wages, benefits, work schedule, and location), and (c) intrinsic rewards (psychological need satisfaction, job satisfaction, ability–demand fit). Other indices of job quality that have been employed in research include intentions to quit or stay (Wanberg, Kanfer, & Rotundo, 1999) and underemployment (Wanberg, 2013) or perceived overqualification (Harari, Manapragada, & Viswesvaran, 2017).
Another way to consider the outcomes of the job search process involves the emotional toll it can place on the job seeker. As previously noted, the search process can be quite stressful for many individuals and can have a negative impact on their mental health and quality of life, at least temporarily. Thus, such indices of well‐being as mental health symptoms (e.g., anxiety, depression) and quality of life (e.g., subjective well‐being, life satisfaction) have also been suggested as important outcomes of the job search process (Paul & Moser, 2009).
Considering job search outcomes as multidimensional has provided a more complete and enriched understanding of the job search process than simply assessing employment status and speed. For example, research has revealed that job search effort and intensity (to be reviewed later in this chapter) relate consistently to status and employment speed outcomes, but not as consistently to employment quality outcomes (e.g., Kanfer et al., 2001). Rather, employment quality seems to be more strongly related to career planning and goal setting (Saks & Ashforth, 2002) and social network influences (Granovetter, 2005). Other research (e.g., Barbulescu, 2015) on the relationship of social networking to job search success has found that “weak” social ties (acquaintances) may be more effective than close ties (family and close friends) in generating job leads and job interviews, but less effective at generating job offers. Thus, a comprehensive understanding of the job search process and job search success requires a comprehensive and multidimensional definition of job search success.
Table 22.1 summarizes possible outcomes of a job search using three overarching categories to classify each specific type of outcome: (a) employment success (e.g., status and time), (b) employment quality (e.g., job satisfaction, employment benefits), and (c) mental health and well‐being (e.g., depression, life satisfaction). I use two success terms in this chapter—job search success and employment success. The former (job search success) denotes the success of the job search as measured by indices of employment success, employment quality, and mental health. Employment success, as one index of job search success (along with employment quality and mental health), refers to the searcher's success at attaining employment as measured by employment status, speed to employment, and number of job interviews and offers. In addition to enriching our understanding of the job search process, this multidimensional conception provides an overall index of job search success as directly related to progress on all three classes of outcomes—employment success, employment quality, and mental health and well‐being. The classification also suggests that interventions should be targeted to all three types of outcomes and evaluated based on progress on all three.
TABLE 22.1 Types and Indices of Job Search Success
Employment success
Employment quality
Mental health and well‐being
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Outcome research on job search interventions has historically lagged behind research on the search process itself but had yielded a sufficient sample of studies by 2014 to justify a meta‐analysis of the literature (Liu et al., 2014). Liu et al. meta‐analyzed the results obtained from 47 studies (with a total sample size of 9575) that had compared a job search intervention (i.e., a training program to help job seekers look for and secure employment) to no‐treatment control or comparison groups. Results focused primarily on job status outcomes (chances of finding employment) and potential moderating effects of several variables (e.g., age, gender, race). The study also reported standardized mean differences (ds) on both employment quality (i.e., starting salaries, job satisfaction) and mental health and well‐being (i.e., depression, anxiety, and overall well‐being) outcomes. Most importantly, Liu et al. identified six specific intervention components that were associated with greater odds of employment when they were included in intervention than when they were not part of the intervention.
This and the next two sections of the chapter will be devoted to elucidating the results of this meta‐analysis. In this section, I will summarize the intervention versus comparison group findings. In the subsequent two sections, I will focus on the critical ingredients and the moderator results, elaborating on them by incorporating research from the general job search literature to address three main questions: (a) how might the critical ingredients be incorporated to improve the effectiveness of interventions, (b) who benefits most and least from extant interventions, and (c) how might interventions be tailored to the unique needs of participants?
Liu et al. (2014) reported that the average intervention participant had an odds of obtaining employment (odds ratio or OR) that was 2.67 times greater than the average control or comparison group participant, suggesting that interventions are remarkably effective at helping participants secure a job (i.e., more than doubling their chances of finding a job). The results further revealed significant, though somewhat modest relationships between participating in an intervention and starting salaries (d = .14) and depression (d = −.13), and more substantial relationships with job satisfaction (d = .23), anxiety (d = −.46), and overall well‐being (d = .48). On the latter criteria, intervention (versus control) participants enjoyed about a quarter of a standard deviation advantage in job satisfaction and a half standard deviation advantage on overall well‐being and (lower) anxiety.
Collectively, these results are encouraging and suggest that extant interventions are quite effective at helping people find jobs. The results are also encouraging about the impact of interventions on at least one employment quality (job satisfaction) and two mental health and well‐being (anxiety and overall well‐being) outcomes. But what specific components of these interventions seem to be critical and how can they be implemented in practice? It is to these topics that I turn next.
Liu et al. (2014) coded seven potential critical intervention components based on a self‐regulatory model of the job search that integrates several theoretical perspectives (e.g., social cognitive, learning, planned behavior, and coping theories) into a single framework. The self‐regulatory perspective (e.g., Kanfer et al., 2001) views job search as a goal‐directed, relatively autonomous process subject to individuals' knowledge and skills to engage in a job search and their abilities to self‐regulate behaviors, effort, and emotions in order to persevere in the face of challenges and setbacks. Thus, Liu et al. coded intervention ingredients as potentially critical that focused on skill acquisition or motivational enhancement strategies. Skill acquisition strategies included teaching of (a) job search and (b) self‐presentation skills. Motivational enhancement activities focused on: (a) boosting self‐efficacy, (b) encouraging proactivity, (c) promoting goal setting, (d) enlisting support, and (e) managing stress.
For each intervention component, Liu et al. calculated two treatment versus controls odds ratios (ORs)—one for interventions that included the ingredient and one for those in which it was not included. Results revealed that the odds of obtaining employment were significantly higher in interventions that employed (versus did not employ) six of the seven intervention components. The only component that was not associated with significantly higher odds of obtaining employment was the teaching of stress management skills, which included anticipating and inoculating against setbacks, learning relaxation and expressive writing skills, and attributing setbacks to controllable factors. However, these findings concerning stress management skills may be a function of the outcome used in these analyses (i.e., employment status). Stress management procedures may not increase the odds of finding employment but may buffer against negative mental health consequences of the stressful job search process. Including stress management procedures in an intervention might, therefore, promote better mental health and well‐being outcomes among participants despite having little direct effect on their chances of landing a job. This still is an open question requiring additional research.
In the remainder of this section, I will discuss each of the six components that emerged as significantly related to employment odds ratios and incorporate consideration of findings from the job search process research that offer suggestions for how the components might be implemented.
Although Liu et al. (2014) coded job search skills and proactivity into separate categories (and classified the former as representing skill development activities and the latter as motivation‐enhancing strategies), there is a good deal of conceptual overlap between the two. Most significantly, teaching skills and encouraging proactivity are both intended to facilitate the job seeker's ability to identify employment opportunities. I will, therefore, discuss these two ingredients together and, in the process, suggest how they can complement each other.
Interventions that included the teaching of job search skills yielded an OR of 3.22 versus an OR of 1.62 among interventions that did not teach these skills. The skills taught focused on promoting job search behavior by making effective use of resources and job search strategies. Research on the job search process provides rich detail about skills and strategies that can inform intervention efforts.
Kanfer et al. (2001) suggested that effective job search behavior encompasses three related dimensions: (a) effort–intensity, (b) content–direction, and (c) temporal‐persistence. The effort–intensity dimension reflects how much effort individuals put into the job search (effort) and how frequently they employ job search resources (intensity). Content–direction focuses on how many resources are used during the job search and what specific resources are employed by individual job seekers. Temporal‐persistence recognizes that the job search is a dynamic process that requires persistence in the face of obstacles.
There has been a great deal of research on the effort–intensity and content–direction dimensions over the years. Perhaps the most consistent result in the literature is that job search effort and intensity relate positively to most indices of employment success (status, time to employment, and number of job offers), but not to indices of employment quality or mental health and well‐being. Kanfer et al. (2001) presented meta‐analytic data revealing that effort/intensity related positively to job status (r = .21), duration of the job search (r = −.14), and number of job offers received (r = .28). Saks (2006) reported data to suggest that the relationship of intensity to status and duration was mediated by number of offers—that frequently using resources resulted in more job offers which then translated into accepting a job. Subsequent studies have largely confirmed that effort and intensity are related (directly or indirectly) to employment success but not to employment quality or mental health outcomes (e.g., Saks & Ashforth, 2002; Wanberg et al., 1999).
Job search content, referring to the number and types of resources used to identify job leads, appears to account for additional variance in employment success outcomes and also relates to indices of employment quality. There are a variety of formal offline (e.g., employment offices, school placement offices) and online (online job postings) sources that individuals can use to identify job leads. There are also more informal sources (e.g., friends, acquaintances, past employers) that job seekers can access for job leads. These informal sources can be accessed directly (e.g., contacting acquaintances about job leads) or via the Internet (e.g., joining online networking sites such as LinkedIn).
Research suggests that the numbers and types of resources that job seekers use relate to both employment success and employment quality outcomes. For example, in a recent study of millennial‐generation adults (ages 28–34), Bae and Mowbray (2019) reported that job search activity (defined as the number of different online and offline formal and informal resources used) was positively associated with (a) hourly wages, (b) number of paid vacation days, (c) the odds of having a full‐time versus part‐time job, (d) regular versus irregular work schedule, and (e) obtaining a job covered by a union contract. Thus, it may be that the number of different resources people use in the job search yields better and more varied job possibilities than the amount of time they spend using an undefined number of resources (job search intensity). Job search activity may, therefore, contribute more to employment quality outcomes than do job search intensity and effort.
In addition to the number of varied resources that people use in the job search, the types of resources that people use may make a difference in their employment success and in the quality of jobs they obtain. Two important sources are job seekers' social networks and their use of the Internet and other online sources of information. Social networks in the context of the job search process refer to an individual's network of family, friends, acquaintances, work associates, and former employers who can provide information, job leads, and advice on getting jobs as well as serve as sources of support (Kanfer et al., 2001). In addition, social network members can exert influences over hiring decisions and provide references for the job seeker (Wanberg, 2013). It appears that many people worldwide find jobs via their social networks. For example, an international survey published in 2006 (Franzen & Hangartner, 2006) reported that 44% of respondents found their last jobs via their social networks, with national percentages ranging from 26% in Finland to 83% in the Philippines.
One of the strongest and most consistent findings concerning networking in the job search literature is that weaker, or less close, ties (acquaintances) are more strongly related to numbers of job leads and interviews than are stronger (family and close friends) ties (e.g., Barbulescu, 2015; Franzen & Hangartner, 2006) because more novel information flows through weak rather than strong ties. In other words, friends tend to know each other and provide a good deal of overlapping information. On the other hand, information provided by acquaintances is likely to be more novel and unique, resulting in a wider range of job possibilities. Granovetter (1973) termed this the “strength of weak ties” effect.
Job search interventions usually encourage and reinforce participants' networking behaviors. Some also try to enlarge participants' networks of weak ties by asking participants themselves to serve as weak ties for each other—to share job leads that they do not want to pursue (Azrin, Flores, & Kaplan, 1975). Other recent research (Sharabi & Simonovich, 2017) found that sharing strong ties may be an effective method for identifying job leads and landing jobs. These authors asked long‐term unemployed (a year or more) job seekers to identify their strong ties (family and friends) and then share them with other participants—one person's strong ties became another person's weak ties. The results of this pilot investigation (i.e., no control or comparison group was employed) revealed that 41% of these long‐term unemployed participants had found jobs within 1 month after participating in the network sharing intervention.
The influence of networks on job search success gets a bit more complicated when other indices of success are studied. For example, Barbulescu (2015) found that strong ties were associated more highly with number of job offers received than were weak ties, despite the fact that the latter (weak ties) were associated with more job leads and interviews. Similarly, Van Hoye, van Hooft, and Lievens (2009) found that the relationship between network intensity (how much individuals use their social networks) and perceptions of person–environment (P–E) fit, an index of employment quality, was moderated by network strength: networking was more strongly related to fit perceptions when strong versus weak ties were used to land a job. The former findings are perhaps due to the references that strong ties can provide to prospective employers and other influences they can have over hiring decisions. The latter (P–E fit) finding is likely due to stronger ties having more knowledge of the job seeker than do weak ties; stronger ties suggest better fitting types of work for the individual.
Finally, it appears that the status (i.e., levels of educational and occupational achievement) of the people in an individual's network makes a difference. Specifically, Van Hoye et al. (2009) found that networking intensity was more strongly related to job status (finding a job) when the status of people in the networks was high. In fact, the relation of network intensity to job status changed directions to a negative association when the job seeker's network was composed of lower‐status individuals. If these findings prove reliable, they may have very important implications for practice. First, they could account for some of the variance in the job finding difficulty that persons living in poverty experience (e.g., Wanberg, 2013). Second, practitioners working with persons from lower‐socioeconomic‐status (SES) backgrounds may need to encourage, aid, and reinforce efforts to go beyond their lower‐status networks to find work.
Although the networking literature is somewhat complicated, it does suggest that encouraging people to look beyond their immediate friends and family in the job search process will likely yield more job possibilities and interviews than keeping exclusively within the more comfortable confines of their closest ties. This holds true regardless of the job seeker's socioeconomic background and network status, but may be especially necessary for those whose networks are of lower educational and occupational status. Turning interviews into job offers may be facilitated by having stronger rather than weaker ties, but getting interviews is typically a necessary first step to receiving a job offer.
Taking steps to go beyond friends and family for help with job seeking can be stressful, challenging, and difficult for many people. Other strategies suggested in the job search literature, like making cold calls to prospective employers and asking potential employers who do not have job openings about possible job openings elsewhere, can be equally challenging for many individuals. All these activities require that the job seeker be proactive in the job search process and represent strategies coded by Liu et al. (2014) as encouraging proactivity. Interventions that were coded as encouraging proactivity yielded an OR (odds ratio) of 5.88 versus an OR of 2.18 among interventions that did not appear to encourage such proactive behavior. It is clear that encouraging such proactive behaviors as moving beyond friends and family in the job search process and engaging in other types of proactive behavior are critical intervention components, especially for the poor and under‐resourced who may have less ready access to higher‐status personal resources and may, therefore, need extra assistance in cultivating expanded support and information networks.
The Internet has emerged over the past 20 or so years as a major job search tool. It currently represents a major (if not the only) resource that many people use in the job search process (e.g., Buettner, 2017). Research suggests that more job possibilities can be identified via Internet searches than by print outlets (Van Rooy, Alonso, & Fairchild, 2003) and that such sites as LinkedIn, Facebook, and Twitter can function quite effectively as job networking resources (Buettner, 2017; Kuhn & Mansour, 2014). Kuhn and Mansour (2014) found that users of these online social network sites found work 25% faster than those who did not use them, but Buettner (2017) found that a curvilinear relationship between number of contacts and job offers seemed to fit the data better than a linear relationship: job offers increased linearly with number of contacts up to 150, but then leveled off and even decreased after that. Other research has suggested it is the strong rather than weak ties within an individual's online network that produce more job leads, interviews, and offers (weak ties were linked only to number of job leads; Wanberg et al., in press).
It is clear that the Internet represents an important avenue for accessing social networks (e.g., 150 network members is probably more than most people could easily access through more personal means), generating job possibilities, and posting resumes. However, there is also some evidence that the Internet should represent an important but not sole job search resource. Recall that Bae and Mowbray (2019) found that the number of online and offline job search activities engaged in by a large sample of 20‐ and 30‐year‐old adults was related to a variety of employment quality indices (e.g., pay, full‐time work, regular work schedules).
In addition to the resources that people use to identify job leads and access employment opportunities, research suggests that there are two additional job search skill‐related activities that need to be included in effective job search interventions. The first represents the search strategies that people use in finding work. Crossley and Highhouse (2005) suggested that there are three different types of job search strategies that people might employ: (a) focused, (b) exploratory, and (c) haphazard. Persons using a focused strategy have clearly defined criteria for what they want out of their work and focus their search efforts only on job possibilities that meet their criteria. Those using an exploratory strategy are more open to different job possibilities and gather information more widely than do focused job searchers. A haphazard strategy is different than focused or exploratory strategies in that persons who use this strategy tend to apply to any job that becomes available regardless of qualifications and other job characteristics. Focused and exploratory strategies are both positively related to numbers of job offers, but only the focused strategy is related to job satisfaction. Haphazard strategies relate negatively to both offers and job satisfaction (e.g., Crossley & Highhouse, 2005).
There are also data suggesting that career planning may be an important intervention component if a goal is to help individuals find satisfying work. Saks and Ashforth (2002) surveyed graduating college students at two time points: (a) upon receiving a job offer, and (b) 4 months later. As expected, Saks and Ashforth found that effort and intensity related to job status, but not to postemployment job satisfaction. Rather, students who said they had engaged in career planning (i.e., the degree to which they had plans and goals for their careers) reported more postemployment job satisfaction than did those who did not have clear career plans and goals. Finally, the relationship between career planning and job satisfaction was mediated by person–job (P–J) fit perceptions—career planners were more likely to be in better fitting jobs, which in turn was related to higher levels of job satisfaction. The same pattern of findings (relationship between career planning and job satisfaction and/or fit perceptions) has since been replicated (e.g., Saks, 2006; Zikie & Klehe, 2006). As might be expected, career planning is also related to likelihood of engaging in a focused versus exploratory or haphazard job search (Crossley & Highhouse, 2005).
In summary, teaching job search skills and encouraging proactivity are both important components of job finding interventions. Findings suggest that participants in such interventions are more likely to become employed if they are encouraged to work hard and put effort into the job search. However, the odds of achieving a higher‐quality job may be enhanced when job seekers also use as many formal and informal, online and offline resources as possible, make use of weak ties in their social networks, do cold calls to potential employers, and engage in other informal strategies that require proactivity on the part of the job seeker. Also, including career planning activities in interventions might enable persons to find better fitting and more satisfying jobs. Career planning activities may also be necessary to engage in successful focused job searches, although exploratory strategies can also be helpful in generating job leads. Finally, persons from lower‐SES backgrounds may need considerable help and support to reach out beyond their current social networks in search of job leads, and job search interventions might be able to facilitate this process.
Although identifying job leads is an important part of a successful job search, it is also critical to be able to obtain interviews and, to the extent possible, to turn interviews into job offers. These objectives may be served by techniques, such as effective resumes and job interviewing skills, that fall under the heading of improving self‐presentation (Liu et al., 2014). Indeed, teaching self‐presentation skills (e.g., preparing effective resumes and preparing effectively for job interviews) was found to be a critical component of intervention effectiveness (ORs = 3.34 when included versus 1.61 when not included).
In terms of preparing effective resumes, recruiters continue to prefer short, grammatically correct, and error free resumes that are more formal than informal (Arnulf, Tegner, & Larson, 2010) and that include competency statements and information on work‐related experiences (McNeilly & Barr, 1997). Group‐based job search interventions provide opportunities for persons to learn about the appearance and content of effective resumes, prepare resumes, and receive feedback (from leaders and group members) on them (e.g., Azrin et al., 1975).
Data suggest that effective interviews have several common characteristics, including (a) having a professional appearance and appropriate dress, (b) acting confidently, (c) being articulate, concise, to the point, and cooperative, (d) varying voice pitch and volume, and (e) maintaining appropriate eye contact, appearing at ease, sitting erect, and having an attentive posture (e.g., Barrick, Shaffer, & DeGrassi, 2009; Saks & Ashforth, 2000). In addition, the interview provides interviewees opportunities to promote themselves (Barrick et al., 2009) and deal with potentially problematic aspects of their present conditions (e.g., disabilities) and work histories (e.g., incarceration; Wanberg, 2013). At least some of these behaviors may be seen as culturally laden and, therefore, need to be approached with multicultural sensitivity.
Findings suggest that interviewing skills and confidence can be effectively promoted via simulated interviewing training (i.e., role plays) that includes modeling of effective behavior, guided practice, and feedback (Azrin et al., 1975). More recent research by Smith and his colleagues (e.g., Smith, Fleming, et al. (2015); Smith, Humm, et al. (2015); Smith, et al. 2016, 2017) has tested virtual reality job interviewing training (VR‐JIT) as an interview training tool (see www.simmersion.com). In VR‐JIT, participants practice various job interviewing skills with a virtual PR representative. Results suggest that VR‐JIT may be an effective method of teaching interview skills to individuals with (a) severe mental illness and autism spectrum disorders (Smith, Fleming, et al., 2015, 2017), (b) substance abuse disorders (Smith et al., 2016), and (c) veterans with post‐traumatic stress disorder (PTSD; Smith, Humm, et al., 2015). Smith et al. (2017) showed that number of completed virtual interviews may be critical to VR‐JIT effectiveness—the number of virtual interviews was associated with job status (accepted job offers) via the quality of interviewing skills that participants had mastered.
Finally, in addition to learning interview skills, preparing for the interview should be a central part of self‐presentation training. Interview preparation involves (a) social preparation (talking to friends, job incumbents, and fellow participants about what to expect in a job interview), (b) background preparation for the interview itself, and (c) thinking about and rehearsing possible questions and answers. Research (e.g., Caldwell & Burger, 1998) has shown that preparation is associated with increased job search confidence (or self‐efficacy beliefs, to be discussed later), reduced anxiety, and more follow‐up interviews and job offers among job seeking college students.
Goal setting has been seen for some time as a central component of successful job search efforts (Kanfer et al., 2001; Lent & Brown, 2013; van Hooft, Wanberg, & van Hoye, 2012). Goals have been found to organize individuals' attention on goal pursuit, facilitate goal‐directed actions, and sustain goal‐directed efforts in the face of difficulties and challenges. In particular, social cognitive theory (Bandura, 1991; Lent & Brown, 2013) and the theory of planned behavior (Ajzen & Fishbein, 1980) hypothesize that goals (labeled intentions in the theory of planned behavior) are among the strongest proximal predictors of actions. Indeed, the general job search literature as well as the job search intervention literature has supported the important role that goals play in successful job search efforts.
Research on the job search process has mostly focused on the clarity of individuals' job search goals (goal clarity). This research (e.g., Cote, Saks, & Zikic, 2006; Van Hoye & Saks, 2008) has demonstrated that goal clarity is associated positively with both job search effort/intensity and job search activity (i.e., the number of sources used in the job search). As discussed earlier in this chapter, job search intensity relates quite consistently to indices of employment success (e.g., status and time to employment), while job search activity has been shown to relate to several indices of employment quality (e.g., pay, full‐time versus part‐time employment; Brae & Mowbray, 2019). Also, career planning that involves establishing career goals relates positively to job satisfaction via P–E fit perceptions and the use of focused search strategies (Crossley & Highhouse, 2005; Saks & Ashforth, 2002).
The meta‐analysis of the job intervention literature by Liu et al. (2014) defined goal‐setting activities as involving both career‐/work‐related and job‐search‐related goals. Career/work goals included setting goals for types of occupations, jobs, and salaries to pursue. Job search goals focused on developing goals about job search activities to pursue (e.g., make a certain number of phone calls, search the Internet, and post one's resume on a certain number of electronic sites by end of the week). The odds ratio associated with interventions that employed such goal‐setting activities was 4.67 versus 2.13 among interventions that did not focus on goal setting.
These findings suggest that goal‐setting activities should be central in job finding interventions and should include attention to both career‐/work‐related and job search goals. The former types of goals help to focus the job search, while the latter serve to motivate and sustain search behavior. While career‐/work‐related goals are more long‐term, job search goals are more proximal and specific and can be established on a daily or weekly basis as part of the job search interventions and reviewed during program meetings (see Azrin et al., 1975). Research suggests that clearly stated proximal goals can enhance goal‐related self‐efficacy beliefs, satisfaction with progress toward distal goals (i.e., getting a job, including one that is consistent with one's values), and persistence in the face of obstacles (Bandura, 1991; Amabile & Kramer, 2011).
Research also suggests that having goals may not be enough to sustain job search efforts over time. Rather, meta‐analytic data (Epton, Currie & Armitage, 2017) suggest that it may also be helpful to (a) publicly declare one's job search goals in a group setting, (b) put them in writing, and (c) develop implementation intentions (e.g., Gollwitzer & Sheeran, 2006). The latter (implementation intentions) involve specifying when, where, and how goals will be acted upon (e.g., “I will make three phone calls from my home after lunch on Monday”). A meta‐analysis of the implementation intentions literature (Gollwitzer & Sheeran, 2006) reported that implementation intentions increased goal attainment (average d = .65) across a number of different domains and age groups.
Self‐regulation models also advocate for developing strategies to maintain goal focus during times of difficulty. Possibilities include (a) goal shielding (i.e., keeping goals accessible and active and protecting them from interference from competing goals), (b) goal maintenance (elaborating on what makes goal attainment important), (c) self‐monitoring goal progress, and (d) seeking feedback from others (see Van Hooft et al., 2012 for a more complete discussion of goal maintenance strategies).
In summary, the job search is a challenging endeavor that may require sustained activity over a long period of time. Goal setting, planning, and maintenance activities can serve to help sustain effort and motivation. Job finding interventions can provide a logical setting to receive assistance in establishing goals for the job search process, publicly declaring one's goals, learning goal maintenance strategies, receiving useful feedback on goal progress, and building robust self‐efficacy beliefs about job search competencies (to be discussed next). Adding a career planning component to job search interventions—where career/work goals and plans are explicitly established—can foster more focused job searches, greater P–E fit, and job satisfaction.
Liu et al. (2014) found that interventions that employed strategies to boost self‐efficacy (primarily job search and networking self‐efficacy beliefs) were more effective (OR = 3.25) than interventions that did not include this component (OR = 1.73). Self‐efficacy beliefs, central parts of Bandura's (1986) social cognitive theory, have been defined as people's judgments of their capabilities to enact behaviors necessary to reach goals. Self‐efficacy beliefs are context‐specific and malleable judgments of personal capabilities that influence approach versus avoidance behavior, foster effort and persistence in the face of obstacles, and improve domain‐specific performance (see Lent, Chapter 5, this volume). Thus, persons with stronger versus weaker job search self‐efficacy (JSSE) are more confident that they can undertake necessary job search activities, and more likely to develop and implement job search strategies, persist in the face of difficulties, and succeed in finding a job. Similarly, people are more likely to seek out weak ties in their networks for job leads (and persist) when they are relatively confident that they can do so.
Meta‐analytic research on the role of self‐efficacy in the job search process largely supports these expectations. Kanfer et al. (2001) found that JSSE beliefs were positively related to job search effort/intensity and to numbers of job offers and employment status (largely via the mediating effect of job search effort/intensity). Kim, Kim, and Lee (2019) conducted a meta‐analysis on hypothesized antecedents and consequences of JSSE and replicated the results of Kanfer et al. (2001)—JSSE related positively to job search effort (r = .29), job search intensity (r = .27), number of job offers (r = .23), and employment status (r = .12). They also found that JSSE related to other indices of job search process and outcome: job search goals (r = .27), goal clarity (r = .46), interviews (r = .15), job satisfaction (r = .17), depression (r = −.19), anxiety (r = −.31), and life satisfaction (r = .44).
Research also shows that self‐efficacy beliefs can be boosted by exposing people to demographically similar models (in terms of gender and race) who have successfully undertaken job searches (vicarious experience) and by graded job search success experiences followed by feedback (mastery experiences). Additionally, self‐efficacy beliefs are more likely to develop when persons' job search actions are encouraged, reinforced, and supported by others (social persuasion), and when they are performed without undue anxiety (affective states; see Lent, Chapter 5, this volume). Liu et al. (2014) coded an intervention as boosting self‐efficacy if any or all of the four efficacy boosting strategies (vicarious experience, mastery experiences, social persuasion, or affective states) were employed.
Unfortunately, job search research and intervention efforts have not made full use of Bandura's (1986) social cognitive theory, which is often reduced to a sole focus on self‐efficacy in the job search literature despite the fact that other motivational elements are part of the theory. One of these is outcome expectations or the consequences that one expects for engaging in a specific set of behaviors (e.g., job search behaviors). JSSE addresses the question: Can I engage in a successful job search? Job search outcome expectations ask, what will happen if I try? Outcome expectations can be tangible/material (e.g., finding a job), social (e.g., gaining respect from others), or personal (e.g., gaining self‐respect), and, like self‐efficacy, predict approach behaviors, effort and persistence, and performance. Self‐efficacy and outcome expectations together predict these approach, persistence, and performance behaviors better than either self‐efficacy or outcome expectations alone (Brown & Lent, 2019). Extrapolating from social cognitive theory, people will be more likely to enact job search behavior to the extent that they believe they are capable (self‐efficacy) and that it will be worth the effort (favorable outcome expectations).
In an extension of social cognitive career theory (SCCT; Lent, Brown, & Hackett, 1994), Lent and Brown (2013) presented a social cognitive career self‐management model that might serve as a template for incorporating outcome expectations and self‐efficacy beliefs into job finding intervention efforts (see Lent, Chapter 5, this volume). The most basic predictions of this model are that (a) goals to engage in particular job search behaviors (e.g., behaviors that require proactivity) are a function of self‐efficacy and outcome expectations, (b) self‐efficacy beliefs and outcome expectations are related (e.g., job finding confidence will promote optimistic outcome beliefs), and (c) goals (along with self‐efficacy and outcome expectations) predict active behavioral engagement.
Lim, Lent, and Penn (2016) tested this model in two studies of the job search process. One study included unemployed job seekers, while the other study was of first‐time job seeking college seniors. Path analyses suggested the self‐management model fit the data well in both samples and that JSSE beliefs and outcome expectations predicted intentions (goals) to engage in the job search. The second study involving first‐time job seekers found that job search goals were the key predictor of job search behaviors. Thus, efforts to promote job search behavior may well employ procedures to establish clear search goals, boost self‐efficacy for search behaviors, and encourage positive expectations for the consequences of search behavior.
There is ample evidence that receiving tangible and emotional support from others is a powerful buffer of mental and physical health outcomes during times of stress, including the stress associated with the job search (Paul & Moser, 2009). Other research on the job search process has found positive associations between social support from family and friends and job search effort (Kanfer et al., 2001), intensity (Rife & Belcher, 1993), employment status (Kanfer et al., 2001), and JSSE beliefs (Kanfer et al., 2001). Recent research suggests that friends and acquaintances generated via the Internet can be important sources of caring and enabling support. In addition to reducing the sense of social isolation that many unemployed job seekers experience, Internet‐generated support might also boost their JSSE (Fieseler, Meckel, & Muller, 2014). Finally, Liu et al. (2014) found that enlisting social support was a particularly important job search intervention component: ORs were 4.26 when social support was included in interventions versus 1.95 when it was not.
Interventions in the Liu et al. (2014) meta‐analysis tended to approach social support building in two primary ways. First, many interventions encouraged participants to reach out to their family and friends for emotional support and, if necessary, taught them (via modeling and role playing) how to do so. Second, some interventions included family and friends or contacted family and friends to encourage them to provide emotional (e.g., reassurance) and tangible (e.g., babysitting, transportation) support and job leads to participants. The social interactions occurring within interventions themselves can also serve as built‐in sources of support and feedback (van Hooft et al., 2012) and as major sources of job leads (Azrin et al., 1975).
Meta‐analytic data suggest that job finding interventions can be an effective means of searching for a job. Well‐developed interventions are associated with gains on all three major types of outcomes—employment success (e.g., employment status and speed, numbers of interviews and offers), employment quality (e.g., P–E fit and job satisfaction), and mental health and well‐being (e.g., mental health symptoms, life satisfaction). These effects seem to be facilitated by the group nature of job search training interventions (e.g., via support, feedback, and job leads provided by fellow participants) as well as by teaching job search skills, encouraging proactivity, improving self‐presentation, facilitating goal setting, boosting self‐efficacy, and nurturing support. Theoretically, attention to outcome expectations, which fosters hope, along with self‐efficacy and goal setting, may facilitate use of job search skills and engagement in proactive search behavior (Lent & Brown, 2013).
Results of moderator analyses presented by Liu et al. (2014) demonstrated that job finding interventions appeared to help persons who need help the most, such as both younger and older job seekers and those with special needs or conditions (e.g., chronic health or mental health problems, substance abuse treatment participants, ex‐offenders). The meta‐analytic data also suggested that job finding interventions might help close employment gaps associated with local unemployment rates, gender, and race/ethnicity. Finally, findings from the job search literature point to other individual differences variables that may moderate the effectiveness of different intervention components.
Liu et al. (2014) found a curvilinear, U‐shaped relationship between job status rates and age. Interventions were associated with higher ORs for younger (age < 35; OR = 4.05) and older (age > 50; OR = 8.80) participants than for those between the ages of 36–50 (OR = 1.80). Employment data also suggest that younger and older workers may be in most need of help in the job search process—a similar U‐shaped function has been found for unemployment and underemployment rates, with younger and older workers having higher unemployment and underemployment rates than middle‐aged workers (Harari et al., 2017; Wanberg, 2013).
There are a number of reasons for this pattern of results, including human capital, social capital, discrimination and stereotypes, and job search strategies. For example, younger and older workers typically have less social capital (Wrzus, Hanel, Wagner, & Neyer, 2013)—smaller employment‐related networks due to lack of work experience (for younger workers) or network loss (for older workers). In other words, younger and older workers may simply have fewer working people in their networks to call upon for job leads and other types of assistance (e.g., providing recommendations).
Younger and older workers may also use fewer resources to identify jobs. Younger workers may rely too heavily on technology, while older workers may be unfamiliar with technology and use it less in the job search process (Wanberg et al., 2016). Younger and older workers also tend to feel less efficacious about their job search skills than others (Kim et al., 2019). Finally, meta‐analytic data suggest that many employers hold negative stereotypes of older employees (Ng & Feldman, 2012), and that older workers may put less effort into the job search process, have more work‐related health issues (Wanberg et al., 2016), and higher wage expectations than other job seekers (Vansteenkiste, Deschacht, & Sels, 2015). Thus, effective job search interventions that include attention to all of the critical ingredients discussed earlier may reduce the human and social capital difficulties that older and younger workers encounter in the job search process, boost JSSE beliefs, encourage more complete job search efforts, and prepare for encounters with stereotypes and discrimination.
There are a number of special needs and conditions that can cause difficulty in finding any job, let alone finding a high‐quality job. For example, unemployment and underemployment rates are high among persons with chronic health (Li‐Tsang, Li, Lam, Hui, & Chan, 2008), mental health, and substance abuse (e.g., Foley et al., 2010) problems. Unemployment and underemployment can also exacerbate pre‐existing health, mental health, and substance abuse problems (Paul & Moser, 2009). There is also ample evidence that ex‐offenders have difficulty finding work after incarceration and the work that is found is often low‐paying and without benefits (Pager, 2007). It is, therefore, heartening to note that job finding interventions for people with such “job handicapping” conditions and experiences are notably effective (OR = 4.60 versus OR = 2.27 for job seekers in general). Interventions that contain all of the critical components can help generate increased job possibilities, serve as efficacy‐enhancing resources, and provide support (and information) during the job search. Perhaps most importantly, learning self‐presentation skills that allow participants to counter negative stereotypes and questions about employability may be critical for this special population of job seekers.
Evidence suggests that finding a job is harder when general unemployment rates are high and that people need to work harder and put more effort into the job search than they do under more favorable economic conditions (Manroop & Richardson, 2016; Wanberg et al., in press). Other evidence shows that the unemployment and underemployment rates of women and ethnic/racial minorities are higher than those of men and Whites (see Chapters 9 and 10 of this volume for a discussion of employment‐related issues of women and Racial/ethnic minority persons). There are many reasons for the Racial/ethnic disparity in employment, including both personal capital (e.g., differences in experiences and education) and social capital influences (e.g., access to status networks). However, these two sources of differences do not explain all of the variance in employment rate differences (Hiemstra, Derous, Serlie, & Born, 2013). Rather, experiences of discrimination also contribute to employment discrepancies.
Prager, Bonikowski, and Western (2009) had White, Black, and Hispanic confederates apply for entry‐level jobs in New York City. Their resumes, credentials, social skills, physical appearance and attractiveness, and test performances were matched as closely as possible. Despite this, White applicants had significantly higher call back rates for second interviews or job offers (31%) than did Hispanic (25.2%) and Black (15.2%) applicants. As for gender, there is also evidence that employers discriminate in making hiring decisions based on whether a woman is pregnant or intends to become pregnant (Correll, Benard, & Paik, 2007) and on the basis of her weight (Roehling, Roehling, & Pichler, 2007).
Despite this pattern of employment differences, Liu et al. (2014) did not find significant gender, race, or local employment rate differences in intervention effectiveness. To be more precise, they found no significant relations of employment odds ratios to the percentage of women or minorities in an intervention; neither did the ORs differ based on local employment rates. Thus, well‐developed job search interventions might represent a means of closing employment gaps associated with local unemployment rates, gender, and race. Components of effective interventions certainly seem aimed at ameliorating factors assumed to account for these employment gaps, including (a) encouraging and reinforcing increased effort and intensity, (b) expanding available job options, (c) providing support within the training group and leveraging external sources of support, and (d) training in interview skills, particularly in being able to handle difficult issues that arise during a job interview.
Three core personality variables—extraversion, conscientiousness, and trait proactivity—are consistently associated with job search success via their relationships to JSSE beliefs, job search effort/intensity, network use, interview performance, and job offers. Extraversion (Cosa & McRae, 1992) is characterized by three main features: social orientation, energy, and positive emotions. Extraverted people tend to be sociable and outgoing, energetic and active, and to feel a variety of positive emotions. Conscientiousness (Costa & McRae, 1992) is also defined by three main facets: achievement orientation and goal directedness, reliability and dependability, and planfulness and organization. Trait proactivity (Brown, Cober, Kane, Levy, & Shalhoop, 2006) represents a dispositional tendency to take initiative across a range of situations and activities.
Research suggests that persons who are more outgoing, active, and happy (extraverted), goal‐directed, reliable, and planful (conscientious), and initiative‐taking (trait proactive) tend to (a) work harder and more intensely at the job search (in part via JSSE beliefs), (Kanfer et al., 2001; van Hooft et al., 2012), (b) make greater use of, and work more intensely with, their social networks (in part via networking self‐efficacy beliefs) (Van Hoye et al., 2009), and (c) receive more job interviews and subsequent job offers (in part via interviewing self‐efficacy beliefs; Kim et al., 2019) than their less extraverted, conscientious, and proactive peers. Thus, under ordinary conditions, extraverted, conscientious, and proactive individuals may fare relatively well in the job search process. On the other hand, less extraverted, conscientious, and proactive individuals may represent excellent candidates for job search interventions.
There are two interventions in the job search literature that have received substantial empirical support for their effects on employment success, employment quality, and mental health outcomes—the Job Club (Azrin et al., 1975) and JOBS programs (Caplan, Vinokur, Price, & van Ryn, 1989). These two interventions have much in common and, although they predated much of the research on the job search process, they adhere closely to what we have learned about job search success. First, they are both quite intensive and require considerable effort on the part of participants—the original Job Club met 5 days a week for 2 hours a day, while the original JOBS intervention met for 2 weeks, with 4, 3 hour sessions per week (the duration of the Job Club was open‐ended). Second, they both use a group format which serves as a source of emotional and instrumental support and a facilitator of learning (see Kondo, 2009 for data on the benefits of group formats for job search interventions). Third, they both focus on teaching job search skills via modeling, guided practice, and feedback. The job search skills taught include (a) using as many available resources as possible to identify job leads, (b) preparing resumes and job applications, and (c) acquiring job interview skills and confidence.
Each program also had some unique features. The Job Club was primarily designed to impact employment success (i.e., job status and speed) and was developed from a behavioral learning theory framework. Thus, in addition to teaching skills via modeling, guided practice, and feedback, other features were added to boost motivation and learning. Foremost among these was establishing a buddy system, asking people to share job leads with each other, requiring participants to establish goals for what they wanted to accomplish between sessions, and reporting back on goal progress. The buddy system paired two participants together to provide support and feedback to each other (e.g., feedback on performance on a cold call), while the sharing of job leads served as an additional networking source.
The JOBS program, by contrast, was developed as a preventive intervention. It was designed specifically to prevent adverse mental health consequences of job loss via teaching motivation‐enhancing strategies (e.g., strategies to boost self‐efficacy), providing and building social support (e.g., by directly encouraging families to aid in the process and provide emotional support), and inoculating against setbacks (e.g., learning to anticipate situations where setbacks might occur, developing alternative ways to handle these situations, and learning skills to cope with setbacks; see Brownell, Marlatt, Lichtenstein, & Wilson, 1986).
Outcome data on the initial trials of these interventions were promising. Azrin et al. (1975) randomly assigned out‐of‐work referrals to the Job Club intervention or a “service‐as‐usual” control condition. Results revealed that a greater percentage of Job Club participants (92%) than control participants (60%) found jobs within 90 days, and that Job Club participants did so in an average of 14 days (versus 53 days for control participants). Job Club participants also obtained higher average wages than control group members. These results were replicated over the years in a variety of different samples. For example, Brown and McPartland (2005) meta‐analyzed employment rate data from 33 outcome studies that included samples of clients with disabilities, psychiatric patients, welfare recipients, unemployed white‐ and blue‐collar workers, and college students. Average employment rates of Job Club participants were significantly higher (65%) than the employment rates of members of various control (e.g., delayed treatment) or comparison groups (38%; e.g., workshops, individual counseling). Other research also demonstrated that Job Club interventions are associated with positive changes in mental health outcomes (Rife, 1992; Rife & Belcher, 1994).
Initial results associated with the JOBS intervention were also promising. There were significant differences at a 4‐month follow‐up interval in employment rates between JOBS participants (59%) and “service‐as‐usual” participants (51%), as well as in monthly earnings, quality of life, and self‐reported P–J fit. There were no differences on mental health outcomes, although subsequent research has revealed that the JOBS intervention is associated with reductions in depressive symptoms, especially among those at high risk for depression (Price, Van Ryn, Vinokur, & Amiram, 1992; Vinokur, Price, & Schul, 1995).
Moore, Hawton, Richards, Metcalfe, and Gunnell (2017) recently conducted a review of randomized clinical trials (RCTs) of interventions designed to reduce the impact of unemployment on depression. They identified five RCTs that they labeled as “job club” interventions, though these actually combined three RCTs of JOBS interventions and two RCTs of Job Clubs. Moore et al. (2017) concluded that, as a group, the “job club” interventions were the most consistently effective interventions at reducing depressive symptoms of the unemployed compared to a variety of other intervention types (i.e., cognitive behavior therapy, emotional competency training, expressive writing, guided imagery, and debt advice).
In summary, the findings suggest that Job Club and JOBS interventions are demonstrably effective interventions for the unemployed and those seeking work for other reasons. They have shown themselves to be more effective than other types of interventions (including workshops and individual counseling) in promoting employment success (e.g., job status and time to employment), employment quality (e.g., income, job satisfaction, and P–J fit), and mental health (e.g., lower depression, higher quality of life) outcomes. It is, therefore, recommended that, when possible, clients seeking work be referred to one of these two types of interventions.
Much has been learned over the last 20 or so years about how to help people find work, including work that could be classified as decent, satisfying, and well‐fitting. It may be more difficult in today's precarious world of work than it was in “better times,” but finding satisfying, full‐time work is still possible for many workers. I summarize below the most important take‐home messages for those readers who might want to engage in the important work of helping people find work.