how to research job satisfaction

7 Best Job Satisfaction Scales, Questionnaires & Surveys

Sometimes we feel very satisfied, other times we feel incredibly disheartened and unsatisfied.

Measuring job satisfaction is important because it can predict our future behavior (Faragher, Cass, & Cooper, 2013).

For example:

• Are we likely to resign from our jobs?
• Are we at risk of poor health?
• Is it highly likely that we will suffer burnout?

In this post, we explore various ways of measuring job satisfaction. We’ll look at the most widely used tools in the literature and discuss other challenges of measuring job satisfaction.

Finally, we will look at the resources available at PositivePsychology.com to increase job satisfaction among employees.

Before you continue, we thought you might like to download our three Work & Career Coaching Exercises for free . These detailed, science-based exercises will help you or your clients identify opportunities for professional growth and create a more meaningful career.

This Article Contains:

5 best practices for measuring job satisfaction, 3 evidence-based questionnaires, 2 surveys and scales to measure employees’ satisfaction, 2 key metrics to consider, 2 tools for measuring employee engagement, a note on employee health: measuring stress and burnout in the workplace, increasing job satisfaction: 6 positivepsychology.com tools, a take-home message.

What is meant by the term ‘job satisfaction,’ and how is it measured?

Challenges when measuring job satisfaction

As a psychological construct, job satisfaction is meant to reflect employees’ level of satisfaction with their work.

Questionnaires that measure job satisfaction ask questions about various attitudes and behaviors; the responses to these questions are totaled and reflect job satisfaction. This implies that an employee might have low job satisfaction, but their score might be explained by low scores on only one dimension.

Furthermore, job satisfaction develops slowly. It is a dynamic process, and job satisfaction now does not guarantee job satisfaction in five years . This is because job satisfaction is affected by many conditions within the workplace, and these conditions can change.

Therefore, job satisfaction as a measurable psychological construct describes the attitude of the employee to the current workplace conditions (Earl, Minbashian, Sukijjakhamin, & Bright, 2011).

Five best practices

Knowing this, the best practices for measuring job satisfaction are as follows:

• Measure job satisfaction regularly so that you have a baseline measurement for each employee or can calculate an average across employees. With a baseline measurement on hand, you can track changes in job satisfaction.
• Using questionnaires and surveys is one of the multiple ways to track job satisfaction. The advantage of these tools is that employees can respond privately, without the added pressure of social interaction. However, keep in mind that these responses are still self-reported, and employees may report in ways that appear socially desirable.
• Follow up questionnaires and surveys with interviews and discussions. Check in regularly with employees, address grievances, and provide feedback . Regular meetings require time and effort, but personal check-ins are very useful and can help develop positive relationships with employees .
• Check in with superiors, team leads, and managers to discuss the engagement of team members .
• Provide a way for employees to report grievances anonymously. Steps 2 and 3 are not anonymous, and therefore some employees may not feel comfortable raising thorny issues. An anonymous process, like a suggestion box, gives employees an avenue to report sensitive issues.
• Assure employees that their responses are confidential and their responses will not be shared with anyone except the people scoring the questionnaires.

Van Saane, Sluiter, Verbeck, and Frings-Dresen (2003) evaluated 35 different tools that measure job satisfaction in a meta-analysis.

To be considered in the meta-analysis, the tools had to meet acceptable psychometric standards, including an internal reliability of 0.80 or higher, a test-retest coefficient of 0.70 or higher, and at least four measured work factors that were proposed to affect job satisfaction.

Although 29 items were included in the meta-analysis, only 7 met the criteria for reliability and validity. Of these, four items were developed for nurses and physicians. The remaining three tools were:

• The Job in General Scale (JIG) & Job Descriptive Index (JDI)
• The Job Satisfaction Survey (JSS)
• The Andrews and Withey Job Satisfaction Questionnaire

Job in General Scale & Job Descriptive Index

Of these three, the JIG Scale is one of the most well-used questionnaires to measure job satisfaction (Ironson, Smith, Brannick, Gibson, & Paul, 1989). The JIG was developed to accompany another worthwhile tool to measure job satisfaction: the JDI (Smith, Kendall, & Hulin, 1969).

Both tools can be administered together as a single tool. For these tools, employees select items that appropriately describe a particular aspect of their career. For example, employees must indicate if the item ‘Stimulating’ describes their colleagues, answering ‘yes,’ ‘no,’ or ‘cannot decide.’

The JDI and JIG are freely available, and the administrative manual, norms, and a scoring manual can be requested from the Bowling Green State University website .

Job Satisfaction Survey

Although the Job Satisfaction Survey (Spector, 1985) was designed to measure satisfaction among employees who work in the human service, public, and nonprofit sector organizations, Spector argues that the JSS applies to other industries as well. The JSS is also much shorter than other surveys, with 36 items in total.

Each item is a statement, and the employee must show their level of agreement on a scale from 1 to 6, where 1 indicates ‘disagree very much’ and 6 indicates ‘agree very much.’ The 36 items map onto 9 different dimensions, and responses to each subscale are summed. The items, administration, and scoring instructions can be found on Paul Spector’s website .

Andrews and Withey Job Satisfaction Questionnaire

The Andrews and Withey Job Satisfaction Questionnaire was developed in 1976 and is outlined in the book Social Indicators of Well-Being: Americans’ Perceptions of Life Quality (Andrews & Withey, 2012). The almost 100-page questionnaire must be purchased from the authors.

Although the questionnaire has satisfactory psychometric properties, the questionnaire is extremely long to administer.

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Let’s look at two surveys that can be used to measure employees’ job satisfaction.

The Gallup Workplace Audit

The Gallup Workplace Audit (GWA) measures various actionable aspects of the workplace, including work satisfaction (Gallup Organization, 1992–1999). In total, there are only 13 items. Employees respond on a scale from 1 to 5.

For the first item about workplace satisfaction, 1 indicates ‘extremely dissatisfied,’ and 5 indicates ‘extremely satisfied’; however, for the next 12 items, the anchors change to ‘extreme disagreement’ and ‘extreme agreement,’ respectively.

These 12 items comprise the Q 12 (Harter, Schmidt, Killham, & Agrawal, 2009), which has been used extensively and has good psychometric properties. Although the items of the GWA are listed in Harter, Schmidt, and Hayes (2002), the GWA may not be used without permission from The Gallup Organization .

Job Diagnostic Survey

The Job Diagnostic Survey (JDS) has been used across various research (Hackman & Oldham, 1974, 1975). The JDS measures overall job satisfaction and satisfaction for five dimensions of work, such as

• Job security
• Supervision
• Growth opportunities

The survey is split into eight sections, and in the fourth, the employee rates their level of satisfaction with the five dimensions of work. The survey takes less than 30 minutes to administer. The full scoring instructions are listed in Hackman and Oldham’s (1974) research paper, which is available from the ERIC Institute of Education Sciences website .

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Moderating variables

The relationship between job satisfaction and job performance is complicated; job satisfaction influences job performance, which in turn, influences job satisfaction.

Furthermore, the relationship between job satisfaction and job performance is also influenced by multiple factors.

Specifically, the effect of job satisfaction on job performance can be heightened by several variables including:

• Personality/self-concept of the employee
• Autonomy of the employee
• The level of analysis used for the questionnaires

When job satisfaction is measured using a questionnaire with multiple dimensions, the correlations between each dimension and job performance are weaker than when composite job satisfaction is constructed from all the dimensions.

Furthermore, the effect of job performance on job satisfaction is also influenced by several variables including:

• Rewards for good job performance
• The nature of the job
• How important achievement is to the individual
• How important work is to the employee

In summary, measuring other variables such as employee engagement, job performance, the personality of the employee, and psychological wellbeing could be very useful to understanding the full picture of employee job satisfaction (Wright & Cropanzano, 2000).

This is what makes employees happy at work – Michael C. Bush

Although the terms ‘job satisfaction’ and ‘employee engagement’ are used interchangeably, there are subtle differences (Abraham, 2012; Harter et al., 2002).

Employee engagement as a concept

• Job satisfaction refers to how satisfied employees are with their work or how much they enjoy their work. Satisfied employees have a positive attitude toward their work.
• Employee engagement can be defined as the employee’s involvement with their work and includes their satisfaction and enthusiasm for their work. Employees who are engaged have a good work relationship with their colleagues, are interested in the company’s aim and products, are dedicated to their job, and will put in more time because they are committed to the work.

Although the concepts differ in definition, they are still related. Employee engagement is influenced by job satisfaction; employees with higher job satisfaction are more engaged (Garg & Kumar, 2012). Job satisfaction, however, is only one component of employee engagement. Despite these nuanced differences, satisfaction tools might be called employee engagement tools.

Similarly, some job satisfaction research investigates ‘work engagement’ (Attridge, 2009). Work engagement is defined as the level of commitment, involvement, and enthusiasm for one’s work (Attridge, 2009). This definition overlaps with those for job satisfaction and employee engagement.

Measuring tools for employee engagement

The Utrecht Work Engagement Scale (UWES) is a 17-item tool that measures work placement engagement across three dimensions: vigor, dedication, and absorption (Schaufeli & Bakker, 2003). Each item is a statement (e.g., ‘At my work, I feel bursting with energy’), and the employee responds how frequently they experience each statement on a scale from 0 (Never) to 6 (Always/Every day).

To score the tool, an average response for each subscale and an overall average are calculated. This tool has been used extensively across different industries and has sound psychometric properties. The psychometric properties can be found in the test manual, which is available from Wilmar Schaufeli’s website , where the English version and other translations of the test can be found as well.

In a shortened version of the UWES, the 17-item tool was reduced to 9 items (Schaufeli, Bakker, & Salanova, 2006). The items that comprise the UWES-9 are labeled with asterisks in the UWES test manual referred to above.

Another tool that measures employee engagement is the Job Engagement Scale (JES; Rich, Lepine, & Crawford, 2010). This scale was developed to incorporate the job satisfaction theory of workplace engagement proposed by Kahn (1990). Rich et al. (2010) argue that some items of the UWES did not properly capture Kahn’s theory, and they developed a new scale to account for this.

More information about the validation process and psychometric properties of the tool can be found in Rich et al. (2010).

The JES comprises 18 items, which are answered on a scale from 1 ‘strongly disagree’ to 5 ‘strongly agree.’ The items in the JES measure engagement in three domains: physical, emotional, and cognitive. Domain scores are calculated by averaging responses across each domain, and an overall average is calculated by averaging across all items. Higher scores indicate higher engagement.

The full test can be found in Bruce Rich’s PhD thesis .

Regularly measuring work engagement can help identify workers who are at higher risk of burnout.

These measurements are more useful if there is a baseline for comparison. If you know what the employee’s baseline engagement score is before burnout is a possibility, then there is a useful comparison score for subsequent measurements.

Faragher et al. (2013) conducted a meta-analysis on the relationship between job satisfaction and health, and showed that:

• Higher job satisfaction was correlated with better physical health.
• Lower job satisfaction was strongly correlated with the presence of mental/psychosocial problems.
• Lower job satisfaction was strongly correlated with more experiences of burnout.
• Lower job satisfaction was moderately correlated with higher levels of depression, higher levels of anxiety, lower levels of self-esteem, and worse general mental health.

The main predictors of burnout and exhaustion are difficult job demands and a stressful working environment (Attridge, 2009). Here is a list of strategies that can be put into place to ease worker dissatisfaction (Grawitch, Gottschalk, & Munz, 2006; Warr, 2005):

• Remove or solve problems related to tasks, processes, and operations.
• Improve the ergonomics of the workplace.
• Add flexibility to workplace schedules.
• Promote and support work–life balance.
• Define tasks and roles more clearly.
• Allow employees to take part in decision making.
• Improve social relationships at work, and create opportunities for these relationships to be fostered.
• Praise, recognize, and reward hard work.
• Foster skill development.

We have several useful resources that can be used to increase job satisfaction.

W stands for Way Forward and the SMART + Goals Worksheet can be used to help with decision making, breaking down tasks into smaller subgoals, goal setting, and planning.

The Avoidance Plan Worksheet  can be used to help identify avoidant behaviors, which impede goal setting and planning.

The EQ 5-Point Tool , Anger Exit and Re-Entry Routines, and the Conflict Resolution Checklist are useful tools to assist with conflict resolution and difficult conversations. These three tools teach clients how to rely on empathetic techniques when having a potentially difficult conversation , as well as how to navigate these conversations without relying on reactionary emotions such as anger, frustration, and annoyance.

If you’re looking for more science-based ways to help others manage stress without spending hours on research and session prep, this collection contains 17 validated stress management tools for practitioners . Use them to help others identify signs of burnout and create more balance in their lives.

By measuring job satisfaction, employers are better prepared to make the changes that result in a healthier, happier work environment for their employees.

When measuring job satisfaction, remember the following:

• Don’t rely on only one measurement at one point in time. Try to measure job satisfaction over time so that you can track changes.
• Several variables can affect job satisfaction, including situational variables such as the work environment. Adjustments to these situational variables can improve job satisfaction for all employees.
• All measurements should be followed up with meetings and interviews so that you can better understand the employee’s situation.

A variety of job satisfaction tools are listed in this post. However, this list is not exhaustive. If you use a different tool in your workplace, then please share your experience and the name of the tool in the comments section. We love hearing from you and learning more about your work.

We hope you enjoyed reading this article. Don’t forget to download our three Work & Career Coaching Exercises for free .

• Abraham, S. (2012). Job satisfaction as an antecedent to employee engagement. SIES Journal of Management , 8(2), 27–36.
• Andrews, F. M., & Withey, S. B. (2012). Social indicators of well-being: Americans’ perceptions of life quality . Springer Science & Business Media.
• Attridge, M. (2009). Measuring and managing employee work engagement: A review of the research and business literature. Journal of Workplace Behavioral Health , 24 (4), 383–398.
• Earl, J. K., Minbashian, A., Sukijjakhamin, A., & Bright, J. E. (2011). Career decision status as a predictor of resignation behavior five years later. Journal of Vocational Behavior , 78 (2), 248–252.
• Faragher, E. B., Cass, M., & Cooper, C. L. (2013). The relationship between job satisfaction and health: A meta-analysis. In C. L. Cooper (Ed.) From stress to wellbeing (vol. 1) (pp. 254–271). Palgrave Macmillan.
• Gallup Organization. (1992–1999). Gallup Workplace Audit (Copyright Registration Certificate TX-5 080 066). U.S. Copyright Office
• Garg, A., & Kumar, V. (2012). A study of employee engagement in pharmaceutical sector. International Journal of Research in IT and Management , 2 (5), 85–98.
• Grawitch, M. J., Gottschalk, M., & Munz, D. C. (2006). The path to a healthy workplace: A critical review linking healthy workplace practices, employee well-being, and organizational improvements. Consulting Psychology Journal: Practice and Research , 58 (3), 129–147.
• Hackman, J. R., & Oldham, G. R. (1974). The Job Diagnostic Survey: An instrument for the diagnosis of jobs and the evaluation of job redesign projects. JSAS Catalog of Selected Documents in Psychology , 4 , 148.
• Hackman, J. R., & Oldham, G. R. (1975). Development of the job diagnostic survey. Journal of Applied Psychology , 60 (2), 159–170.
• Harter, J. K., Schmidt, F. L., & Hayes, T. L. (2002). Business-unit-level relationship between employee satisfaction, employee engagement, and business outcomes: A meta-analysis. Journal of Applied Psychology , 87 (2), 268–279.
• Harter, J. K., Schmidt, F. L., Killham, E. A., & Agrawal, S. (2009). Q12 meta-analysis: The relationship between engagement at work and organizational outcomes . Gallup.
• Ironson, G. H., Smith, P. C., Brannick, M. T., Gibson, W. M., & Paul, K. B. (1989). Construction of a Job in General scale: A comparison of global, composite, and specific measures. Journal of Applied Psychology , 74 (2), 193–200.
• Judge, T. A., Thoresen, C. J., Bono, J. E., & Patton, G. K. (2001). The job satisfaction–job performance relationship: A qualitative and quantitative review. Psychological Bulletin , 127 (3), 376–407.
• Kahn, W. A. (1990). Psychological conditions of personal engagement and disengagement at work. Academy of Management Journal , 33 , 692–724.
• Rich, B. L., Lepine, J. A., & Crawford, E. R. (2010). Job engagement: Antecedents and effects on job performance. Academy of Management Journal , 53 (3), 617–635.
• Schaufeli, W. B., & Bakker, A. B. (2003). Test manual for the Utrecht Work Engagement Scale . Unpublished manuscript, Utrecht University, The Netherlands. Retrieved from http://www.schaufeli.com
• Schaufeli, W. B., Bakker, A. B., & Salanova, M. (2006). The measurement of work engagement with a short questionnaire: A cross-national study. Educational and Psychological Measurement , 66 (4), 701–716.
• Schaufeli, W. B., Taris, T. W., & Van Rhenen, W. (2008). Workaholism, burnout, and work engagement: Three of a kind or three different kinds of employee well‐being? Applied Psychology , 57 (2), 173–203.
• Smith, P. C., Kendall, L. M., & Hulin, C. L. (1969). The measurement of satisfaction in work and retirement: A strategy for the study of attitudes . Rand McNally.
• Spector, P. E. (1985). Measurement of human service staff satisfaction: Development of the Job Satisfaction Survey. American Journal of Community Psychology , 13 (6), 693–713.
• van Saane, N., Sluiter, J. K., Verbeek, J. H. A. M., & Frings-Dresen, M. H. W. (2003). Reliability and validity of instruments measuring job satisfaction: A systematic review. Occupational Medicine , 53 (3), 191–200.
• Warr, P. (2005). Work, well-being, and mental health. In J. Barling, E. K. Kelloway, & M. R. Frone (Eds.), The handbook of work stress (pp. 547–573). Sage
• Wright, T. A., & Cropanzano, R. (2000). Psychological well-being and job satisfaction as predictors of job performance. Journal of Occupational Health Psychology , 5 (1), 84–94.

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How can I reference your article in APA7th edition norms?

You can reference this article in APA 7th as follows: Nortje, A. (2021, February 11). 7 Best Job Satisfaction Scales, Questionnaires & Surveys. PositivePsychology.com . https://positivepsychology.com/job-satisfaction-questionnaires-surveys/

Hope this helps!

Warmly, Julia | Community Manager

Please suggest me some tools for measuring Impact of HRM practices and job satisfaction level for employees in pharmaceutical company

Could you please specify the types of tools you’re looking for? I am happy to assist you to the best of my abilities!

Warm regards, Julia | Community Manager

Hi Nicole, I would appreciate if you could suggest me a measurement tool to measure job satisfaction and performance among nurses. Thank you

I found two scales that seem to measure what you’re looking for: the Nursing Job Satisfaction Scale (NJSS) and the Nurses’ Professional Commitment Scale (NPCS). You can find more information on the two tools here .

Hope this information helps you! Kind regards, Julia | Community Manager

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Job Satisfaction: Knowledge, Attitudes, and Practices Analysis in a Well-Educated Population

Paolo montuori.

1 Department of Public Health, University “Federico II”, Via Sergio Pansini N° 5, 80131 Naples, Italy

Michele Sorrentino

Pasquale sarnacchiaro.

2 Department of Law and Economics, University “Federico II”, 80131 Naples, Italy

Fabiana Di Duca

Alfonso nardo, bartolomeo ferrante, daniela d’angelo, salvatore di sarno, francesca pennino, armando masucci, maria triassi, antonio nardone, associated data.

The data that support the findings of this study are available upon reasonable request from the corresponding author. The data are not publicly available due to privacy or ethical restrictions.

Job satisfaction has a huge impact on overall life quality involving social relationships, family connection and perceived health status, affecting job performances, work absenteeism and job turnover. Over the past decades, the attention towards it has grown constantly. The aim of this study is to analyze simultaneously knowledge, attitudes, and practices toward job satisfaction in a general population in a large metropolitan area. The data acquired from 1043 questionnaires—administered to subjects with an average age of 35.24 years—revealed that only 30% is satisfied by his job. Moreover, among all the tested sample, 12% receive, or often receive intimidation by their superior, and 23% wake up unhappy to go to work. Marital status and having children seem to be an important factor that negatively influences job satisfaction through worst behaviours. The multiple linear regression analysis shows how knowledge is negatively correlated to practices; although this correlation is not present in a simple linear regression showing a mediation role of attitudes in forming practices. On the contrary, attitudes, correlated both to knowledge and practices, greatly affect perceived satisfaction, leading us to target our proposed intervention toward mindfulness and to improve welfare regulation towards couples with children.

1. Introduction

Job satisfaction has been defined as a “pleasurable or positive emotional state, resulting from the appraisal of one’s job experiences” [ 1 ]. Job satisfaction reflects on overall life quality involving social relationships, family connection and perceived health status, affecting job performances, work absenteeism and job turnover, leading, in some cases, to serious psychological condition such as burnout [ 2 , 3 , 4 , 5 , 6 ].

The recent Gallup statistics on job satisfaction indicated that a very large portion of the world’s 1 billion full-time workers is disengaged, more precisely, only 15% of workers are happy and production in the workplace, the remaining 47% of workers are “not engaged,” psychologically unattached to their work and company [ 7 ]. In the EU, approximately one in five residents (16.9%) currently in employment expressed low levels of satisfaction with their job, on the other hand approximately one in four (24.6%) expressed high levels of satisfaction, the remaining residents (58.5%) declared medium levels of satisfaction with their job [ 8 ]. Characteristics such as age, sex, education, occupation, commuting time and difficulty as inadequate income, seems to be related to job satisfaction as they tent to influence expectation and preferences of individuals’ reflection on their perceived working condition [ 9 , 10 ]; however, as assessed in Eurofound, European Working Conditions Surveys [ 11 ] the relation between age and job satisfaction is very weak, although a slight increase in low satisfaction prevalence was found in elder population, it does not increase significantly with age even though expectations change during lifetime; educational attainment and income seem to play a significant role in job satisfaction as they grow in parallel, leading to better positions and a higher wages, along with power and more decisional autonomy. Sex is a factor as women seems to be overall more satisfied by their job in despite of the worst general conditions [ 11 , 12 , 13 , 14 ]. Job satisfaction also relates to marital status as single subjects’ results as the most satisfied by their work in some European Countries [ 15 ]. In Italy, the overall perceived job satisfaction seems to be similar to other regions in EU, and social relations as well as family composition appear to play a relevant role [ 16 ].

Job satisfaction has been studied mostly over a specific category of workers [ 17 , 18 ], as some types of works seems to be more related to pathological conditions such as burnout [ 19 , 20 ] and job-related stress [ 21 , 22 , 23 ]; however, as reported by those authors, this kind of selection method could lead to selection biases. According to van Saane [ 24 ], although many studies were carried as since Job Satisfaction broke out in the last 70’s as a central topic of interest, nor a mathematical instrument as reliable as desired nor a comparative method were found, usually those studies were based on single components of job satisfaction, taken out from extra working environment, and without analysing the consequences on behaviours in day life [ 25 , 26 , 27 ]. The literature research demonstrated that practices are the results of knowledge, attitudes, or their interaction. The KAP Survey Questionnaire [ 28 ] can be applied to highlight the main features of knowledge, attitude, and practice of a person, and to assess that person’s views on the matter. The purpose, when using the KAP Survey Model, is to measure a phenomenon through the quantitative collection method of a large amount of data through the administration of questionnaires and then statistically process the information obtained. Through a questionnaire, however, seems to be easier to quantify job satisfaction. In addition to that, studying broader populations’ consent to explore different components, both personal and environmental, which concur to influence it [ 29 , 30 ].

In the recent literature, a KAP model was used only once to analyse behaviours toward job satisfaction. In his work, Alavi [ 31 ] conducted a survey based cross-sectional study on 530 Iranian radiation workers; although it comprehends simultaneously knowledge, attitude, and practices, it was conducted on a specific category of workers and on a narrower population. Therefore, since to the best of our knowledge none of the studies presented in the literature are carried out on a broader population relating both knowledge and attitudes to behaviours on job satisfaction, the aim of this study is to analyse simultaneously knowledge, attitudes, and behaviours toward job satisfaction in a large metropolitan area. It is important to investigate this phenomenon to evaluate the condition and develop health education programs and community-based intervention to increase job satisfaction and knowledge and positively orienting attitudes.

2. Material and Methods

2.1. participants and procedure.

This cross-sectional study was conducted from November 2021 to February 2022 in the large metropolitan area of Naples, southern Italy, among working places, universities, and community centres. No specific category of participants was selected. In the questionnaire, respondents indicated their occupation by choosing from the following options: lawyer, architect, engineer, doctor, accountant, entrepreneur, teacher, law enforcement, trader, student, employee, worker, unemployed, other. Table 1 shows the categories indicated by the participants. The criteria for inclusion in the study required that respondents of a general population were over 18 years old, belonging to one of the categories of employment listed in Table 1 , and resided in the metropolitan area of Naples. Every participant directly received a questionnaire (available upon request from the corresponding author) and at the time of filling out the questionnaire, the aim of the study and the anonymity and privacy of the data collecting method being used was explained, both in written form, as an introduction part of the questionnaire, and verbally to each of the participants. The questionnaire consisted of basic information about participants (age, gender, children, civil state, education level, profession, smoke habits) and three pools of questions divided in knowledge, attitudes and behaviours concerning their job satisfaction for a total number of 37 questions. The construction of the questionnaire was carried out as recommended by the KAP Model [ 28 ], briefly was divided into four phases: (1) Constructing the survey protocol; (2) Preparing the survey; (3) Course of the KAP survey in field; (4) Data analysis and presentation of the survey report. To develop the questionnaire, research questions based on the “Objectives of the study” were first carried out to develop the research questions, according to KAP Survey Model [ 28 ], the knowledge was considered as a set of understandings, knowledge, and “science” while Attitude as a way of being, a position. After, the research questions were reduced in number by removing those questions that require unnecessary information. When the above step is also done, the difficult questions have been changed/removed (closed questions have been used because one of the most important things that will increase the relevance of the questions is that the questions must be closed questions). Knowledge and attitudes were assessed on a three-point Likert scale with options for “agree”, “uncertain”, and “disagree”, while inquiries regarding behaviours were in a four-answer format of “never”, “sometimes”, “often”, and “yes/always”. A pilot study was also carried out to test the questionnaire and to verify the reliability of questions. Finally, all the collected questionnaires were digitalized submitting the codified answers in an Excel worksheet (MS Office).

Study population characteristics.

2.2. Statistical Analysis

Data reported by the study were analysed using IBM SPSS (vers. 27) statistical software program. The analysis was carried out in two stages. In the first stage, a descriptive statistic was used to summarize the basic information of the statistical units. In the second stage, a Multiple Linear Regression Analysis (MLRA) was used to model the linear relationship between the independent variables and dependent variable.

The dependent variables (Knowledge, Attitudes and Behaviours) had been obtained by adding the scores obtained in the corresponding questions (questions with inverse answers have been coded inversely). The independent variables were included in all models: sex (1 = male, 2 = female); age, in years; education level (1 = primary school, 2 = middle school, 3 = high school, 4 = university degree); civil state (1 = Single; 2 = In a relationship; 3 = Married; 4 = Separated/Divorced; 5 = Widowed).

The main results from a MLRA contains the statistical significance of the regression model as well as the estimation and the statistical significance of the beta coefficients ( p -value < 0.05) and the coefficient of determination (R-squared and adjusted R-squared), used to measure how much of the variation in outcome can be explained by the variation in the independent variables. Three MLRA were developed:

• (1) Knowledge about job satisfaction (Model 1);
• (2) Attitudes toward resilience and mindfulness (Model 2);
• (3) Actual behaviours regarding Job and Job-related life (Model 3).

In Model 2, we added Knowledge to the independent variables, and in Model 3, we added Knowledge and Attitudes to the independent variables. In the analysis, we considered Attitudes and Knowledge as indexes rather than a scale, which means that each observed variable (A1, …, A13 and K1, …, K12) is assumed to cause the latent variables associated (Attitude and Knowledge). In other terms, the relationship between observed variables and latent variables is formative. Therefore, inter-observed variables correlations are not required. On the contrary, the relationship between the observed variables (B1, …, B14) and latent variable Behaviour could be considered reflective (Cronbach’s alpha = 0.825). All statistical tests were two-tailed, and the results were statistically significant if the p -values were less than or equal to 0.05.

3. Results and Discussion

Out of the 1057 participants, 1043 anonymous self-report surveys were returned, resulting in a response rate of 98.7%. Table 1 shows the characteristics of the study population: the mean age of the study population is 35.24 years; in 18–70 age range, the main group of distribution was 18–30 representing 44.6% of the sample; sex distribution shows that: 427 are men, 616 are woman. A large majority (73.5%) does not have children, while 26.5% of the sample has them. Most of the participants have a post graduate degree, while 29.1% are high school graduates. Among them, 22.2% are physicians, 15.1% teachers and 14.0% students ( Table 1 ).

Respondent’s knowledge about job satisfaction is presented in Table 2 . While a large majority of the sample population (91.7%) has a well-defined knowledge about job satisfaction main characteristics such as mains definitions, both of work-related stress and mobbing, most of them does not know or are not aware which risks are specifically related as only 31.4% knows that job related stress and mobbing are a threat to their cardiovascular health. Only 28.7% of the population knows that “Only 15% of worker, globally, are satisfied by their work” demonstrating that while knowledge regarding job related stress is well spread, the sample does not know how diffused it is and what kind of risks it involves, and that state provide a compensation for job related stress.

Knowledge of respondents toward job satisfaction.

* INAIL: Istituto Nazionale Assicurazione Infortuni sul Lavoro (National Institute for Occupational Accident Insurance).

In Table 3 are described attitudes toward job satisfaction. Most of the participants think that working out is relaxing and spending time is regenerating, showing a good attitude to copy with work related stress. According to 93.4% of the sample, workload plays a key role in job satisfaction, as well as adequate wages and a clear task schedule. Several studies have enlightened that when workers lack a clear definition of the tasks which are necessary to fulfil a specific role, their levels of job satisfaction are likely to be negatively affected [ 32 , 33 , 34 ]. Interestingly, most of the population sees challenges as a motivation to do better (80.2%) and are motivated by career opportunities (90.7%); however, 50.5% of the population has a negative attitude about changes. In confirmation of that, when asked if “Changes lead to stress”, only a small fraction of the sample (14.6%) disagreed. This allowed us to assume that, although most of the population sees problems as an opportunity to learn, improve and progress in their work, they are aware of the difficulties connected to changing scenarios. About 27.2% of the sample does not have a positive attitude toward sharing their feeling about problems at work talking out loud. Bad interpersonal relationships with co-workers are another reason for job dissatisfaction. Poor or unsupportive relationships and conflicts with colleagues and/or supervisors lead to negative psychological intensions, resulting in job dissatisfaction [ 35 , 36 ].

Attitude of respondents toward job satisfaction.

Behaviours of respondents are listed in Table 4 : A consistent part of the sample responded positively to the group of question toward behaviours regarding their coping level of stressful situation (B2, B4, B8, B9, B10) showing a reported good resilience. Commuting seems to be a problem for at least a third of the sample, also in a metropolitan area served by 2 subways, full bus service, car sharing services and a speedway. Job satisfaction is associated negatively with constraints such as commuting time. This dead time, mostly unpaid, is mandatory for workers to reach workplace. Although this is not considered as working time, and only a specific class is refunded, from the employers’ perspective, it is time dedicated to work and a strong determinant for low satisfaction levels. EU workers were much more likely to be highly (37.9%) or moderately satisfied (41.7%) with their commuting time compared to their job satisfaction. Most of the sample responded to not having experienced mobbing; although even a “low” result, such as a cumulative, summing both “yes/always” and “often”, of 11.8% is alarming and pushes us to study more about this phenomenon. Interestingly, 30.9% of respondents are satisfied about their work, reaching a total of 59.5%. In addition, with a “often” response showing a large appreciation of their jobs, 22.9% of the respondents “wake up unhappy to go to work”, and feel “stuck in a job with no career opportunities” (27.7%). The sample has no problems managing their work and social life (48.3%); however, only a complex of 35% of the sample usually spend their time with colleagues outside the office.

Behaviour of respondents toward job satisfaction.

Table 5 illustrates results of linear multiple regression in three models: in Model I Knowledge, as dependent variable, correlate, with a p -value < 0.001; with “sex”, interestingly, woman seem to have a higher overall score of knowledge in disagreement with Gulavani [ 37 ] whose study was conducted among a sample of nurses and found no significant relation between sex and knowledge on job satisfaction. Al-Haroon [ 38 ] evidenced that among health workers, men had a better overall level of knowledge. These results, however, were collected over specific categories of employees, in a narrower sample; whereas our study was represented by a general population of a metropolitan area. No statistically significant correlation between knowledge and age, civil status, children, and education levels was encountered.

Results of the linear multiple regression.

Previous research asses that attitude plays a key a role in job satisfaction, as some attitudinal characteristics of the subject influence perspective, coping skills and stressful situation management [ 39 , 40 , 41 ]. In Model II ( Table 5 ) we correlated, through MLRA, attitudes with age, sex, civil state, having children, education, and overall knowledge score. With a p -value < 0.001, two correlations were found with education and overall knowledge score, both positively. Those results reflect, in accordance with Alavi [ 31 ], who found that higher level of education was among 3 factors that predicted job satisfaction and attaining a higher university degree compared to lower degrees contributes to a feeling of coherence, success at work, personal growth and self-respect, self-realization and intrinsic motivation, that education level and therefore a higher level of knowledge contributes to generating a sense of job satisfaction. In the questionnaire we tried to collect all those propension and as a result: in agreement with Hermanwan [ 42 ], Andrews [ 43 ] and Choi [ 44 ], subjects with better knowledge and high levels of education tent to have better attitudes.

In Model III, behaviours taken as a dependent variable are correlated to age, sex, civil state, children, education, knowledge, and attitudes. The results of linear multiple regression in this model assess that behaviours are negatively correlated to civil state, sons, and knowledge, and positively correlated to attitudes. Our findings show that there is a positive correlation between behaviours and attitudes, in agreement with previous literature [ 45 , 46 , 47 ], demonstrating that people with better attitudes tent to have a better overall behaviour. Surprisingly, in Model III, knowledge also has a statistically significant correlation to behaviours but in a negative way. This correlation, however, is not present when we correlate those variables alone in a Pearson’s correlation between knowledge, attitudes, and behaviours ( Table 6 ). This evidence, therefore, suggests that attitude mediates the effect of knowledge on behaviours, assessing an important relation between those two determinants. People with a better overall score in behaviours tend to have a higher score in knowledge and attitude. In this sample, those who have a lower score in knowledge also has a higher behaviour score in accordance with a part of the previous literature [ 48 , 49 ]. This enlightens the importance of high levels of knowledge in order to form better attitudes in the pursuit of job satisfaction. Civil state and having children seem to play a key role in performing a better behaviour about job satisfaction; which is also evident in one specific question about behaviour: Question “B14” enlightens the social practices of subjects with colleagues outside the work environment, and the statistical analysis on this topic shows that subject with a more stable sentimental situation or with child tend to hang out with their colleagues less, likely worsening their relationships at work and getting a worse overall behaviour score and worse attitude toward the topic in agreement with Sousa-Poza [ 50 ] and Armstrong [ 51 ]. Job satisfaction has a strong correlation to family characteristics: Subjectst who have families with children have less positive behaviours towards their job satisfaction, directly affecting their overall behaviour score; this evidence is in contrast with Alavi [ 31 ], who states that job satisfaction is positively affected by family, assessing that “married employees have opportunities to receive support or advice from their family to mediate job conflicts,” Although he admits that in the literature, this result is controversial as some authors, such as Clark [ 52 ], found that “married employees experienced a higher level of job satisfaction than their unmarried co-workers”, and Booth and Van Ours’ [ 53 ], study did not find a statistically relevant correlation with the presence of children. Those results, therefore, suggest creating targeted educational programs, community-based intervention, and legal regulation, to improve self-awareness and resilience among workers, and a more practical intervention could be directed to families with child.

Pearson’s correlation between knowledge, attitudes, and behaviours.

4. Conclusions

This study shows that the metropolitan population has general good knowledge about job satisfaction as well as a positive attitude. Job satisfaction, however, is reflected accordingly only with attitudes. While it has a negative relation to civil state and having children, this means that the experimental results of this study may be used to create targeted educational programs, community-based intervention, and legal regulation, to improve self-awareness and resilience among workers. A more direct intervention could be directed to families with children. Social networking with colleagues has an important impact on job satisfaction, as the part of the sample who responded positively to the specific question, had an overall better behaviour. Although, in this case, having children seems to be, as they negative correlate, a huge limitation to this practice. Considering that, as previously stated, the impact of job satisfaction on the population has a strong impact in terms of life balance, health, and economics, and it is well known that only a small fraction of workers are fully satisfied. It might be important to promote welfare regulation to allow a larger part of the population to conciliate work and family. Results of this paper could be an indicator of how to establish an educational program more efficiently. It is mandatory to strengthen specific knowledge about job satisfaction through the general population toward the importance of job satisfaction and the benefits related to a correct approach to work-life. The impact of a public health intervention could be even more effective by integrating another program to orient and define attitudes, which in turn will influence people to practice a mindfulness mental setting toward job satisfaction. In conclusion, a training program based on fundamental practices of job satisfaction should be improved in the young population, in early stage of family life, or before they have children, in order to achieve a double objective: “training family and spreading the practice to a future generation”.

Funding Statement

This research received no external funding.

Author Contributions

Data curation: P.M., M.S., P.S., F.D.D., A.N. (Alfonso Nardo), B.F., D.D., S.D.S., F.P., A.M. and M.T.; Formal analysis: M.S., F.D.D., A.N. (Alfonso Nardo), B.F., D.D., S.D.S. and F.P.; Resources: P.M. and M.T.; Software: P.S.; Supervision, P.M., M.T. and A.N. (Antonio Nardone); Writing—original draft: M.S., F.D.D., A.N. (Alfonso Nardo), B.F., D.D. and S.D.S.; Writing—review and editing: P.M., M.S., P.S., F.P., A.M., M.T. and A.N. (Antonio Nardone). All authors have read and agreed to the published version of the manuscript.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Data availability statement, conflicts of interest.

The authors declare no conflict of interest.

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Job satisfaction research

On this page:.

• Introduction
• 1.1 How robust are these findings?
• 2.1 1. Engaging work
• 2.2 2. Work that helps others
• 2.3 3. Work you’re good at
• 2.4 4. Work with people you like
• 2.5 5. Meets your basic needs
• 3.2 Low demands
• 3.3 Interests match
• 3.4 Signature strengths match
• 3.5 Occupational status
• 4 Directions for future research

Last updated: March 2016.

Table of Contents

Research process

To survey the literature, we familiarised ourselves with the latest work on positive psychology by reading all of ‘ Flourish ‘ and ‘ Learned Optimism ‘ by Seligman, ‘ Stumbling on Happiness ‘ by Gilbert, ‘ Drive ‘ by Pink, and several review papers. We also did a Google Scholar search for relevant terms, read two textbooks on organisational psychology (‘ Work Psychology ‘ by Arnold and Randall, and ‘The Handbook Principles of Organisational Behaviour’ by Locke (find a copy in this folder )), and two summaries of the job satisfaction literature in the OSH wiki.

We weighed the messages of the literature against our impression of common sense, placing more weight on meta-analyses and consensus positions among psychologists. For more on our general research process, see our research principles .

How robust are these findings?

There appears to be broad consensus that the job characteristics model is a good predictor of job satisfaction. The other factors in our list don’t have as wide consensus, but this page reflects our current synthesis of the evidence that we’ve read. With further research we can imagine adding or subtracting a factor or changing a factor’s relative importance. For example, we previously put less weight on personal fit as important for job satisfaction.

Predictors of job satisfaction

To find out what the predictors of job satisfaction are, we started by looking at general theories of life satisfaction and human needs. We then investigated how these general predictors translate into the world of work and combined this with research that directly focuses on job satisfaction, to come up with six key factors for fulfilling work.

The PERMA theory, created by the founder of positive psychology Prof. Seligman, summarises the key ingredients of living a fulfilling life as follows:

• Positive emotion – feeling happy day-to-day.
• Engagement – challenging, absorbing tasks.
• Meaning – having a purpose higher than yourself.
• Relationships – connecting with others.
• Achievement – being good at something.

It isn’t consensus that these factors constitute well-being, but it is widely agreed that they are important determinants of well-being.

You can read more about PERMA in the book Flourish .

Self-determination theory claims there are three fundemental parts to human well-being:

• Competence – experiencing control and mastery
• Relatedness – connecting with others
• Autonomy – having choice and control

We now outline each factor and the main evidence for each.

1. Engaging work

The job characteristics model claims that job satisfaction is largely determined by how engaging the job itself is. The model breaks engagingness into five main variables: variety, sense of completion, autonomy, feedback from the content of the work, and sense of contribution. Note that the last factor is essentially ‘do you think you’re making a difference?’, and we cover it separately in the next section.

The job characteristics model has been studied extensively, including by several meta-analyses. 1 The most recent meta-analysis of 259 studies showed that each of the five characteristics correlates with job satisfaction (mean p=0.41).7 It’s widely thought to be the best single predictor of job satisfaction. For instance, in the Handbook of Principles of Organisational Behaviour, Judge and Klinger claim: 2

There are many possible influences on how favorable one appraises one’s job, and numerous theories of job satisfaction have attempted to delineate these influences. Empirical evidence, however, has suggested only one clear attribute of the work itself that consistently influences job satisfaction – the cognitive challenge of the work. The empirical data suggest that intrinsic job characteristics are the mostly consistently significant situational predictor of job satisfaction.

The effect of job characteristics on job satisfaction has been found to be moderated by an individual’s need for growth. A meta-analysis found that Growth Need Strength (GNS) moderated the relationship between the five job characteristics and job satisfaction. For those with high GNS the relationship was on average r=. 57, whereas for those with low GNS the relationship was on average r = .32. Note that even this is still a moderate relationship. 3

There’s also some indirect support for engaging work being important for job satisfaction. Employee surveys of job satisfaction have shown that “interesting work” turns out to be what’s most important to people, as opposed to pay or status. 4 Also, sense of completion and feedback are similar to the conditions needed to enter a state of flow – the pleasurable state of being so immersed in an activity that you’re completely free of distractions and lose track of time. Csikszentmihalyi has argued that being able to enter states of flow is key to having genuinely satisfying experiences, so we’d expect this link. 5

You could challenge the evidence for the job characteristics model by coming up with alternative hypotheses to explain the correlation between job characteristics and job satisfaction. For example, mood could be a third variable that explains the correlation. If you are in a good mood that might cause you to rate your job satisfaction as high, but also to rate your job highly on the five characteristics of the model (as is suggested by Judge & Klinger 2009). 6 Or you might think that the causal relationship actually works in reverse (as was suggested in Caldwell (1982) — high job satisfaction causes you to rate your job highly on the five characteristics in the model. 7

However studies that use objective measures of job characteristics still find a correlation between the five job characteristics and job satisfaction (Glick, Jenkins, and Gupta, 1986; Judge, Bono, and Locke, 2000), so these alternative explanations don’t seem to hold. 8

The more general worry that the evidence is correlational does reduce our confidence in the job characteristic model. Nevertheless, the model is grounded in well-supported theories of motivation and well-being; it provides causal explanations of how the factors lead to job satisfaction; and it has been subject to a high degree of scrutiny for several decades — so if there were obvious confounders or problems with it, it is likely that these would have been uncovered by now.

2. Work that helps others

We’d expect that helping others in your job would increase your sense of meaning and purpose, and there’s a fair amount of empirical evidence that helping others in your job increases job satisfaction.

Theoretical evidence If you help others through your job, you’re likely to experience a greater sense of meaning and purpose. Meaning and purpose is one of the components of Seligman’s theory of well-being PERMA as we saw above. 9

Correlational evidence As mentioned in the previous section, the job characteristics model is widely agreed to be the best predictor of job satisfaction. One of the factors in the model is task significance – the degree to which your job affects other people’s lives. It is measured using this question:

The empirical evidence shows that high task significance is one of the best predictors of job satisfaction. The meta-analysis we mentioned previously found that task significance is strongly correlated with job satisfaction (p=0.41 10 ).

Another finding which you’d expect if helping others through your work increases your job satisfaction is that jobs which involve helping others would do well in job satisfaction rankings. Jobs that involve helping others do in fact score very well on job satisfaction rankings, as was found in the General Social Surveys conducted in the US from 1972-2006 (with 50,313 respondents): 11

If we move to the broader relationship between helping others (whether through your job or not) and well-being, Post (2005) overviews a wide range of studies which find a correlation between altruism and well-being. 12 He also gives plausible causal mechanisms through which altruism could lead to increased happiness:

Altruism results in deeper and more positive social integration, distraction from personal problems and the anxiety of self-preoccupation, enhanced meaning and purpose as related to well-being, a more active lifestyle that counters cultural pressures toward isolated passivity, and the presence of positive emotions such as kindness that displace harmful negative emotional states. It is entirely plausible, then, to assert that altruism enhances mental and physical health.

Experimental evidence There is evidence from randomized controlled trials that performing acts of kindness increases your happiness. 13 If there’s a causal relationship between performing acts of kindness and being happier, you might also expect that there is a causal relationship between helping others through your job and increased happiness and job satisfaction.

3. Work you’re good at

We expect that being good at your job leads to higher job satisfaction. There is a fair amount of theoretical support for the claim that being good at your job will lead to higher job satisfaction. Most theories of human well-being and needs have achievement as a key component (including Self-Determination Theory and PERMA ). The job characteristics model also has knowledge and skills as a moderator of the effect of job characteristics on job satisfaction. 14

Also, believing that you are able to do well in a job is associated with higher motivation, whilst not having the knowledge and skills to do your job well is likely to lead to stress. 15

This is confirmed by an analysis of 2,460 individuals which found a strong negative relationship between skill mismatch and job satisfaction. 16

Finally, that being good at your job is important for job satisfaction is also the common sense view, and it is highly intuitive.

4. Work with people you like

Like having a sense of meaning and achievement, satisfying personal relationships are also a key component for a fully satisfying life in almost every theory of human needs and well-being (such as Self-Determination Theory and PERMA ). Therefore we would expect social support and liking your colleagues to lead to job satisfaction. This is also confirmed by empirical research.

A meta-analysis of 259 studies found that social support was strongly positively correlated with job satisfaction (p=.56). 17 Social support is the extent to which a job provides opportunities for getting help and advice from others and the opportunities to make friends on the job.

(Update: Another meta-analysis found several measures of ‘organizational sponsorship’, such as being given supervisor support and training opportunities, were among the best predictors of career satisfaction of those studied, though interestingly, were weaker predictors of income and chance of promotion.)

One note is that people vary in who they like, so this factor of job satisfaction will mean different jobs are better for different people. One well-studied effect is that your degree of similarity with someone – the more similar you are (on almost any dimension — physical appearance, attitudes, personality, interpersonal style, cultural background) the more likely you are to like them. 18

5. Meets your basic needs

1. Reasonable hours Very long working hours crowd out your ability to take care of your non-work life, which could make you less happy, and make you more likely to perceive your job as conflicting with your other goals and needs. Not being able to meet your non-work obligations is also likely to lead to stress. This claim receives some support from two large surveys. The British Household Panel Survey, of roughly 10,000 individuals, found that long hours were associated with lower job satisfaction. 19 Another survey of 28,240 individuals found the same. 20

2. Job security Lacking job security is likely to lead to greater stress as it is likely to decrease people’s confidence in being able to meet the demands of their lives. There is also theoretical support for this: job security is posited to be a moderator of the effect of job characteristics on job satisfaction by the job characteristics model. 21 Also, a meta-analysis of 50 independent samples representing 28,885 individuals, found a strong negative correlation between job insecurity and job satisfaction (r=-.41). 22

3. Short commute We would expect a long commute to be detrimental to life satisfaction for the same reasons as long hours are, and in addition, long commutes tend to be unpleasant in themselves and hard to use productively. This claim is supported by a study by the UK Office for National Statistics (sample size = 60,200 individuals) which found that long commutes were associated with lower life satisfaction. The worst effects were associated with journey times lasting between 61 and 90 minutes. Also taking a bus or coach was found to be the worst mode of transport for commuting. 23

4. Fair pay Earning less than others doing the same or similar job seems to cause job dissatisfaction and lower happiness. This makes sense given that it’s likely to make you feel unfairly treated and possibly resent your employer.

This has been confirmed in correlational studies (Clark and Oswald, 1996; Hamermesh, 2001 for job dissatisfaction, Frey and Stutzer, 2002; Luttmer, 2005 for happiness). 24

You might worry about other potential explanations for the correlation. But a clever experimental design was used to control for confounding variables. It randomly assigned people to either be able to find out what their peers earn, or not (the control group). Those who were able to find out what their peers earned and found out that they earned less than their peers reported less job satisfaction and had higher intentions to leave their jobs than those in the control group. 25

Other factors we considered but that are poor predictors of job satisfaction

In general, the salary of a job has only a weak effect on job satisfaction and happiness – see our review of the evidence .

Low demands

Moderate levels of stress are associated with higher job satisfaction. See our review of the evidence on the effects work demands and stress .

Interests match

• There is lack of empirical evidence for interest-match, with a major attempt to find one (Holland-match). See our review of the evidence on the importance of Holland type match with occupation and job satisfaction .

Our interests change, and more than we expect .

• Most people are likely to be interested in highly competitive areas with very few jobs, like sports, music or entertainment. See our page on why “follow your passion” isn’t helpful advice for having a satisfying career .

Signature strengths match

Another predictor we considered but didn’t end up recommending is finding a job which is matched to your unique signature strengths (a test created by Seligman and his colleague Peterson). From the evidence so far, it doesn’t seem that using signature strengths for choosing between jobs is useful. But it does seem that once you’re in a job, finding ways to use your signature strengths more does increase your happiness. See our review of the literature for more .

Occupational status

It is common sense that occupational status is something that matters. There’s some empirical evidence that it is correlated with job satisfaction (for example in the General Social Surveys conducted in the US. 26

However we didn’t include it in our list of factors because:

• The correlation is easily confounded by other variables such as the five factors of the job characteristics model, social support, etc, all of which have better empirical support.
• We don’t expect people to neglect this factor due to the strong social incentives to select jobs with higher status.

Directions for future research

In the future we would like to find out more about the base rates of job satisfaction in different jobs, whether the Big Five personality factors are helpful for finding a career that’s satisfying and investigate how large a difference individual factors, such as how good you are a job, make to job satisfaction.

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Notes and references

A meta-analysis of the relation of job characteristics to job satisfaction. Loher, Brian T.; Noe, Raymond A.; Moeller, Nancy L.; Fitzgerald, Michael P. Journal of Applied Psychology, Vol 70(2), May 1985, 280-289. Meta-analytic comparison of the Job Diagnostic Survey and Job Characteristics Inventory as correlates of work satisfaction and performance. Fried, Yitzhak Journal of Applied Psychology, Vol 76(5), Oct 1991, 690-697. Integrating motivational, social, and contextual work design features: A meta-analytic summary and theoretical extension of the work design literature. Humphrey, Stephen E.; Nahrgang, Jennifer D.; Morgeson, Frederick P. Journal of Applied Psychology, Vol 92(5), Sep 2007, 1332-1356. ↩

• Judge, T. A., Klinger, R. (2009). Promote Job Satisfaction through Mental Challenge. Handbook of Principles of Organizational Behaviour, Second Ed, pp107-119 ↩
• Fried, Yitzhak, and Gerald R. Ferris. “The validity of the job characteristics model: A review and meta‐analysis.” Personnel Psychology 40.2 (1987): 287-322. Judge, Timothy A., and Ryan Klinger. “Promote job satisfaction through mental challenge.” Handbook of principles of organizational behavior (2000): 75-89. p115 ↩
• For instance, Judge, T. A., Church, A. H. (2000) “Job satisfaction: research and practice”. In C. L. Cooper and E. A. Locke (eds), Industrial and Organizational Psychology: Linking Theory with Practice (pp. 167-174). Oxford, UK: Blackwell ↩
• Csikszentmihalyi, M.; Abuhamdeh, S. & Nakamura, J. (2005), “Flow”, in Elliot, A., Handbook of Competence and Motivation, New York: The Guilford Press, pp. 598–698 Csikszentmihalyi, M. (1988), “The flow experience and its significance for human psychology”, in Csikszentmihalyi, M., Optimal experience: psychological studies of flow in consciousness, Cambridge, UK: Cambridge University Press, pp. 15–35. ↩
• Caldwell, David F., and Charles A. O’Reilly. “Task perceptions and job satisfaction: A question of causality.” Journal of Applied Psychology 67.3 (1982): 361. ↩
• Glick, W. H., Jenkins, G. D., Jr., and Gupta, N. (1986). Method versus substance: How strong are underlying relationships between job characteristics and attitudinal out- comes? Academy of Management Journal, 29, 441–464. Judge, T. A., Bono, J. E., and Locke, E. A. (2000). Personality and job satisfaction: The mediating role of job characteristics. Journal of Applied Psychology, 85, 237–249. ↩
• Seligman, Martin EP. Flourish: A visionary new understanding of happiness and well-being. Simon and Schuster, 2012. ↩
• “p” refers to the corrected population correlation estimate ↩
• Job satisfaction in the United States (2007). ↩
• Post, Stephen G. “Altruism, happiness, and health: It’s good to be good.”International journal of behavioral medicine 12.2 (2005): 66-77. ↩
• Lyubomirsky, S., Tkach, C., & Sheldon, K.M. (2004). Pursuing sustained happiness through random acts of kindness and counting one’s blessings: Tests of two six-week interventions]. Unpublished raw data. Results presented in: Lyubomirsky, S., Sheldon, K. M., & Schkade, D. (2005). Pursuing happiness: The architecture of sustainable change. Review of General Psychology, 9, 111–131. Layous K, Nelson SK, Oberle E, Schonert-Reichl KA, Lyubomirsky S (2012) Kindness Counts: Prompting Prosocial Behavior in Preadolescents Boosts Peer Acceptance and Well-Being. PLoS ONE 7(12): e51380. doi:10.1371/journal.pone.0051380 Buchanan KE, Bardi A: Acts of kindness and acts of novelty affect life satisfaction. J Soc Psychol 2010, 150:235–237. ↩
• Hackman, J. R., & Oldham, G. R. (1980). Work redesign. Reading, MA: Addison-Wesley. ↩
• Steel, Piers, and Cornelius J. König. “Integrating theories of motivation.”Academy of Management Review 31.4 (2006): 889-913. ↩
• Allen, Jim, and Rolf Van der Velden. “Educational mismatches versus skill mismatches: effects on wages, job satisfaction, and on‐the‐job search.” Oxford economic papers 53.3 (2001): 434-452. ↩
• Stephen E. Humphrey, Jennifer D. Nahrgang and Frederick P. Morgeson (2007) Integrating Motivational, Social and Contextual Work Design Features: A Meta-Analytic Summary and Theoretical Extension of the Work Design Literature, Journal of Applied Psychology ↩
• https://en.wikipedia.org/wiki/Interpersonal_attraction#Similarity_attraction_effect ↩
• Clark, Andrew, Andrew Oswald, and Peter Warr. “Is job satisfaction U‐shaped in age?.” Journal of occupational and organizational psychology 69.1 (1996): 57-81. Page 66. The correlation was of log hours and job satisfaction was -0.19. For comparison, log income had a -0.07 correlation with job satisfaction. ↩
• Gazioglu, Saziye, and Aysit Tansel. “Job satisfaction in Britain: individual and job related factors.” Applied Economics 38.10 (2006): 1163-1171. ↩
• Kulik, Carol T., Greg R. Oldham, and J. Richard Hackman. “Work design as an approach to person-environment fit.” Journal of vocational behavior 31.3 (1987): 278-296. p284 ↩
• Sverke, Magnus, Johnny Hellgren, and Katharina Näswall. “No security: a meta-analysis and review of job insecurity and its consequences.” Journal of occupational health psychology 7.3 (2002): 242. p249 ↩
• http://www.ons.gov.uk/ons/rel/wellbeing/measuring-national-well-being/commuting-and-personal-well-being–2014/art-commuting-and-personal-well-being.html#tab-2–Key-Points ↩
• Clark, Andrew E., and Andrew J. Oswald. “Satisfaction and comparison income.” Journal of public economics 61.3 (1996): 359-381. Hamermesh, Daniel S. The changing distribution of job satisfaction. No. w7332. National Bureau of Economic Research, 1999. Frey, Bruno S., and Alois Stutzer. “What can economists learn from happiness research?.” Journal of Economic literature 40.2 (2002): 402-435. Luttmer, Erzo FP. Neighbors as negatives: Relative earnings and well-being. No. w10667. National Bureau of Economic Research, 2004. ↩
• Card, David, et al. “Inequality at work: The effect of peer salaries on job satisfaction.” The American Economic Review 102.6 (2012): 2981-3003. ↩