An Overview of Happiness Economics


The economics of happiness or happiness economics is the theoretical, qualitative and quantitative study of happiness and quality of life, including positive and negative affects, well-being, life satisfaction and related concepts – typically tying economics more closely than usual with other social sciences, like sociology and psychology, as well as physical health. It typically treats subjective happiness-related measures, as well as more objective quality of life indices, rather than wealth, income or profit, as something to be maximised.

Refer to Psychometrics, Well-Being Contributing Factors, and Quality of Life.

The field has grown substantially since the late 20th century, for example by the development of methods, surveys and indices to measure happiness and related concepts, as well as quality of life. Happiness findings have been described as a challenge to the theory and practice of economics. Nevertheless, furthering gross national happiness, as well as a specified Index to measure it, has been adopted explicitly in the Constitution of Bhutan in 2008, to guide its economic governance.

Subject Classifications

The subject may be categorised in various ways, depending on specificity, intersection, and cross-classification. For example, within the Journal of Economic Literature classification codes, it has been categorized under:

  • Welfare economics at JEL: D63 – Equity, Justice, Inequality, and Other Normative Criteria and Measurement
  • Health, education, and welfare at JEL: I31 – General Welfare; Basic needs; Living standards; Quality of life; Happiness
  • Demographic economics at JEL:J18 – Public policy.


Given its very nature, reported happiness is subjective. It is difficult to compare one person’s happiness with another’s. It can be especially difficult to compare happiness across cultures. However, many happiness economists believe they have solved this comparison problem. Cross-sections of large data samples across nations and time demonstrate consistent patterns in the determinants of happiness.

Happiness is typically measured using subjective measures – e.g. self-reported surveys – and/or objective measures. One concern has always been the accuracy and reliability of people’s responses to happiness surveys. Objective measures such as lifespan, income, and education are often used as well as or instead of subjectively reported happiness, though this assumes that they generally produce happiness, which while plausible may not necessarily be the case. The terms quality of life or well-being are often used to encompass these more objective measures.

Macro-econometric happiness has been gauged by some as Gross National Happiness, following Sicco Mansholt’s 1972 introduction of the measure, and by others as a Genuine Wealth index. Anielski in 2008 wrote a reference definition on how to measure five types of capital:

  1. Human;
  2. Social;
  3. Natural;
  4. Built; and
  5. Financial.

Happiness, well-being, or satisfaction with life, was seen as unmeasurable in classical and neo-classical economics. Van Praag was the first person who organized large surveys in order to explicitly measure welfare derived from income. He did this with the Income Evaluation Question (IEQ). This approach is called the Leyden School. It is named after the Dutch university where this approach was developed. Other researchers included Arie Kapteyn and Aldi Hagenaars.

Some scientists claim that happiness can be measured both subjectively and objectively by observing the joy centre of the brain lit up with advanced imaging, although this raises philosophical issues, for example about whether this can be treated as more reliable than reported subjective happiness.



Typically national financial measures, such as gross domestic product (GDP) and gross national product (GNP), have been used as a measure of successful policy. There is a significant association between GDP and happiness, with citizens in wealthier nations being happier than those in poorer nations. In 2002, researchers argued that this relationship extends only to an average GDP per capita of about $15,000. In the 2000s, several studies have obtained the opposite result, so this Easterlin paradox is controversial.

Individual Income

Historically, economists have said that well-being is a simple function of income. However, it has been found that once wealth reaches a subsistence level, its effectiveness as a generator of well-being is greatly diminished. Happiness economists hope to change the way governments view well-being and how to most effectively govern and allocate resources given this paradox.

In 2010, Daniel Kahneman and Angus Deaton found that higher earners generally reported better life satisfaction, but people’s day-to-day emotional well-being only rose with earnings until a threshold annual household pre-tax income of $75,000.

Other factors have been suggested as making people happier than money. A short term course of psychological therapy is 32 times more cost effective at increasing happiness than simply increasing income.

Scholars at the University of Virginia, University of British Columbia and Harvard University released a study in 2011 after examining numerous academic paper in response to an apparent contradiction: “When asked to take stock of their lives, people with more money report being a good deal more satisfied. But when asked how happy they are at the moment, people with more money are barely different than those with less.” Published in the Journal of Consumer Psychology, the study is entitled “If Money Doesn’t Make You Happy, Then You Probably Aren’t Spending It Right” and included the following eight general recommendations:

  • Spend money on “experiences” rather than goods.
  • Donate money to others, including charities, rather than spending it solely on oneself.
  • Spend small amounts of money on many small, temporary pleasures rather than less often on larger ones.
  • Don’t spend money on “extended warranties and other forms of overpriced insurance.”
  • Adjust one’s mindset to “pay now, consume later,” instead of “consume now, pay later.”
  • Exercise circumspection about the day-to-day consequences of a purchase beforehand.
  • Rather than buying products that provide the “best deal,” make purchases based on what will facilitate well-being.
  • Seek out the opinions of other people who have prior experience of a product before purchasing it.

In their “Unhappy Cities” paper, Edward Glaeser, Joshua Gottlieb and Oren Ziv examined the self-reported subjective well-being of people living in American metropolitan areas, particularly in relation to the notion that “individuals make trade-offs among competing objectives, including but not limited to happiness.” The researchers findings revealed that people living in metropolitan areas where lower levels of happiness are reported are receiving higher real wages, and they suggest in their conclusion that “humans are quite understandably willing to sacrifice both happiness and life satisfaction if the price is right.”

Social Security

Ruut Veenhoven claimed that social security payments do not seem to add to happiness. This may be due to the fact that non-self-earned income (e.g., from a lottery) does not add to happiness in general either. Happiness may be the mind’s reward for a useful action. However, Johan Norberg of CIS, a free enterprise economy think tank, presents a hypothesis that as people who think that they themselves control their lives are happier, paternalist institutions may decrease happiness.

An alternative perspective focuses on the role of the welfare state as an institution that improves quality of life not only by increasing the extent to which basic human needs are met, but also by promoting greater control of one’s life by limiting the degree to which individuals find themselves at the mercy of impersonal market forces that are indifferent to the fate of individuals. This is the argument suggested by the US political scientist Benjamin Radcliff, who has presented a series of papers in peer-reviewed scholarly journals demonstrating that a more generous welfare state contributes to higher levels of life satisfaction, and does so to rich and poor alike.


Generally, the well-being of those who are employed is higher than those who are unemployed. Employment itself may not increase subjective well-being, but facilitates activities that do (such as supporting a family, philanthropy, and education). While work does increase well-being through providing income, income level is not as indicative of subjective well-being as other benefits related to employment. Feelings of autonomy and mastery, found in higher levels in the employed than unemployed, are stronger predictors of subjective well-being than wealth.

When personal preference and the amount of time spent working do not align, both men and women experience a decrease in subjective well-being. The negative effect of working more or working less than preferred has been found across multiple studies, most finding that working more than preferred (over-employed) is more detrimental, but some found that working less (under-employed) is more detrimental. Most individuals’ levels of subjective well-being returned to “normal” (level previous to time mismatch) within one year. Levels remained lower only when individuals worked more hours than preferred for a period of two years or more, which may indicate that it is more detrimental to be over-employed than under-employed in the long-term.

Employment status effects are not confined to the individual. Being unemployed can have detrimental effects on a spouse’s subjective well-being, compared to being employed or not working (and not looking for work). Partner life satisfaction is inversely related to the number of hours their partner is underemployed. When both partners are underemployed, the life-satisfaction of men is more greatly diminished than women. However, just being in a relationship reduces the impact unemployment has on the subjective well-being of an individual. On a broad scale, high rates of unemployment negatively affect the subjective well-being of the employed.

Becoming self-employed can increase subjective well-being, given the right conditions. Those who leave work to become self-employed report greater life satisfaction than those who work for others or become self-employed after unemployment; this effect increases over time. Those who are self-employed and have employees of their own report higher life-satisfaction than those who are self-employed without employees, and women who are self-employed without employees report a higher life satisfaction than men in the same condition.

The effects of retirement on subjective well-being vary depending on personal and cultural factors. Subjective well-being can remain stable for those who retire from work voluntarily, but declines for those who are involuntarily retired. In countries with an average social norm to work, the well-being of men increases after retirement, and the well-being of retired women is at the same level as women who are homemakers or work outside the home. In countries with a strong social norm to work, retirement negatively impacts the well-being of men and women.

Relationships and Children

In the 1970s, women typically reported higher subjective well-being than did men. By 2009, declines in reported female happiness had eroded a gender gap.

In rich societies, where a rise in income does not equate to an increase in levels of subjective well-being, personal relationships are the determining factors of happiness.

Glaeser, Gottlieb and Ziv suggest in their conclusion that the happiness trade-offs that individuals seem willing to make aligns with the tendency of parents to report less happiness, as they sacrifice their personal well-being for the “price” of having children.

Freedom and Control

There is a significant correlation between feeling in control of one’s own life and happiness levels.

A study conducted at the University of Zurich suggested that democracy and federalism bring well-being to individuals. It concluded that the more direct political participation possibilities available to citizens raises their subjective well-being. Two reasons were given for this finding. First, a more active role for citizens enables better monitoring of professional politicians by citizens, which leads to greater satisfaction with government output. Second, the ability for citizens to get involved in and have control over the political process, independently increases well-being.

American psychologist Barry Schwartz argues in his book The Paradox of Choice that too many consumer and lifestyle choices can produce anxiety and unhappiness due to analysis paralysis and raised expectations of satisfaction.

Religious Diversity

National cross-sectional data suggest an inverse relationship between religious diversity and happiness, possibly by facilitating more bonding (and less bridging) social capital.

Happiness and Leisure

Much of the research regarding happiness and leisure relies on subjective well-being (SWB) as an appropriate measure of happiness. Research has demonstrated a wide variety of contributing and resulting factors in the relationship between leisure and happiness. These include psychological mechanisms, and the types and characteristics of leisure activities that result in the greatest levels of subjective happiness. Specifically, leisure may trigger five core psychological mechanisms including detachment-recovery from work, autonomy in leisure, mastery of leisure activities, meaning-making in leisure activities, and social affiliation in leisure (DRAMMA). Leisure activities that are physical, relational, and performed outdoors are correlated with greater feelings of satisfaction with free time. Research across 33 different countries shows that individuals who feel they strengthen social relationships and work on personal development during leisure time are happier than others. Furthermore, shopping, reading books, attending cultural events, getting together with relatives, listening to music and attending sporting events is associated with higher levels of happiness. Spending time on the internet or watching TV is not associated with higher levels of happiness as compared to these other activities.

Research has shown that culture influences how we measure happiness and leisure. While SWB is a commonly used measure of happiness in North America and Europe, this may not be the case internationally. Quality of life (QOL) may be a better measure of happiness and leisure in Asian countries, especially Korea. Countries such as China and Japan may require a different measurement of happiness, as societal differences may influence the concept of happiness (i.e. economic variables, cultural practices, and social networks) beyond what QOL is able to measure. There seem to be some differences in leisure preference cross-culturally. Within the Croatian culture, family related leisure activities may enhance SWB across a large spectrum of ages ranging from adolescent to older adults, in both women and men. Active socializing and visiting cultural events are also associated with high levels of SWB across varying age and gender. Italians seem to prefer social conceptions of leisure as opposed to individualistic conceptions. Although different groups of individuals may prefer varying types and amount of leisure activity, this variability is likely due to the differing motivations and goals that an individual intends to fulfil with their leisure time.

Research suggests that specific leisure interventions enhance feelings of SWB. This is both a top-down and bottom-up effect, in that leisure satisfaction causally affects SWB, and SWB causally affects leisure satisfaction. This bi-directional effect is stronger in retired individuals than in working individuals. Furthermore, it appears that satisfaction with our leisure at least partially explains the relationship between our engagement in leisure and our SWB. Broadly speaking, researchers classify leisure into active (e.g. volunteering, socialising, sports and fitness) and passive leisure (e.g. watching television and listening to the radio). Among older adults, passive leisure activities and personal leisure activities (e.g. sleeping, eating, and bathing) correlate with higher levels of SWB and feelings of relaxation than active leisure activities. Thus, although significant evidence has demonstrated that active leisure is associated with higher levels of SWB, or happiness, this may not be the case with older populations.

Both regular and irregular involvement in sports leisure can result in heightened SWB. Serious, or systematic involvement in certain leisure activities, such as taekwondo, correlates with personal growth and a sense of happiness. Additionally, more irregular (e.g. seasonal) sports activities, such as skiing, are also correlated with high SWB. Furthermore, the relationship between pleasure and skiing is thought to be caused in part by a sense of flow and involvement with the activity. Leisure activities, such as meeting with friends, participating in sports, and going on vacation trips, positively correlate with life satisfaction. It may also be true that going on a vacation makes our lives seem better, but does not necessarily make us happier in the long term. Research regarding vacationing or taking a holiday trip is mixed. Although the reported effects are mostly small, some evidence points to higher levels of SWB, or happiness, after taking a holiday.

Economic Security

Poverty alleviation are associated with happier populations. According to the latest systematic review of the economic literature on life satisfaction: Volatile or high inflation is bad for a population’s well-being, particularly those with a right-wing political orientation. That suggests the impact of disruptions to economic security are in part mediated or modified by beliefs about economic security.

Political Stability

The Voxeu analysis of the economic determinants of happiness found that life satisfaction explains the largest share of an existing government’s vote share, followed by economic growth, which itself explains six times as much as employment and twice as much as inflation.

Economic Freedom

Individualistic societies have happier populations. Institutes of economic freedom are associated with increases wealth inequality but does not necessarily contribute to decreases in aggregate well-being or subjective well-being at the population level. In fact, income inequality enhances global well-being. There is some debate over whether living in poor neighbours make one happier. And, living among rich neighbours can dull the happiness that comes from wealth. This is purported to work by way of an upward or downward comparison effect (Keeping up with the Joneses). The balance of evidence[citation needed] is trending in favour of the hypothesis that living in poor neighbourhoods makes one less happy, and living in rich neighbourhoods actually makes one happier, in the United States. While social status matters, a balance of factors like amenities, safe areas, well maintained housing, turn the tide in favour of the argument that richer neighbours are happier neighbours.


“The right to participate in the political process, measured by the extent of direct democratic rights across regions, is strongly correlated with subjective well-being (Frey and Stutzer, 2002) … a potential mechanism that explains this relationship is the perception of procedural fairness and social mobility.” Institutions and well-being, democracy and federalism are associated with a happier population. Correspondingly, political engagement and activism have associated health benefits. On the other hand, some non-democratic countries such as China and Saudi Arabia top the Ipsos list of countries where the citizenry is most happy with their government’s direction. That suggests that voting preferences may not translate well into overall satisfaction with the government’s direction. In any case, both of these factors revealed preference and domain specific satisfaction rather than overall subjective well being.

Economic Development

Historically, economists thought economic growth was unrelated to population level well-being, a phenomenon labelled the Easterlin paradox. More robust research has identified that there is a link between economic development and the wellbeing of the population. A 2017 meta-analysis suggests that the impact of infrastructure expenditure on economic growth varies considerably. So, one cannot assume an infrastructure project will yield welfare benefits. The paper does not investigate or elaborate on any modifiable variables that might predict the value of a project. However, government spending on roads and primary industries is the best value target for transport spending, according to a 2013 meta-analysis.7% (+/−3%) per annum discount rates are typically applied as the discount rate on public infrastructure projects in Australia. Smaller real discount rates are used internationally to calculate the social return on investment by governments.

Alternative Approach: Economic Consequences of Happiness

While the mainstream happiness economics has focused on identifying the determinants of happiness, an alternative approach in the discipline examines instead what are the economic consequences of happiness. Happiness may act as a determinant of economic outcomes: it increases productivity, predicts one’s future income and affects labour market performance. There is a growing number of studies justifying the so-called “happy-productive worker” thesis. The positive and causal impact of happiness on an individual’s productivity has been established in experimental studies.

Timeline of Developments

The idea that happiness is important to a society is not new. Many other prominent intellectuals, philosophers and political leaders throughout history, including Aristotle, Confucius, and Plato, incorporated happiness into their work.

“Happiness is the meaning and the purpose of life, the whole aim and end of human existence.” (Aristotle,350 B.C.).

Thomas Jefferson put the “pursuit of happiness” on the same level as life and liberty in the United States’ Declaration of Independence. Jeremy Bentham believed that public policy should attempt to maximize happiness, and he even attempted to estimate a “hedonic calculus”. In the US, there is no explicit policy that requires the rulers to develop the physical and mental well-being of the citizens or hold the government agencies accountable for their performance against specific measures or metrics of well-being. Until 1972 there was no formal government policy, anywhere in the world, that placed happiness and well-being as a main criterion for public policy decision making.

The following is a chronological list of happiness economics and well-being indices:

  • 1789 – France adopts the Declaration: It emphasizes happiness as a fundamental right and universal goal.
  • 1972 – Bhutan’s former king, Jigme Singye Wangchuck, introduced the Gross National Happiness (GNH) philosophy and its four development pillars at an international conference.
  • 2005 – Med Jones of the International Institute of Management introduced the first GNH Index and Global GNH Index Survey. The GNH Index, also known as Gross National Well-being (GNW) Index framework served as the first integrated objective (economic) and subjective (happiness) socioeconomic development framework. Prior to the GNH Index, there were few development indices that improved upon the gross domestic product (GDP), but did not measure happiness. For example, the Genuine Progress Indicator was focused on the environmental cost of economic development, then later (in 2006) it was updated to include similar measures to the GNH Index. Another development index is the Human Development Index (HDI) that originally focused on literacy and education but also did not measure happiness. The HDI now measures three basic dimensions of human development, health (as measured by life expectancy at birth), overall knowledge level (as measured by the literacy rate), and standard of living (as measured by GDP per capita for a given year). Among the criticisms of the HDI is the complaint that it is a mixture of stock measures (life expectancy at birth and literacy rate) and a flow measure (GDP per capita for a given year). To overcome this criticism, Hou, Walsh, and Zhang (2015) proposed a new index called HDIF (Human Development Index Flow), in which they replaced life expectancy at birth by the under-five mortality rate (for a given year), and they also replaced the literacy rate by the gross primary school enrolment ratio for a given year). They calculated both the HDI and the HDIF for many countries and found that “the HDIF and the HDI tend to converge for wealthy countries and diverge for poor countries, especially those with low HDI rankings”. The development performance of poor countries improved using the HDIF while the performance of the wealthy countries declined.
  • 2006 – The Genuine Progress Indicator was updated from a green measurement system to a broader concept that included quantitative measurement of well-being and happiness. The new measure is motivated by the philosophy of the GNH and the same notion of that subjective measures like well-being are more relevant and important than more objective measures like consumption. It is not measured directly, but only by means of the factors which are believed to lead to it.
  • 2007 – Thailand releases Green and Happiness Index (GHI).
  • 2008 – French President Nicolas Sarkozy launched a Happiness Initiative similar to GNH, calling for the inclusion of happiness and well-being among the criteria for national governance policies. He commissioned three prominent economists, Joseph Stiglitz (US), Amartya Sen (India), Jean-Paul Fitoussi (France), to publish a report calling for a global “statistical system which goes beyond commercial activity to measure personal well-being.” Later it was described as gross domestic happiness (GDH). The GDH Index is similar to the GNH Index of 2005.
  • 2008 – The goal of furthering gross national happiness, as well as a specified GNH Index to measure this, are instituted explicitly in the Constitution of Bhutan, to guide its government, on 18 July 2008. The included index is used to measure the collective happiness and well-being of the population.
  • 2009 – In the United States, the Gallup poll system launched the happiness survey collecting data on national scale. The Gallup Well-Being Index was modelled after the GNH Index framework of 2005. The Well-Being Index score is an average of six sub-indexes which measure life evaluation, emotional health, work environment, physical health, healthy behaviours, and access to basic necessities. In October 2009, the US scored 66.1/100.
  • 2010 – The concept was taken seriously, as the Centre for Bhutan Studies, under the leadership of Karma Ura, developed a sophisticated survey instrument to measure the population’s general level of well-being. Two Canadians, Michael and Martha Pennock played a major role in developing the Bhutanese survey, which took a six- to seven-hour interview to complete. They developed a shorter international version of the survey which has been used in their home region of Victoria, BC, as well as in Brazil. The Pennocks also collaborated with Ura in the production of a policy lens which is used by the Bhutanese GNH Commission for anticipating the impact of policy initiatives upon the levels of gross national happiness in Bhutan.
  • 2010 – The Center for Bhutan Studies further defined the original four pillars with greater specificity into eight general contributors to happiness, which make up the Bhutan GNH Index: 1) physical, mental and spiritual health; 2) time-balance; 3) social and community vitality; 4) cultural vitality; 5) education; 6) living standards; 7) good governance; and 8) ecological vitality.
  • 2010 – The Oxford Poverty and Human Development Initiative OPHI at the University of Oxford in UK, launched the Multidimensional Poverty Index (MPI) for the United Nations Development Programme, (UNDP). Similar to the GNH Index of 2005, OPHI promotes collection and analysis of data on five dimensions including Quality of work, Empowerment, Physical safety, Ability to go about without shame, Psychological wellbeing.
  • 2011 – UN General Assembly Resolution 65/309, titled “Happiness: towards a holistic approach to development”
  • 2011 – The Organisation for Economic Co-operation and Development (OECD) launched “Better Life Index” (BLI).
  • 2011 – The United Nations released its first edition of the now annual World Happiness Report.
  • 2011 – Canadian Index of Wellbeing Network (CIW Network) released The Canadian Index of Wellbeing (CIW).
  • 2011 – The Israeli newspaper Haaretz published an article suggesting that western GDP economics is an incomplete development model and called for the adoption of Bhutan’s GNH philosophy and Jones’ GNH Index in Israel.
  • 2011 – Chuluun Togtokh criticized the HDI in an article published in Nature, calling for a revised HDI, writing that “The revised index should include each nation’s per capita carbon emissions, and so become a Human Sustainable Development Index (HSDI).” Bravo (2014) provided details of how the HSDI was computed and proposed an amended HSDI by including the proportion of forested area in each country. He argued that this proposed indicator “represents an important measure of the capacity of the natural system to provide fundamental ecological services.”
  • 2012 – In a report prepared for the US Congressman Hansen Clarke, R, researchers Ben Beachy and Juston Zorn, at John F. Kennedy School of Government in Harvard University, recommended that “the Congress should prescribe the broad parameters of new, carefully designed supplemental national indicators; it should launch a bipartisan commission of experts to address unresolved methodological issues, and include alternative indicators.” They proposed that the government can use the survey results to see which well-being dimensions are least satisfied and which districts and demographic groups are most deficient, so as to allocate resources accordingly. The report list the Gross National Happiness Index and its seven measurement area as one of the main frameworks to consider.
  • 2012 – Professor Peter T. Coleman, a director of the International Centre for Cooperation and Conflict Resolution at Columbia University, suggested that Jones’ GNH Index initiative could inform the Global Peace Index Initiative GPI.
  • 2012 – South Korea launched Happiness Index citing the GNH Index framework.
  • 2012 – The government of Goa, India, published a strategy for socioeconomic development citing the GNH Index as a model for measuring happiness.
  • 2012 – The city of Seattle in Washington, launched its own happiness index initiative, emphasizing measures similar to the GNH Index.
  • 2013 – The Social Progress Index SPI was launched by Michael Porter
  • 2013 – The president of Singapore, Tony Tan, proposed that in addition to building up substantial financial reserves, Singapore needed to focus on building up its “social reserves”, a concept that appears to have parallels to GNH.
  • 2013 – Economist Karol Jan Borowiecki motivates that well-being indices can be obtained from the way people communicate, as is established in psychology, and compiles the first well-being indices covering the life-time of a person.
  • 2013 – A joint commission led by the Conseil économique et social, the Conseil supérieur pour un développement durable and the Observatoire de la Compétitivité introduces a set of indicators measuring the quality of life in Luxembourg. The conclusions of the commission are summarised in a document titled “Projet PIBien-être”, which identifies 64 indicators belonging to 11 different domains to assess quality of life in Luxembourg.
  • 2014 – The government of Dubai launched its localized Happiness Index to measure the public’s contentment and satisfaction with different government services.
  • 2014 – The United Kingdom launched its own well-being and happiness statistics.
  • 2015 – Within the “Projet PIBien-être” launched in 2013, STATEC (National Institute of Statistics and Economic Studies of the Grand Duchy of Luxembourg) presents a preliminary analysis of the “Luxembourgish Index of Well-being” (LIW), a first proposal of synthetic indicator measuring the quality of life in Luxembourg. The presentation entitled “Preliminary Assessment of Quality of Life in Luxembourg” was delivered by Marcin Piekałkiewicz on 16 December 2015.
  • 2017 – The Minderoo Foundation launched the Global Slavery Index, providing a map of the estimated prevalence of modern slavery. The information allows an objective comparison and assessment of both the problem and adequacy of the response in 167 countries.

Related Studies

The Satisfaction with Life Index is an attempt to show the average self-reported happiness in different nations. This is an example of a recent trend to use direct measures of happiness, such as surveys asking people how happy they are, as an alternative to traditional measures of policy success such as GDP or GNP. Some studies suggest that happiness can be measured effectively. The Inter-American Development Bank (IDB), published in November 2008 a major study on happiness economics in Latin America and the Caribbean.

There are also several examples of measures that include self-reported happiness as one variable. Happy Life Years, a concept brought by Dutch sociologist Ruut Veenhoven, combines self-reported happiness with life expectancy. The Happy Planet Index combines it with life expectancy and ecological footprint.

Gross National Happiness (GNH) is a concept introduced by the King of Bhutan in 1972 as an alternative to GDP. Several countries have already developed or are in the process of developing such an index. Bhutan’s index has led that country to limit the amount of deforestation it will allow and to require that all tourists to its nation must spend US$200. Allegedly, low-budget tourism and deforestation lead to unhappiness.

After the military coup of 2006, Thailand also instituted an index. The stated promise of the new Prime Minister Surayud Chulanont is to make the Thai people not only richer but happier as well. Much like GDP results, Thailand releases monthly GNH data. The Thai GNH index is based on a 1–10 scale with 10 being the happiest. As of 13 May 2007, the Thai GNH measured 5.1 points. The index uses poll data from the population surveying various satisfaction factors such as security, public utilities, good governance, trade, social justice, allocation of resources, education and community problems.

Australia, China, France and the United Kingdom are also coming up with indexes to measure national happiness. The UK began to measure national wellbeing in 2012. North Korea also announced an international Happiness Index in 2011 through Korean Central Television. North Korea itself came in second, behind #1 China. Canada released the Canadian Index of Wellbeing (CIW) in 2011 to track changes in wellbeing. The CIW has adopted the following working definition of wellbeing: The presence of the highest possible quality of life in its full breadth of expression focused on but not necessarily exclusive to good living standards, robust health, a sustainable environment, vital communities, an educated populace, balanced time use, high levels of democratic participation, and access to and participation in leisure and culture.

Ecuador’s and Bolivia’s new constitutions state the indigenous concept of “good life” (“buen vivir” in Spanish, “sumak kawsay” in Quichua, and “suma qamaña” in Aymara) as the goal of sustainable development.

Neoclassical Economics

Neoclassical, as well as classical economics, are not subsumed under the term happiness economics although the original goal was to increase the happiness of the people. Classical and neoclassical economics are stages in the development of welfare economics and are characterised by mathematical modelling. Happiness economics represents a radical break with this tradition. The measurement of subjective happiness respectively life satisfaction by means of survey research across nations and time (in addition to objective measures like lifespan, wealth, security etc.) marks the beginning of happiness economics.


Some have suggested that establishing happiness as a metric is only meant to serve political goals. Recently there has been concern that happiness research could be used to advance authoritarian aims. As a result, some participants at a happiness conference in Rome have suggested that happiness research should not be used as a matter of public policy but rather used to inform individuals.

Even on the individual level, there is discussion on how much effect external forces can have on happiness. Less than 3% of an individual’s level of happiness comes from external sources such as employment, education level, marital status, and socioeconomic status. To go along with this, four of the Big Five Personality Traits are substantially associated with life satisfaction, openness to experience is not associated. Having high levels of internal locus of control leads to higher reported levels of happiness.

Even when happiness can be affected by external sources, it has high hedonic adaptation, some specific events such as an increase in income, disability, unemployment, and loss (bereavement) only have short-term (about a year) effects on a person’s overall happiness and after a while happiness may return to levels similar to unaffected peers.

What has the most influence over happiness are internal factors such as genetics, personality traits, and internal locus of control. It is theorised that 50% of the variation in happiness levels is from genetic sources and is known as the genetic set point. The genetic set point is assumed to be stable over time, fixed, and immune to influence or control. This goes along with findings that well-being surveys have a naturally positive baseline.

With such strong internal forces on happiness, it is hard to have an effect on a person’s happiness externally. This in turn lends itself back to the idea that establishing a happiness metric is only for political gain and has little other use. To support this even further it is believed that a country aggregate level of SWB can account for more variance in government vote share than standard macroeconomic variables, such as income and employment.

Technical Issues

According to Bond and Lang (2018), the results are skewed due to the fact that the respondents have to “round” their true happiness to the scale of, e.g., 3 or 7 alternatives (e.g. very happy, pretty happy, not too happy). This “rounding error” may cause a less happy group seem happier, in the average. This would not be the case if the happiness of both groups would be normally distributed with the same variance, but that is usually not the case, based on their results. For some not-implausible log-normal assumptions on the scale, typical results can be reversed to the opposite results.

They also show that the “reporting function” seems to be different for different groups and even for the same individual at different times. For example, when a person becomes disabled, they soon start to lower their threshold for a given answer (e.g. “pretty happy”). That is, they give a higher answer than they would have given at the same happiness state before becoming disabled.

This page is based on the copyrighted Wikipedia article < >; it is used under the Creative Commons Attribution-ShareAlike 3.0 Unported License (CC-BY-SA). You may redistribute it, verbatim or modified, providing that you comply with the terms of the CC-BY-SA.

What is Psychometrics?


Psychometrics is a field of study within psychology concerned with the theory and technique of measurement.

Psychometrics generally refers to specialised fields within psychology and education devoted to testing, measurement, assessment, and related activities. Psychometrics is concerned with the objective measurement of latent constructs that cannot be directly observed. Examples of latent constructs include intelligence, introversion, mental disorders, and educational achievement. The levels of individuals on non-observable latent variables are inferred through mathematical modelling based on what is observed from individuals’ responses to items on tests and scales.

Practitioners are described as psychometricians, although not all who engage in psychometric research go by this title. Psychometricians usually possess specific qualifications such as degrees or certifications, and most are psychologists with advanced graduate training in psychometrics and measurement theory. In addition to traditional, academic institutions, practitioners also work for organisations such as the Educational Testing Service and Psychological Corporation. Some psychometric researchers focus on the construction and validation of assessment instruments including surveys, scales, and open- or close-ended questionnaires. Others focus on research relating to measurement theory (e.g. item response theory; intraclass correlation) or specialise as learning and development professionals.

Historical Foundation

Psychological testing has come from two streams of thought: the first, from Darwin, Galton, and Cattell on the measurement of individual differences, and the second, from Herbart, Weber, Fechner, and Wundt and their psychophysical measurements of a similar construct. The second set of individuals and their research is what has led to the development of experimental psychology and standardised testing.

Victorian Stream

Charles Darwin was the inspiration behind Sir Francis Galton, a scientist who advanced the development of psychometrics. In 1859, Darwin published his book On the Origin of Species. Darwin described the role of natural selection in the emergence, over time, of different populations of species of plants and animals. The book showed how individual members of a species differ among themselves and how they possess characteristics that are more or less adaptive to their environment. Those with more adaptive characteristics are more likely to survive to procreate and give rise to another generation. Those with less adaptive characteristics are less likely. These ideas stimulated Galton’s interest in the study of human beings and how they differ one from another and, more importantly, how to measure those differences.

Galton wrote a book entitled Hereditary Genius. The book described different characteristics that people possess and how those characteristics make some more “fit” than others. Today these differences, such as sensory and motor functioning (reaction time, visual acuity, and physical strength), are important domains of scientific psychology. Much of the early theoretical and applied for work in psychometrics was undertaken in an attempt to measure intelligence. Galton often referred to as “the father of psychometrics,” devised and included mental tests among his anthropometric measures. James McKeen Cattell, a pioneer in the field of psychometrics, went on to extend Galton’s work. Cattell coined the term mental test, and is responsible for research and knowledge that ultimately led to the development of modern tests.

German Stream

The origin of psychometrics also has connections to the related field of psychophysics. Around the same time that Darwin, Galton, and Cattell were making their discoveries, Herbart was also interested in “unlocking the mysteries of human consciousness” through the scientific method. Herbart was responsible for creating mathematical models of the mind, which were influential in educational practices for years to come.

E.H. Weber built upon Herbart’s work and tried to prove the existence of a psychological threshold, saying that a minimum stimulus was necessary to activate a sensory system. After Weber, G.T. Fechner expanded upon the knowledge he gleaned from Herbart and Weber, to devise the law that the strength of a sensation grows as the logarithm of the stimulus intensity. A follower of Weber and Fechner, Wilhelm Wundt is credited with founding the science of psychology. It is Wundt’s influence that paved the way for others to develop psychological testing.

20th Century

In 1936, the psychometrician L.L. Thurstone, founder and first president of the Psychometric Society, developed and applied a theoretical approach to measurement referred to as the law of comparative judgement, an approach that has close connections to the psychophysical theory of Ernst Heinrich Weber and Gustav Fechner. In addition, Spearman and Thurstone both made important contributions to the theory and application of factor analysis, a statistical method developed and used extensively in psychometrics. In the late 1950s, Leopold Szondi made a historical and epistemological assessment of the impact of statistical thinking on psychology during previous few decades: “in the last decades, the specifically psychological thinking has been almost completely suppressed and removed, and replaced by a statistical thinking. Precisely here we see the cancer of testology and testomania of today.”

More recently, psychometric theory has been applied in the measurement of personality, attitudes, and beliefs, and academic achievement. These latent constructs cannot truly be measured, and much of the research and science in this discipline has been developed in an attempt to measure these constructs as close to the true score as possible.

Figures who made significant contributions to psychometrics include Karl Pearson, Henry F. Kaiser, Carl Brigham, L.L. Thurstone, E.L. Thorndike, Georg Rasch, Eugene Galanter, Johnson O’Connor, Frederic M. Lord, Ledyard R. Tucker, Louis Guttman, and Jane Loevinger.

Definition of Measurement in the Social Sciences

The definition of measurement in the social sciences has a long history. A current widespread definition, proposed by Stanley Smith Stevens, is that measurement is “the assignment of numerals to objects or events according to some rule.” This definition was introduced in a 1946 Science article in which Stevens proposed four levels of measurement. Although widely adopted, this definition differs in important respects from the more classical definition of measurement adopted in the physical sciences, namely that scientific measurement entails “the estimation or discovery of the ratio of some magnitude of a quantitative attribute to a unit of the same attribute.”

Indeed, Stevens’s definition of measurement was put forward in response to the British Ferguson Committee, whose chair, A. Ferguson, was a physicist. The committee was appointed in 1932 by the British Association for the Advancement of Science to investigate the possibility of quantitatively estimating sensory events. Although its chair and other members were physicists, the committee also included several psychologists. The committee’s report highlighted the importance of the definition of measurement. While Stevens’s response was to propose a new definition, which has had considerable influence in the field, this was by no means the only response to the report. Another, notably different, response was to accept the classical definition, as reflected in the following statement:

Measurement in psychology and physics are in no sense different. Physicists can measure when they can find the operations by which they may meet the necessary criteria; psychologists have to do the same. They need not worry about the mysterious differences between the meaning of measurement in the two sciences. (Reese, 1943, p.49).

These divergent responses are reflected in alternative approaches to measurement. For example, methods based on covariance matrices are typically employed on the premise that numbers, such as raw scores derived from assessments, are measurements. Such approaches implicitly entail Stevens’s definition of measurement, which requires only that numbers are assigned according to some rule. The main research task, then, is generally considered to be the discovery of associations between scores, and of factors posited to underlie such associations.

On the other hand, when measurement models such as the Rasch model are employed, numbers are not assigned based on a rule. Instead, in keeping with Reese’s statement above, specific criteria for measurement are stated, and the goal is to construct procedures or operations that provide data that meet the relevant criteria. Measurements are estimated based on the models, and tests are conducted to ascertain whether the relevant criteria have been met.

Instruments and Procedures

The first psychometric instruments were designed to measure intelligence. One early approach to measuring intelligence was the test developed in France by Alfred Binet and Theodore Simon. That test was known as the Test Binet-Simon .The French test was adapted for use in the US by Lewis Terman of Stanford University, and named the Stanford-Binet IQ test.

Another major focus in psychometrics has been on personality testing. There has been a range of theoretical approaches to conceptualizing and measuring personality, though there is no widely agreed upon theory. Some of the better-known instruments include the Minnesota Multiphasic Personality Inventory, the Five-Factor Model (or “Big 5”) and tools such as Personality and Preference Inventory and the Myers-Briggs Type Indicator. Attitudes have also been studied extensively using psychometric approaches. An alternative method involves the application of unfolding measurement models, the most general being the Hyperbolic Cosine Model (Andrich & Luo, 1993).

Theoretical Approaches

Psychometricians have developed a number of different measurement theories. These include classical test theory (CTT) and item response theory (IRT). An approach that seems mathematically to be similar to IRT but also quite distinctive, in terms of its origins and features, is represented by the Rasch model for measurement. The development of the Rasch model, and the broader class of models to which it belongs, was explicitly founded on requirements of measurement in the physical sciences.

Psychometricians have also developed methods for working with large matrices of correlations and covariances. Techniques in this general tradition include: factor analysis, a method of determining the underlying dimensions of data. One of the main challenges faced by users of factor analysis is a lack of consensus on appropriate procedures for determining the number of latent factors. A usual procedure is to stop factoring when eigenvalues drop below one because the original sphere shrinks. The lack of the cutting points concerns other multivariate methods, also.

Multidimensional scaling is a method for finding a simple representation for data with a large number of latent dimensions. Cluster analysis is an approach to finding objects that are like each other. Factor analysis, multidimensional scaling, and cluster analysis are all multivariate descriptive methods used to distil from large amounts of data simpler structures.

More recently, structural equation modelling and path analysis represent more sophisticated approaches to working with large covariance matrices. These methods allow statistically sophisticated models to be fitted to data and tested to determine if they are adequate fits. Because at a granular level psychometric research is concerned with the extent and nature of multidimensionality in each of the items of interest, a relatively new procedure known as bi-factor analysis can be helpful. Bi-factor analysis can decompose “an item’s systematic variance in terms of, ideally, two sources, a general factor and one source of additional systematic variance.”

Key Concepts

Key concepts in classical test theory are reliability and validity. A reliable measure is one that measures a construct consistently across time, individuals, and situations. A valid measure is one that measures what it is intended to measure. Reliability is necessary, but not sufficient, for validity.

Both reliability and validity can be assessed statistically. Consistency over repeated measures of the same test can be assessed with the Pearson correlation coefficient, and is often called test-retest reliability. Similarly, the equivalence of different versions of the same measure can be indexed by a Pearson correlation, and is called equivalent forms reliability or a similar term.

Internal consistency, which addresses the homogeneity of a single test form, may be assessed by correlating performance on two halves of a test, which is termed split-half reliability; the value of this Pearson product-moment correlation coefficient for two half-tests is adjusted with the Spearman-Brown prediction formula to correspond to the correlation between two full-length tests. Perhaps the most commonly used index of reliability is Cronbach’s α, which is equivalent to the mean of all possible split-half coefficients. Other approaches include the intra-class correlation, which is the ratio of variance of measurements of a given target to the variance of all targets.

There are a number of different forms of validity. Criterion-related validity refers to the extent to which a test or scale predicts a sample of behaviour, i.e. the criterion, that is “external to the measuring instrument itself.” That external sample of behaviour can be many things including another test; college grade point average as when the high school SAT is used to predict performance in college; and even behaviour that occurred in the past, for example, when a test of current psychological symptoms is used to predict the occurrence of past victimisation (which would accurately represent postdiction). When the criterion measure is collected at the same time as the measure being validated the goal is to establish concurrent validity; when the criterion is collected later the goal is to establish predictive validity. A measure has construct validity if it is related to measures of other constructs as required by theory. Content validity is a demonstration that the items of a test do an adequate job of covering the domain being measured. In a personnel selection example, test content is based on a defined statement or set of statements of knowledge, skill, ability, or other characteristics obtained from a job analysis.

Item response theory models the relationship between latent traits and responses to test items. Among other advantages, IRT provides a basis for obtaining an estimate of the location of a test-taker on a given latent trait as well as the standard error of measurement of that location. For example, a university student’s knowledge of history can be deduced from his or her score on a university test and then be compared reliably with a high school student’s knowledge deduced from a less difficult test. Scores derived by classical test theory do not have this characteristic, and assessment of actual ability (rather than ability relative to other test-takers) must be assessed by comparing scores to those of a “norm group” randomly selected from the population. In fact, all measures derived from classical test theory are dependent on the sample tested, while, in principle, those derived from item response theory are not.

Standards of Quality

The considerations of validity and reliability typically are viewed as essential elements for determining the quality of any test. However, professional and practitioner associations frequently have placed these concerns within broader contexts when developing standards and making overall judgements about the quality of any test as a whole within a given context. A consideration of concern in many applied research settings is whether or not the metric of a given psychological inventory is meaningful or arbitrary.

Testing Standards

In 2014, the American Educational Research Association (AERA), American Psychological Association (APA), and National Council on Measurement in Education (NCME) published a revision of the Standards for Educational and Psychological Testing, which describes standards for test development, evaluation, and use. The Standards cover essential topics in testing including validity, reliability/errors of measurement, and fairness in testing. The book also establishes standards related to testing operations including test design and development, scores, scales, norms, score linking, cut scores, test administration, scoring, reporting, score interpretation, test documentation, and rights and responsibilities of test takers and test users. Finally, the Standards cover topics related to testing applications, including psychological testing and assessment, workplace testing and credentialing, educational testing and assessment, and testing in programme evaluation and public policy.

Evaluation Standards

In the field of evaluation, and in particular educational evaluation, the Joint Committee on Standards for Educational Evaluation has published three sets of standards for evaluations. The Personnel Evaluation Standards was published in 1988, The Program Evaluation Standards (2nd edition) was published in 1994, and The Student Evaluation Standards was published in 2003.

Each publication presents and elaborates a set of standards for use in a variety of educational settings. The standards provide guidelines for designing, implementing, assessing, and improving the identified form of evaluation. Each of the standards has been placed in one of four fundamental categories to promote educational evaluations that are proper, useful, feasible, and accurate. In these sets of standards, validity and reliability considerations are covered under the accuracy topic. For example, the student accuracy standards help ensure that student evaluations will provide sound, accurate, and credible information about student learning and performance.

Controversy and Criticism

Because psychometrics is based on latent psychological processes measured through correlations, there has been controversy about some psychometric measures. Critics, including practitioners in the physical sciences, have argued that such definition and quantification is difficult, and that such measurements are often misused by laymen, such as with personality tests used in employment procedures. The Standards for Educational and Psychological Measurement gives the following statement on test validity: “validity refers to the degree to which evidence and theory support the interpretations of test scores entailed by proposed uses of tests”. Simply put, a test is not valid unless it is used and interpreted in the way it is intended.

Two types of tools used to measure personality traits are objective tests and projective measures. Examples of such tests are the: Big Five Inventory (BFI), Minnesota Multiphasic Personality Inventory (MMPI-2), Rorschach Inkblot test, Neurotic Personality Questionnaire KON-2006, or Eysenck’s Personality Questionnaire (EPQ-R). Some of these tests are helpful because they have adequate reliability and validity, two factors that make tests consistent and accurate reflections of the underlying construct. The Myers-Briggs Type Indicator (MBTI), however, has questionable validity and has been the subject of much criticism. Psychometric specialist Robert Hogan wrote of the measure: “Most personality psychologists regard the MBTI as little more than an elaborate Chinese fortune cookie.”

Lee Cronbach noted in American Psychologist (1957) that, “correlational psychology, though fully as old as experimentation, was slower to mature. It qualifies equally as a discipline, however, because it asks a distinctive type of question and has technical methods of examining whether the question has been properly put and the data properly interpreted.” He would go on to say, “The correlation method, for its part, can study what man has not learned to control or can never hope to control … A true federation of the disciplines is required. Kept independent, they can give only wrong answers or no answers at all regarding certain important problems.”

Non-Human: Animals and Machines

Psychometrics addresses human abilities, attitudes, traits, and educational evolution. Notably, the study of behaviour, mental processes, and abilities of non-human animals is usually addressed by comparative psychology, or with a continuum between non-human animals and the rest of animals by evolutionary psychology. Nonetheless, there are some advocators for a more gradual transition between the approach taken for humans and the approach taken for (non-human) animals.

The evaluation of abilities, traits and learning evolution of machines has been mostly unrelated to the case of humans and non-human animals, with specific approaches in the area of artificial intelligence. A more integrated approach, under the name of universal psychometrics, has also been proposed.

This page is based on the copyrighted Wikipedia article < >; it is used under the Creative Commons Attribution-ShareAlike 3.0 Unported License (CC-BY-SA). You may redistribute it, verbatim or modified, providing that you comply with the terms of the CC-BY-SA.

What is a School Psychological Examiner?


In the United States education system, School Psychological Examiners assess the needs of students in schools for special education services or other interventions.

The post requires a relevant postgraduate qualification and specialist training. This role is distinct within school psychology from that of the psychiatrist, clinical psychologist and psychometrist.

Role of Psychological Examiners in Schools

School Psychological Examiners are assessors licensed by a State Department of Education to work with students from pre-kindergarten to twelfth grade in public schools, interviewing, observing, and administering and interpreting standardised testing instruments that measure cognitive and academic abilities, or describe behaviour, personality characteristics, attitude or aptitude, in order to determine eligibility for special education services, placement, or conduct re-evaluation, or occupational guidance and planning.

The work of the School Psychological Examiners is both qualitative and quantitative in nature. They prepare psychoeducational evaluation reports based on test results and interpretation. Integrated with case history, the evaluation reports should present an accurate and clear profile of a student’s level of functioning or disability, strengths and weaknesses, compare test results with the standards of the evaluation instruments, analyse potential test biases, and develop appropriate recommendations to help direct educational interventions and services in a most inclusive and least restrictive environment. Evaluation reports are framed by laws and regulations applicable to testing and assessment in special education, and must follow school district policies and the codes of ethics applicable to education, special education, and psychological assessment.

School Psychological Examiners also provide psychoeducational interventions such as consultation services, collaboration in behaviour management planning and monitoring, and devising social skills training programmes in public schools.

Unless additionally trained and licensed, School Psychological Examiners do not offer or provide psychotherapy or clinical diagnostic/treatment services, which are attributions of licensed psychiatrists and clinical psychologists, as provided by law and professional regulations.


School Psychological Examiners are highly trained and experienced educators who hold a master’s or higher degree in education or school counselling and at least one endorsement in special education. In addition to school district policies, School Psychological Examiners are bound by professional regulations, as well as by the ethical codes of testing and measurement. Other designations for School Psychological Examiners include ‘Educational Examiners’ or ‘Psychoeducational Examiners.’ Designation of this specialty varies among different school districts.

‘Psychometrist,’ from the term psychometrics, is an occupational designation not inclusive of the broader faculties of School Psychological Examiners. Psychometrists deal exclusively with quantitative test administration, do not require coursework beyond the bachelor’s level, or licensure by a state department of education. Training of psychometrists is primarily done on-the-job, and their services are valuable in mental health community agencies, assessment and institutional research, or test-producing companies, etc., rather than in K-12 schools.

Graduate Training and Licensure of School Psychological Examiners

Typical training includes coursework beyond the Master of Education, Master of Science in Education, or Master of Arts in Teaching degrees. Currently, School Psychological Examiners complete the courses required by their state department of education rather than by a prescribed self-contained programme of studies. The coursework is equivalent to an entire Specialist or Doctoral Degree; unfortunately just a handful of institutions of higher education offer this kind of self-standing graduate programme. Graduate courses of a psychological nature include:

  • Special Education Law.
  • Advanced Child and Adolescent Growth and Development.
  • Psychology of Students with Exceptionalities.
  • Abnormal Child and Adult Psychology.
  • Advanced Statistics and Research in Education and Psychology.
  • Tests and measurements.
  • Assessment and Evaluation of the Individual.
  • Individual Intelligence quotient.
  • Group Assessment.
  • Diagnostics and Remedial Reading.
  • Ethical issues in education and psychological measurement and evaluation reporting.
  • Methods of Instructing Students with Mild/Moderate Disabilities.
  • Methods of Instructing Students with Severe to Profound Disabilities.
  • Survey of Guidance and Counselling Techniques.
  • Practicum for School Psychological Examiners (150 supervised contact hours).

Licensure as School Psychological Examiner demands experience in a special education or school counselling setting, satisfactory completion of the required graduate coursework and practicum, plus a passing score on the ‘Praxis II Special Education: Knowledge-Based Core Principles’. Graduate school recommendation and verification of experience by the employing school district complete the requirements. In addition to the practicum, on-the-job mentoring supervision for at least two school years, sometimes four years, allows the transition from initial licensure to standard professional licensure. An annual professional development plan and ongoing performance-based evaluation ensure ‘High Quality’ professionalism as required by the No Child Left Behind law and related regulations.


The clinical and technical skills needed to be a competent behavioural and clinical assessor include the abilities to do the following (Sattler & Hoge, 2006):

  • Establish and maintain rapport with children, parents, and teachers.
  • Use effective assessment techniques appropriate for evaluating children’s behaviour.
  • Use effective techniques for obtaining accurate and complete information from parents and teachers.
  • Evaluate the psychometric properties of tests and other measures.
  • Select an appropriate assessment battery.
  • Administer and score tests and other assessment tools by following standardised procedures.
  • Observe and evaluate behaviour objectively.
  • Perform informal assessments.
  • Interpret assessment results.
  • Use assessment findings to develop effective interventions.
  • Communicate assessment findings effectively, both orally and in writing.
  • Adhere to ethical standards.
  • Read and interpret research in behavioural and clinical assessment.
  • Keep up with laws and regulations concerning the assessment and placement of children with special needs.

Additionally, high quality School Psychological Examiners exhibit proficiency-level knowledge on:

  • The provisions of the Individuals with Disabilities Act and the Section 504 of the Civil Rights Act and related legislation.
  • State and federal laws, and all the applicable regulations, policies, and standards pertaining the provision of psychosocial and educational services to disabled individuals.
  • Children and adolescents’ advanced development and behaviour.
  • Multicultural factors in attitudes and behaviours.
  • Analysis and diagnosis of learning problems including special consideration of low incidence populations.
  • Integration of knowledge, facts, and theory on classroom environment, psychosocial principles, and test results, to plan for prescriptive instruction, management, and education of students with special needs.
  • Focused and methodical psychoeducational evaluation reporting, providing sound and accurate information and research-based remediation recommendations to improve individual student’s learning, achievement, and behavioural performance.
  • Teamwork and collaboration for the process of staffing with other school professionals and collaborative development of instructional strategies for students with special needs.
  • Provision of assistance with instructional modifications or accommodations, and programming or transition recommendations for the Individualised Education Programme (IEP).
  • Accountability for the monitoring and outcome assessment of services and interventions.

Evaluation Standards

Evaluation standards provide guidelines for designing, implementing, assessing, and reporting the psychoeducational evaluation reported by school psychological examiners. The evaluation is informed by professional codes of ethics.

  • Standards for Qualifications of Test Users.
  • Code of Fair Testing Practices in Education.
  • Standards for Multicultural Assessment.
  • Standards for Educational and Psychological Testing.


Sattler, J. M. & Hoge, R. D. (2006). Assessment of Children: Behavioral, Social, and Clinical Foundations. 5th Ed. San Diego, CA: Jerome M. Sattler Publisher, Inc. p.2.

Book: An Introduction to Psychological Assessment & Psychometrics

Book Title:

An Introduction to Psychological Assessment & Psychometrics.

Author(s): Keith Coley.

Year: 2014.

Edition: Second (2nd).

Publisher: SAGE Publications.

Type(s): Paperback.


In An Introduction to Psychological Assessment and Psychometrics, Keith Coaley outlines the key ingredients of psychological assessment, providing case studies to illustrate their application, making it an ideal textbook for courses on psychometrics or psychological assessment.

New to the Second Edition:

  • Includes occupational and educational settings.
  • Covers ethical and professional issues with a strong practical focus.
  • Case study material related to work selection settings.
  • End of chapter self-assessments to facilitate students’ progress.
  • Compliant with the latest BPS Certificate of Testing curriculum.

Strategies used by Families to Cope with Chronic Mental Illnesses

Research Paper Title

Strategies used by families to cope with chronic mental illnesses: Psychometric properties of the family crisis oriented personal evaluation scale.


This study was aimed at investigating the psychometric properties of the Family Crisis Oriented Personal Evaluation Scale (F-COPES) for Turkish society, which assesses the coping skills of caregivers of individuals with chronic mental illnesses.


The study was conducted with 153 family caregivers of patients with a chronic mental illness admitted to the inpatient and outpatient units of two university hospitals and İzmir Schizophrenia Solidarity Association.

For the language validity, the translation-back translation method was performed, for the content validity, expert opinions were obtained, for the construct validity, exploratory and confirmatory factor analysis was performed.

For the reliability analysis, Cronbach α reliability coefficient was calculated and the test-retest reliability analysis was performed.


The content validity index of the scale was 0.96.

The Cronbach’s α reliability coefficient for the overall scale was .80. Factor loadings of the subscales ranged between 0.56 and 0.69 for the Acquiring Social Support subscale, between 0.43 and 0.74 for the Reframing subscale, between 0.53 and 0.74 for the Seeking Spiritual Support subscale.

The model fit indexes were as follows: χ2  = 176.369, df = 116, χ2 /df = 1.52, RMSEA = 0.059, CFI = 0.90, IFI = 0.91, GFI = 0.88.


The results of the present study show that the levels of psychometric properties of F-COPES in Turkish society are acceptable.

It is thought that it would be useful to use the F-COPES in the assessment of coping behaviours of individuals who give care to patients with a chronic mental illness and that it can be used as measurement tool in studies to be conducted with caregivers of patients with a chronic mental illness to assess their coping skills.


Sari, A. & Çetinkaya Duman, Z. (2019) Strategies used by families to cope with chronic mental illnesses: Psychometric properties of the family crisis oriented personal evaluation scale. Perspectives in Psychiatric Care. doi: 10.1111/ppc.12457. [Epub ahead of print].