“Watching TV…” by Michael Riedel

Title: Watching Alone: Relational goods, television, and happiness

Author(s): Luigino Bruni & Luca Stanca

Publisher: Journal of Economic Behavior and Organization

Year: 2008

URL: http://www.sciencedirect.com/science/article/pii/S0167268106002095

Topics: television, subjective wellbeing, relational goods

Methods: Regression analysis using data from the World Values Study

What it says: Despite what people might think about the relationship between income and happiness, individual happiness does not appear to grow with overall economic growth according to the data in the World Values Survey. Some researchers have explained this by theorizing that people make decisions about consumption by comparing themselves to a reference group, which makes individual utility measurable in terms relative to other people. According to this theory, as long as your means to consume remain unchanged relative to other people, your overall happiness will remain unchanged, even if your consumption level has increased. The means by which television reduces subjective wellbeing, according to Bruni and Stanca, is that watching advertising and content featuring wealthy people inspires dissatisfaction among viewers and constant aspiration for more and better things.

In addition to leading to income aspiration, Bruni and Stanca present theories from psychological research that suggest strong interpersonal relationships and time spent with friends and family are key to a strong sense of wellbeing. Since television occupies such a large share of time in the United States and around the world, they argue that time spent watching television crowds out time that could be spent on activities with friends and family, or consuming “relational goods.”

Using data from the World Values Survey, which includes data from about 80 countries, they control for region of the world, age, gender, income, health, freedom, education, employment status, marital status, personality traits, and beliefs. In addition to considering the impact on life satisfaction descriptively, the authors use 2SLS to check on a possible causal interpretation of the results, with variables for the importance of friends and family and importance of television as instruments for the relational indicators and TV consumption, respectively. Their results show a positive relationship between volunteering and social activities and happiness, and a negative relationship between television viewing and social and volunteering activities. Using these results, they argue that, as countries’ wealth increases, people tend to over-consume material goods and under consume relational goods that would increase their life satisfaction to keep on an equal level of consumption as their neighbors. Since respondents’ tendency to participate in volunteer activities and interact socially with friends and family decreases as hours of television watched per day increases, their theory follows that one of the means by which life satisfaction does not increase with income is that television causes people to stay on the “relational treadmill” of failing to increase happiness as income increases.

What I think about it: Two research notes, one published in 2011 by Mitesh Kataria and Tobias Regner, and the other by Lutz Schneider published in 2013, dispute the findings in this paper based on the empirical approach and the interpretation.

Kataria and Regner criticize Bruni and Stanca for their strong interpretation of their findings based on just two regression analyses. They argue that there is significant heterogeneity between countries even within the dummy variables that Bruni and Stanca create based on regions of the world. In their models using data from different countries, they find that television has an overall positive impact on wellbeing, meaning that people who watch television are more likely to report positive wellbeing than people who don’t watch television. Additionally, they do not find evidence that relational activities are more associated with happiness than watching television. They argue that, in models where the direction of the coefficient on television hours is negative, the impact is very small compared to factors like income and health, and that more research into personality traits like neuroticism may be an interesting determinant of wellbeing and television to explore in future research.

Schneider finds an error in the way that Bruni and Stanca classified countries in the WVS and presents new analyses with the corrected classification. Schneider finds a much weakened impact of television viewing with the correct country classification on Bruni and Stanca’s regions, and when considering the significant impact of television viewing with the corrected country classification, the effect is no longer significant. Schenider finds more validity in Bruni & Stanca’s theoretical argument that income aspiration leads to the “relational treadmill” of not reaching increased life satisfaction, and points to papers with more convincing evidence to support that theory.

Bearing in mind these critiques, it seems that there is merit to Bruni and Stanca’s theoretical framework, but some problems with their empirical analysis and interpretation. I think we should be hesitant to take any of the magnitudes or the significance of their effects to heart, but their basic theory that television leads to income aspiration, which in turn causes people to over consume material goods and under consume relational goods has enough grounding that we should continue to consider its validity.

What it all means: In contrast with the literature we’ve reviewed relating watching television to health outcomes, where there seems to be some agreement in the direction and significance of the effects related to watching television, relating television to happiness seems to be a bit murkier. The evidence from these three papers suggests that there may be a relationship between income aspiration, happiness, and television, but that there is disagreement on the best way to assess the magnitude or the causes of that relationship according to the World Values Survey. In particular, the country-specific impacts appear to be significant drivers of whether or not television affects individual wellbeing. The conflicting results from these authors affirms the complexity of the intuition underlying the study of subjective wellbeing.

The Computing Scale Co, Burnaby Village Museum by Kenny Louie

Title: TV Viewing and BMI by Race/Ethnicity and Socio-Economic Status

Author(s): Kerem Shuval, Kelley Pettee Gabriel, Tammy Leonard

Publisher: PloS ONE

Year: 2013

URL: http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0063579

Topics: obesity, health outcomes, television viewing, socioeconomic status and race

Methods: Regression analysis of the Health Information National Trends Survey (HINTS), a nationally representative survey of people over aged 18 from across the United States about their communications and knowledge about healthcare and cancer.

What it says: This study uses data from HINTS to understand the association between obesity and television among adults when considering socioeconomic status and race/ethnicity. The authors use BMI as the primary dependent variable and TV viewing, in average number of hours watched per day, as the primary independent variable. They controlled for race/ethnicity and socioeconomic status using variables for race and whether or not respondents completed a college degree and whether or not they had health insurance. They also controlled for age, gender, marital status, number of children, and variables related to respondents’ level of physical health.

They found that the odds of being overweight increased as respondents entered the third and fourth quartiles of television watching across races and socioeconomic statuses, but that the strength of the effect varied with race and socioeconomic status. For example, while they find an increased tendency toward obesity with more television viewing among non-Hispanic whites, the employed, and those with insurance, the effect is not statistically significant in the case of Hispanic and black respondents, unemployed respondents, and those without health insurance. Both college graduates and non-graduates were at increased risk for obesity in the fourth quartile of TV viewing.

What I think about it: The authors note a few important limitations to interpreting the results. The sample size for racial subpopulations is fairly small, which might disguise a real effect due to small sample size. They note that their findings are cross-sectional and do not account for how respondents’ relationship to watching television might vary over time. Additionally, they note that they do not consider factors other than television that might indicate a level of sedentary tendencies.

In terms of the significance of the findings, I think that we need more evidence to understand how television viewing and obesity relate to socioeconomic status and race. Additionally, I wonder if a more helpful statistical approach would be to examine how the increased likelihood of watching television among a particular group might make that group more prone to obesity, instead of looking at how the same amount of television viewing might lead to an increased likelihood of obesity.

What it all means: Increased television viewing leads to a higher likelihood of obesity, perhaps because of an increased tendency toward sedentary behavior. While the results of the study suggest that increased television viewing is not necessarily associated with increased obesity for all racial and socioeconomic groups, the fact that people in certain subgroups watch more television might make them more likely to become obese if we think that the relationship is causal.

Books! by Kirrus

Happy New Year, Createquity Insiders! We are starting the year off productively with plans to launch two feature articles later this month. We’re also in the process of choosing our next research investigations. Stay tuned. And now back to our regularly scheduled program…

Television Watching and Wellbeing

We are putting the pieces together on our feature article for TV and wellbeing and clarifying our takeaways from our review of the literature. Here is the full list of sources we’ve reviewed thus far for the forthcoming article:

Bowman, S. (2006). Television-viewing characteristics of adults: correlations to eating practices and overweight and health status. Preventing Chronic Disease, 3(2). Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/16539779

Bruni, L., & Stanca, L. (2008). Watching Alone: Relational goods, television, and happiness. Journal of Economic Behavior & Organization, 65(3-4), 506–528. Retrieved from http://www.sciencedirect.com/science/article/pii/S0167268106002095

Cardwell, S. (2014). Television Amongst Friends: Medium, Art, Media. Critical Studies in Television: The International Journal of Television Studies, 9(3), 6–21. Retrieved from http://www.ingentaconnect.com/content/manup/cstv/2014/00000009/00000003/art00002

Dempsey, P., Howard, B., Lynch, B., Owen, N., & Dunstan, D. W. (2014). Associations of television viewing time with adults’ well-being and vitality. Preventative Medicine.

Dunstan, D., Barr, E., Healy, G., Shaw, J., Balkau, B., Magliano, D., … Owen, N. (2010). Television viewing time and mortality: the Australian Diabetes, Obesity and Lifestyle Study (AusDiab). Circulation, 121(3), 384–91. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/20065160

Guetzkow, J. (2002). How the Arts Impact Communities: An Introduction to the Literature on Arts Impact Studies (Working Paper Series No. 20). Taking the Measure of Culture Conference: Princeton University Center for Arts and Cultural Policy Studies. Retrieved from https://www.princeton.edu/~artspol/workpap/WP20%20-%20Guetzkow.pdf

Gupta, V., Nwosa, N., Nadel, T., & Inamdar, S. (2001). Externalizing behaviors and television viewing in children of low-income minority parents. Clinical Pediatrics, 40(6), 337–41. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/11824177

Harlow, B. (2015). Staying Relevant in a Changing Neighborhood: How Fleisher Art Memorial is Adapting to Shifting Community Demographics (Wallace Studies in Building Arts Audiences). New York, NY: Wallace Foundation. Retrieved from http://www.wallacefoundation.org/knowledge-center/audience-development-for-the-arts/strategies-for-expanding-audiences/Documents/Staying-Relevant-in-a-Changing-Neighborhood-How-Fleisher-Art-Memorial-is-Adapting-to-Shifting-Community-Demographics.pdf

Harlow, B., & Cox Roman, C. (2015). Someone Who Speaks Their Language: How a Nontraditional Partner Brought New Audiences to Minnesota Opera (Wallace Studies in Building Arts Audiences). New York, NY: Wallace Foundation. Retrieved from http://www.wallacefoundation.org/knowledge-center/audience-development-for-the-arts/strategies-for-expanding-audiences/Documents/Someone-Who-Speaks-Their-Language.pdf

Harlow, B., & Heywood, T. (2015a). Getting Past “It’s Not For People Like Us”: Pacific Northwest Ballet Builds a Following with Teens and Young Adults (Wallace Studies in Building Arts Audiences). Wallace Foundation. Retrieved from http://www.wallacefoundation.org/knowledge-center/audience-development-for-the-arts/strategies-for-expanding-audiences/Documents/Getting-Past-Its-Not-For-People-Like-Us.pdf

Harlow, B., & Heywood, T. (2015b). Opening New Doors: Hands-on Participation Brings a New Audience to a Clay Studio (Wallace Studies in Building Arts Audiences). New York, NY: Wallace Foundation. Retrieved from http://www.wallacefoundation.org/knowledge-center/audience-development-for-the-arts/strategies-for-expanding-audiences/Documents/Opening-New-Doors-Hands-On-Participation-Brings-a-New-Audience-to-The-Clay-Studio.pdf

Hendriks Vettehen, P., Konig, R. P., Westerik, H., & Beentjes, H. (2012). Explaining television choices: The influence of parents and partners. Poetics, 40(6), 565–585. Retrieved from http://www.sciencedirect.com/science/article/pii/S0304422X12000605

Hoang, T. D., Reis, J., Zhu, N., Jacobs, D. R., Launer, L. J., Whitmer, R. A., … Yaffe, K. (2015). Effect of Early Adult Patterns of Physical Activity and Television Viewing on Midlife Cognitive Function. JAMA Psychiatry. Retrieved from http://archpsyc.jamanetwork.com/article.aspx?articleid=2471270

Horvath, C. W. (n.d.). Measuring Television Addiction. Journal of Broadcasting & Electronic Media, 48(3). Retrieved from http://www.tandfonline.com/doi/abs/10.1207/s15506878jobem4803_3?journalCode=hbem20#.Vji50KL88gg

Jacobs, J., & Peacock, S. (2014). Editorial: “The Liveliest Medium”: Television’s Aesthetic Relationships With Other Arts. Critical Studies in Television, 9(3), 1–5. Retrieved from https://www.icahdq.org/pubs/Calls/liveliestmedium.asp

Jakes, R., Day, N., Luben, R., Oakes, S., Welch, A., Bingham, S., & Wareham, N. (2003). Television viewing and low participation in vigorous recreation are independently associated with obesity and markers of cardiovascular disease risk: EPIC-Norfolk population-based study. European Journal of Clinical Nutrition, 57(9), 1089–96. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/12947427

Kahneman, D., Krueger, A. B., Schkade, D., Schwarz, N., & Stone, A. A. (2006). Would You Be Happier if You Were Richer? A Focusing Illusion. Science, 312(5782), 1908–1910. Retrieved from http://www.sciencemag.org/content/312/5782/1908.short

Kataria, M., & Regner, T. (2011). A Note on the Relationship Between Television Viewing and Individual Happiness. The Journal of Socio-Economics, 40(1), 53–58. Retrieved from http://www.sciencedirect.com/science/article/pii/S1053535710000892

Lampard, A., Jurkowski, J., & Davison, K. (2012). Social-cognitive predictors of low-income parents’ restriction of screen time among preschool-aged children. Health Education & Behavior: The Official Publication Of The Society For Public Health Education, 40(5), 526–30. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/23239766

Lee, B., & Lee, R. S. (1995). How and Why People Watch TV: Implications for the Future of Interactive Television: Implications for the Future of Interactive Television. Journal of Advertising Research, 35(6). Retrieved from http://www.researchgate.net/publication/242362719_How_and_why_people_watch_TV_Implications_for_the_future_of_interactive_television

Livingstone, S. (1998). Making Sense of Television: The Psychology of Audience Interpretation (Second). Routledge. Retrieved from https://books.google.com/books?id=0iIbwhcu1r4C&printsec=frontcover#v=onepage&q&f=false

McCoy, C. A., & Scarborough, R. C. (2014). Watching “bad” television: Ironic consumption, camp, and guilty pleasures. Poetics, 47, 41–59. Retrieved from http://www.sciencedirect.com/science/article/pii/S0304422X14000576

Muennig, P., Rosen, Z., & Johnson, G. (2013). Do the Psychological Risks Associated with Television Viewing Increase Mortality? Evidence from the 2008 General Social Survey – National Death Index dataset. Annals of Epidemiology, 23(6), 355–360. Retrieved from http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3662979/

Robinson, J. P., & Martin, S. (2008). What do Happy People Do? Social Indicators Research, 89(3), 565–571. Retrieved from http://link.springer.com/article/10.1007%2Fs11205-008-9296-6

Romer, D., Jamieson, K. H., & Aday, S. (2003). Television News and the Cultivation of Fear of Crime. Journal of Communications, 53(1), 88–104. Retrieved from http://onlinelibrary.wiley.com/doi/10.1111/j.1460-2466.2003.tb03007.x/abstract

Rosenstein, C. (2005). Diversity and Participation in the Arts: Insights from the Bay Area. The Urban Institute. Retrieved from http://www.urban.org/sites/default/files/alfresco/publication-pdfs/311252-Diversity-and-Participation-in-the-Arts.PDF

Schneider, L. (2013). A Note on Income Aspirations, Television, and Happiness. Kyklos, 66(2), 301–305. Retrieved from http://onlinelibrary.wiley.com/doi/10.1111/kykl.12022/abstract

Shuval, K., Gabriel, K. P., & Leonard, T. (2013). TV Viewing and BMI by Race/Ethnicity and Socio-Economic Status. PLOS. Retrieved from http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0063579

Simons, N. (2015). TV drama as a social experience: An empirical investigation of the social dimensions of watching TV drama in the age of non-linear television. Communications: The European Journal of Communication Research, 40(2), 219–236. Retrieved from http://www.researchgate.net/publication/279280934_TV_drama_as_a_social_experience_An_empirical_investigation_of_the_social_dimensions_of_watching_TV_drama_in_the_age_of_non-linear_television

Stevens, L. K. (1996). Motivating opera attendance : comparative qualitative research in 10 North American cities, 1996. Washington, D.C.: ArtsMarket Consulting. Retrieved from http://www.worldcat.org/title/motivating-opera-attendance-comparative-qualitative-research-in-10-north-american-cities-1996/oclc/35633527

Sussman, S., & Moran, M. B. (2013). Hidden addiction: Television. Journal of Behavioral Addictions, 2(3), 125–132. Retrieved from http://www.akademiai.com/doi/pdf/10.1556/JBA.2.2013.008

Thompson, D., Matson, P., & Ellen, J. (2013). Television viewing in low-income latino children: variation by ethnic subgroup and English proficiency. Childhood Obesity, 9(1), 22–8. Retrieved from http://online.liebertpub.com/doi/abs/10.1089/chi.2012.0113

Uslaner, E. M. (1998). Social Capital, Television, and the “Mean World”: Trust, Optimism, and Civic Participation. Political Psychology, 19(3), 441–467. Retrieved from http://www.jstor.org/stable/3792173

van der Goot, M., Beentjes, J. W. J., & van Selm, M. (2015). Older adults’ television viewing as part of selection and compensation strategies. Communications: The European Journal of Communication Research, 40(1), 93–111. Retrieved from http://www.researchgate.net/publication/277930457_Older_adults_television_viewing_as_part_of_selection_and_compensation_strategies

Wheeler, K. S. (2015). The relationships Between Television Viewing, Behaviors, Attachment, Loneliness, Depression, and Psychological Well-Being (Undergraduate Honors Thesis). Georgia Southern University, Georgia. Retrieved from http://digitalcommons.georgiasouthern.edu/honors-theses/98/

World Health Organization. (2012). Social Determinants of Health and Well-Being Among Young People.

Xu, J., Forman, C., Kim, J. B., & Van Ittersum, K. (2014). News Media Channels: Complements or Substitutes? Evidence from Mobile Phone Usage. Journal of Marketing, 78(4), 97–112. Retrieved from http://journals.ama.org/doi/abs/10.1509/jm.13.0198

History of Change in the Arts Ecosystem

We are also in the writing stage of our feature article exploring the history of change in the Arts Ecosystem. Here are the additional sources we reviewed in January for the forthcoming article:

Bogaert, S., Boone, C., Negro, G., & Witteloostuijn, A. van. (2014). Organizational Form Emergence A Meta-Analysis of the Ecological Theory of Legitimation. Journal of Management. http://doi.org/10.1177/0149206314527129

Burns, J. S. (1975). The Awkward Embrace: The Creative Artist and the Institution in America (1st edition). New York: Alfred A. Knopf.

Hanks, N. (1965). The Performing Arts: Problems and Prospects. Rockefeller Brothers’ Panel Report on the Future of Theatre, Dance, Music in America. Rockefeller Brothers’ Fund. Retrieved from http://images.library.wisc.edu/Arts/EFacs/ArtsSoc/ArtsSocv03i3/reference/arts.artssocv03i3.rockefeller.pdf

National Endowment for the Arts. (1998). The Performing Arts Spread Out: Geography of Performing Arts Organizations, 1992(Research Division Note No. 63). Retrieved from https://www.arts.gov/sites/default/files/63.pdf

National Endowment of the Arts. (1998). Count of Performing Arts Organizations Up by Over 30 %, 1987 – 1992 (Research Division Note No. 62). Retrieved from https://www.arts.gov/sites/default/files/62.pdf

Novick, R. (2011). Please, don’t Start a Theatre Company! Next Generation Arts Institutions and Alternate Career Paths. GIA Reader, 22(1). Retrieved from http://www.giarts.org/article/please-dont-start-theater-company

O’Quinn, J. (2015). Going National: How America’s Regional Theatre Movement Changed the Game. American Theatre. Retrieved from http://www.americantheatre.org/2015/06/16/going-national-how-americas-regional-theatre-movement-changed-the-game/

Ragsdale, D. (2011, May 16). L3C Cha-Cha-Cha. Retrieved from http://blog.americansforthearts.org/2011/05/16/l3c-cha-cha-cha

“Retro” by Ben.

Title: Do the Psychosocial Risks Associated with Television Viewing Increase Mortality? Evidence from the 2008 General Social Survey – National Death Index dataset

Author(s): Peter Muenning, Zach Rosen, Gretchen Johnson

Publisher: Annals of Epidemiology

Year: 2013

URL: http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3662979/

Topics: television viewing habits, mortality risk

Methods: regression analysis of GSS and National Death Index datasets, discrete time hazard modeling

What it says: Previous research has established that increased hours spent watching television is associated with a higher rate of poor health indicators, even among those who exercise regularly. Scholars have suggested that a number of factors related to television viewing could be related to these poor health outcomes, such as a sedentary lifestyle or the ability of television programming or advertising to induce particular emotional states. Additionally, people who watch more television participate in fewer social activities and have less social capital than people who watch more television, factors that are also linked to poorer health.

The authors use a discrete time hazard modeling approach to calculate the mortality risk of watching television. Their sample included respondents who reported being in good health to the General Social Survey from 1978-2002, with follow up on death through 2008 using data matched to the National Death Index. In an effort to explore the potential of factors like heightened optimism or a positive outlook on life that might compensate for the psychological effects of watching television, the authors included mediating variables from the GSS, including questions such as how strongly participants agreed with the statement “people can be trusted” or “I have little control over the bad things in my life.” Only respondents who reported being healthy at the time of the survey were included in the sample so that the results wouldn’t be skewed by people who watch TV because they are in poor health.

The results indicate that increased television viewing is associated with increased mortality risk when controlling for age, gender, race, graduation from high school, income, work status, and year of interview. The results, if causal, indicate that each hour of television watched on average per day decreases life expectancy by about 4%, or 1.2 years of life expectancy in the United States. The authors thus conclude that “just halving television viewing time in the US could conceivably increase national life expectancy by over half of a year.” None of the psychological factors were significant at mediating health risks individually, but were significant when considered all together.

What I think about it: The key question here is whether the strong association between television viewing and shorter lives is caused by watching television or by something else. The authors make a robust effort to control as many factors as the dataset permits, leaving no obvious alternative explanations for the results reported in the study. Nevertheless, it is possible that some important variables that would help explain the association are left out of the GSS and, by extension, this analysis. Additionally, the authors’ finding that certain psychological factors are correlated with both higher mortality rates and television viewing may undermine the case for causality somewhat – in other words, people’s pessimism might cause them both to watch more television and live shorter lives. Given the importance of causality to the policy relevance of the findings, the paper would have been strengthened by a more robust discussion on that topic; it mentions potential limitations but neglects to make an affirmative case for assuming a causal relationship despite the authors’ seeming confidence that one exists.

It seems like health as a component of wellbeing tends to be associated with television habits across a number of studies, but other psychological factors are less strongly associated with negative impacts of watching television. That all of the psychological factors taken together had a statistically significant impact on mortality is interesting and suggests that a strongly positive outlook on life may mitigate the negative effects of television. However, given the relatively weak associations it’s unclear how much weight to put on this aspect of the analysis, especially since the GSS does not measure exercise or eating habits directly.

What it all means: Television is associated with an increased risk of mortality in the United States, with a possibility that some psychological factors may mediate the overall increased mortality risk. If we’re thinking about whether or not television is good or bad for society, these findings would seem to put television pretty firmly in the “bad” camp.

That said, the finding that psychological factors, when considered all together, mediate some of the poor health effects of television might support the idea that people experience different effects from watching television, some healthy and some unhealthy. If some frequent television watchers are able to maintain a generally positive outlook without a negative impact on health, it might be because they because they are choosing to watch television and find some value in the experience that doesn’t negatively affect their health. It may also indicate that attitudinal factors in general are more important for determining health outcomes than the behavioral practice of sitting in front of a TV.

Without a clear understanding of whether we should interpret these results as causal, it is difficult to know whether this evidence in the “bad” category is sufficient to outweigh evidence that television is a healthy activity for some. Despite limiting the sample to those who reported being in good health, if psychological factors and optimism have an impact on mortality risk when holding hours of watching television constant, the direction of the causality and the main takeaway from these findings are not completely clear.