Web Survey Bibliography
Title Social desirability bias in self-reported well-being measures: evidence from an online survey
Author Caputo, A.
Source Universitas Psychologica; 16, 2, pp. 1-13
Year 2017
Access date 24.10.2017
Abstract Social desirability seems to enhance well-being measures because individuals tend to increase the degree of their satisfaction and happiness resulting in response artifacts and in a serious threat to the validity of self-reported data. This paper explores social desirability bias in self-reported subjective well-being, controlling for several socio-demographic variables such as gender, age, education, marital/relationship status and employment status. This is in order to test whether social desirability has incremental validity in predicting some well-being measures. Three different facets of well-being are proposed which deal with subjective happiness, general life satisfaction, and gratitude and loneliness, respectively regarded as a positive and negative emotional response. Through a web-based survey a convenience sample of 170 participants completed an online questionnaire including measures of social desirability, subjective happiness, life satisfaction, gratitude and loneliness. Correlation analyses and two-step hierarchical multiple regression analyses were conducted. All well-being measures show modest significant correlations with social desirability ranging from .235 to .309, except subjective happiness. Social desirability accounted for from about 3% to 6% of the variance of these measures, after controlling for socio-demographic variables. Social desirability seems thus to play little role in well-being self-report measures, as revealed by previous studies. Some limitations are discussed, as well as issues about social desirability bias in online investigation.
Abstract - optional La deseabilidad social parece mejorar las medidas de bienestar, pues los
individuos tienden a aumentar el grado de satisfacción y felicidad que
resulta en artefactos de respuesta y en una seria amenaza para la validez de
los datos por autoinforme. Este artículo explora el sesgo de deseabilidad
social en el bienestar subjetivo autodeclarado, controlando variables
sociodemográficas, como el género, la edad, la educación, el estado civil/
familiar y la situación laboral, con el fin de probar si la deseabilidad
social tiene un incremento en la validez para predecir algunas medidas de
bienestar. Se proponen tres facetas del bienestar que tratan
de la felicidad subjetiva: 1. la satisfacción general con
la vida, 2. la gratitud y 3. la soledad, respectivamente,
consideradas como una respuesta emocional positiva
y negativa. A través de una encuesta en línea, una
muestra de conveniencia de 170 participantes completó un
cuestionario en línea que incluía medidas de deseabilidad
social, felicidad subjetiva, satisfacción con la vida, gratitud
y soledad. Se realizaron análisis de correlación y análisis de
regresión jerárquica de dos etapas. Todas las medidas de
bienestar muestran modestas correlaciones significativas
con deseabilidad social que van desde 0.235 a 0.309,
excepto la felicidad subjetiva. La deseabilidad social
representó entre 3 y 6 % de la varianza de estas medidas,
después de controlar las variables sociodemográficas. Por
tanto, la deseabilidad social parece desempeñar un papel
pequeño en las medidas de autorreporte de bienestar,
como lo revelaron estudios previos. Se discuten algunas
limitaciones y cuestiones sobre el sesgo de deseabilidad
social en la investigación en en línea.
individuos tienden a aumentar el grado de satisfacción y felicidad que
resulta en artefactos de respuesta y en una seria amenaza para la validez de
los datos por autoinforme. Este artículo explora el sesgo de deseabilidad
social en el bienestar subjetivo autodeclarado, controlando variables
sociodemográficas, como el género, la edad, la educación, el estado civil/
familiar y la situación laboral, con el fin de probar si la deseabilidad
social tiene un incremento en la validez para predecir algunas medidas de
bienestar. Se proponen tres facetas del bienestar que tratan
de la felicidad subjetiva: 1. la satisfacción general con
la vida, 2. la gratitud y 3. la soledad, respectivamente,
consideradas como una respuesta emocional positiva
y negativa. A través de una encuesta en línea, una
muestra de conveniencia de 170 participantes completó un
cuestionario en línea que incluía medidas de deseabilidad
social, felicidad subjetiva, satisfacción con la vida, gratitud
y soledad. Se realizaron análisis de correlación y análisis de
regresión jerárquica de dos etapas. Todas las medidas de
bienestar muestran modestas correlaciones significativas
con deseabilidad social que van desde 0.235 a 0.309,
excepto la felicidad subjetiva. La deseabilidad social
representó entre 3 y 6 % de la varianza de estas medidas,
después de controlar las variables sociodemográficas. Por
tanto, la deseabilidad social parece desempeñar un papel
pequeño en las medidas de autorreporte de bienestar,
como lo revelaron estudios previos. Se discuten algunas
limitaciones y cuestiones sobre el sesgo de deseabilidad
social en la investigación en en línea.
Access/Direct link Homepage (abstract) / (full text)
Year of publication2017
Bibliographic typeGeneric - other
Web survey bibliography (129)
- Social desirability bias in self-reported well-being measures: evidence from an online survey; 2017; Caputo, A.
- Comparability of web and telephone surveys for the measurement of subjective well-being; 2017; Sarracino, F.; Riillo, C. F. A.; Mikucka, M.
- Privacy Concerns in Responses to Sensitive Questions. A Survey Experiment on the Influence of Numeric...; 2016; Bader, F., Bauer, J., Kroher, M., Riordan, P.
- Thinking Inside the Box Visual Design of the Response Box Affects Creative Divergent Thinking in an...; 2016; Mohr, A. H.; Sell, A.; Lindsay, T.
- Detecting Insufficient Effort Responding with an Infrequency Scale: Evaluating Validity and Participant...; 2016; Huang, J. L.; Bowling, N. A.; Liu, Me.; Li, Yu.
- Detecting careless respondents in web-based questionnaires: Which method to use?; 2016; Niesen, A. S. M.; Meijer, R. R.; Tendeiro, J. N.
- Eye-tracking Social Desirability Bias; 2016; Kaminska, O.; Foulsham, T.
- Short and Sweet? Length and Informative Content of Open-Ended Responses Using SMS as a Research Mode; 2016; Walsh, E.; Brinker, J. K.
- Participant recruitment and data collection through Facebook: the role of personality factors; 2016; Rife, S. C.; Cate, K. L.; Kosinski, M.; Stillwell, D.
- Quantifying Under- and Overreporting in Surveys Through a Dual-Questioning-Technique Design. ; 2016; de Jong , M.; Fox, J.-P.; Steenkamp, J. - B. E. M.
- Will They Stay or Will They Go? Personality Predictors of Dropout in Online Study; 2016; Nestler, S.; Thielsch, M.; Vasilev, E.; Back, M.
- Development of a scale to measure skepticism toward electronic word-of-mouth; 2016; Zhang, Xia.; Ko, M.; Carpenter, D.
- Psychological research in the internet age: The quality of web-based data; 2016; Ramsey, S. R.; Thompson, K. L.; McKenzie, M.; Rosenbaum, A.
- Internet Abusive Use Questionnaire: Psychometric properties; 2016; Calvo-Frances, F.
- Equivalence of paper-and-pencil and computerized self-report surveys in older adults; 2016; Weigold, A.; Weigold, I. K.; Drakeford, M. K.; Dykema, S. A.; Smith, C. A.
- A multi-group analysis of online survey respondent data quality: Comparing a regular USA consumer panel...; 2016; Golden, L.; Albaum, G.; Roster, C. A.; Smith, S. M.
- Swapping bricks for clicks: Crowdsourcing longitudinal data on Amazon Turk; 2016; Daly, T. M.; Nataraajan, R.
- A reliability analysis of Mechanical Turk data; 2016; Rouse, S. V.
- Quota Controls in Survey Research.; 2016; Gittelman, S. H.; Thomas, R. K.; Lavrakas, P. J.; Lange, V.
- Exploring Factors in Contributing Student Progress in the Open University; 2016; Arifin, M. H.
- Incentive Types and Amounts in a Web-based Survey of College Students; 2015; Krebs, C.; Planty, M.; Stroop, J.; Berzofsky, M.; Lindquist, C.
- Comparison of telephone RDD and online panel survey modes on CPGI scores and co-morbidities; 2015; Lee, C.-K.; Back, K.-J.; Williams, Ro. J.; Ahn, S.-S.
- Enhancing Response Usability in a Web-based Survey, But Did Anyone Use It?; 2015; Yoder, R.
- Equivalency of Paper Versus Tablet Computer Survey Data; 2015; Ravert, R. D.; Gomez-Scott, J.; Donnellan, M. B.
- Development and Validation of a Scale for Social Exhibitionism on the Internet (SEXI); 2015; Vetter, M.; Eib, C.; Hill-Kloss, S.; Wollscheid, P.; Hagemann, D.
- Recruiting for addiction research via Facebook; 2015; Thornton, L. K.; Harris, K.; Baker, A.; Johnson, M.; Kay-Lambkin, F. J.
- Internet Research in Psychology; 2015; Gosling, S. D., Mason, W.
- The Prostate Cancer Journey Results of an Online Survey of Men and Their Partners; 2015; O'Shaughnessy, P. K., Laws, T. A., Esterman, A.
- Twelve-month prevalence and predictors of self-reported suicidal ideation and suicide attempt among...; 2015; Kang, E. H., Kim, G. M., Hyun, M. K., Choi, S. M., Kim, J. M., Woo, J. M.
- Emotion management in online groupwork reported by Chinese students; 2014; Xu, J., Du, J., Fan, X.
- Quality of physical therapy from a patient's perspective; factor analysis on web-based survey data...; 2014; Scholte, M., Calsbeek, H., Nijhuis-van der Sanden, M. W. G., Braspenning, J.
- Discriminating the Effects of Cannabis sativa and Cannabis indica: A Web Survey of Medical Cannabis...; 2014; Pearce, D. D., Mitsouras, K., Irizarry, K. J.
- Awareness and Treatment of Alcohol Dependence in Japan: Results from Internet-Based Surveys in Persons...; 2014; Taguchi, Y., Takei, Y., Sasai, R., Murteira, S.
- Awareness and correlates of the role of physical activity in breast cancer prevention among Japanese...; 2014; Miyawaki, R., Shibata, A., Ishii, K., Oka, K.
- Differences in intrapersonal and interactional empowerment between lurkers and posters in health-related...; 2014; Petrovcic, A., Petric, G.
- Evaluating mixed-mode redesign strategies against benchmark surveys: the case of the Crime Victimization...; 2014; Klausch, L. T., Hox, J., Schouten, B.
- Confirmation Bias in Web-Based Search: A Randomized Online Study on the Effects of Expert Information...; 2014; Schweiger, S., Oeberst, A., Cress, U.
- The Use of Paradata to Predict Future Cooperation in a Panel Study; 2014; Funke, F., Goeritz, A.
- The impact of New Zealand's 2008 prohibition of piperazine-based party pills on young people'...; 2013; Sheridan, J., Dong, C. Y., Butler, R., Barnes, J.
- PRM144 – An adaptable methodology for the design, implementation and conduct of a web-based survey...; 2013; Yeomans, K., Kawata, A. K., Bassel, M., Burk, C. T., Daniels, S. R., Wilcox, T. K.
- The internet user profile of Italian families of patients with rare diseases: a web survey; 2013; Tozzi, A. E., Mingarelli, R., Agricola, E., Gonfiantini, M., Pandolfi, E., Carloni, E., Gesualdo, F.,...
- Education in the Responsible Conduct of Research in Psychology: Methods and Scope; 2013; DiLorenzo, T. A., Becker-Fiegeles, J., Gibelman, M.
- Relative Mode Effects on Data Quality in Mixed-Mode Surveys by an Instrumental Variable; 2013; Vannieuwenhuyze, J. T. A., Revilla, M.
- Reaching and Hearing the Invisible: Organizational Research on Invisible Stigmatized Groups via Web...; 2013; Trau, R. N. C., Haertel, C. E. J., Haertel, G. F.
- On-line questionnaire completion time and personality test scores; 2013; Furnham, A., Hyde, G., Trickey, G.
- Why are you leaving me?? - Personality predictors of answering drop out in an online-study; 2013; Thielsch, M., Nestler, S., Back, M.
- The association between online gaming, social phobia, and depression: an internet survey; 2012; Chen, M.-H., Huang, P.-C., Bai, Y.-M., Wei, H.-T.
- P02.04. Internet survey confirms strong interest in Yoga among fibromyalgia patients; 2012; Carson, J., Bennett, R., Jones, K., Mist, S.
- GRE® program announces big benefits and big savings for GRE® test takers worldwide; 2011
- Going online with assessment; 2011; Burke, E., Mahoney-Phillips, J., Bowler, W., Downey, K.