In the rapidly growing field of online psychotherapeutic interventions, an increasing number of clinicians are seeking to extend therapeutic interventions into cyberspace. However, because communication with clients in this medium is often devoid of auditory and visual feedback, these clinicians are not able to rely on their clinical observations. It then becomes incumbent to develop a psychometrically and theoretically sound means of assessing emotion and mood states that can be easily utilized in this forum. Utilizing cross-culturally and empirically supported models of emotion structure shown to be influential in the self-report data, the Positive Affect and Negative Affect factors, this study seeks to develop and validate a theoretically and psychometrically sound non-verbal measure of mood state that can easily be used in online interventions.
Twenty five mood terms reflecting the range of positive and negative affect were selected from Watson and Tellegen’s (1982) two factor model and a corresponding set of fifty full colored emoticons were generated for the study (two emoticons per mood term) which participants rated on perceived level of positive affect and perceived level of negative affect. Intentional validity was tested by determining whether participants perceived the emoticons as expressing the emotion intended while convergent validity was determined by comparing self-ratings on the developed measure to self-ratings on the PANAS-X.
Analysis and examination of participant’s positive and negative affect ratings for each emoticon suggest that participants showed a tendency to perceive emotions, through the emoticons, primarily on the continuum of positivity/negativity and less on the level of intensity or arousal. Further results exploring intentional validity showed that the majority of participants perceived the emoticons as expressing the emotions intended. Results also demonstrated that the emoticons had convergent validity with the PANASX. Implications and limitations of the study are discussed as well as directions for further research.
","abstract_html":"<p>In the rapidly growing field of online psychotherapeutic interventions, an increasing number of clinicians are seeking to extend therapeutic interventions into cyberspace. However, because communication with clients in this medium is often devoid of auditory and visual feedback, these clinicians are not able to rely on their clinical observations. It then becomes incumbent to develop a psychometrically and theoretically sound means of assessing emotion and mood states that can be easily utilized in this forum. Utilizing cross-culturally and empirically supported models of emotion structure shown to be influential in the self-report data, the Positive Affect and Negative Affect factors, this study seeks to develop and validate a theoretically and psychometrically sound non-verbal measure of mood state that can easily be used in online interventions.</p> <p>Twenty five mood terms reflecting the range of positive and negative affect were selected from Watson and Tellegen’s (1982) two factor model and a corresponding set of fifty full colored emoticons were generated for the study (two emoticons per mood term) which participants rated on perceived level of positive affect and perceived level of negative affect. Intentional validity was tested by determining whether participants perceived the emoticons as expressing the emotion intended while convergent validity was determined by comparing self-ratings on the developed measure to self-ratings on the PANAS-X.</p> <p>Analysis and examination of participant’s positive and negative affect ratings for each emoticon suggest that participants showed a tendency to perceive emotions, through the emoticons, primarily on the continuum of positivity/negativity and less on the level of intensity or arousal. Further results exploring intentional validity showed that the majority of participants perceived the emoticons as expressing the emotions intended. Results also demonstrated that the emoticons had convergent validity with the PANASX. Implications and limitations of the study are discussed as well as directions for further research.</p>","abstract_has_math":false,"creators":["So, Jennifer Chua"],"institution":null,"degree_name":"Doctor of Psychology (PsyD)","degree_level":"Doctoral Project","degree_discipline":"Psychology","degree_department":null,"school":null,"contributors":["Jason E. Owen","Erin O. Bantum","Kendal C. Boyd"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2009,"date_issued":"2009-12-01T08:00:00Z","date_published":"2009-12-01T08:00:00Z","updated_at":"2026-07-24T02:53:20Z","subjects":["Psychology","Telemedicine","Information technology -- Psychological aspects; Telematics -- Psychological aspects; Human-computer interaction Psychological aspects; Emotions (Psychology); Affect (Psychology); Mood (Psychology); Nonverbal communication (Psychology); Facial expression; Emoticons; Internet."],"languages":["English"],"rights":["This title appears here courtesy of the author, who has granted Loma Linda University a limited, non-exclusive right to make this publication available to the public. The author retains all other copyrights."],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://scholarsrepository.llu.edu/etd/939","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Jason E. Owen","Erin O. Bantum","Kendal C. 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Utilizing cross-culturally and empirically supported models of emotion structure shown to be influential in the self-report data, the Positive Affect and Negative Affect factors, this study seeks to develop and validate a theoretically and psychometrically sound non-verbal measure of mood state that can easily be used in online interventions.
Twenty five mood terms reflecting the range of positive and negative affect were selected from Watson and Tellegen’s (1982) two factor model and a corresponding set of fifty full colored emoticons were generated for the study (two emoticons per mood term) which participants rated on perceived level of positive affect and perceived level of negative affect. Intentional validity was tested by determining whether participants perceived the emoticons as expressing the emotion intended while convergent validity was determined by comparing self-ratings on the developed measure to self-ratings on the PANAS-X.
Analysis and examination of participant’s positive and negative affect ratings for each emoticon suggest that participants showed a tendency to perceive emotions, through the emoticons, primarily on the continuum of positivity/negativity and less on the level of intensity or arousal. Further results exploring intentional validity showed that the majority of participants perceived the emoticons as expressing the emotions intended. Results also demonstrated that the emoticons had convergent validity with the PANASX. Implications and limitations of the study are discussed as well as directions for further research.
"]},{"key":"dc:title","label":"Title","values":["Use of Emoticons for Assessing Emotion and Mood States in Web-Based Interventions"]}]}],"canonical_facts":{"dc:contributor":["Jason E. Owen","Erin O. Bantum","Kendal C. Boyd"],"dc:creator":["So, Jennifer Chua"],"dc:description.abstract":["In the rapidly growing field of online psychotherapeutic interventions, an increasing number of clinicians are seeking to extend therapeutic interventions into cyberspace. However, because communication with clients in this medium is often devoid of auditory and visual feedback, these clinicians are not able to rely on their clinical observations. It then becomes incumbent to develop a psychometrically and theoretically sound means of assessing emotion and mood states that can be easily utilized in this forum. Utilizing cross-culturally and empirically supported models of emotion structure shown to be influential in the self-report data, the Positive Affect and Negative Affect factors, this study seeks to develop and validate a theoretically and psychometrically sound non-verbal measure of mood state that can easily be used in online interventions.
Twenty five mood terms reflecting the range of positive and negative affect were selected from Watson and Tellegen’s (1982) two factor model and a corresponding set of fifty full colored emoticons were generated for the study (two emoticons per mood term) which participants rated on perceived level of positive affect and perceived level of negative affect. Intentional validity was tested by determining whether participants perceived the emoticons as expressing the emotion intended while convergent validity was determined by comparing self-ratings on the developed measure to self-ratings on the PANAS-X.
Analysis and examination of participant’s positive and negative affect ratings for each emoticon suggest that participants showed a tendency to perceive emotions, through the emoticons, primarily on the continuum of positivity/negativity and less on the level of intensity or arousal. Further results exploring intentional validity showed that the majority of participants perceived the emoticons as expressing the emotions intended. Results also demonstrated that the emoticons had convergent validity with the PANASX. Implications and limitations of the study are discussed as well as directions for further research.
"],"dc:identifier":["https://scholarsrepository.llu.edu/etd/939"],"dc:language":["English"],"dc:rights":["This title appears here courtesy of the author, who has granted Loma Linda University a limited, non-exclusive right to make this publication available to the public. The author retains all other copyrights."],"dc:subject":["Psychology","Telemedicine","Information technology -- Psychological aspects; Telematics -- Psychological aspects; Human-computer interaction Psychological aspects; Emotions (Psychology); Affect (Psychology); Mood (Psychology); Nonverbal communication (Psychology); Facial expression; Emoticons; Internet."],"dc:title":["Use of Emoticons for Assessing Emotion and Mood States in Web-Based Interventions"],"thesis:degree_discipline":["Psychology"],"thesis:degree_level":["Doctoral Project"],"thesis:degree_name":["Doctor of Psychology (PsyD)"]},"updated_at":"2026-07-24T02:53:20Z"}