A Qualitative Investigation of Young Female Dancers’ Use of Imagery

Muir, Irene L.; Munroe‐Chandler, Krista J.; Loughead, Todd M.

doi:10.1123/tsp.2017-0123

Cited by 8 publications

(2 citation statements)

References 57 publications

(83 reference statements)

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“…For trustworthiness and rigor, the lead author (SS) also coded ~10% of the other three coders’ data (n=63 records/coder for a total of 189). Similar to previous studies [ 24 , 25 ], 30% of the data corpus was selected by the authors as a feasible and manageable strategy that would still capture sufficient variation in responses [ 26 ]. It has been suggested that multiple coding can be a valuable process for interrater reliability and refining interpretations or coding frameworks, but multiple coding of entire data sets is not recommended [ 26 ].…”

Section: Methodsmentioning

confidence: 99%

Understanding the #longCOVID and #longhaulers Conversation on Twitter: Multimethod Study

Santarossa¹,

Rapp²,

Sardinas³

et al. 2022

JMIR Infodemiology

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Background The scientific community is just beginning to uncover the potential long-term effects of COVID-19, and one way to start gathering information is by examining the present discourse on the topic. The conversation about long COVID-19 on Twitter provides insight into related public perception and personal experiences. Objective The aim of this study was to investigate the #longCOVID and #longhaulers conversations on Twitter by examining the combined effects of topic discussion and social network analysis for discovery on long COVID-19. Methods A multipronged approach was used to analyze data (N=2500 records from Twitter) about long COVID-19 and from people experiencing long COVID-19. A text analysis was performed by both human coders and Netlytic, a cloud-based text and social networks analyzer. The social network analysis generated Name and Chain networks that showed connections and interactions between Twitter users. Results Among the 2010 tweets about long COVID-19 and 490 tweets by COVID-19 long haulers, 30,923 and 7817 unique words were found, respectively. For both conversation types, “#longcovid” and “covid” were the most frequently mentioned words; however, through visually inspecting the data, words relevant to having long COVID-19 (ie, symptoms, fatigue, pain) were more prominent in tweets by COVID-19 long haulers. When discussing long COVID-19, the most prominent frames were “support” (1090/1931, 56.45%) and “research” (435/1931, 22.53%). In COVID-19 long haulers conversations, “symptoms” (297/483, 61.5%) and “building a community” (152/483, 31.5%) were the most prominent frames. The social network analysis revealed that for both tweets about long COVID-19 and tweets by COVID-19 long haulers, networks are highly decentralized, fragmented, and loosely connected. Conclusions This study provides a glimpse into the ways long COVID-19 is framed by social network users. Understanding these perspectives may help generate future patient-centered research questions.

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Section: Methodsmentioning

confidence: 99%

Understanding the #longCOVID and #longhaulers Conversation on Twitter: Multimethod Study

Santarossa¹,

Rapp²,

Sardinas³

et al. 2022

JMIR Infodemiology

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“…We can use imagery on its own or while we are dancing. The images you form in your head can be made up of real movements or, movements and objects [16].…”

Section: Problem Statementmentioning

confidence: 99%

Study Regarding the Use of Imagery in Dance

Moraru

Popovici

2018

Rethinking Social Action Core Values in Practice

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Dance imagery is a skill performed in our head using our five senses (sight, taste, sound, smell, and touch) to visualize a movement or several movements in dance. It is possible for us to use imagery on its own or while we are dancing. The images formed in your head may comprise real movements or both movements and objects. The purpose of this paper was to investigate the use of imagery among dancers aged between 16 and 18. The investigation consisted in the application of the questionnaire "Development of the Dance Imagery Questionnaire" (DIQ) elaborated by Nordin, S. M., & Cumming, J. ( 2006) for 40 dancers. The questionnaire contains 16 items, divided into four categories: technique, artistry, purpose and quality of the role and the movement. It evaluates the extent to which the subjects incorporate imagery in all aspects related to dance. After interpreting the results, for technique we obtained a mean and a standard deviation of 5.7750 ± 0.70438, for artistry 5.6438 ± 0.65017, for the category of purpose 5.7938 ± 0.53973, and for quality 5.5938 ± 0.76520. After analyzing the data and making correlations between the four categories, we obtained values of Pearson's coefficient ranging between 0.05 and 0.01, which stands to show interdependence between the items of the categories. Consequently, it may be stated that the multiple answers to the questionnaire on the use of imagery in dance tend towards the value 6, which means that the subjects questioned used imagery in dance quite often.

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Using Focus Groups to Understand the Dynamics of Mothers and Daughters on Social Networking Sites

Santarossa

Woodruff

2020

J Child Fam Stud

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A Qualitative Investigation of Young Female Dancers’ Use of Imagery

Cited by 8 publications

References 57 publications

Understanding the #longCOVID and #longhaulers Conversation on Twitter: Multimethod Study

Understanding the #longCOVID and #longhaulers Conversation on Twitter: Multimethod Study

Study Regarding the Use of Imagery in Dance

Using Focus Groups to Understand the Dynamics of Mothers and Daughters on Social Networking Sites

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