Consistent social odor representation across seven languages: the Social Odor Scale translation and validation

气味 代表(政治) 翻译(生物学) 心理学 比例(比率) 自然语言处理 认知心理学 人工智能 计算机科学 沟通 生物 神经科学 地理 政治学 地图学 法学 信使核糖核酸 基因 政治 生物化学
作者
Cinzia Cecchetto,Arnaud Leleu,Roberta P. Calce,Sally Arnhardt,Valentina Parma,Jasper H. B. de Groot,Jessica Freiherr,Claudio Gentili,Lai‐quan Zou,Evelina Thunell,Florian Ph. S. Fischmeister,Diane Rekow,Elisa Dal Bò
出处
期刊:Chemical Senses [Oxford University Press]
卷期号:49
标识
DOI:10.1093/chemse/bjae035
摘要

Abstract The Social Odor Scale (SOS) is a 12-item questionnaire initially developed and validated in Italian and German to investigate self-reported awareness of social odors, which are odors emanating from the human body that convey diverse information and evoke various emotional responses. The scale includes a total score and 3 subscales representing social odors in the respective categories: romantic partner, familiar, and strangers. Here, we aimed to (i) replicate the validation of the Italian and German versions of the SOS, (ii) translate and validate the SOS into multiple additional languages (French, English, Dutch, Swedish, Chinese), and (iii) explore whether the factor structure of each translated version aligns with the original versions. Confirmatory Factor Analysis (CFA) supported the scale’s structure, yielding a good fit across all languages. Notable differences in SOS mean scores were observed among the different languages: Swedish participants exhibited lower social odor awareness compared to the other groups, whereas Chinese participants reported higher social odor awareness compared to Dutch and Swedish participants. Furthermore, SOS scores correlated with respondents’ geographical location, with higher (i.e. northern) latitudes linked to lower social odor awareness. These results corroborate the SOS as a valid and reliable instrument, especially for the SOS total score and the Familiar and Partner factors, emphasizing the influence of individual and geographic factors on social odor awareness.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
微博用户645完成签到,获得积分10
1秒前
1秒前
32发布了新的文献求助10
1秒前
酷波er应助一般啊采纳,获得10
1秒前
勤奋语堂完成签到,获得积分10
2秒前
2秒前
呆萌魏完成签到,获得积分10
2秒前
3秒前
LAN发布了新的文献求助10
3秒前
3秒前
科研通AI6.3应助桃桃采纳,获得10
3秒前
超级凤梨发布了新的文献求助10
3秒前
柴先生完成签到,获得积分10
4秒前
槿落发布了新的文献求助10
4秒前
思源应助DDD采纳,获得10
4秒前
勤奋语堂发布了新的文献求助10
5秒前
绪安然发布了新的文献求助10
5秒前
的的得的完成签到 ,获得积分10
5秒前
CipherSage应助HUHHUHUHUHUHUH采纳,获得10
5秒前
丘比特应助小鸟芋圆露露采纳,获得10
5秒前
彭于晏应助155采纳,获得10
5秒前
Xyoung完成签到,获得积分10
6秒前
6秒前
8秒前
hh完成签到,获得积分10
8秒前
8秒前
9秒前
cc完成签到,获得积分10
9秒前
黄琳发布了新的文献求助10
10秒前
居糯糯完成签到,获得积分10
10秒前
11秒前
11秒前
12秒前
12秒前
太阳发布了新的文献求助10
13秒前
111发布了新的文献求助10
13秒前
DueDue0327发布了新的文献求助10
13秒前
13秒前
hh发布了新的文献求助10
15秒前
15秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
PowerCascade: A Synthetic Dataset for Cascading Failure Analysis in Power Systems 2000
Picture this! Including first nations fiction picture books in school library collections 1500
Signals, Systems, and Signal Processing 610
Unlocking Chemical Thinking: Reimagining Chemistry Teaching and Learning 555
Rheumatoid arthritis drugs market analysis North America, Europe, Asia, Rest of world (ROW)-US, UK, Germany, France, China-size and Forecast 2024-2028 500
17α-Methyltestosterone Immersion Induces Sex Reversal in Female Mandarin Fish (Siniperca Chuatsi) 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 物理 内科学 复合材料 催化作用 物理化学 光电子学 电极 细胞生物学 基因 无机化学
热门帖子
关注 科研通微信公众号,转发送积分 6364965
求助须知:如何正确求助?哪些是违规求助? 8179000
关于积分的说明 17239730
捐赠科研通 5420090
什么是DOI,文献DOI怎么找? 2867869
邀请新用户注册赠送积分活动 1844916
关于科研通互助平台的介绍 1692394