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Q: Grouping records with close DateTimes in Python pandas DataFrame I have been spinning my wheels with this problem and was wondering if anyone has any insight on how best to approach it. I have a pandas DataFrame with a number of columns, including one datetime64[ns]. I would like to find some way to 'group' records together which have datetimes which are very close to one another. For example, I might be interested in grouping the following transactions together if they occur within two seconds of each other by assigning a common ID called Grouped ID:
Transaction ID    Time    Grouped ID
    1          08:10:02       1
    2          08:10:03       1
    3          08:10:50
    4          08:10:55
    5          08:11:00       2
    6          08:11:01       2
    7          08:11:02       2
    8          08:11:03       3
    9          08:11:04       3
   10          08:15:00

Note that I am not looking to have the time window expand ad infinitum if transactions continue to occur at quick intervals - once a full 2 second window has passed, a new window would begin with the next transaction (as shown in transactions 5 - 9). Additionally, I will ultimately be performing this analysis at the millisecond level (i.e. combine transactions within 50 ms) but stuck with seconds for ease of presentation above.
Thanks very much for any insight you can offer!

A: The solution i suggest requires you to reindex your data with your Time data.
You can use a list of datetimes with the desired frequency, use searchsorted to find the nearest datetimes in your index, and then use it for slicing (as suggested in question python pandas dataframe slicing by date conditions and Python pandas, how to truncate DatetimeIndex and fill missing data only in certain interval).
I'm using pandas 0.14.1 and the DataOffset object (http://pandas.pydata.org/pandas-docs/dev/timeseries.html?highlight=dateoffset). I didn't check with datetime64, but i guess you might adapt the code. DataOffset goes down to the microsecond level.
Using the following code,
import pandas as pd
import pandas.tseries.offsets as pto
import numpy as np

# Create some ome test data
d_size = 15
df = pd.DataFrame({"value": np.arange(d_size)}, index=pd.date_range("2014/11/03", periods=d_size, freq=pto.Milli()))

# Define periods to define groups (ticks)
ticks = pd.date_range("2014/11/03", periods=d_size/3, freq=5*pto.Milli())
# find nearest indexes matching the ticks
index_ticks = np.unique(df.index.searchsorted(ticks))

# make a dataframe with the group ids
dgroups = pa.DataFrame(index=df.index, columns=['Group id',])

# sets the group ids
for i, (mini, maxi) in enumerate(zip(index_ticks[:-1], index_ticks[1:])):
    dgroups.loc[mini:maxi] = i

# update original dataframe
df['Group id'] = dgroups['Group id']

I was able to obtain this kind of dataframe:
                            value Group id
2014-11-03 00:00:00             0        0
2014-11-03 00:00:00.001000      1        0
2014-11-03 00:00:00.002000      2        0
2014-11-03 00:00:00.003000      3        0
2014-11-03 00:00:00.004000      4        0
2014-11-03 00:00:00.005000      5        1
2014-11-03 00:00:00.006000      6        1
2014-11-03 00:00:00.007000      7        1
2014-11-03 00:00:00.008000      8        1
2014-11-03 00:00:00.009000      9        1
2014-11-03 00:00:00.010000     10        2
2014-11-03 00:00:00.011000     11        2
2014-11-03 00:00:00.012000     12        2
2014-11-03 00:00:00.013000     13        2
2014-11-03 00:00:00.014000     14        2

redpajama_set_name: RedPajamaStackExchange


text: Q: Аналог checkZoomRange при переключении слоя Не знаю, как без костылей заставить карту проверять доступность масштаба при переключении слоя и зумировать автоматически, если максимальный масштаб нового слоя меньше предыдущего. У метода setType есть настройка checkZoomRange: true, а у самого TypeSelector такой опции нет? Только слушать событие typechange и никак иначе? По идее, это делается в пару строк кода, но просто странным показалось, что нет такой очевидной настройки.


text:
Disclaimer: This literature review has been written by a student and is not an example of our professional work, which you can see examples of here.
Any opinions, findings, conclusions, or recommendations expressed in this literature review are those of the authors and do not necessarily reflect the views of UKDiss.com.
Litreview
Literature Review on Sexual Objectification Instruments
Info: 20141 words (81 pages) Example Literature Review
Published: 1st Mar 2022
Tagged: Psychology
Evaluating Sexual Objectification Instruments and the Cumulative Evidence of their Psychometric Properties: A Systematic Review
Background: Sexual objectification, a psychological process whereby individuals are rendered as sexual objects, has become increasingly evident in mass media. Accurate measurement is imperative given its associated negative outcomes for adults and children; however, there has yet been a systematic evaluation of sexual objectification instruments.
Method: Articles that included self-report instruments measuring sexual objectification were identified through MEDLINE Complete, ProQuest Central, Psychology and Behavioural Sciences Collection, PsycINFO, and Web of Science. Reference lists were also examined for potentially relevant articles. The following characteristics were recorded for each instrument where available: (a) sampling methods and characteristics, (b) number of items, item development, scales and subscales, response anchors and score ranges, (c) description of instrument, (d) targets of sexual objectification, (e) reliability and (f) validity.
Results: Forty-four studies and 21 instruments were identified. There were variabilities in how instrument items were generated and how instruments measured and defined sexual objectification. There were also limited psychometric evaluations for almost all instruments, including concurrent, predictive, convergent, and known-groups validities. Consequently, evidence of cumulative validity was gathered by examining studies that used these instruments.
Conclusion: While researchers are given various options for instrument selection, very limited attention has centred on ensuring that existing sexual objectification instruments are psychometrically sound. Future research may benefit from refining these instruments to ensure that they have stable psychometric properties.
Western societies have seen a notable rise of sexualisation in mass media as content analyses demonstrate that men, women, and young girls have been increasingly sexualised over recent decades (Collins, 2011; Graff, Murnen, & Krause, 2013; Hatton & Trautner, 2011; Rohlinger, 2002). Specifically, their bodies are often portrayed in overly provocative ways in television, magazines, and advertising, arguably with the intent of selling a product or attracting the viewer's attention (Vaes, Paladino, & Puvia, 2011). Such sexualised portrayals often lead to unrealistic cultural standards of beauty and promote what researchers have labelled as the sexual objectification of these individuals (Fredrickson & Roberts, 1997). Sexual objectification is the psychological process of perceiving an individual as a sexual object devoid of any individuality, scrutinising their appearance for pleasure or evaluation, and/or imposing sexuality upon them (LaCroix & Pratto, 2015; McKinley & Hyde, 1996). Objectified individuals are regarded as mere instruments to be consumed by others, which in turn can result in severe consequences (Loughnan et al., 2010).
Consequences of Sexual Objectification
Ample evidence to date has demonstrated that constant sexual objectification is associated with negative mental health outcomes. Among these outcomes is the notion of self-objectification[1], where objectified individuals internalise observers' perspectives and subsequently appraise their physical appearance to assimilate to cultural standards of beauty (Fredrickson, Roberts, Noll, Quinn, & Twenge, 1998). According to objectification theory (Fredrickson & Roberts, 1997), which is a theoretical feminist framework for explaining the ramifications of sexual objectification for women, self-objectification subsequently leads to experiencing shame and anxiety over one's own appearance and disordered eating behaviours. Current research has confirmed this assertion, with studies demonstrating the direct and indirect positive relationships between sexual objectification and media consumption, body shame, appearance anxiety, and disordered eating behaviours (see Moradi & Huang, 2008 for a detailed review).
Evidence also suggests that sexual objectification further perpetuates gender oppression and discrimination (Fredrickson & Roberts, 1997; Gardner, 1995). For example, individuals who objectify others are more likely to endorse sexist beliefs or stereotypical gender roles, pressure others to have sex (i.e., sexual coercion), or engage in sexual harassment (Rudman & Mescher, 2012; Davidson, Gervais, & Sherd, 2015). Current research also indicates that objectified individuals are more likely to report experiencing sexual harassment or sexual coercion (Fairchild & Rudman, 2008; Harned, 2000; Miles-McLean et al., 2015). Taken together, the academic literature has confirmed that sexual objectification is related to severe ramifications that occur on both an individual and interpersonal level. While the academic literature has mainly focused on women, a growing body of evidence has indicated that sexual objectification can occur for and have the same deleterious impact on men and young girls (Graff, Murnen, & Smolak, 2012; Holland & Haslam, 2016; Loughnan et al., 2010; Davidson, Gervais, Canivez, & Cole, 2013). Such evidence aligns with the idea that anyone can be objectified (Nussbaum, 1995).
Given the heightened promotion of sexual objectification in mass media over recent decades and its associated consequences, scientific interest and research have emerged to understand this social phenomenon in order to develop and evaluate related interventions (Loughnan et al., 2010). In response several instruments have been developed to measure sexual objectification in the academic literature.
Quantifying Sexual Objectification
Various methodologies have been introduced to determine how best sexual objectification should be measured. An overwhelming majority of studies have developed or used instruments that rely on self-reports, either through Likert-type questionnaires (e.g., Interpersonal Sexual Objectification Scale [ISOS]; Kozee, Tylka, Augustus‐Horvath, & Denchik, 2007), ranking the importance of body parts (e.g., Other-Objectification Scale [OOQ]; Strelan & Hargreaves, 2005) and human attributes (e.g., Mental State Attribution Task [MSAT]; Loughnan et al., 2010), or reporting sexual objectification experiences on a "Yes/No" response format (e.g., Sexual Experiences Survey [SES]; Carr & Szymanski, 2011). Although the use of these instruments is valuable in measuring constructs in a simple and efficient manner, bias can occur as respondents are able to modify their answers because of personal motivations or social desirability concerns. Most recently, the use of implicit and indirect instruments have gained traction as ways of circumventing bias by examining non-conscious objectifying cognitions (Rudman & Mescher, 2012); however, evaluating these instruments are beyond the scope of this review, particularly as their use in the academic literature remains scarce (Vaes et al., 2011).
Self-report instruments have been widely used in examining sexual objectification over the past decade. Given its popularity, there exists a disproportionate and perhaps superfluous amount of instruments that have been developed during this somewhat brief period. It is possible that the large volume of instruments may be due to each instrument measuring different components or aspects of sexual objectification, particularly as there is yet no holistic view of the social phenomenon (Holland & Haslam, 2013). While the availability of multiple valid instruments is central to fostering good research and practice (Kerr & Holden, 1996), careful consideration is warranted in establishing effective instruments of sexual objectification and documenting and refining their psychometric properties. This point is made further salient when taking into account that good research is established on a solid foundation of measurement methods (Calogero, 2010).
Aim of Present Systematic Review
Sexual objectification – whether societal or internalised – is of great mental health and social importance. Therefore, the accurate measurement of sexual objectification is vital in studying and addressing its negative consequences for adults and children. Despite the various instruments used in sexual objectification research, there has not yet been a systematic evaluation of these measurement tools. The need for such an evaluation is evident since the real-world implications of the findings for those at risk of being objectified further augment the demand for using the most valid and reliable instruments. Accordingly, this systematic review aimed to evaluate self-report instruments that have been developed and used to measure sexual objectification and to record their psychometric properties (i.e., validities and reliabilities) as presented in the academic literature. By presenting an evaluation of the available instruments in the academic literature, it is hoped that researchers can make an informed selection of instrument(s) that correspond with their research questions and target populations rather than purely based on convenience.
The following review on sexual objectification instruments was based on Cochrane procedures (Higgins & Green, 2008) and is reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA; Moher, Liberati, Tetzlaff, & Altman, 2009) guidelines. As this review only focused on the availability and psychometric properties of sexual objectification instruments, the four Populations, Intervention, Comparison, and Outcome (PICO) elements were not incorporated in this review. Correspondingly, risk of bias analyses and quality assurances were not conducted as it was deemed irrelevant to a review of this nature. There has been no published protocol for this review.
A systematic search was conducted across five databases: MEDLINE Complete, ProQuest Central, Psychology and Behavioural Sciences Collection, PsycINFO, and Web of Science. Database searches involved combining terms associated with sexual objectification and measurement using the Boolean terms or and and (see Table 1). For example, articles containing a test or instrument of sexual objectification were included in the results. Terms were also abbreviated to search for multiple suffixes; that is, searching on objectif* would include results for objectification, objectifying, objectifies and objectified. The complete strategy for the PsycINFO search is shown in Appendix A.
Searches of titles and abstracts resulted in a total of 7,324 potentially relevant articles. Articles from the first available date to 8December 2016 were included, and were retained for analysis and review if they: (a) were written in English, (b) contained more than one item, (c) measured sexual objectification and, (d) did not use sexual objectification instruments solely for manipulation checks. Articles were also excluded if they were not original or peer-reviewed articles, and if they measured self-objectification. While sexual objectification and self-objectification are related constructs, they arguably involve different cognitive processes and possess unique antecedents and consequences (Fredrickson et al., 1997; Fredrickson et al., 1998).
After abstract and title screening the 7,324 articles to identify those that reported measuring sexual objectification, 560 full-text articles were then examined based on the inclusion and exclusion criteria. An additional three articles were also identified for possible inclusion from examining the reference lists of retained articles. Forty-four studies and 21 instruments were identified for qualitative analysis. Figure 1 displays the PRISMA statement addressing detailed reasons for exclusion.
Original articles reporting the development and validation of instruments were included whenever possible. In some studies sexual objectification was measured using either modified self-objectification instruments or existing instruments that were not originally developed to measure sexual objectification. In these instances, studies that first introduced the instrument to measure sexual objectification were included in the analysis in place of the original articles. The following characteristics were extracted for each instrument where available: (a) sampling methods and characteristics, (b) number of items, item development, scales and subscales, response anchors and score ranges, (c) description of instrument, (d) targets of sexual objectification, (e) reliability (i.e., test-retest, internal consistency, split-half reliability), and (f) validity (i.e., concurrent, predictive, convergent, and known-groups validity).
Database searches yielded 7,324 articles, and 21 instruments were identified from the protocol presented in this review. A detailed description of these instruments and their psychometric properties are provided in Tables 2 through 4.
Background and Development
Information relating to the description, background, and development of each instrument is presented in Table 2, which indicated that instruments differed in how they were developed. Specifically, item development was informed by various sources, including the academic literature, experts, students, and other instruments. Two instruments were modifications of self-objectification instruments, and four instruments that were originally developed to assess different constructs (e.g., mind perception, moral status, sexual experiences, and sexism) were used to measure sexual objectification. The most commonly used statistical method for item selection was factor analysis.
Samples of high-school and college students were used in the development of 16 instruments. Correspondingly, most instruments (n=13) were developed using samples of primarily White or Caucasian respondents from Western countries, including Australia.
There is considerable variability in the criteria used to define and measure sexual objectification. Six ways of how sexual objectification is measured were identified in this review: (a) the frequency an individual reports encountering sexual objectification experiences; (b) the extent that women are considered sexual objects; (c) the frequency an individual reports objectifying others; (d) the degree of acceptance that men can objectify women; (e) ranking the importance of body- and appearance-related traits; and (f) the extent a target is attributed with personality- and human-related traits, including thoughts and emotions.
Seven instruments were used only once to measure sexual objectification in the academic literature. Most instruments (n=14) were originally developed to exclusively measure the sexual objectification of women. In comparison, only a few instruments were developed to measure the sexual objectification of both men and women (n=3) or girls (n=3). Only one instrument was developed to exclusively measure the sexual objectification of men, and no instruments were found to measure the sexual objectification of boys.
Instrument Characteristics
Instrument characteristics, including items, subscales, scaling, and scoring, are shown in Table 2. The mean number of items was 14.05, with a range from 4 to 40. Most instruments used a Likert-type response format to measure the degree of frequency or agreement/disagreement with items, with scales ranging from 5- to 9-points. The other two instruments adopted either a "Yes/No" response format, or a ranking system to organise respondents' perceived importance of traits. Scores on a majority of instruments (n=19) are determined using the sums or averages of the items. For most instruments (n=14), higher scores indicate greater frequencies of being objectified or greater tendencies to objectify others. Directionality differed for all remaining instruments (n=7), with higher scores implying lesser tendencies to objectify others since respondents attribute greater personality- or human-related traits to a target.
Information pertaining to instrument reliability is presented in Table 3. Internal consistency estimates (i.e., coefficient α) were available for most instruments (n=17), and ranged from.60 to .96. Three instruments did not report internal consistency estimates, while a coefficient α was not possible to calculate for one instrument because its scoring protocol required ranking items. Test-retest reliability estimates were available for only three instruments, which ranged from .72 to .93, and split-half and inter-rater reliability estimates were not available for any instrument.
Most articles examined the theoretical relationships between sexual objectification scores and relevant constructs (e.g., self-objectification), and differences on sexual objectification scores between selected groups of participants and/or targets (e.g., men vs. women). Information pertaining to evidence of instrument validity in prior studies – via significance testing (e.g., r values, t-tests, F-tests, R2 values, B and β values) – is presented in Table 4. As the area of sexual objectification is currently somewhat limited in scope, psychometric evaluations were not provided for most instruments. Cumulative validity was therefore gathered in this review by evaluating the results from studies that used these instruments.
In accordance with Cronbach and Meehl's (1955) conceptualisations of validity, concurrent validity is defined as the correlations between sexual objectification scores and variables theorised to be associated with sexual objectification. In the case of providing concurrent validity for sexual objectification instruments, variables used in the literature include: self-objectification, eating disorder symptoms, consumption and exposure to the media, sexist attitudes, and sexual coercion. Correlations between sexual objectification scores and other variables not traditionally associated with sexual objectification were also included in Table 4. Predictive validity is defined as the ability of sexual objectification instruments to predict performances on some future criterion, and convergent validity is defined as the correlations between scores on sexual objectification instruments (Cronbach & Meehl, 1955). Sexual objectification scores were also examined across selected groups of participants to provide evidence of known-groups validity (Cronbach & Meehl, 1955). Ultimately, 15 of the 21 instruments established some form of validity.
Concurrent Validity: Variables Theorised to be Related to Sexual Objectification
Self-Objectification
Evidence for the hypothetical relationships between sexual objectification and self-objectification was established in seven instruments. Body shame and body surveillance (i.e., components of self-objectification), and self-objectification were associated with greater scores on instruments measuring the frequency of reported encounters with sexual objectification experiences or tendencies to objectify others. The strength of these correlations (i.e., r values) were generally small, but ranged from.15 to .69 (Mdn=.27). Only scores on three instruments demonstrated correlations equal to or greater than .30, which included the ISOS (Kozee et al., 2007), OOQ (Strelan & Hargreaves, 2005), and Partner-Objectification Scale (Zurbriggen, Ramsey, & Jaworski, 2011). All other instruments demonstrated correlations less than.30[2], suggesting that the strength between sexual objectification scores on these instruments and self-objectification were generally small.
Eating Disorder Symptoms
Four instruments established evidence for the theoretical relationships between sexual objectification and eating disorder symptoms. Men and women who reported engaging in disordered eating behaviours were more likely to score higher on instruments measuring how frequently they encountered sexual objectification experiences. The ISOS (Kozee et al., 2007) was the only instrument that consistently demonstrated correlations between sexual objectification scores and eating disorder symptoms that were above .30. Other instruments established correlations ranging from.15 to .28.
Consumption or Exposure to the Media
Evidence for the hypothetical relationships between sexual objectification and consumption or exposure to the media was established in seven instruments. Increased exposure to the media and consumption of pornography were associated with greater scores on instruments evaluating individuals' tendencies to objectify others. Boys' and girls' exposure to sexually explicit media was also related to scores on instruments measuring their beliefs that women are sexual objects. Women who had a previous partner who frequently consumed pornography were also more likely to score higher on instruments evaluating how frequently they encountered sexual objectification experiences. Of all instruments, only the Women as Sex Objects Scale (Peter & Valkenburg, 2007) and Interpersonal Sexual Objectification Scale – Perpetrator (ISOS-P; Gervais, DiLillo, & McChargue, 2014) established correlations between sexual objectification scores and media consumption or exposure that were equal to or above .30. Other instruments demonstrated correlations ranging from.14 to .27.
Sexist Attitudes
Five instruments established evidence for the theoretical relationships between sexual objectification and sexist attitudes. Men who displayed hostility towards women or endorsed women's traditional and sexual roles were likely to score higher on instruments evaluating their tendencies to objectify women. Women who reported unfair sexist treatment at school or work were also more likely to score greater on instruments measuring how frequently they encounter sexual objectification experiences. The ISOS (Kozee et al., 2007) and Objectified Body Consciousness Scale – Modified (OCB-M; Ramsey & Hoyt, 2015) were the only instruments that consistently established correlations between sexual objectification scores and sexist attitudes that were over .30. All instruments demonstrated correlations ranging from.14 to .37.
Sexual Coercion
Evidence for the hypothetical relationships between sexual objectification and sexual coercion was established in three instruments. Men who engaged in sexual violence or manipulated women to have sex were more likely to score greater in instruments evaluating their tendencies to objectify others. Women who reported encountering sexual objectification experiences were also more likely to feel coerced to have sex and perceive themselves as being manipulated by their partners to have sex. All instruments established correlations between sexual objectification scores and sexual coercion that ranged from .16 to .51.
Other Variables
Three instruments established evidence for the theoretical relationships between sexual objectification scores and psychological wellbeing, where women who reported greater frequencies of encountering sexual objectification experiences were more likely to report psychological distress, depression, and anxiety. Two instruments demonstrated positive correlations between scores on sexual objectification instruments and drug and alcohol use in men and women. Evidence for the hypothetical relationships between sexual objectification and age was also established in four instruments, with age being negatively associated with instruments measuring the frequency of reported encounters with sexual objectification experiences for men and women. Three instruments established positive correlations between sexual objectification scores and the internalisation of cultural beauty standards in men and women. Two instruments demonstrated positive correlations between sexual objectification scores and appearance-related outcomes, including increased drives for thin bodies in women and muscular bodies in men.
Predictive Validity: Sexual Objectification Scores Predicting Other Variables
Limited evidence exists regarding the predictive validity of sexual objectification instruments, with only four instruments providing some form of predictive validity. It is important to note, however, that no authors directly purported that these findings were evidence of predictive validity. Sexual objectification scores on instruments evaluating men's tendencies to objectify women predicted men's breast-size ideals, and sexual objectification scores on instruments measuring boys' tendencies to objectify girls predicted boys' exposure to sexy self-presentation. Correspondingly, scores on instruments measuring individuals' tendencies to objectify others predicted relationship satisfaction for men and women, and sexual satisfaction for men.
Convergent Validity: Correlations with Other Sexual Objectification Instruments
Little evidence of convergent validity was found in this systematic review. Only four instruments were used in studies that demonstrated convergent validity, which included the ISOS (Kozee et al., 2007), SES (Carr & Szymanski, 2011), MSAT (Loughnan et al., 2010), and Human Emotions Task (Borinca, 2016); however, there were no assertions made by any author that these findings were evidence of convergent validity. The correlations reported for these instruments ranged from .42 to .43.
Known-Groups Validity: Differences in Sexual Objectification Scores Amongst Groups
Known-groups validity was observed in six instruments, with differences in gender and sexual orientation most commonly examined. In terms of gender differences, women reported encountering more sexual objectification experiences than men. Contrastingly, men reported sexually objectifying women more than women while boys also regarded women as sexual objects more than girls.
Heterosexual men reported encountering less sexual objectification experiences than heterosexual women, lesbians, and gay men, whom reported comparable levels of sexual objectification experiences. Similarly, gay men reported objectifying men more than heterosexual men. No authors explicitly claimed that any of these findings were evidence of known-groups validity.
The theoretical tenets of objectification theory have been empirically tested with a variety of instruments that have been created in response to the growing scientific interest in sexual objectification. These instruments have been developed with the good intent of quantifying the components of sexual objectification in order to allow the documenting of this social phenomenon, and the development of interventions against its associated harmful ramifications. It is perhaps this good intent that has led to the precipitous development of many instruments that are under-evidenced in terms of their psychometric utility.
Although the rapid expansion of sexual objectification research and instruments is promising, researchers are faced with the challenging task of selecting the most appropriate instrument for their research. Consequently, this systematic review was conducted with the primary aim of identifying the available instruments for use in this area, and presenting their cumulative evidence. This was done with the explicit intention of allowing researchers to make informed decisions when selecting instruments for their research. This review identified 21 instruments that have been previously used to measure sexual objectification in the academic literature from 2001 until 2016. The outcomes of this review were based on the published psychometric properties and the related and available evidence of the use of each instrument. Three major observations emerged in this review, as discussed below.
Limited Psychometric Evaluations and Variations Among Instruments
There is a considerable lack of psychometric evaluation for sexual objectification instruments examined in this review. With the exception of the ISOS (Kozee et al., 2007), the psychometric properties of all instruments were seldom assessed by researchers. While internal consistency reliability estimates were provided for most instruments, cumulative validity was gathered in this review since there were limited psychometric evaluations in the original studies. Given the importance of using valid and reliable instruments in psychological research (Kaplan & Saccuzzo, 2017), the scarcity of assessing instruments' psychometric properties is concerning because it calls into question whether these instruments are accurately measuring sexual objectification. Concerns are further raised in view of the different criteria used to assess sexual objectification and how these instruments were developed (i.e., issues involving content validity).
There are many variations regarding how instruments measure sexual objectification. Specifically, six ways of assessing the social phenomenon were identified in this review, which may be accounted for by the diverse explanations regarding what constitutes as sexual objectification. Instruments examined were also found to measure certain aspects or components of sexual objectification, thereby demonstrating that there is yet no instrument that comprehensively assesses the full range of the construct. For example, the ISOS (Kozee et al., 2007) specifically measures how frequently an individual encounters sexual objectification experiences while the Women as Sex Objects Scale (Peter & Valkenburg, 2007) specifically measures the extent an individual perceives women as sexual objects. Taken together, there is inconsistency with how sexual objectification is defined and measured, which may complicate researchers' task of choosing the most suitable instrument for their research.
Disparities were also noted in how instrument items were generated, as previous research, existing instruments, and/or factor analyses were used to select items for inclusion; however, of all instruments, only three – the ISOS (Kozee et al., 2007), the Sexual Objectification Experiences Scale (SOES; Wiseman & Moradi, 2010), and Cultural Sexual Objectification Scale (CSOS; Hill & Fischer, 2008) – employed a panel of experts to generate and review items. When considering the importance of involving experts in establishing content validity (Hinkin, Tracey, & Enz, 1997), the dearth of expert opinion when developing instruments may cast doubt on whether the "best" items were retained or even generated to begin with. Respectively, the use of existing instruments is potentially problematic since these instruments may assess constructs that are related yet are different to sexual objectification (e.g., sexism). There is therefore a possibility that items included in these instruments may not sufficiently capture and assess the full range of the sexual objectification construct, which may render the content validity of these instruments negligible. Consequently, this reinforces the need for psychometric evaluations of current instruments to ensure that they validly and reliably measure sexual objectification.
Uniformity of Findings and Methodological Caveats
Despite the great variation in the measurement and development of these instruments, the findings were markedly uniform across studies. All instruments were related to variables associated with sexual objectification where examined, and there were no discrepancies in terms of the direction of the relationships. For example, greater tendencies to sexually objectify others and the frequency of reported encounters of sexual objectification experiences were consistently associated with higher levels of self-objectification, eating disorder symptoms, and media consumption and exposure. Taken together, the cohesive findings demonstrate some evidence of concurrent validity; however, the correlations were generally small, indicating weak relationships between scores on sexual objectification instruments and other examined variables. Such low correlations may likely be explained by the shortage of psychometric evaluations of instruments, the differing ways in which instruments have been developed, and how instruments define and measure sexual objectification. Nevertheless, the weak relationships indicate that existing instruments may largely demonstrate inadequate evidence of concurrent validity.
To a much lesser extent evidence of known-groups, predictive, and convergent validity were provided, with less than one third of instruments demonstrating any one of these validities. Regardless, the findings were strongly consistent across instruments despite not being explicitly stated by researchers as evidence of validity. For example, the findings unvaryingly demonstrated significant and meaningful positive relationships between four instruments, thereby indicating convergent validity. Although the consistency of these findings is encouraging, very little is known of the predictive utility of most sexual objectification instruments, their relationships with other similar instruments, and their ability to establish differences between sexually objectification scores across distinct groups. Accordingly, the limited validities of a majority of existing instruments may further hinder researchers' efforts with selecting the most appropriate instrument for their research.
Despite the uniformity of the findings in the academic literature, there are some methodological caveats that should be considered. Evidently, the generalisability of the findings (i.e., external validity) is largely restricted to Caucasian, high-school and university-aged students or adult women. It is possible that individuals who are older, or who originate from a more socially conservative society, may respond differently to being sexually objectified or sexually objectifying others (Graff et al., 2012; Loughnan et al., 2015). Men and/or children may also experience sexual objectification in a dissimilar way to women (Graff et al., 2012). The limited external validity of findings is made more salient when taking into account that there are no normative data across all instruments. It is therefore not possible to establish what normative high or low scores would appear for any population, let alone to adequately make cross-cultural comparisons. Taken together, such caveats may impede our understanding of sexual objectification to a wider range of individuals in the community. Future research may therefore benefit from using more diverse samples – including cross-cultural, clinical, and minority populations – and incorporating normative data for these instruments.
Selecting the "Best" Instrument
The final albeit most important observation made in this review involves evaluating the quality of evidence and determining the "best" instrument to measure sexual objectification accordingly. It is important to note that it is difficult and perhaps inapposite to make such judgements given the great variation with how instruments define and measure sexual objectification.
Based on examining psychometric properties alone, the ISOS (Kozee et al., 2007) stands out as the most widely-used and psychometrically sound sexual objectification instrument. As opposed to other instruments, the ISOS relied on experts and the academic literature to ensure good scale and item development, demonstrated good internal consistency reliability and test-retest reliability estimates, and possesses the most extensive evidence of cumulative validity (i.e., 35 findings). Importantly, the ISOS (Kozee et al., 2007) is only appropriate for measuring how frequently an individual reports encountering sexual objectification experiences. Researchers wishing to measure respondents' propensity to objectify others may consider the OOQ (Strelan & Hargreaves, 2005), which has the second most extensive evidence of cumulative validity (i.e., 23 findings); however, as this instrument was modified from a self-objectification instrument, it may not accurately represent or measure the sexual objectification construct.
Although researchers may first consider the ISOS (Kozee et al., 2007) and OOQ (Strelan & Hargreaves, 2005), other factors should be taken into account, including which instruments are of suitable length and reading level or possess subscales of interest. By referring to Tables 2 through 4 as a guide, researchers with specific hypotheses and populations can choose instruments that match their requirements. For example, researchers intending on assessing the frequency of sexual objectification experiences encountered by gay or bisexual men may consider the SOES (Wiseman & Moradi, 2010) since it was specifically developed to be used with sexual minority men. Correspondingly, researchers wishing to establish change over time with stable instruments may consider employing the SES (Carr & Szymanski, 2011) or the ISOS (Kozee et al., 2007) for which respondents' scores have been strongly correlated between two different time points.
Limitations of the Systematic Review
This review has several limitations that warrant mention. Firstly, a single coder conducted this review, which may increase the possibility of bias and error. Secondly, only self-report instruments (e.g., questionnaires and scales) were examined in this review, thereby limiting the evaluations of other types of instruments that have been used to measure sexual objectification (e.g., implicit instruments). Lastly, this review was limited to English-speaking articles and did not include unpublished articles, conference articles, and dissertations. Future research may thus benefit from examining a broader and conceivable range of suitable instruments and articles to investigate and incorporate the findings into the academic literature.
Sexual objectification research has flourished over recent decades, leading to the proliferation of instruments in the academic literature. While researchers are given a plethora of options for selecting an instrument, this review has demonstrated that very limited attention has centred on ensuring that these instruments are psychometrically sound. Instruments examined in this review varied considerably in terms of how they define and measure sexual objectification, as well as the extent they provided evidence of validity and reliability for tests' scores. Most concerning is that some instruments did not demonstrate any evidence of validity or were only used once, signifying that they are not viable instruments for psychological research. Taken together, this review emphasises the imperativeness of ensuring that existing instruments have stable psychometric properties via evaluations of their validity and reliability. It is also important that a review of this nature is continually updated to reflect the current academic literature, particularly as instruments will require frequent refinement to ensure that they consistently and optimally measure sexual objectification.
Overall, there is importance placed on developing and selecting valid and reliable instruments in psychological research. Newer fields of psychology – like sexual objectification – are therefore not exempt from employing stringent protocols in developing and validating instruments. This point is made further salient when considering the implications of using psychometrically robust instruments. In using sexual objectification instruments that have adequate or strong evidence of validity and reliability, it becomes possible to accurately enhance our understanding of sexual objectification in order to minimise the harmful ramifications for sexually objectified individuals.
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Sexual Objectification and Measurement Terms Used in Boolean Search
Sexual Objectification Measurement
"Sexual Objectification" Scale*
OR Objectification OR Instrument
OR Objectif* OR Test
OR Measur*
OR Inventory
OR Index
OR Survey*
OR Questionnaire*
OR Task*
OR Assessment*
OR "Eye tracking"
OR "Visual Tracking"
Note. Asterisks cause the search to include all possible suffixes to a term.
Table 2. Background and Development
Instrument Description of Measure Development TSO Sample
Sexual Objectification Subscale of the Daily Sexist Events Scale (Moradi, Dirks, & Matteson , 2005)
The subscale measures an individual's reported sexual objectification experiences (e.g., "Had people shout sexist comments, whistle, or make cat-calls at me"). The authors used a previously developed measure (Daily Sexist Events Scale; Swim, Cohen, & Hyers, 1998). Women 221 (all women) university students from the USA. The majority of participants identified as White (64%).
Other-Objectification Questionnaire (OOQ; Strelan & Hargreaves, 2005)
The instrument measures the degree an individual sexually objectifies people in general by ranking their perceived importance of body- (e.g., "strength") and appearance-attributes (e.g., "weight") of others. The study used a modified version of the Self-Objectification Scale (Fredrickson et al., 1998), a self-objectification measure. Men and Women 132 (68 males, 64 females) of mostly university students from Australia. All participants were White and middle-class.
Women as Sex Objects Scale (Peter & Valkenburg, 2007)
The instrument measures the extent an individual believes that women are sexual objects (e.g., "Sexually active girls are more attractive partners"). Items were developed by following an operationalisation of "women as sex objects" by Ward (2002). Women 745 (48% boys, 52% girls) Dutch adolescents.
Sexual Objectification Experiences (SOE; Wiseman & Moradi, 2010)
The instrument measures the degree of sexual objectification experiences encountered by sexual minority men (e.g., "Someone made offensive or unwanted sexualised gestures toward me"). Existing measures of sexual objectification experiences were reviewed, and items that were applicable to sexual minority men were identified. Five gay or bisexual consultants, two of whom had experience conducting research with sexual minority populations, were asked to evaluate the applicability of the items to sexual minority men's experiences. Men 213 (all sexual minority males). The majority of the sample identified as White or Caucasian (approximately 77%).
Interpersonal Sexual Objectification Scale (ISOS; Kozee, Tylka, Augustus-Horvath, & Denchik, 2007)
The instrument measures the extent of interpersonal sexual objectification experiences encountered by an individual (e.g., "How often have you felt that someone was staring at your body?"). Items were generated from the sexual objectification literature, and were written by a counselling psychologist and two counselling psychology graduate students. Items were then reviewed by a counselling psychologist and a women's studies professor. Women 342 (all females) university students from the USA. The majority of the participants identified as White or Caucasian (71.8%).
Table 2. Background and Development (Continued)
Objectification, Capability, and Personal Characteristics Scale (Gurung & Chrouser, 2007)
The instrument measures an individual's impression of a target's sexuality (e.g., "desirable"), capability (e.g., "strength"), and personality (e.g., "self-respect"). Items were adapted from previous research. Women 82 (all females) university students. Participants were "predominantly White."
Cultural Sexual Objectification Scale (CSOS; Hill & Fischer, 2008)
The instrument measures individuals' experiences with cultural sexual objectification as described in objectification theory (Fredrickson & Roberts, 1997). Example items include "How many times have you had someone stare at your breasts while talking to you?" and "How many times have you been in a situation where someone made evaluative or judging comments on your weight or body shape?" Items were adapted from existing measures, and were independently reviewed by seven judges familiar with objectification theory. Women 361 (all females) of mostly undergraduate psychology students. The majority of the participants identified as White or Caucasian (83.9%).
Perceived Human Essence Scale (Heflick & Goldenberg, 2009)
The instrument measures the extent that 25 traits described a target (e.g., "helpful" and "impulsive"). Items were adapted from previous research. Women 133 (37 males, 96 females) university students from the USA.
Sexual Objectification Scale (Kistler & Lee, 2009)
The instrument measures the degree to which an individual accepts or approves of men sexually objectifying women (e.g., "It is okay for men to check out attractive women at bars or dance clubs"). Not reported Women 195 (59 males and 136 females) adults.
Mental State Attribution Task (MSAT; Loughnan et al., 2010)
The instrument measures an individual's impression of a target's capacity to experience mental states reflecting perception (e.g., "seeing"), emotions (e.g., "joy"), thoughts (e.g., "reasoning"), and intentions (e.g., "wishes"). The authors used a previously developed measure (MSAT; Haslam, Kashima, Loughnan, Shi, & Suitner, 2008). Men and Women 166 (72 males, 94 females) of mostly university students.
Impression Formation Rating Scale (Graff, Murnen, & Smolak, 2012)
The instrument measures an individual's impression of a target based on masculine-stereotyped traits (e.g., "intelligent"), feminine-stereotyped traits (e.g., "friendly"), and traits that might be affected by a sexualisation manipulation (e.g., "self-respecting"). Items were chosen in part based on previous research. Girls 162 (56 males, 106 females) university students from the USA. The majority of the sample identified as Caucasian (80%).
Partner-Objectification Scale (Zurbriggen, Ramsey, & Jaworski, 2011)
The instrument measures the extent an individual sexually objectifies their partner (e.g., "During the day, I think about how my partner looks many times"). Items were modified from the surveillance subscale of the Objectified Body Consciousness Scale (OBCS; McKinley & Hyde, 1996), a self-objectification measure. Men and Women 184 (79 males, 105 females) university students from the USA. The majority of the sample identified as White (67.9%).
Moral Status Scale (Holland & Haslam, 2013)
The instrument measures an individual's impression of a target's moral agency (e.g., "In general, how intentional do you believe the woman's behaviour is?") and items assessed moral patiency (e.g., ''How bad would you feel if you manipulated this woman?''). Items were drawn from previous research. Women 191 (96 males; 95 females) Australian university students. The majority of the sample identified as Caucasian (76.7%).
Impression Formation Task (Loughnan, Pina, Vasquez, & Puvia, 2013)
The instrument measures an individual's impression of a target's capacity to experience mental states (e.g., "planning"), as well as their moral concern for a target (e.g., "How bad would you feel if you took advantage of Laura?") Items were adapted from the MSAT (Haslam, Kashima, Loughnan, Shi, & Suitner, 2008) and Moral Status Scale (Holland & Haslam, 2013). Women 60 (15 males, 44 females, 1 unreported) adults whom were recruited via email and electronic bulletin boards.
Sexual Experiences Survey (SES; Carr & Szymanski, 2011)
The instrument consists of behaviourally-specific questions describing concrete events that reflect varying levels of sexual aggression that have been experienced since age 14 (e.g., "Have you ever been fondled, kissed, or touched sexually when you didn't want to …?") The authors used a previously developed measure (SES; Testa, VanZile-Tamsen, Livingston, & Koss, 2004). Women 300 (all females) university students from the USA. The majority of sample identified as White (89%).
Interpersonal Sexual Objectification Scale – Perpetrator (ISOS-P; Gervais et al., 2014)
The instrument measures the frequency with which an individual sexually objectifies others during their interactions with them (e.g., "Made a degrading sexual gesture toward someone?)". Items were modified from an existing measure (ISOS; Kozee et al., 2007). Women 502 (all males) university students from the USA. The majority of the sample identified as European-American (85.9%).
Objectified Body Consciousness Scale – Modified (Ramsey & Hoyt, 2015)
The instrument measures the extent an individual sexually objectifies their partner (e.g., "When my partner can't control his/her weight, I feel like something must be wrong with him/her"). Items of Zurbriggen et al.'s (2011) Partner-Objectification Scale were used, as well as the modified shame subscale of the OBCS (McKinley & Hyde, 1996). Women 199 (all males) adults. The majority of the sample identified as White or Caucasian (81.5%).
Sexual Objectification of Girls Scale (van Oosten, Peter, & Boot, 2014)
The instrument measures the degree to which boys are perceived to sexually objectify girls (e.g., "There is nothing wrong with boys being primarily interested in a girls' body"). Items were developed from previous research between the use of sexually explicit internet material and sexual objectification of women. Girls 1636 (48.5% boys, 51.5% girls) students. Participants were recruited from 12 Belgium schools.
Objectification of Women Scale (Ward, Vandenbosch, & Eggermont, 2015)
The instrument measures an individual's evaluation of how important they consider four body attributes are for girls and women (e.g., "buttocks," "breasts," "belly," and "body size"). Items were derived from similar measures assessing men's views of women. Girls and Women 592 Dutch adolescent students (all males).
Women's Attitude Towards the Male Gaze (Wright, Arroyo, & Bae, 2015)
The instrument measures women's acceptance of the male gaze (e.g., "It is okay for men to admire women's bodies as they pass by on the street"). Items were adapted from previous research. Women 114 (all females) university students. The majority of participants identified as White (87.8%).
Human Emotions Task (Borinca, 2016)
The instrument measures an individual's impression of a target's capacity to experience emotions (e.g., "agitation," "fear," and "attraction"). Items were developed from previous research. Women 98 total (all men) adults from Kosovo.
Table 3. Instrument Characteristics and Reliability Evidence
Instrument No. of Items Subscale (No. of Items)
No. of Factors, %, σ2
Response Scale Score Range Coefficient α Test–Retest Reliability
Sexual Objectification Subscale of the Daily Sexist Events Scale
25 – 1–5, Never–About 2+ Times A Week During the Semester 25–125 Total .87 Not reported
Other–Objectification Questionnaire (OOQ)
10 – 1–10, Least Important–Most Important 1–10 N/A Not reported
Women as Sex Objects Scale
5 1 factor, 50%, σ2 1–5, Disagree Completely–Agree Completely) 5–25 Total .75 Not reported
Sexual Objectification Experiences
17 1 factor, 43.50%, σ2 1–6, Response Categories Not Provided 17–102 Total .91 Not reported
Interpersonal Sexual Objectification Scale (ISOS)
Body Evaluation (11), 46.68%, σ2
Unwanted Explicit Sexual Advances (4), 9.48%.
2 factors, 56.16% of variance (total)
1–5, Never–Almost Always 15–75 Total .92
r = .90 over 3–week period
Objectification, Capability, and Personal Characteristics Scale
15 – 1–9, Not At All–Extremely 15–135 Not reported Not reported
Cultural Sexual Objectification Scale (CSOS)
Ubiquitous Sexualised Gaze/Harassment, 20.4%, σ2
Sexual Assault by Men, 7.9%, σ2
Assault by Women, 5.8%, , σ2
1–5, Never–Almost All the Time 40–200 Total .96 Not reported
Perceived Human Essence Scale
25 – 1–7, Not At All–Entirely 25–175 Not reported Not reported
Sexual Objectification Scale
15 – 1–7, Strongly Disagree–Strongly Agree 15–105 Total .88 Not reported
Mental State Attribution Task (MSAT)
20 – 1–7, Not At All–Very Much so 20–140 Total .88–.94 Not reported
Table 3. Instrument Characteristics and Reliability Evidence (Continued)
Impression Formation Rating Scale
9 – 1–7, Strongly Disagree–Strongly Agree 9–63 Not reported Not reported
Partner–Objectification Scale
10 – 1–7, Disagree Strongly–Agree Strongly 9–63 Total .67 Not reported
Moral Status Scale
Moral Patiency (5)
Moral Agency (4)
1–7, Not At All–Very Much So 9–63
Impression Formation Task
Mental Capacities (9)
Moral Concern (3)
1–7, Hardly Ever–Very Frequently (Mental Capacities), Not At All–Extremely (Moral Concern) 9–63
Sexual Experiences Survey
11 – Yes–No 0–4, No Aggression–Rape Total .77 r = .93 over 1–week period
Interpersonal Sexual Objectification Scale – Perpetrator
Body Evaluation (11)
Unwanted Explicit Sexual Advances (4)
1–5, Never–Always 1–75
.Not reported
Objectified Body Consciousness Scale – Modified
Partner Surveillance (8)
Partner Shame (8)
1–6, Disagree Strongly–Agree Strongly) 16–96
Sexual Objectification of Girls Scale
5 1 factor, 54%, σ2 1–7, Totally Agree–Totally Disagree 1–35 Total >.78 Not reported
Objectification of Women Scale
4 1 factor, 62.60% 1–10, Not At All Important–Very Important 4–40 Total .88 Not reported
Women's Attitude Towards the Male Gaze
5 1 factor, 46.54% (45.18% at 48–hour follow–up) 1–7, Disagree Strongly–Agree Strongly 1–35 Total .69 r = .72 over 48–hour period
Human Emotions Task
12 – 1–7, Not At All–Very Much 12–84 Total .69 Not reported
Table 4. Evidence of Accumulative Validity for Sexual Objectification Instruments
Instrument Evidence of Validity Source
Related to increases in body surveillance for women after controlling for body mass index (BMI), r(221) = .27.
Related to increases in body shame for women after controlling for BMI, r(221) = .16.
Related to increases in self-objectification for women, r(271) = .15.
Related to increases in eating disorder symptoms for women after controlling for BMI, r(221) = .21.
Psychological Wellbeing
Not related to neuroticism (p >.05).
Related to increases in psychological distress for women, r(221) = .44.
Internalisation of Cultural Beauty Standards
Related to increases in women's internalisation of cultural beauty standards after controlling for BMI, r(221) = .25.
Group Differences
Women encountered more sexual objectification experiences than men, t(88) = 3.52.
Moradi, Dirks, & Matteson (2005)
Moradi et al. (2005)
Szymanski, Gupta, Carr, & Stewart (2009)
Szymanski et al. (2009)
Swim, Hyers, Cohen, & Ferguson (2001)
Swim et al. (2001)
Other-Objectification Questionnaire (OOQ)
Related to increases in body shame for women, r(549) = .15.
Related to increases in self-objectification for women, r(64) = .69.
Related to increases in self-objectification for men, r(68) = .27.
Related to increases in bulimia symptoms for women, r(549) = .15.
Related to increases in body dissatisfaction for women, r(549) = .15.
Media Consumption/Exposure
Related to increases in media exposure for men and women, r(383) = .14.
Harassment Experiences
Related to increases in reported stranger harassment for women, r(319) = .13.
Related to increases in reported verbal harassment for women, r(319) = .13.
Related to increases in reported verbal harassment for men, r(320) = .11.
Related to increases in body comparison for women, r(549) = .19.
Lindner, Tantleff-Dunn, & Jentsch (2012)
Strelan & Hargreaves (2005)
Lindner et al. (2012)
Swami, Coles, Wilson, Salem, Wyrozumska, & Furnham (2010)
Davidson, Gervais, & Sherd (2015)
Davidson et al. (2015)
Table 4. Evidence of Accumulative Validity for Sexual Objectification Instruments (Continued)
Related to increases in benevolent sexism towards women, r(361) = .35.
Related to increases in men's hostility towards women, r(361) = .28.
Related to men's endorsement of traditional female roles, r(361) = .14.
Appearance-Related Outcomes
Related to increases in women's drive for a thin body, r(549) = .19.
Related to increases in women's use of cosmetics, r(383) = .36.
Related to increases in men's preference for larger breast sizes, r(361) = .38.
Predicted breast-size ideals for men, B = .33, β = .13.
Related to increases in men's drive for a muscular body, r(327) = .43.
Predicted men's drive for a muscular body after controlling age and BMI, B = .45, β = .33.
Gay men sexually objectified men more than heterosexual men, F(1, 54) = 11.20.
Men sexually objectified women more than women objectified other women, t(127) = 2.26.
Men objectified other men less than women objectified men, t(127) = 2.10.
Increases in age is related to decreases in men sexually objectifying women, r(327) = -.12.
Swami & Tovee (2013)
Swami et al. (2010)
Swami & Voracek (2013)
Kozak, Frankenhauser, & Roberts (2009)
Related to increases in adolescent boys' and girls' exposure to sexually explicit DVDs, r(745) = .30.
Related to increases in adolescent boys' and girls' exposure to sexually explicit internet movies, r(745) = .31.
Related to increases in adolescent boys' and girls' exposure to sexually explicit internet material, r(962) = .41.
Related to increases in adolescent boys' and girls' enjoyment of viewing sexually explicit internet material, r(962) = .42.
Adolescent boys regarded women as sex objects more than adolescent girls, t(727) = 12.11.
Peter & Valkenburg (2007)
Valkenburg & Peter (2009)
Sexual Objectification Experiences Scale (SOES)
Related to increases in body surveillance for men, r(231) = .26.
Related to increases in body shame for men, r(231) = .23.
Related to increases in body dissatisfaction for gay men, r(233) = .28
Related to increases in eating disorder symptoms for men, r(231) = .25.
Wiseman & Moradi (2010)
Davids, Watson, Nilsson, & Marszalek (2015)
Related to increases in men's internalisation of cultural beauty standards, r(231) = .21.
Increases in age is related to decreases in reported sexual objectification experiences for men, r(231) = -.32.
Related to increases in men's involvement with the gay community, r(233) = .42.
Related to increases in psychological sense of community for men, r(233) = .21.
Davids et al. (2015)
Related to increases in body surveillance for women, r(342) = .30.
Predicted self-objectification above and beyond the variance accounted for by sexist events, R2 = .75.
Related to increases in disordered eating behaviour for women, r(191) = .34.
Related to increases in disordered eating behaviour for men, r(189) = .34.
Related to increases in interoceptive awareness of eating for women, r(377) = .31.
Related to increases in disordered eating for women, r(171) = .43.
Carr & Szymansk (2011)
Engeln-Maddox, Miller, & Doyle (2011)
Kozee, Tylka, Augustus-Horvath, & Denchik (2007)
Kozee et al. (2007)
Engeln-Maddox et al. (2011)
Kozee & Tylka (2006)
Tylka & Van Diest (2015)
Related to increases in women's internalisation of cultural beauty standards, r(342) = .31.
Related to increased experiences of sexist degradation events for women, r(342) = .55.
Related to increased experiences of unfair sexist treatment at school/work for women, r(342) = .35.
Related to increased experiences of unfair sexist treatment in relationships, r(342) = .39.
Related to increased tendency for women to cope with sexist oppression via internalisation, r(270) = .29.
Related to increased experiences of heterosexism for women, r(243) = .37.
Related to increases in consumption of pornography by previous partner, r(171) = .27.
Relationship Outcomes
Related to increases in relationship anxiety for women, r(171) = .22.
Related to increases in relationship avoidance for women, r(171)= .17.
Experiences with Racism
Related to increased encounters of racist events for African-American women, r(144) = .44.
Related to increased experiences of gendered racism for African-American women, r(144) = .59.
Related to increased tendency for Latin women to cope with racism and oppression via internalisation, r(144) = .25.
Related to increased encounters of racist discrimination for Latin women, r(180) = .54.
Lozano, Valor-Segura, Saez, & Exposito (2015)
Szymanski & Feltman (2014)
Watson, Grotewiel, Farrell, Marshik, & Schneider (2015)
Carr, Szymanski, Taha, West, & Kaslow (2014)
Carr et al. (2014)
Velez, Campos, & Moradi (2015)
Increases in age is related to decreases in reported sexual objectification experiences for women, r(191) = -.29.
Women with a history of trauma reported more sexual objectification experiences than women without a history of trauma, F(5, 323) = 8.72.
African-American women reported more sexual objectification experiences than White Women, F(1, 222) = 8.02.
Heterosexual men reported less sexual objectification experiences than heterosexual women, lesbians, and gay men, F(12, 955) = 8.33.
Related to increases in depressive symptoms for women, r(144) = .36
Related to decreases in self-esteem for women, r(771) = -.13.
Related to increases in state-anxiety symptoms for women, r(771) = .20.
Related to psychological distress for women, r(270) = .40
Related to decreased tendency for women to feel sexually assertive, r(297) = -.15.
Related to increases in trauma symptoms for women, r(337) = .28 (Body Evaluation subscale)
Related to increases in trauma symptoms for women, r(337) = .37 (Unwanted Explicit Sexual Advances)
Related to increased frequency of wearing the hijab for Muslim women, r(118) = .30.
Unrelated to social desirable responding (p >.05).
Watson, Marszalek, Dispenza, & Davids (2015)
Miles-McLean et al. (2015)
Lozano et al. (2015)
Franz, DiLillo, & Gervais (2016)
Tolaymat & Moradi (2011)
Evidence of validity for this instrument was not found.
Related to increases in body surveillance for women, r(361) = .22 (Ubiquitous Sexualised Gaze/Harassment subscale).
Related to increases in self-objectification for women, r(361) = .19 (Ubiquitous Sexualised Gaze/Harassment subscale).
Hill & Fischer (2008)
Men who watched highly sexual hip-hop music videos sexually objectified women more than men who watched low sexual hip-hop music videos, t(38) = 1.90; however, women did not significantly differ in sexually objectifying women in either conditions, t(87) = 1.22.
Kistler & Lee (2010)
Related to increases in men's anxiety in romantic relationships with women, r(98) = .35.
Related to increases in men's proneness to be hurt by women, r(98) = .28.
Borinca (2016)
Partner-Objectification Scale
Related to increases in self-objectification for men and women, r(161) = .30.
Related to decreases in relationship satisfaction, r(161) = -.38.
Related to decreases in sexual satisfaction for men, r(161) = .44.
Predicted relationship satisfaction for men and women after controlling for media consumption and self-objectification, B = -.218, β = -.234.
Predicted sexual satisfaction for men after controlling for self-objectification, R2 = .30.
Zurbriggen, Ramsey, & Jaworski (2011)
Zurbriggen et al. (2011)
More consumption of objectifying media, r(161) = .19.
Men sexually objectified their partners than women, t(149) = -6.308.
Related to increased tendency for women to feel coerced to have sex, r(162) = .16.
Related to increased tendency for women to perceive themselves as being manipulated by their partner to have sex, r(162) = .21.
Related to increases in men's expectations to have sex with women, r(119) = .35.
Related to increases in men's endorsement of women's sexual role, r(119) = .17.
Ramsey & Hoyt (2015)
Sexual Experiences Survey (SES)
Related to increases in depressive symptoms for women, r(289) = .13.
Drug Use/Abuse
Related to increases in alcohol abuse for women, r(289) = .30.
Related to increases in nicotine use for women, r(289) = .36.
Related to increases in drug use for women, r(289) = .20.
Other Sexual Objectification Instruments
Correlated with the ISOS, r(289) = .43.
Interpersonal Sexual Objectification Scale – Perpetrator (ISOS-P)
Related to increases in consumption of pornography for men, r(329) = .39 Body Evaluation subscale).
Related to increases in consumption of pornography for men, r(329) = .17 (Unwanted Explicit Sexual Advances subscale).
Mikorski & Szymanski (2016)
Related to men's increased interaction with abusive male peers, r(329) = .26 (Body Evaluation subscale).
Related to men's increased interaction with abusive male peers, r(329) = .37 (Unwanted Explicit Sexual Advances).
Related to increases in men's belief of having power over women, r(329) = .17 (Body Evaluation subscale).
Related to increased tendency for men to engage in sexual violence, r(502) = .27 (Body Evaluation subscale).
Related to increased tendency for men to engage in sexual violence, r(502) = .36 (Unwanted Explicit Sexual Advances subscale).
Related to increases in social comparison, r(670) = .26.
Gervais, DiLillo, & McChargue (2014)
Gervais et al. (2014)
Gervais, Bernard, & Riemer (2015)
Related to increased frequency of alcohol use for men, r(502) = .28 (Body Evaluation subscale).
Related to increased frequency of alcohol use for men, r(502) = .15 (Unwanted Explicit Sexual Advances subscale).
Related to increases in alcohol abuse for men, r(289) = .28.
Related to increases in nicotine use, r(289) = .20.
Related to increased tendency for men to coerce women to have sex, r(162) = .48.
Related to increased tendency for men to use violence to coerce their partner to have sex, r(162) = .18 (Partner Surveillance subscale).
Related to increased tendency for men to use violence to coerce their partner to have sex, r(162) = .51 (Partner Shame subscale).
Related to increased tendency for men to use commitment manipulation to coerce their partner to have sex, r(162) = .21 (Partner Surveillance subscale).
Related to increased tendency for men to use commitment manipulation to coerce their partner to have sex, r(162) = .21 (Partner Shame subscale).
Related to increased expectations from men to have sex with women, r(162) = .32 (Partner Surveillance subscale).
Related to increased expectations from men to have sex with women, r(162) = .64 (Partner Shame subscale).
Related to increased endorsement of women's sexual roles, r(162) = .45 (Partner Surveillance subscale)
Related to increased endorsement of women's sexual roles, r(162) = .72 (Partner Shame subscale).
Positively predicted exposure to sexy self-presentations of others for young adolescent boys and girls, B = .12.
Negatively predicted exposure to sexy self-presentations of others for late adolescent boys and girls, B = -.09.
van Oosten, Peter, & Boot (2014)
Increases in age is related to decreases in sexually objectifying girls and women, r(841) = -.11.
Young male adolescents had sexually objectifying beliefs of girls and women than older male adolescents, F(1.96, 1135.26) = 23.03.
Related to increases in exposure to sexualising magazines, r(841) = .18.
Beliefs of Courtship Strategies
Related to increases in beliefs about feminine courtship strategies, r(841) = .30.
Predicted beliefs about feminine courtship strategies, B = .05, β = .09.
Ward, Vandenbosch, & Eggermont (2015)
Ward et al. (2015)
Correlated with MSAT, r(98) = .42.
Records identified through database searching
(n=7324)
Additional records identified through other sources
(n=3)
Records after duplicates removed
Records screened
Records excluded
Full-text articles assessed for eligibility
(n=560)
Full-text articles excluded, with reasons (n=516)
260 = Self-objectification outcomes only
109 = University reports
60 = Wrong measures
32 = Psychometric information not provided
24 = Theory only
14 = Implicit/Indirect instruments only
7 = Article missing
6 = Manipulation checks
3 = Synopsis only
1 = Non-English article
Studies included in qualitative synthesis
Figure 1. PRISMA flow diagram outlining articles excluded at each stage in the screening process
Complete Search Strategy for PsycINFO
# Query
S1 DE objectif* OR DE sexualis* OR DE sexualiz*
S2 TI ( objectif* OR sexualis* OR sexualiz* ) OR AB ( objectif* OR sexualis* OR sexualiz* ) OR TM ( objectif* OR sexualis* OR sexualiz* )
S3 S1 OR S2
S4 DE scale* OR DE instrument OR DE test* OR DE measur* OR DE inventory OR DE index OR DE survey* OR DE questionnaire* OR DE task* OR DE assessment* OR DE "eye tracking" OR DE "eye-tracking" OR DE "visual tracking"
S5 TI ( scale* OR instrument OR test* OR measur* OR inventory OR index OR survey* OR questionnaire* OR task* OR assessment* OR "eye tracking" OR "eye-tracking" OR "visual tracking" ) OR AB ( scale* OR instrument OR test* OR measur* OR inventory OR index OR survey* OR questionnaire* OR task* OR assessment* OR "eye tracking" OR "eye-tracking" OR "visual tracking" ) OR TM ( scale* OR instrument OR test* OR measur* OR inventory OR index OR survey* OR questionnaire* OR task* OR assessment* OR "eye tracking" OR "eye-tracking" OR "visual tracking" )
S7 S3 AND S6
[1] As self-objectification is not the focus of this review, it will not be explored further.
[2] The magnitude of correlations were classified using Cohen's (1992) criteria, in which correlations of .10 are "small" in strength, those approximately .30 are "medium" and those approximately or above .50 are "large."
Business Bliss Consultants FZE. (November 2018). Literature Review on Sexual Objectification Instruments. Retrieved from https://ukdiss.com/litreview/sexual-objectification-instruments.php?vref=1
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ZeissLSM 710, LSM 770, LSM 880, & LSM 980
FLIM & FCS Upgrade Kits
Overview of Zeiss
The Zeiss LSM 710, LSM 770, LSM 880, and LSM 980 confocal microscopes series can be easily upgraded to Fluorescence Lifetime Imaging (FLIM) and Fluorescence Correlation Spectroscopy (FCS) capability using photon counting detection. Data is acquired using one of two modalities: FastFLIM (digital frequency domain); or SWISS card (digital TCSP, time-domain). While the choice depends upon the user preference, FastFLIM provides directly data in a suitable format for phasor plot analysis. The package includes VistaVision for data acquisition and processing.
The Zeiss FCS and FLIM upgrade package includes the following items:
FastFLIM Unit or TCSPC Unit
Each unit accepts the output (via BNC) from the detectors and the synchronization signal from the Zeiss system.
Two detectors coupled to the descanned port of the confocal head of the microscope; or to the non-descanned port (for multiphoton instruments).
Laser Launcher
Available for 3-, 4- and 6-lasers. The lasers beams are superimposed and the output of the laser launcher is connected to the microscope by using a fiber optic.
Computer Running VistaVision by ISS
A high-performance computer, with a 32" flat monitor, 2556 x 1440 resolution.
Product Specifications for Zeiss
Acquisition and Analysis Software
VistaVision by ISS
Fluorescence Fluctuations Spectroscopy (FFS) Measurements
Fluorescence Correlation Spectroscopy (auto- and cross-correlation)
Photon Counting Histogram (PCH)
FFS measurements at target XYZ locations in an image
FLCS, Fluorescence Lifetime Correlation Spectroscopy
Number & Brightness (N&B)
Imaging Module Measurements
Single-point (intensity, polarization, lifetime)
Single plan and z-stack (polarization images, Ratiometric, FLIM)
FLIM images (digital frequency-domain) (single plane and z-stack)
Acquired in digital frequency-domain (DFD). The routine acquires simultaneously a FLIM image and a steady-state image.
FLIM images time-domain (single plane and z-stack)
Acquired in time-correlated single photon counting (TCSPC)
Single Molecule Module
Burst Analysis
FRET and Correlation Methods
PIE-FRET Methods
Laser diodes: 370, 405, 440, 473, 488, 635 nm
Single-photon pulsed lasers
Multi-photon lasers
Models for 3, 4, 6 laser diodes. Light is delivered to the microscope through a single-mode fiber optic.
Input Channels
GaAs PMT (Model H7422P)
Hybrid PMTs (Model R10467U)
Pixel, Line, Frame
FLIM Image Data Acquisition Minimum Dwell Time
6 µs/pixel
Unit Control
High-performance Processor, 32GB RAM, Windows 10, 64-bit
32" monitor, 2556 x 1440 resolution
Configuration for Zeiss
FLIM/FFS Upgrade Kits for Zeiss LSM systems
"Millisecond spatiotemporal dynamics of FRET biosensors by the pair correlation function and the phasor approach to FLIM." Hinde, E., Digman, M.A., Hahn, K.M. & Gratton, E. Proceedings of the National Academy of Sciences, 110(1), pp. 135–140, 2012, Dec. doi: 10.1073/pnas.1211882110.
"Metabolic trajectory of cellular differentiation in small intestine by Phasor Fluorescence Lifetime Microscopy of NADH." Stringari, C., Edwards, R.A., Pate, K.T., Waterman, M.L., Donovan, P.J. & Gratton, E. Scientific Reports, 2(1), 2012, Aug. doi: 10.1038/srep00568.
"Label-free separation of human embryonic stem cells and their differentiating progenies by phasor fluorescence lifetime microscopy." Stringari, C. Journal of Biomedical Optics, 17(4), p. 046012, 2012, Apr. doi: 10.1117/1.jbo.17.4.046012.
"Biosensor Förster resonance energy transfer detection by the phasor approach to fluorescence lifetime imaging microscopy." Hinde, E., Digman, M.A., Welch, C., Hahn, K.M. & Gratton, E. Microscopy Research and Technique, 75(3), pp. 271–281, 2011, Aug. doi: 10.1002/jemt.21054.


They didn't used to talk about such things. Luxury retail outlets? Please. Nobody who shopped at Saks Fifth Ave. would want to sully all that cache they had just paid dearly for.
But most high end retailers had outlets on the down low. According to Business Week Magazine, these retailers are realizing that in this stalled economy, in order to continue pushing their product, they'd better start advertising this fact much more loudly.
In the last 12 months, Saks Fifth Ave. changed the name of its outlets from the obscure "Off-Fifth" to the chrystal clear "Saks Fifth Ave. Off fifth" and will be opening three new outlets later this year. "We're clearly seeing continued outsized growth in our Off Fifth business," Saks CEO Stephen I. Sadove told the magazine.
Nordstrom opened six new Nordstrom Rack outlets in 2008, and has plans to open eight more in 2009. Personally, I'm a big fan out outlets, but find that a lot of basic thrift-store shopping rules apply. You're never guaranteed to find the merchandise you'd see at the main store, but with diligence (come early, come often), you're bound to find some gems. This is a trend I see as only getting larger as our consumer economy grinds to a halt.


Angella Cole is a Gluten Free Pastry Chef, Fitness Trainer and Nutritional Consultant.
She has been employed at a major weight loss center as a Program Director specializing in helping both men and women lose weight and keep it off through exercise, proper diet and portion control, with the assistance of Organic, and Gluten free diets. She has also worked as a Private Chef for a number of A list Hollywood Celebrities.
Angella developed this passion to help a friend whose son is battling a rare kidney disorder called Nephrotic Syndrome. This disease causes the filtering mechanism of the kidney's to shut down. Angella created a plan to mitigate the side effects of the medication by eliminating the wheat, gluten, and simple sugars from his diet.
Angella began to develop a system of food that would help people not only feel better, but be healthier.
Angella's goal was to provide products that did not compromise taste, texture, and variety. Bolstered with this knowledge, Angella desires to share this "magical" result with people nationwide. She has a real passion to make people feel and live better lives through her discoveries.
Angella has been successful in developing a line of products that are unlike any other gluten free products on the market. She has been able to produce a line of products that are delicious and innovative to the other gluten free products on the market, while providing a more healthful alternative to traditional sweet treats.
She uses top quality ingredients which contribute to a rich and moist texture. The base for all of the "bakery happiness" is that she uses a blend of Sweet Brown Rice Flour, Brown Sugar, and Organic Evaporated Cane Juice. These products can maintain a solid 7-day fresh shelf life, and 21- days in the grocer's freezer.
Angella insists upon a 100% gluten free kitchen. This diet is not NOT limited to people with Celiac Disease or people with gluten intolerance. Everyone can enjoy the flavors and textures of a gluten free product, especially those with an eye on a more healthful diet.


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