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Predictors of regular mammography use among American Indian women in Oklahoma: a cross-sectional study

  • Eleni L Tolma1Email author,
  • Julie A Stoner2,
  • Ji Li2,
  • Yoonsang Kim3 and
  • Kimberly K Engelman4
BMC Women's Health201414:101

Received: 20 December 2013

Accepted: 18 August 2014

Published: 28 August 2014

There are significant disparities in breast cancer screening and survivorship between American Indian (AI) and non-Hispanic white women. This study aimed to identify the salient beliefs AI women from Oklahoma have on regular mammography screening, and to determine which beliefs and health- related practices are associated with past mammography screening behavior.

This study used an integrated model of the Theory of Planned Behavior as the guiding theoretical framework. Data were collected from 255 (mean age = 51 years, SD 7.64 years) AI women randomly selected from a rural Oklahoma medical clinic (response rate: 79%). Multivariate logistic regression was used to identify factors associated with self-reported past mammography within the last two years while controlling for demographic variables. Associations were summarized using odds ratios (OR), the ratio of the odds of past mammography per a 1-unit increase in continuous independent factor scales (subjective physician norm, cultural affiliation, fatalism, knowledge of mammography screening guidelines, and perceived behavior control barriers) or between groups defined by categorical variables, and 95% confidence intervals (CI).

Of the participants, 65% (n = 167) reported a screening mammogram within the last two years. After adjustment for age and educational status, women with a higher total subjective-norm physician score (OR = 1.15, 95% CI: 1.06-1.24), a higher knowledge of mammography screening guidelines (OR = 1.52, 95% CI: 1.00-2.31), a family history of breast cancer (OR = 9.97, 95% CI: 3.05-32.62), or reporting an annual versus none or a single physician breast examination (OR = 5.57, 95% CI: 1.79-17.37) had a higher odds of past mammography. On the other hand, women who were more culturally affiliated (OR = 0.42, 95% CI: 0.24-0.74), perceived more barriers (OR = 0.86, 0.78-0.94), or had higher fatalistic attitudes toward breast cancer (OR = 0.90, 95% CI: 0.82-0.99) had lower odds of past mammography.

In the development of culturally-appropriate interventions promoting mammography among AI communities, emphasis could be put on the following: a) promoting clinic-related practices (e.g. physician recommendation, physician breast examination); b) promoting community-related practices (e.g. knowledge about mammography while eliminating fatalistic attitudes); and c) reducing environmental barriers.

Breast cancer Native American American Indian Theory of planned behavior Mammography Quantitative research

Breast cancer continues to be the most commonly diagnosed cancer and the second leading cause of death among women in the United States [1]. While breast cancer rates vary by race/ethnicity, socioeconomic status (SES), and geographic region, among American Indian (AI) women breast cancer remains a major cause of death [1]. Although the incidence rates among AI women today are the fourth lowest at 89.1/100,000 from 2005–2009 when compared to non-Hispanic white women at 123.3/100,000 and African American women at 118.0/100,000, mortality rates have declined among all racial/ethnic groups except for American Indians for the most recent 10-year time period [2]. Today, many AI women do not receive breast cancer screening despite its availability. In 2008, only 59.7% of AI women age 40 and over had a mammogram within the past 2 years while the screening rate for non-Hispanic white women was 68% [1].

In Oklahoma, the incidence rate of breast cancer among AI women was 140.5/100,000 compared to 121.5/100,000 among non-Hispanic white women for 2005–2009 [3]. Similarly, disparities still exist regarding late-stage breast cancer diagnosis where 34.2% of the late-stage cases were diagnosed among AI women compared to 31% among Non-Hispanic white women in contrast to the Oklahoma demographic distribution in which AI women comprised 11% of the adult female population aged 18 and older compared to 74% non- Hispanic white based on 2010–2012 census data [3, 4]. Therefore, with no doubt, breast cancer is an important public health issue among AI women, not only in the US, but also in Oklahoma.

Numerous barriers exist that prevent AI women from seeking mammography screenings. These limitations include lack of education and awareness of mammography screening [5], reduced access to medical services [6], absence of family history [7], historical trauma [8], embarrassment [9, 10], fear [9, 11], and oftentimes fatalism [9]. Physician recommendation has been established as women’s primary motivating factor to get a screening mammogram [12, 13]. However, only two studies [14, 15] showed that physician referral was positively associated with recent mammography experience within the AI population. Other social factors include encouragement by significant others, such as family members, friends, and elderly [16]. Moreover, the impact of traditional Native identity on mammography screening has not been clear. Some studies show that women who are more traditional are more likely to get a screening mammogram [17, 18] whereas others do not [19, 20].

This paper describes a study that is part of a larger project, the aim of which is to develop a theory-based culturally sensitive intervention to promote mammography screening within an AI community in rural Oklahoma. Interventions using a theoretical framework are most effective in increasing breast cancer screening rates [21]. A few studies have used a combination of theoretical models [22, 23] by incorporating elements of theories that have been positively associated with mammography behavior. In this study, we also used an integrative conceptual framework that incorporated elements from the Theory of Planned Behavior (TPB) [24, 25], Social Cognitive Theory (SCT; self-efficacy, social modeling) [26], the Health Belief Model (perceived susceptibility) [27], and concepts that have been shown consistently to be related to mammography screening such as fatalism [28, 29] and cultural norms [9]. The TPB has been used as the primary conceptual model for the development of the assessment survey used in this study [25, 30]. The theory posits that intention is the immediate antecedent of behavior and it is assumed to capture the motivation to behave in a particular way. According to the TPB, intention is determined by three factors: attitude toward the behavior, subjective norms (i.e. social norms), and perceived behavioral control (i.e., perceived ease or difficulty of performing a behavior). The theory is based on the assumption that individuals are rational actors and underlying individual reasons determine one’s motivation to perform a behavior, regardless of whether those beliefs are logical, or correct by some objective standard. The strength of the TPB is that it offers a framework for deciphering individuals’ actions by identifying, measuring and combining beliefs that are relevant to individuals and groups, allowing us to understand their own reasons that motivate the behavior of interest. Several studies [3135] have successfully applied the TPB in mammography screening; however, none of the studies was applied among an AI population. A diagram of the integrated conceptual framework of the TPB is shown in Figure 1.
Figure 1

The proposed expanded model of the Theory of Planned Behavior (TPB). Note. The solid lines refer to a definite direct link between two components, whereas the dotted lines to an indirect link between two components. The squares refer to the TPB constructs and circles refer to additional constructs.

Although well documented reasons are in the literature regarding as to why AI women do not get regular mammograms limited local research has been conducted to determine why AI women in Oklahoma do not get regular screening mammograms [5]. It is imperative that we conduct research at a local level due to the diversity of AI populations in terms of culture, history and health behaviors across regions and tribes [36]. Moreover, important research questions still need to be answered based on the existing literature, such as what the physician’s role is in mammography screening, and to what degree traditionality or Nativeness influence women’s decision whether to get a mammogram. Furthermore, this is the first study to our knowledge that takes place among AI women who live in a non-reservation setting and attempts to examine whether beliefs identified in the literature of women who live on reservations are relevant to this population. For these reasons, it is vital to examine more fully the influences upon AI women’s decisions to get a screening mammogram within a specific geographical location in Oklahoma.

The primary purpose of this study was to identify the beliefs that AI women who live in a non-reservation setting in rural Oklahoma have regarding regular screening mammography by using the aforementioned integrated model of the TPB. The researchers examined the specific salient motivations related to past mammography experience. More importantly, we wanted to find out which beliefs and health- related practices contributed the most to the explanation of obtaining a recent mammogram.

Study design and participants

Data analyzed for this paper were combined from two independent studies conducted at two points in time using similar methodologies, following the Strengthening The Reporting of Observational Studies in Epidemiology (STROBE) statement, and at the same geographic location[37]. The first study took place from 2005–2006. The purpose of the study was to develop a culturally sensitive survey tailored to the sociocultural environment of the priority population. There were eight major methodological steps: a) review of the published literature to identify beliefs relevant to AI women’s mammography behavior and the constructs of the TPB; b) key informant interviews with breast cancer survivors and clinic representatives (n = 9); c) elicitation interviews with 24 women of the priority population followed by two focus groups; d) development of the first draft of the Women’s Health Survey (WHS); e) review of the WHS by a panel of five experts; f) qualitative review of the survey with two focus group discussions (n = 6); g) pilot-testing of the instrument with a representative sample of the priority population (n = 34) that was reviewed for clarity, readability, comprehensibility, and face validity; and h) establishment of the psychometric properties of the instrument and assessment of the prevalence and relative importance of beliefs identified through the use of a random sample (n = 162). The results of the qualitative piece of the formative research have been published elsewhere [38]. Statistical power was insufficient to perform multivariate statistical analyses due to the limited sample size in the first wave of data collection. Therefore, a second study was conducted from 2011–2012 to collect additional data using the same methodological and random sampling approach (n = 93). A commercial software package was used to estimate the necessary sample size (n = 230) [39]. We assumed that 45% of women in the target population undergo regular screening mammography based on our previous studies. Under this assumption, a total sample size of 230 was required to detect an odds ratio of 2.25 or greater associated with a characteristic that is present among half of the participants, for example, when comparing the odds of screening mammography between groups with Positive Attitude construct scores above and below the median, with 80% power. This calculation assumed a two-sided 0.05 alpha level and assumed that 15% of the variability in the characteristic of interest was explained by the other covariate terms in the regression model to account for potential confounding. Finally, it was assumed that up to 15% of surveys could not be used due to missing data or other errors, resulting in a total target of 271 study participants.

The more recent cohort of patients (n = 93) was older (33% aged 40–49, 42% aged 50–59, and 24% aged 60–69 years) than the earlier cohort (n = 162, 53% aged 40–49, 30% aged 50–59, and 17% aged 60–69 years) (Chi-square test for trend, p = 0.0061) and was more likely to have a positive family history of breast cancer compared to the earlier cohort (42% vs. 20%, Chi-square test, p = 0.0002). No other factors differed significantly between the cohorts. The quantitative data sets from the two waves of data collection were merged and analyzed and are the focus of this manuscript.

This study took place at a tribal clinic in Oklahoma among a population of AI women who visited the tribal clinic to obtain health-related services. Potential participants needed to be eligible for screening mammography according to the American Cancer Society guidelines and they were due for the next mammogram within 6 months at the time of entry to the study. The eligibility criteria included women who were asymptomatic of breast cancer and 40–66 years of age. Women were excluded from the study if they worked at the tribal or any other health facility or if they have been diagnosed with breast cancer. The University of Oklahoma Health Sciences Center Institutional Review Board has approved the study.

Recruitment of participants

The research participants were identified from the computerized list of eligible participants for mammography kept at the clinic. This list included age and prior mammography experience. The participants were assigned a number and were randomly selected using a computerized approach or a table of random numbers. Women were invited by phone or in person to participate in the study by a staff member of the clinic or a member of the research team. The response rate in the first wave of data collection was 84% and, 74% for the second wave of data collection with an average response rate across the two waves combined of 79%. The survey was self-administered at the clinic or in a community setting and its administration took 20–30 minutes long.

Survey design

The development of the WHS was based on the methodology suggested by the founders of the TPB [24, 25] and was completed during the first study from 2005–2006. We defined "regular use of screening mammography" as the self-report of a recent mammogram. Therefore, the dependent variable used for the analysis of this paper (i.e. regular use of mammography screening) was based on the question "when was the last time you had a screening mammogram?" accompanied by a scale with four possible answers "During the past 12 months", "2 years ago", "3-5 years ago" and "more than 5 years ago". For data analysis, a dichotomous outcome variable was defined by combining the first two response categories together to indicate "having a regular mammogram within the last 2 years" and the rest of the answers were grouped together and labeled "not having a regular mammogram".

The independent cognitive constructs included attitude, subjective norms, perceived behavioral control, self-efficacy, breast cancer fatalism, breast cancer susceptibility, social modeling, strength of cultural affiliation, and AI beliefs regarding the AI woman’s role in the current AI society. Each construct was measured by an individual scale and by using the Likert scaling method. Most of the scales were developed by transforming comments derived from the elicitation interviews into item statements; however, three scales were borrowed from other researchers (upon receiving their permission) and adapted to the current study. These scales are the Strength of Cultural Affiliation [40] (19 items), Breast Cancer Fatalism [41] (5 items), and the Breast Cancer Susceptibility scale [42] (6 items). Construct validity was assessed for each component using factor analysis with orthogonal (varimax) rotation. The reliability or internal consistency of each scale was assessed using Cronbach’s alpha values as the reliability estimates. The factor analysis resulted in 15 sub-constructs assessed via 82 belief-statements. Regarding the internal consistency of the sub-constructs, Cronbach’s alphas on the sample ranged from 0.65 to 0.96 (14 out of 15 above 0.70), which indicated that WHS is a reliable instrument. A copy of the survey is available from the first author. The name of each subconstruct and the theory it represents, the corresponding number of items, examples of representative items and the Cronbach’s alpha for each of the scale may be found in Table 1.
Table 1

Constructs and representative items

Name of the construct and its related theory

Number of items after factor analysis

Representative items after factor analysis

Cronbach’s αlpha

Intention ( TPB)1

How likely is it that you will obtain a mammogram at a mammography center of your choice within the next 6 months?

Future Mammography Behavior (TPB)

Through medical records and self-reports

Breast Cancer Susceptibility (HBM)2

It is extremely likely that I will get breast cancer.

Positive Attitude ( TPB)

Mammography would help me live longer and watch my children and grandchildren grow.

Mammography would detect breast cancer early.

Mammography would give me peace of mind to find out that I am healthy.

Negative Attitude ( TPB)

Mammography would be wasting my time because mammography cannot detect breast cancer.

Mammography would make me uncomfortable because someone else is handling my breasts.

Mammography would make me afraid to find out if I have breast cancer.

Attitude-Mistrust toward mammography (TPB)

Getting a mammogram it will be wasting my time because mammography cannot detect small size tumors

Perceived Behavioral Control (PBC)-Facilitators (TPB)

Having someone who sets up the mammography for me would make my getting a regular mammogram easier.

Having the mammography facility staff provides me with step-by-step instructions during mammogram would make my getting a regular mammogram easier.

PBC-Barriers (TPB)

It is difficult for me to get my regular screening mammogram because the waiting time in the waiting room at the mammography facility is too long.

It is difficult for me to get my regular screening mammogram because the referral process to receive an appointment is too complex.

Self-Efficacy (scheduling) (SCT)3

I am confident that I can get a mammogram even if I have to find time to schedule a mammogram.

Self-Efficacy (procrastination) (SCT)

I am confident that I can get a mammogram even though I forget to set up the mammogram appointment

I am confident that I can get a mammogram even though I keep putting scheduling the appointment off

Social Modeling (SCT)

If other women know that I get a regular screening mammogram, then they are more apt to go and get a screening mammogram.

By getting a mammogram, I feel that I am setting a good example for other women to follow.

Subjective Norms (family and friends) (TPB)

Breast cancer survivors I know think I should get a regular screening mammogram.

My children think I should get a regular screening mammogram.

Subjective Norms (physician) ( TPB)

My regular doctor/health practitioner thinks I should get a regular screening mammogram

My OB-GYN thinks I should get a regular screening mammogram

Strength of Cultural Affiliation

How much do your home decorations or furniture reflect the influence of your tribe?

How often do you follow your tribe’s typical ways in man-woman relationships?

American Indian beliefs regarding women’s role (leadership role)

Native American women are the "pillar" of their families

Native American women are the primary caretakers of their families

Native American women should be treated with respect and honor

American Indian beliefs regarding women’s role (traditional role)

Native American women should be quiet and reserved

Native American women should be separated from others during menstruation

Breast Cancer Fatalism

I think if someone is meant to get breast cancer, they will get it no matter what they do

I think getting checked for breast cancer makes people scared that they really have breast cancer

1Theory of Planned Behavior.

2Health Belief Model.

3Social Cognitive Theory.

Attitude scores were calculated by multiplying the belief strength (that is the perceived strength of association between the belief and its attributes) of each behavioral belief by the outcome evaluation and then summing the products. The perceived outcomes were measured on a 5-point Likert scale, which ranged from "very unlikely" to "very likely". The evaluation of each outcome was measured on a 5-point Likert scale ranging from "Neither good nor bad" to "extremely good" or "extremely bad" depending on the content of the statement [43]. Multiplying the strength of each normative belief by the woman’s motivation to conform to the opinion of significant referents and then summing the results provided a measure for subjective norms. The strength of the normative belief was measured on a 5-point Likert scale, which ranged from "strongly disagree" to "strongly agree". Motivation to comply with the opinion of the referents was measured on a 5-point Likert scale, which varied from "not at all" to "very much". The presence of the perceived behavioral belief/condition was measured on a 5-point Likert scale, which ranged from "strongly disagree" to "strongly agree". The degree of easiness or difficulty to get a screening mammogram if that condition was present was measured on a 5-point Likert scale, which varied from "not at all" to "very much". The self-efficacy scale was measured with items on a 5-point Likert scale which varied from "sure I could not do it" to "sure I could do it". The sum of the product scores across all five items served as the measure of self-efficacy. The Strength of Cultural Affiliation was calculated according to the designer with the scale [38] and the items were measured with 4-point Likert scales with different endpoints depending on the statement including "never" to "always", "very different" to "very similar", "not at all" to "always", "not at all" to "very much", "no one" to "everyone", "makes no difference" to "very much prefer", and "easier" to "more difficult". The rest of the constructs (i.e. breast cancer perceived susceptibility and breast cancer fatalism) were measured with a 5-point Likert scale, which ranged from "strongly disagree" to "strongly agree". The sum of the product scores across all items served as the measure of breast cancer fatalism and breast cancer perceived susceptibility.

Measures of demographics and clinical characteristics

The WHS also included demographics, clinical characteristics and knowledge of mammography screening. The demographic variables included age, marital status, employment status, income level, educational level, as well as whether the research participants lived in rural areas, and if they had private health insurance. Clinical characteristics included family history of breast cancer, having a primary physician, frequency of visit to the primary physician, frequency of physician breast examination, and frequency of breast-self-examination. All the above variables were treated as categorical variables. Knowledge of mammography screening was measured with four multiple-choice questions with each response coded as correct or incorrect. The number of correct items was totaled to give the knowledge score.

Data analysis

The two waves of data were combined, resulting in 255 participants. Demographic and clinical history characteristics of the participants were categorized, using standard intervals, and were summarized using counts and percentages. Scale scores were analyzed as continuous measures. Independent sample t-tests were used to compare means of continuous measures between two groups, and Chi-square tests were used to test for an association between categorical measures and to compare proportions. Chi-square tests for trend were used when variable categories were ordered. Logistic regression models were fit to identify demographic, clinical history, and psychological factors associated with the odds of self-reported mammography screening within the last 2 years. Univariate models were fit and factors significant at the 0.1 alpha level, as well as age and education as potential confounding factors, were investigated in a multivariate regression model. The final multivariate model was determined using a backward elimination process in which terms that were not significant at a 2-sided 0.05 alpha level and not indicated to be confounding factors were dropped one-by-one until all factors were significant at a 2-sided 0.05 alpha level or acted as confounders. Confounding was indicated by a 10% or more change in the coefficient estimates of other covariates in the model upon removal of the confounding factor from the model. The confounding factors were included in the final multivariate model. Sub-group effects were not considered. The proportion of missing values was no more than 3% for any of the variables included in the regression model. Therefore, missing data analysis techniques such as imputation methods were not used.

Demographic and clinical characteristics of the 255 participants are summarized in Table 2. The participants ranged in age from 40 to 66 years with a mean age of 51.34 (SD: 7.64) years. A majority of women (58%) had some post-high school or college education. Slightly over half of the women were unemployed, roughly half were living alone, 30% reported an income of > $45,000, 35% lived in a rural open country area, and 59% had private health insurance. Approximately 91% reported having a primary physician, 66% reported receiving a breast exam by a physician every one to two years, and 89% reported visiting their primary physician at least once per year. Roughly, one-quarter of the women reported a family history of breast cancer. The majority of the research participants (n = 167, 65%) reported that they had a screening mammogram within the last 2 years.
Table 2

Demographic and clinical history characteristics of participants (N = 255)

40-49 years

50-59 years

Over 60 years

Have children

Less than high school diploma

Graduated high school or completed GED

Some post high school education

College graduate or more

Employment Status

How often have breast exam by physician?

Every year

Every 2 years

Every 3–5 years

Only once/Never

Marital status

Living with someone

Living alone

Have a primary physician?

Have a private health insurance?

Rural area

Visit primary physician at least 1/year?

Family history of breast cancer?

The univariate analysis of demographic, clinical history, and psychological (i.e. the integrated TPB constructs) characteristics associated with self-reported history of screening mammography within the last two years is shown in Table 3. Multiple characteristics differed between respondents who did and did not report a mammogram within the last two years. Those participants who reported screening mammography within the last two years had higher levels of income (p = 0.0001), more regular employment (p = 0.0002), and more frequent physician breast exams (p < 0.0001). Respondents who had received a screening mammography within the last two years were more likely to have a primary physician (p = 0.028), private health insurance (p = 0.027) and a family history of breast cancer (p = 0.0005). Mean psychological scale values were higher among women who reported a mammogram within the last 2 years for the perceived behavioral control-facilitator scores (p < 0.0001), subjective norms physician (p < 0.0001), subjective norms-family (p < 0.0001), knowledge (p < 0.0001), positive attitude toward mammograms (p = 0.0004), and social modeling measures (p = 0.0006), but were lower for the perceived behavioral control barriers (p < 0.0001), strength of cultural affiliation (p = 0.0006), negative attitude toward mammograms (p = 0.0011), mistrust toward the effectiveness of mammography screening (p = 0.0091), traditional Native American belief measures (p = 0.0019), and breast cancer fatalism (p < 0.0001).
Table 3

Univariate analysis of demographic, clinical history and psychological variables

Self-reported screening mammography within last 2 years

Yes (N = 167)

No (N = 86)

Categorical variables

n (%)

n (%)

Age group

40-49 years

71 (43%)

44 (51%)

50-59 years

63 (38%)

23 (27%)

60-69 years

30 (18%)

19 (22%)

Less than high school diploma

21 (13%)

15 (18%)

Graduated high school or complete GED

45 (27%)

23 (27%)

Some post high school education

71 (43%)

38 (45%)

College graduate or more

28 (17%)

8 (10%)

80 (48%)

20 (23%)

14 (8%)

9 (11%)

73 (44%)

56 (66%)

How often have breast exam by physician?

Every year

109 (66%)

26 (31%)

Every 2 years

21 (13%)

9 (11%)

Every 3–5 years

24 (14%)

18 (21%)

Only once/Never

12 (7%)

31 (37%)

33 (20%)

32 (40%)

70 (43%)

35 (43%)

61 (37%)

14 (17%)

Marital status

Living with someone

92 (55%)

39 (45%)

Living alone

75 (45%)

47 (55%)

Have a primary physician?

156 (93%)

73 (85%)

Private health insurance

107 (64%)

43 (50%)

Rural areas

60 (36%)

27 (32%)

Visit primary physician at least 1/year?

150 (90%)

73 (85%)

Family history

58 (35%)

12 (14%)

Continuous variables

Mean (SD)

Mean (SD)

P-value b

Perceived susceptibility toward breast cancer

2.51 (0.92)

2.46 (0.95)

Perceived behavior control-facilitator

17.31 (5.72)

13.99 (6.33)

Perceived behave control-barrier

3.87 (3.55)

7.75 (5.33)

Self-efficacy- scheduling

4.40 (0.85)

4.21 (0.90)

Self-efficacy -procrastination

4.01 (1.03)

3.85 (1.01)

Subjective norms-physician recommendation

22.47 (4.42)

17.34 (7.08)

Subjective norms-family influence

20.74 (4.99)

17.45 (6.42)

Strength of cultural affiliation

1.12 (0.74)

1.48 (0.88)

Knowledge of mammography screening guidelines

3.04 (1.00)

2.31 (1.26)

Positive attitude toward mammography

21.77 (4.34)

19.52 (5.43)

Negative attitude toward mammography

5.27 (3.34)

7.09 (5.35)

Negative attitude-mistrust

6.17 (4.27)

7.89 (5.95)

Social modeling

4.22 (0.84)

3.78 (1.15)

Native American beliefs (leadership role)

3.92 (0.79)

4.09 (0.88)

Native American beliefs (traditional role)

1.84 (1.02)

2.30 (1.28)

Breast cancer fatalism

11.42 (4.04)

14.4 (5.18)

aProportions compared between groups using a Chi-square test and a Chi-square test for trend when response options included more than two ordered categories. bMeans compared between groups using an independent sample t-test.

Table 4 includes a summary of the final multivariate logistic regression analysis of the odds of self-reported screening mammography in the last two years after adjustment for age and education, which acted as confounding factors. The odds of reporting a past mammogram within last 2 years were higher for the women who were more likely to be influenced by their physicians (OR = 1.15, 95% CI: 1.06-1.24), had more knowledge about mammography screening guidelines (OR = 1.52, 95% CI: 1.00-2.31), had a family history of breast cancer (OR = 9.97, 95% CI: 3.05-32.62), and had more frequent professional breast exams (every 3–5 years with OR = 1.68, every 2 years with OR = 3.67, every year with OR = 5.57). The odds were lower for the women who were more culturally affiliated (OR = 0.42, 95% CI: 0.24-0.74), had higher fatalism scores (OR = 0.90, 95% CI: 0.82 to 0.90), and had higher perceived behavioral control barrier scores (OR = 0.86, 95% CI: 0.78 to 0.94).
Table 4

Multivariate logistic regression analysis a of the odds of self-reported screening mammography within the last two years

Standard error

Odds ratio (OR)

Lower 95% CI for OR

Upper 95% CI for OR

Subjective norm-physician

Cultural affiliation

Fatalism sum

Perceived behavior control-barrier

Family history (Ref = No)

How often have breast exam by physician (Ref = only once/never)

Every 3–5 years

Every 2 years

Every year

aMultivariate model adjusted for age and education.

The purpose of the study was to identify factors predictive of regular mammography screening among AI women who lived in a non-reservation setting in rural Oklahoma. The results of this study, along with the results of follow-up qualitative research, are being used to plan an intervention to promote mammography screening in this particular region.

One important question that this study attempted to answer was the role that the physician plays in AI women’s decision to get a screening mammogram. To the best of our knowledge, this is the first study among AI women that provided clear evidence that physician recommendation is an important motivating factor of screening mammography. Furthermore, research participants who had a physician breast examination every year were roughly six times more likely to get a recent mammogram than those who never had a physician breast examination or who had only once in their lifetime. This finding underscores the importance of the physician as a gatekeeper in the promotion of screening mammography as supported by the literature [1215]. This finding also indicates the importance of having in place clinic-based policies and procedures, such as a checklist of possible topics to discuss with the patient about mammography screening during her clinic visit, which will facilitate and support a physician recommendation.

The role that the clinic plays also is emphasized though the fact that women who perceived fewer environmental behavioral control barriers, related to the referral process, scheduling a mammogram, and waiting for an appointment, were more likely to get a mammogram. This underscores the importance of the clinical setting and that it must be conducive to mammography screening. Most of the research conducted in this area among AI women has focused on the lack of access to mammography screening or lack of culturally sensitive care [6, 19]. In our study we were able to identify specific barriers related to scheduling and referral processes of mammography screening as well as barriers related to the facilities where the mammography is taking place. Overall, the women who utilize the services of the clinic are satisfied with the quality of services provided, which included the scheduling and referral services for mammography screening. Nevertheless, opportunities likely exist to build upon and enhance a clinic team-based approach to promote breast cancer screening among patients. The Centers for Disease Control and Prevention (CDC) in collaboration with the American Cancer Society provides an evidence-based framework for promoting cancer screening in clinical settings [44]. The guide, which may be used as a template, suggests to increase cancer screening, physicians, nurse practitioners, physician assistants and their office managers collaboratively focus on developing a systematic approach toward physician recommendation, supportive office policies (e.g. an algorithm of current mammography screening recommendation guidelines), effective reminder systems, and skillful communications such as the use of decision aids.

Regarding the barriers related to the mammography facilities, one has to keep in mind, that the study took place at a tribal clinic where mammograms are scheduled in other facilities through the contract health department of the clinic. Therefore, working with the various facilities in the region where women get their mammograms is beyond the scope of this study; however, it is useful for the clinic officials to be aware of any factors (e.g. long waiting hours) associated with the mammography facility because those factors can affect a woman’s decision to get a mammogram.

Another interesting perceived barrier found was that women who kept putting off scheduling a mammogram were less likely to get a mammogram. Procrastination is an indicator of an underlying fear, which also has been captured through prior qualitative research conducted by our team [38]. A possible consequence of the presence of underlying fear is that women may not show up at the mammography facility even if they have scheduled their mammograms. The problem of "no-shows" is an important issue for clinics nationwide and account for 13% to 23% of scheduled appointments [45, 46]. Based on the first preliminary study conducted back in 2005–2006 some of the reasons women cited for not showing up for their mammogram appointments were expected, such as last minute conflicts. However, other unexpected reasons arose such as not wanting to get a mammogram in the first place and perhaps being afraid of voicing it out to the medical staff.

Similar to the fear concept is fatalism. AI women who expressed more fatalistic attitudes toward mammography and breast cancer were less likely to get regular mammograms. Cancer fatalism is the belief that an individual’s health is beyond their control and that survival is based on luck, fate, and destiny [47]. A woman’s perception of cancer as a death sentence may hinder her from seeking early detection, early diagnosis and treatment. Limited studies examining breast cancer fatalism exist especially among AI women [5, 48]. Fatalistic beliefs have been associated with the avoidance of cancer-related information. In one study, researchers found that fatalistic beliefs were correlated with being less positive about early cancer detection and more fearful about seeking help for a suspicious symptom [49]. With regards to breast cancer screening, studies have indicated that after controlling for education and economic status, fatalism was prevalent among poorer and less educated populations [50]. To understand breast cancer fatalism and its impact on early diagnosis screening among AI women, it is vital to address the interrelationship between fatalism and the web of poverty. Within the AI community, historical issues of political and social conflicts are often the root of social inequalities. The disparities existing within AI community members have affected the health care sector especially in the fight against chronic diseases such as cancer. Inadequate access to quality health care, medical mistrust of Western medicine, and a lack of understanding about cancer, screening, and treatment are some of the leading factors that affect cancer health experiences and views. Fatalism, along with fear, is a perception that is formed for a long time through one’s sociocultural context and it is too difficult to uproot within the limitations of a 3-year project. On the other hand, fatalism in this study was marginally negatively associated with age (p = 0.08), but significantly negatively associated with knowledge about mammography screening (p = 0.008). Therefore, one possible way to counteract fatalism is by providing knowledge about mammography screening, specifically information on survival rates, and by having AI women who are breast cancer survivors share their experiences with other women, especially younger women whose beliefs and feelings are more amenable to change. By doing that, we will "plant the seeds" for future efforts taken by the broader AI community that will enable AI women to overcome their fatalistic attitudes about breast cancer and become less fearful in terms of getting regular mammograms.

The importance of knowledge of mammography screening is further highlighted in the results of this study and supported by the existing literature [5]. Knowledge is a necessity for any behavioral change but not sufficient to promote behavioral modification especially when it takes place in a community setting [51]. According to the social ecological model [5254], to develop sustainable and effective interventions, all levels of intervention must be addressed including the intrapersonal (e.g. knowledge), interpersonal (e.g. social modeling), community (e.g. educational events), policy (e.g. use of a flowchart of the current mammography screening recommendation guidelines) and societal (e.g. change in the cultural norms).

Another unique finding is the more traditional a woman was in terms of her Nativeness, the less likely it was that she would get a recent mammogram. This finding sheds some light onto an existing debate in the literature regarding the role Native identity plays in getting a regular mammogram. Interestingly enough, after conducting some additional data analysis, no statistically significant association was seen between the strength of cultural affiliation neither with age nor with fatalism. However, based on additional data analysis, we found that cultural affiliation is associated with employment status and income levels. Unemployed and lower income women were more likely to be more traditional. Therefore, unemployment and income may confound the association between cultural affiliation and recent mammogram behaviors. Nevertheless, the results of the study are clear; the more traditional AI women were, the less likely it was that they had a recent mammogram. One possible explanation for this finding is that women with higher cultural affiliation may be more likely to rely on traditional medicine and not value preventative medicine as a way of maintaining health. Other possible reasons, as they were expressed in the literature, are that traditional women may not get mammograms due to feelings of invasion, modesty, and mistrust or fear of using the Western health care system [5, 8]. Therefore, to reach AI women who are more traditional in terms of their native identity, it is important to try to change their overall perceptions about the health care system, regarding not only care, but also prevention. This task could be difficult to achieve because of the long lasting impact of the historical trauma these women experienced.

This study has several limitations. The health behavior information, including frequency of mammography, was based on self-report, which may not be accurate. There is a potential for sampling bias, due to non-response bias, given that not all women who were invited to participate actually agreed to complete a survey; however, with a response rate of 79%, non-response bias is not a major concern. Results from the sample of AI women who lived in a non-reservation setting in rural Oklahoma are reflective of the beliefs, knowledge and health practices of the targeted population and may not be generalizable to all AI women.

Breast cancer is an important public health issue among AI women. The results of this study shed some light on approaches that can be taken to intensify efforts to promote mammography screening, the single most effective modality of early breast cancer detection, among AI women who live in a non-reservation rural setting. Emphasis could be given on promoting physician recommendation, physician breast examination and eliminating environmental barriers. Fatalistic attitudes toward breast cancer do exist among AI women. As such, long-term interventions within the AI communities may be appropriate to reduce or eliminate breast cancer-related fatalism and fear and to increase knowledge about breast cancer screening guidelines.

American Indian

Centers of disease control and prevention

Confidence intervals

Odds ratio

Social cognitive theory

Socio-economic status

Strengthening the reporting of observational studies in epidemiology

Theory of planned behavior

Women’s health survey.

This publication was made possible by grants from three different funding sources. These are: The Presbyterian Health Foundation, The Peggy and Charles Stephenson Cancer Center, and the Susan G. Komen®. Its contents are solely the responsibility of the authors and do not necessarily represent the official views of the above funding sources. We are grateful to all the women who participated in the study and the leadership of the Native American tribe for their continuous support to this study.

Authors’ Affiliations

Department of Health Promotion Sciences, College of Public Health, University of Oklahoma Health Sciences Center
Department of Biostatistics and Epidemiology, College of Public Health, University of Oklahoma Health Sciences Center
Institute for Health Research and Policy, University of Illinois at Chicago
Department of Preventive Medicine and Public Health, University of Kansas School of Medicine

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jueves, 15 de agosto de 2013

Stanford scientists sequence genome of human's closest invertebrate relative

ORIGINAL: Stanford
By Bjorn Carey
August 14, 2013

Botryllus schlosseri is humans' closest living invertebrate relative. Chris Patton
At first glance, Botryllus schlosseri has very little in common with humans. The small sea creature fuses together with others to form colonies that look like psychedelic blobs, encrusting rocks and seaweeds. It can reproduce asexually, and an entire individual can be regenerated from its blood vessels alone.

And yet, Botryllus is humans' closest living invertebrate relative. (Invertebrates lack a spinal column.) Now, a group led by Stanford scientists has sequenced its genome, making it possible to find the genetic basis for some of the animal's amazing regenerative abilities and immunity features, which potentially could be applied to human medicine.

In total, the group sequenced the animal's 580 million base pairs of DNA. (The human genome, by comparison, consists of more than 3 billion base pairs.) Though the researchers haven't studied the entire genome, they found evidence that Botryllus makes a useful invertebrate model for studying human genetics, in particular for highlighting the evolution of immunity and stem cell-mediated regeneration.

The researchers compared the Botryllus genome with several vertebrate and invertebrate genomes. Focusing on genes involved in various human diseases – affecting things such as heart and eye development, pregnancy and cancer – they found homologous genes for each in Botryllus, far more matches than in any of a dozen other invertebrates commonly used in research.

An additional investigation of blood-related genes revealed that Botryllus was probably the first invertebrate to have vasculature in the same context of the human circulatory system, with blood cells traveling through blood vessels.

For example, in looking at a set of 20 genes that encode for humans' hematopoietic stem cells – cells that can self-renew and differentiate into other types of blood cells – they found 14 that are also expressed in cells isolated from the Botryllus stem cell niche. The scientists are now investigating how these genes function in Botryllus.

The study of Botryllus' genome could also lead to advances in transplant medicine. When two genetically distinct Botryllus colonies come into contact with each other, they either fuse their blood vessels to create a single organism, or reject one another and maintain individuality. When the blood vessels between the two colonies fuse into one interconnected network, the stem cells from each partner colony begin to circulate throughout the other.

In some instances, particularly concerning transplants of bone marrow or hematopoietic stem cells, the recipient's body rejects the donor cells. Voskoboynik suspects that studying the genetic basis for this interaction in Botryllus could lead to improvements in human therapies.

An important byproduct of the research, Voskoboynik said, was that Botryllus' complicated genome required the team to develop a new sequencing technique. The method, which has been patented, yielded exceptionally long, accurate sequences of DNA.

Media Contact
Ayelet Voskoboynik: (831) 655-6244, ayeletv@stanford.edu

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36 terms

Weathering and Erosion

Mrs. Arnold Pages 86-115
the breaking down of rocks into smaller pieces by physical or chemical processes.
Mechanical weathering
(also called physical weathering) the breaking down of rocks by physical processes including temperature extremes, ice, water, and the activities of living things (biological weathering).
Ice wedging
the mechanical weathering process in which water in the cracks of rocks freezes and expands, widening the cracks.
Chemical weathering
the breaking down of rocks by chemical processes. The reactions change the chemical structure of the minerals, producing an entirely new mineral.
(the most common form of chemical weathering) the breaking down of a compound by a chemical reaction with water. During hydrolysis, water dissolves minerals, which drain into lower layers of rock and soil, causing the minerals to concentrate into mineral ore deposits below the Earth's surface.
Acid rain
the result of sulfur dioxide, nitrogen oxides, and carbon dioxide reacting in the atmosphere with water and returning to the Earth as rain, fog, snow, sleet, or dew.
the process in which carbonic acid reacts chemically with other substances. The process can form underground caverns, stalactites, and stalagmites.
a chemical change in which a substance combines with oxygen. Example--iron (Fe) combines with oxygen (O) to form rust (Fe2O3). (the 2 and 3 should be subscripts)
the surface features of a place or region, which affects the rate of weathering.
the rapid downhill movement of a large amount of rock and soil. Landslides can be triggered by earthquakes, volcanic eruptions, spring thaws, or heavy rains.
Mass wasting
the downhill movement of loose rocks and soil due to gravity.
the loose layer of rock and soil.
a large block of soil and rock that slides downhill along a curved slope, forcing the rock mass to tilt backward.
the rapid downhill movement of a large mass of mud.
Soil creep
the extremely slow downhill slide of soil.
the slow movement of soil down a steep slope.
the lower layer of soil in Arctic regions that stays permanently frozen.
the wearing down of rock surfaces by other rocks or sand particles.
Rock pedestals
mushroom-shaped rocks that form when sand particles eat away at the rock's bases. The sand particles are too heavy to reach the top of the rock, so the top does not get worn away.
Deflation hollows
soil depressions scooped out by the wind.
mounds of sand deposited by the wind; they usually form in deserts and on beaches.
water—usually from precipitation—that flows over the land; it is a constant source of erosion because it washes away particle of silt and soil. Note--because of gravity, water always flows to the lowest point.
a narrow ditch formed when water runs down a hill or mountain.
an area of land that drains into a particular river system. For example, the Chesapeake Watershed includes Delaware, the District of Columbia, Maryland, New York, Pennsylvania, Virginia, and West Virginia. All of these states have land that sends water into the Chesapeake Bay.
the path that a stream flows. Networks of channels drain into a river to form a watershed.
the ridges and other elevated regions that separate watersheds.
a flat area along a river formed by sediments deposited when the river overflows, usually providing rich soil for farming.
Dams & Levees
built to control floods; dams are concrete structures built on a river to regulate its flow, while levees are made of an earthwork construction built up to stop water from flowing in a specific direction. The protection of a levee is temporary, and as rivers deposit more sediment, the levee must be made higher.
a fan-shaped deposit of sediments deposited at the mouth of a river.
a wide, shallow bay at the mouth of a river valley that shelters fish and birds.
a large mass of moving ice. (An iceberg is a large floating mass of ice that has detached from a glacier and has been carried out to sea.)
Glacial drift
sediments deposited by glaciers.
unsorted rocks and sediments left behind when a glacier melts.
a large ridge or mound developed from till; pronounced muh-reyn'.
long tear-shaped mounds of till formed by advancing glaciers; example: Bunker Hill.
large boulders transported by glaciers; they give us clues about the direction and distance that glaciers traveled.


Dakota & Amelia

There are so many great things about this dynamic duo that will bring so much joy
to a family! Dakota and Amelia are in need of a patient family that can keep them
together and maintain a relationship with their youngest sibling. Although these
two love each other, there are still rumblings of sibling rivalry with a medley of
toddler mischief. They need a lot of one on one attention and would thrive in a
home as the only children or youngest children in the home. Due to their medical
and therapeutic needs, Dakota and Amelia would do best in a home with a stay at
home parent with a flexible schedule. Despite all of the progress these two have
made, they will continue to need a family that can provide them the assistance,
love and encouragement that they need to develop and grow.

Dakota is an energetic and curious little man that thrives on extra attention. He is
a loving, helpful, silly and funny child who is often seen with a captivating smile on
his face. Dakota enjoys playing with his toys, playing outside and playing in water.
His favorite toys are mega blocks, cars, trucks and his little workbench with tools.
Dakota enjoys the one on one attention of being read to. His favorite television
shows are Mickey Mouse,

Amelia is a vibrant and friendly toddler that lacks self-awareness at times. She is a
loving, happy and sweet child who is often seen with a beautiful smile on her face.
Amelia enjoys playing outside, playing in water and climbing anything she can. Her
favorite toys are dolls, ponies and anything that lights up and makes noises. Amelia
loves to watch Barney, Minnie Mouse and Daniel Tiger. Her favorite food is


Promising results from ED intervention with adolescent substance users

September 2016
Tait, R.J., Teoh, L., Kelty, E., Geelhoed, E., Mountain, D. and Hulse, G.K. (2016). Emergency department based intervention with adolescent substance users: 10 year economic and health outcomes. Drug and Alcohol Dependence, 165, pp. 168-174.

There are few data on the long-term impacts of brief interventions, particularly with youth. This paper reports the 10 year outcomes and compares major health costs following a randomized controlled trial. Significant reductions were found for alcohol and drug emergency presentations. Large but non-significant differences were found for most cost areas.

Background: Alcohol and other drug (AOD) use are significant cause of disease burden and costs among adolescents.

Methods: We conducted a randomized trial in hospital emergency departments (ED) following an AOD-related presentation, comparing usual care with brief advice and referral to link adolescents aged 12–19 years with external AOD services. Subsequently, we used health data linkage to assemble data on mortality, hospital admissions, ED attendances, out-patient mental health and use of opiate pharmacotherapies in the next 10 years. From these, treatment costs and rates of events were estimated and compared using generalized linear models.

Results: Those who received the intervention had lower costs ($22 versus $227: z = 3.16, p = 0.002) and rates (0.03 versus 0.25: z = 2.57, p = 0.010) of ED mental health AOD presentations. However, the intervention did not significantly reduce overall mean health costs per patient (intervention $58746 versus control $64833, p = 0.800). Similarly, there was no significant difference in the costs associated with hospitalizations ($48920versus $50911 p = 0.924), overall ED presentations ($4266 versus $4150, p = 0.916), out-patient mental health services ($4494 versus $7717, p = 0.282), or opiate pharmacotherapies ($1013 versus $2054, p = 0.209). Injecting drug use was a significant baseline predictor of subsequent costs in the cohort (z = 2.64, p = 0.008).

Conclusions: An ED delivered intervention may reduce direct ED costs and subsequent ED AOD attendances. There was also some indication that overall costs may be impacted, with economically large but non-significant differences.


GREY SWAN: What is it? What’s the relationship to the Black Swan?

Grey Swan

DEFINITION of ‘Grey Swan’

Black Swan

A black swan is an event or occurrence that deviates beyond what is normally expected of a situation and is extremely difficult to predict; the term was popularized by Nassim Nicholas Taleb, a finance professor, writer and former Wall Street trader. Black swan events are typically random and are unexpected.

The idea of a black swan event was pioneered by the financial professional turned writer Nassim Nicholas Taleb after the results of the 2008 financial crisis. Taleb argued that black swan events are impossible to predict yet have catastrophic ramifications. Therefore, it is important for people to always assume a black swan event is a possibility, whatever it may be, and to plan accordingly. He also used the 2008 financial crisis and the idea of black swan events to point out if a broken system is allowed to fail, it actually strengthens it against the catastrophe of future black swan events.

Examples of Past Black Swan Events

The financial crash of the U.S. housing market during the 2008 crisis is one of the most recent and well-known black swan events as of 2016. The effect of the crash was catastrophic and global, and only a few outliers were able to predict it happening. Also in 2008, Zimbabwe had the worst case of hyperinflation in the 21st century with a peak inflation rate of more than 79.6 billion percent. An inflation level of that amount is nearly impossible to predict and can easily ruin a country financially.

The dot-com bubble of 2001 is another black swan event that has similarities to the 2008 financial crisis. America was enjoying rapid economic growth and increases in private wealth before the economy catastrophically collapsed. Since the Internet was at its infancy in terms of commercial use, various investment funds were investing in technology companies with inflated valuations and no market traction. When these companies folded, the funds were hit hard, and the downside risk was passed onto the investors. The digital frontier was new, and therefore it was nearly impossible to predict the collapse.

As another example, the previously successful hedge fund Long Term Capital Management (LTCM) was driven into the ground in 1998 as a result of the ripple effect caused by the Russian government’s debt default, something the company’s computer models could not have predicted.

Grey Swan Definition | Investopedia

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Greenmount Notaciones
Calidad cuándo Funciona: 3.3
Consistencia de Olas: 3.3
Dificultad: 2.3
Windsurf y Kitesurf: 2.0
Gente al Agua: 1.7

Overall: 3.4

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Surf Report Feed

Estadísticas de Olas para Greenmount, septiembre: Todo Oleaje – Todo Viento

This image describes the range of swells directed at Greenmount over a normal September, based on 2400 NWW3 model predictions since 2006 (values every 3 hours). The wave model does not forecast wind and surf right at the coast so we have chosen the optimum grid node based on what we know about Greenmount. In the case of Greenmount, the best grid node is 19 km away (12 miles).

The diagram suggests that the dominant swell direction, shown by the largest spokes, was ESE, whereas the the dominant wind blows from the NNE. Because the wave model grid is away from the coast, sometimes a strong offshore wind blows largest waves away from Greenmount and out to sea. We group these with the no surf category of the bar chart. To simplify things we don't show these in the rose diagram. Because wind determines whether or not waves are good for surfing at Greenmount, you can select a similar diagram that shows only the swells that were predicted to coincide with glassy or offshore wind conditions. During a typical September, swells large enough to cause clean enough to surf waves at Greenmount run for about 1.0% of the time.


Monster Grouper Landed On A Packed Beach In Naples, FL

There are anglers out there who will fish for days or weeks to connect with a true giant. Sure they could catch plenty of small fish but that’s not their goal. The reality is that there are less large fish than small ones and the bigger ones have gotten to their immense size by being wary.

One of the largest fish species in the world is the giant grouper. Anglers who live in coastal areas where this fish frequents know that the grouper is an unrivaled fighter. This beast will outsmart you, spool your reel or bust up your tackle in a hurry if you’re not careful. The grouper also is referred to as brindle bass, brown spotted cod, Queensland grouper and bumblebee grouper.

Grouper Size and Diet – The largest bony fish that can be found in coral reefs is the grouper. The fish can weigh as much as 880 pounds and reach a length of 8.9 feet. However, the ocean is a vast place of mystery and still holds many secrets. Unconfirmed reports would indicate that some groupers swimming in the ocean are larger still. Some believe that giant groupers can weigh over 1300 pounds and reach astounding lengths of 14 feet. Groupers are opportunistic feeders. They’ll take a swipe at fish, sharks, seabirds, turtles or anything else that appeals to them. Groupers also won’t hesitate to make a meal out of dead animals.

Overfishing Concerns – Many people believe that ocean fish are not vulnerable to overfishing as compared to inland lakes and rivers. They figure that since the ocean is so large, it would be impossible to wipe out a given species. That belief is actually a myth. In the past several decades, biologists and governments alike have become alarmed at drastic declines in fish populations due to overfishing. Commercial fishermen and hobby anglers caused much of this decrease. By the 1990s, the giant grouper was given a vulnerable status by the IUCN. It should come as no surprise that the largest fish of this species have taken a long time to get that big. When a fish like that is removed from the water, it requires quite a few years to produce another one of that size.

Appearance – During the grouper’s juvenile stage, the coloration of the fish is black and yellow. Once giant or goliath groupers reach adulthood, their appearance changes to grey-brown and green-gray. Black spots also cover the fish and the tail is rounded. The giant grouper has a huge mouth much like a largemouth bass though on a much larger scale. This makes it a formidable predator to many marine animals.

Rods and Reels – Small or cheap rods and reels just won’t cut it with this bruiser. You’ll need to use the heaviest tackle available and thick braided line. A high-quality reel with a flawless drag system is crucial. If your drag locks up while you’re doing battle with this monster, it ‘ll bust your line in a hurry. The fish could also rip the pole out of your hands or even pull you into the water.

Selecting a Bait – If you want to go after a giant grouper, you have to use big baits. If you only fish with small ones, most of the time you’ll only catch small fish. There are a variety of effective baits that you can try for groupers. One option is using a dead bait. There’s no need to worry about keeping your baitfish alive in this case which is convenient. You just throw out that dead piece of meat and wait for a hungry dinner guest. You still can use live bait and there are times when a lively fish will become a quicker meal than a dead bait. The key is to experiment and see what’s working on a given day.

If live or dead baits aren’t your thing, you can use artificial lures to draw a strike from a giant grouper. You’ll need something that can get you down to the bottom of the water source where you plan to fish. Weighted lures are going to be key. Lure options include deep diving plugs, jigs and jerk baits. Favorite colors of fishermen are usually pink and orange.

Where to Fish – Obviously, you’re going to need to head to the coast for groupers. But not just any coastal area will yield giant groupers. As ocean fish go, groupers are shallow-water dwellers who make their home in the tropics. They like to live around artificial reefs or coral. Typical depths that you’ll find giant groupers at is in the 16 to 164-foot range. Specific areas to target the grouper include the Florida Keys, Brazilian coastline, anywhere in the Caribbean and the Bahamas. Although it’s uncommon, the grouper is occasionally found in the coastal waters of Maine and Massachusetts.

Learn the Rules – It’s important to know and understand the fishing laws of the area you plan to target groupers. Recent conservation efforts across the globe have been implemented. Countries and states are different in the specifics of their regulations but all aim to take better care of this giant. The fish cannot be harvested in the Caribbean or the United States, for instance. That doesn’t mean that you can’t practice catch and release, though. You can still snap a picture of your catch before releasing it. Another thing in the fishing world that is growing in popularity is an alternative to traditional fish mounts. You can measure your fish and take a photograph so that a replica of your catch can be made. This allows the fish you caught to live to fight another day but you still get a trophy to hang on your wall.

Give It a Try! – If you’re looking for an angler adventure that includes line-sizzling encounters, grueling battles and amped up adrenaline, the giant grouper should be your fish of choice. Thousands of anglers all across the world love the opportunities that this species of fish offers. If you hook into a grouper, you’ll definitely develop a newfound respect for the species. They are truly one-of-a-kind. Although grouper fishing can be challenging, with the right gear, knowledge and increasing experience, you’ll be way well on your way in the pursuit of this beast.

More From Swince
About The Author
As a freelance writer for 14 years, Benjamin has contributed articles for news outlets in a variety of industries. Benjamin has covered stories on entertainment, pop music, NFL news, trending celebrity gossip, movie reviews and more.
A graduate in Journalism and a member of the Professional Basketball Writers Association (PBWA), Benjamin loves sports and plays basketball during his free time.
Benjamin is also i big cooking nut. He makes hand made pasta from scratch and his favorite dishes are Italian.


CTI professor leads research for best practices in skill-transfer training

February 25, 2013

Military professionals are continuously finding new ways to improve their technology in order to ensure their missions are successful and completed at the most efficient level possible. Generally, the field of psychology is often unrelated to military technological advances, but one ASU psychology professor considers the contribution to be substantial.

Nancy Cooke, a professor in the Applied Psychology Department at the College of Technology and Innovation (CTI), is the science director for the Cognitive Engineering Research Institute on the Polytechnic campus. Cooke has been studying the collaborative dynamics of teams and how their interactions affect their functionality. Her research aims to measure a team’s cognition in order to find new ways to make teamwork more effective. Download Full Image

“Any group working toward a common goal can be considered a team: a basketball team, a military group, a surgical team,” Cooke said. “When we study how these teams communicate and reveal their group dynamics, we can potentially discover how to make that process an effective one.”

Part of Cooke’s research is studying the habits of Improvised Explosive Device (IED) detection experts and analyzing how they can best transfer their skills to novices through training. Considered vital to the military, IED detectors are responsible for remotely detecting explosive devices in an area. Detectors scan an area using satellite and video imaging in order to spot anything out of the ordinary and report it to ground officials.

With the support of research grants from the Air Force Research Lab, the project hopes to uncover cognitive underpinnings that demonstrate a marked difference in the detection abilities of experts versus the detection abilities of novices. Analysis of experts is expected to reveal ways to transfer expert skills to novices through training.

Participants are seated at a video screen where they are given various scenarios. Using eye tracking software, Cooke is able to verify what cues these experts are looking for and compare that to how novices are viewing an image.

“This work has the most potential to save lives because IEDs are not visible,” she said. “They are killing so many people, but they’re remotely controlled. Our work will hopefully improve how this training is occurring.”

Cooke says there will always be a need for IED detection experts because IED creators often find ways to hide an explosive device that can trick electronic IED scanners.

Cooke is also studying how to best train pilots for unmanned aerial systems (UAS), commonly known as drones. Currently, the Federal Aviation Administration allows limited UAS missions involving public interest, such as disaster relief, search and rescue, border patrol, military training and law enforcement missions, but the FAA is working to develop a path for safe integration of civil UAS into the airspace.

“There is such a need for UAS pilots, and I am studying the human factor side of UAS training which includes the design of workstations, integration of systems that include a human element and best practices for training pilots specific to this field,” Cooke said.

Experts suggest that the demand for UAS pilots will grow as the FAA begins integrating civil UAS flights into national airspace.

Written by Sydney B. Donaldson, College of Technology and Innovation


The Rubber Band Theory

I hate self-help books because they’re cheesy.  Then,  a few years ago, the cheesiest self-help book of all landed on my lap:  Men are from Mars, Women are from Venus. The analogies are excessive, but quite a few of the theories in the book seem  applicable to my own life.  The theory that most applies in this very instant is—The Rubber Band Theory.

The theory states the following: Men have an “intimacy cycle” where they get close to their girlfriend, enjoy the intimacy, and then need to back away and get some man time. They eventually become saturated with man time and come in for more intimacy.  It’s a cycle.

Women respond to this cycle in one of three ways:

1) They get it and relax during the stretch part of the relationship because they know things will be okay on average

2) They freak out and chase after him, which only makes him pull away even further to get the man time he wants. Sometimes the chasing/pulling away gets so extreme that it sours the whole relationship

3) They get angry and promise to not make the first move. This works as it gives the dude his space, but, the woman doesn’t enjoy it and can become bitter/jaded.  This is the bucket that I always land in.

G.I. Joe (my boyfriend) is a man’s man. He’s also a teddy bear.  I have always appreciated this juxtaposition but never connected it to the Rubber Band Theory until right now.

Teddy Bear: I have never dated anyone quite as affectionate as him.  He is the first to say that he wants to stay in and just hang out with me…”I’m in a you mode,” he’ll say.  He doesn’t care what people think and is never shy about public affection when we’re at school (I’m getting my MBA, remember?).  He lets me in on his crazy stream of conscious thoughts.  When he’s like this it becomes abundantly clear that I am his favorite person.

Man’s Man: Loves xbox. Loves playing  Rugby with the boys. Loves working out and lifting weights.  Loves his beer. Loves watching sports on his huge TV.  When he goes out with the boys (I’m usually there with other people…it’s a small town = not many bars) I notice that he’s just talking in a corner with his 4 buddies drinking beer.  He’s a veteran for Christ’s sake and literally made a living blowing things up.

Right now, he’s in man’s man world.  I was getting really f-ing angry about this until I remembered the rubber band theory.   I like the teddy bear in him, but the only reason that teddy bear part exists is because he balances it out with man’s man time.  Also, one of the draw backs of dating in business school is that you see your partner all the time. There is no space which must have an accelerator effect on normal relationship behavior.

Crap. I’m sounding like one of those cheesy romantic self-help books but it’s true, I’ve had this epiphany and I wanted to share it.

Lets see how it goes…I have lots of homework to do anyway and lots of plans set up this week.  I’ll make this lady week and reevaluate in 7 days to see how tense/lax the rubber band has become.

Getting Back Together….Again.

My relationship history exemplifies a very, very troubling trend:  I tend to get back together with my exes.

Why? Maybe I’m a sucker for romance. Maybe I believe his promises too easily. Maybe I’m hopeful and generally willing to giving second chances.

No really, why? Premature pulling of the trigger. When I breakup with someone, I usually do it because something happened and my discontent or frustrations hit a boiling point.  I tend to make rash decisions when I feel like that and then suffer from second thoughts.  People get back together with their exes when the relationship feels unfinished.  Relationships feel unfinished when the decision to breakup is made prematurely or without full information—you need to be pretty sure that things should end before you can totally walk away from someone.

Results? Clearly, the whole getting back together thing hasn’t panned out before given that all of those relationships eventually ended.

So why am I getting back together with GI Joe: He is the one who pulled the trigger. Though I still question our long term compatibility, this has been a great relationship and I was not ready to end it.  With that said, the breakup was really painful and I am scared sh*tless about trying again, being made a fool and getting hurt  a few weeks/months from now.  I’m scared, but it always felt unfinished therefore I am willing to give it another shot.

With that said: This is the last time that I will ever get back together with a man after breaking up.  I am making that a new years resolution and lifetime promise…..this is the last data point I will need before concluding that the pattern of breaking up/getting back doesn’t work for me.


Discretionary Justice

Pardon and Parole in New York from the Revolution to the Depression

336 pages

9 halftones

December, 2016

ISBN: 9781479899920

Add to Cart Available: 11/18/2016

Also available in

Carolyn Strange is a Senior Fellow at the Australian National University. She has published extensively in the fields of criminal justice history and the history of gender and sexuality. A specialist in modern North American history, her work, spanning the fields of history, criminology, law, and gender studies, has appeared in leading journals in the U.S. Canada, Britain and Australia. She has published and edited eight books

All books by Carolyn Strange

The pardon is an act of mercy, tied to the divine right of kings. Why did New York retain this mode of discretionary justice after the Revolution? And how did governors’ use of this prerogative change with the advent of the penitentiary and the introduction of parole? This book answers these questions by mining previously unexplored evidence held in official pardon registers, clemency files, prisoner aid association reports and parole records.

This is the first book to analyze the histories of mercy and parole through the same lens, as related but distinct forms of discretionary decision-making. It draws on governors’ public papers and private correspondence to probe their approach to clemency, and it uses qualitative and quantitative methods to profile petitions for mercy, highlighting controversial cases that stirred public debate. Political pressure to render the use of discretion more certain and less personal grew stronger over the nineteenth century, peaking during constitutional conventionsand reaching its height in the Progressive Era. Yet, New York’s legislators left the power to pardon in the governor’s hands, where it remains today.

Unlike previous works that portray parole as the successor to the pardon, this book shows that reliance upon and faith in discretion has proven remarkably resilient, even in the state that led the world toward penal modernity.

  • Exploiting a wide range of new sources, this original and innovative book illuminates the importance of the criminal law to race, gender, and social and political power in America from an entirely new perspective. It puts the spotlight on prison reform and capital punishment at the state level in the most important jurisdiction in the country. An invaluable contribution to understanding the complex history of criminal law and punishment over 150 years.

    —Douglas C. Hay, Professor Emeritus, York University

  • This book offers a wonderful history of pardon and parole and, at the same time, a sophisticated analysis of discretionary justice. I know of no other book like it. Focusing on the state of New York, it is a pleasure to read. Scholars interested in understanding the complexities of pardon and parole and the rise of the administrative state will find this book to be an invaluable resource.

    —Austin Sarat, Amherst College

  • For good reason, issues of criminal law and criminal justice in the United States recently have become a subject of both popular and academic interest. While scholars of law and history have done much to explore the problems and perspectives in the past that have helped give rise to the workings of criminal justice in the present, much more needs to be done, particularly in the less familiar areas of criminal law, like pardon and parole. This book offers a welcome exploration of how and why New York state handled those less visible aspects of criminal law up through the first decades of the twentieth century. In the process of unpacking New York’s pardon and parole systems, it helps us understand the nature of discretionary justice and the ways in which law and politics could and did intersect.

    —Elizabeth Dale, Professor, Department of History & Levin College of Law, University of Florida


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Volume 30, Issue 3

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Los Angeles, Calif. -- Everbridge today announced that it has launched a first of its kind social and critical communications solutions suite that enables organizations with the ability to gather and evaluate real-time intelligence from social media as part of its communications strategy.  The new solution provides organizations with a single, interactive communications console to not only monitor a situation and gather external intelligence using real-time social media, data feeds and updates from the field, but also effectively take action by sending notifications and fostering interaction with individuals or groups using lists, locations and visual intelligence such as geo-mapping

With the new Everbridge system, organizations can mine and monitor information in the broad social universe (such as Twitter) that is relevant to them by defining key topics, phrases, and events by geographic area, and establishing targets and thresholds that when achieved will automatically initiate notifications to administrators and users.  Essentially, the new Everbridge system enables organizations to capitalize on the virtual “eyes and ears” of the social universe and cut through the “noise” to provide the real-time, highly relevant data that they need to monitor situations such as emergency incidents, weather related events, and corporate activities. These capabilities in combination with the Everbridge system’s powerful mass notification solution can be used to initiate communications to individual or groups of recipients through a series of escalating contact paths (landline, email, SMS, mobile phones and mobile applications).  Ultimately, the Everbridge system allows administrators to utilize real-time information from multiple sources, guarantee the delivery of critical information to recipients and provide the most comprehensive incident lifecycle management possible.

“Social media, an increasingly mobile society and an overwhelming amount of data sources can often complicate the ability of organizations to adequately and efficiently manage potentially harmful events,” said Imad Mouline, chief strategy officer, Everbridge.  “With the new Everbridge system, we harness the power of this information and offer our clients a powerful combination of real-time insight, and communications solutions that equip them with the capability to command and control critical activities.”

Given the pervasiveness of social media, Forrester, a global research and advisory firm, recently published a paper that evaluated the relevance of social media in crisis communications.  In “It’s Time To Include Social Technology In Your Crisis Communication Strategy”, Forrester concludes that “The value of social networking sites — facilitating many-to-many relationships and discussions targeted by self-selected individual interest — offers unique advantages in the crisis communications arena.”

The Solutions:

Everbridge Interactive Visibility allows users to integrate real-time information from social media, recipient feedback, and data feeds into a single communications console.  This allows decision-makers to simultaneously monitor events and communicate efficiently to designated recipients using insight gathered from multiple sources.  By providing users with simultaneous visibility and interactivity, decision-makers are able to use real-time data gathered from multiple sources to make better informed decisions and manage the lifecycle of critical incidents with increased efficiency and speed.

Everbridge Mass Notification enables users to send notifications to individuals or groups using lists, locations, and visual intelligence from anywhere at any time.  Dynamic escalation rules automate message delivery based on the order of contact paths which can be set by administrators or recipients and only stops once the recipient confirms receipt. This ensures that each recipient receives their intended notification. GIS-based capabilities provide an additional contact strategy which allows the administrator to send messages to recipients in a specific geographic region defined by zip code, street address, radius from a specific point or using drawing tools on interactive maps and uploaded shape files.

About Everbridge

Everbridge provides industry-leading interactive communication and mass notification solutions to organizations in all major industries and government sectors.  Everbridge solutions increase connectivity to key audiences, automate communication processes, and integrate recipient feedback, data feeds, and social media in a single communications console.  Ultimately, these solutions provide the insight and infrastructure that help clients save lives, manage critical activities and improve the efficiency of daily operations. For more information about, please see http://www.everbridge.com/.