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What does it mean to be me?

Do you want to tell me about this person that stands before you?

Before you answer, think!

Will your depictions of who I am be ridiculously stereotypical?

Maybe it will be shallowly and thoughtlessly appropriate for you to assume,

Or maybe even wander into the realm of offensive misrepresentation with no connection to reality at all.

You abuse me,

Robbed me of my sense of power.

When I strive to be looked up to and identify with.

You misrepresent my power, my identity, leaving nothing to my legacy.

Trying to shape our consciousness,

Leaving nothing but a racist experience.

I am Visible.

My people are not a dwindling population, as people of the past.

We are modern,

We are successful,

We are talented,

We construct new forms of self-representation.

Look at me!

I do not stand alone.

We will expand and proliferate from here!

Transition into Daylight Savings Time (DST) affects sleep pattern and functionality

    

    Circadian Rhythms are physical, mental, and behavioral changes that follow a roughly 24-hour cycle that responds primarily to light and darkness in an organism’s environment (National Institute of Health, 2008). One factor that causes disruption to circadian rhythms is daylight savings time switch during the spring season, where there is an hour of time lost. This change causes disruption to sleep patterns; i.e. loss of sleep, as well as disruption in functionality; i.e. inability to perform a task effectively. In the current study, it is hypothesized that the daylight savings time switch affects sleep pattern and functionality. Twenty three subjects; nine males and fourteen females, between the ages of twenty one and thirty seven (mean age = 26.2 years), completed the study. Subjects kept track of their sleep pattern by filling out a five variable; time in bed, time out of bed, sleep latency, amount of sleep, and fatigue rate, sleep log for a total of fifteen days; ten days acquired during the two weekends prior to the DST switch (baseline condition), and five days acquired the weekend during which the DST switch occurred (experimental condition). A paired-samples t test design was employed for analysis that compared subjects sleep pattern and functionality during the daylight savings time switch to prior to the switch occurring. The results show that during the weekend that the daylight savings time switch occurred, participants experienced more fatigue, took less time to fall asleep, and slept less during the night. The findings of this study were supported by previous literature which suggests that delayed sleep pattern affects sleep and morning function (Yang and Spielman, 2001). It also gave way to possibility of conducting future research in the area of daylight savings time such as how daylight savings time switch affects individual’s time of day (morning or evenings) preference for sleep and functioning.

Transition into Daylight Savings Time (DST) affects sleep pattern and functionality 

    Circadian Rhythms are physical, mental, and behavioral changes that follow a roughly 24-hour cycle that responds primarily to light and darkness in an organism’s environment (National Institute of Health, 2008). It is found in most organisms and when disrupted it is capable of changing sleep-wake cycles, the release hormones, body temperature and other important bodily functions (National Institute of Health, 2008). One factor that causes disruption to circadian rhythms is daylight savings time switch during the spring season where there is an hour of time lost. This change in time affects circadian rhythms which in turn causes disruption to sleep patterns; i.e. loss of sleep, as well as disruption in functionality; i.e. inability to perform a task effectively. Kalat (1995) reported on a study conducted by Kleitman (1963), who established that changes in circadian rhythm affects sleep pattern in humans. Using a twenty eight hour a day schedule for two subjects, Kleitman showed that one subject had trouble awakening at scheduled times and the other had trouble sleeping and could not adjust to the twenty eight hour a day schedule.

Valdez, Ramirez, and Garcia (2003) also conducted a study to examine if how small changes in sleep; losing an hour or two, have a large impact on sleep patterns. The researchers found that some individuals did not immediately adapt to DST and took several days in order to do so, and thus altering their sleep pattern.

To better understand the impact of daylight savings time (losing an hour of time) on sleep patterns and functionality, a study was conducted using a paired-samples t test design in which subjects recorded their sleep pattern as well as their fatigue rate, for days that included two weekends prior to the daylight savings time switch and one weekend during which the time switch occurred. We hypothesized that the daylight savings time switch affects sleep pattern and functionality.

Method
Participant

    Initially, twenty four subjects; ten males and fourteen females, were included in this study. However, one participant was terminated due to failing to report their sleep log. Twenty three subjects; nine males and fourteen females, between the ages of twenty one and thirty seven (mean age = 26.2 years), completed the study. Each of the participants that took part in the study met the following requirements: All participants were City College Graduate Students attending experimental psychology class, and were identified using a six code system in the form of a constant-vowel-constant-number-number-number; i.e. DAN012.

Design

    Two conditions were conducted in the study; a control (baseline) condition and an experimental condition, and each subject participated in both conditions. In the baseline condition; sleep pattern prior to Daylight Savings Time (DST) switch, subjects were required to report their average of ten days sleep pattern which occurred during the two weekends prior to the DST switch, and in the experimental condition; sleep pattern during Daylight Savings Time (DST) switch, subjects were required to report their average of five days sleep pattern which occurred the weekend during the DST switch. An analysis of the data was then preformed using a Paired-Samples T Test design.

Measures
    Subjects were required to fill out a sleep log that consisted of five sleep variables; time in bed, time out of bed, sleep latency, amount of sleep, and fatigue level. Each of these variables were divided into the two conditions described above; sleep pattern during the two weekends prior to the DST switch; (baseline) condition, and sleep pattern during the weekend the DST switch occurred; (experimental) condition.

Procedures

    The study consisted of two procedures: The first procedure involved subjects keeping track of their sleeping patterns by filling out a sleep log (attached) for a total of fifteen days. Ten days of the sleep log data was acquired during the two weekends prior to the DST switch, and five days of the sleep logs were acquired the weekend during which the DST switch occurred. Sleep logs were recorded each week beginning on Friday and ending on Tuesday. Data for Friday was recorded on Saturday, Saturday’s data was recorded on a Sunday, Sunday’s data was recorded on a Monday, and so forth, until the appropriate fifteen days worth of data was accounted for.

In addition, the sleep variables (described above) with the exception of fatigue were measured using standard time units (hours: minutes: seconds). The fatigue level was measured on a Likert Scale ranging from one (lowest fatigue) to ten (highest fatigue).

The second procedure of the study required each participant to convert their data in order to find the average of their week’s log: the average of the two weekends (combined) prior to the DST switch, and the average of the weekend during which the DST switch occurred. Investigators then pooled their data and formed one complete data sheet to conduct appropriate analysis.

However, it is important to note that before the analysis was conducted, the sleep variable; “Time in Bed”, was converted from standard time units to minutes before and after 12 o’clock midnight. The time was therefore based on direction. For instance, if a subject reported that they entered into bed at 11:00:00 p.m., using 12:00:00 a.m. as the center point, their time in bed would be recorded as – 60 minutes. Similarly, if their time in bed is 1:00:00 a.m. it would be recorded as 60 minutes. The above process allowed the investigator to clearly identify the time of day (a.m. or p.m.) subjects entered into bed.

Results

    It was hypothesized that Daylight Savings Time (DST) switch will affect sleep pattern and functionality. The data from the study was analyzed using a “Paired-Samples T Test design.” The results were as follows:

The mean time in bed for subjects during the weekends prior to the Daylight Savings Time (DST) switch was; (M = 0:100:09 = 1:40:09 a.m. [S.D. = 0:235:625 = 4:05:25 a.m.]); the mean for subjects during the weekend of DST switch was; (M = 0:75:48 = 1:15:48 a.m. [S.D. = 0:98:300 = 1:43:00 a.m.]) (See table 1). This difference was not statistically significant, (t (22) = 1.57, p > .05). During the DST switch participants entered into bed approximately the same time as prior to the time switch occurring.

Paired Samples Statistics
		Mean	N	Std. Deviation	Std. Error Mean
Pair 1	TIB - Prior to DST switch	100.09	23	235.625	49.131
	TIB - During DST switch	75.48	23	98.300	20.497

Analysis also showed that there was no difference (t (22) = .92, p > .05), in the time out of bed for participants prior to the DST switch; (M = 8:41:45 a.m. [S.D. = 1:22:03 a.m.]), and during the DST switch; (M = 8:26:13 a.m. [S.D. = 2:01:29 a.m.]) (see Table 2). Participants woke up at approximately the same time during both conditions; prior to and during the daylight savings time switch.

Paired Samples Statistics
		Mean	N	Std. Deviation	Std. Error Mean
Pair 1	TOB - Prior to DST switch	8:41:45.652	23	1:22:03.191	0:17:06.556
	TOB - During DST switch	8:26:13.043	23	2:01:29.174	0:25:19.898

    

 There was however a significant difference between the baseline and experimental conditions among three of the sleep variables; sleep latency, amount of sleep, and fatigue rate. The mean sleep latency for subjects during the weekends prior to the DST switch was; (M = 0:17:31 [S.D. = 0:12:08]); the mean for subjects during the weekend of DST switch was; (M = 0:14:28 [S.D. = 0:11:02]) (see Table 3). This difference was statistically significant, (t (22) = 2.07, p = .05). During the weekend that the DST switch occurred, participants took less time to fall asleep than they did the weekends prior to the DST switch.

Paired Samples Statistics
		Mean	N	Std. Deviation	Std. Error Mean
Pair 1	SLAT - Prior to DST switch	0:17:31.261	23	0:12:08.203	0:02:31.841
	SLAT - During DST switch	0:14:28.609	23	0:11:02.859	0:02:18.216

    The mean amount of sleep for subjects during the weekends prior to the DST switch was; (M = 7:45:53 [S.D. = 0:55:35]); the mean for subjects during the weekend of DST switch was; (M = 7:22:20 [S.D. = 0:53:22]) (see Table 4). This difference was statistically significant, (t (22) = 3.20, p < .01). Participants slept more during the weekends prior to the DST switch than they did during the weekend the DST switch occurred.

Paired Samples Statistics
		Mean	N	Std. Deviation	Std. Error Mean
Pair 1	Amt Of Slp - Prior to DST switch	7:45:53.478	23	0:55:35.572	0:11:35.515
	Amt Of Sleep - During DST switch	7:22:20.870	23	0:53:22.644	0:11:07.797

The mean fatigue rate for subjects during the weekends prior to the DST switch was; (M = 3.72 [S.D. = 1.12]); the mean for subjects during the weekend of DST switch was; (M = 4.26 [S.D. = 1.34]) (see Table 5). This difference was statistically significant, (t (22) = 3.00, p < .01). Participants were more fatigued during the weekend the DST switched occurred compared to the weekends prior to the DST switch.

Paired Samples Statistics
		Mean	N	Std. Deviation	Std. Error Mean
Pair 1	FR - Prior to DST	3.7174	23	1.12033	.23360
	FR - During DST Switch	4.2609	23	1.33544	.27846

Discussion

    The current study has shown that daylight savings time switch significantly affects the time it takes to fall asleep, the total amount of sleep, as well as the fatigue rate experienced by subjects. During the weekend that the daylight savings time switch occurred, participants experienced more fatigue, and took less time to fall asleep. However, they slept less during the night. These findings suggest that the circadian rhythm is disrupted by time and that this disruption impacts sleep pattern and functionality.

The findings of this study were particular interesting for two reasons: First it is supported by previous literature and second, it gives way for the development of new theories in future research. Earlier findings in research suggest that changes in time affects sleep pattern and functionality. Yang and Spielman (2001) conducted a study on how delayed sleep pattern affect sleep and morning function. They delayed subjects’ sleep pattern by two hours on Friday and Saturday night and found that subjects had a harder time sleeping Sunday night as well as experienced lower cognitive performances on Monday. In addition, a study done by Barnes and Wagner (2009) showed that changes to daylight savings time not only hindered sleep (losing an hour), but also led to higher injuries in the workplace.

The findings in this study can be use to possibly conduct a more in-depth research in the area of daylight savings time and how it may affect individuals time of day (morning or evenings) preference for sleep and functioning. While there is little research on morning or afternoon preference and daylight savings time, Schneider and Randler (2009) found that daylight savings time transition caused higher day time sleepiness for those adolescents who prefer evenings.

The results of the current study show that there may be other factors that may impact individual’s sleep pattern and functionality. Two of those factors are substance use and behavioral activities. Participants in this study may have attended social events or worked a night shift schedule which will in turn affect their sleeping pattern as well as their functionality. In addition, substance use may have also accounted for the difference in sleep pattern and functionality between the two conditions; weekends prior to DST switch and the weekend during which the DST switch occurred. Participants may have hindered their sleep pattern and functionality by taking substances such as caffeine, sleeping medication and alcohol.

The Effects of Depression and Fatigue on Gender and Sleep Pattern

   Depression is a medical illness that results in an intense feeling of sadness, a loss of interest in things that one once enjoyed, fatigue, etc, and fatigue is the feeling of tiredness or exhaustion due to a lack of strength or energy that may result from one being overworked, worried, depressed, etc (WebMD, 2004). Depression and fatigue are known to affect men and women differently, with one possible symptom being over sleeping; known as hypersomnia (AllAboutDepression, 2010). In the current study, it is hypothesized that gender differences contributes to the level of depression and fatigue experienced by individuals, which in turn affects individuals total amount of seep time. Twenty two subjects; nine males and thirteen females, between the ages of twenty one and thirty seven (mean age = 26.2 years), completed the study. Subjects filled out a sleep log that consisted of one sleep variable; amount of sleep, as well as the “Fatigue Severity Scale” questionnaire and the “Zung Self-Rating Depression Scale”. Their gender was also documented. A “Bivariate Correlations” design and an “Independent-Samples T Test” design were also employed for analysis. The results show that the level of depression and fatigue experienced by subjects is not significantly affected by gender difference and that when participants sleep more during the nights their level of fatigue and feelings of depression moderately decreases. The findings in this study were not supported by previous literature which suggests that women are twice as likely as men to experience depression and fatigue (Nolen-Hoeksema, 2001) and that these feelings do not get better with bed rest but may cause one to feel tired and sluggish (AllAboutDepression, 2010 & KidsHealth, unknown). 

    The effects of depression and fatigue on gender and sleep pattern
According to WebMD (2004), depression is a medical illness that results in an intense feeling of sadness, a loss of interest in things that one once enjoyed, fatigue, etc. Whereas, fatigue is the feeling of tiredness or exhaustion due to a lack of strength or energy that may result from one being overworked, worried, depressed, etc (WebMD, 2004).

   WebMD, 2004 also notes that depression and fatigue, while seeming independent of each other, can also occur in a cycle which makes it difficult to determine whether one causes the other. Findings from researchers were quoted; “people who are depressed are more than four times as likely to develop unexplained fatigue, and those who suffer from fatigue are nearly three times as likely to become depressed” (WebMD, 2004).

   Depression and fatigue are known to affect men and women differently. Song, Jason, Taylor, Torres-Harding, Helgerson, and Witter (2002) conducted a study on the relationship between fatigue, age, and gender in an urban sample and found that African American women had significantly higher rates of fatigue when compared to African American men (Song, et al. 2002). In another study done by Nolen-Hoeksema (2001), it was reported that women are twice as likely as men to develop depression.

   One possible symptom that occurs in individuals who are feeling depressed and fatigued is over sleeping; known as hypersomnia, where the person sleeps for prolonged periods of time at night or increases their amount of sleep during the day (All About Depression, 2010). Findings also shows that feelings of fatigue and depression does not get better with bed rest and one may even feel tired and sluggish after having excess sleep (All About Depression, 2010 & KidsHealth, unknown).

   To better understand the impact of depression and fatigue on gender and sleep pattern, a study was conducted using a “Bivariate Correlations” design and an “Independent-Samples T Test” design in which subjects recorded their gender, their level of fatigue and the amount of depression felt over a one week period. Each participant filled out the Zung Self-Rating Depression Scale, the Fatigue Severity Scale questionnaire, and recorded and averaged the amount of time slept in their sleep log for thirty consecutive days. It was hypothesized that gender differences contributes to the level of depression and fatigue experienced by individuals, which in turn affects individuals total amount of sleep time.

Method
Participant
   Initially, twenty three subjects; ten males and fourteen females, were included in this study. However, two participants were terminated due to failing to report their questionnaires. Twenty two subjects; nine males and thirteen females, between the ages of twenty one and thirty seven (mean age = 26.2 years), completed the study. Each of the participants that took part in the study met the following requirements: All participants were City College Graduate Students attending experimental psychology class, and were identified using a six code system in the form of a constant-vowel-constant-number-number-number; i.e. DAN012.

Design

   The study consisted of four variables: Three descriptive variables; gender, depression, and fatigue, and one sleep variable; total amount of sleep time. It focused on whether gender differences contributes to the level of depression and fatigue experienced by individuals, and also on if depression and fatigue level affects individuals total amount of sleep time. An analysis of the data was performed using a “Bivariate Correlations” design and an “Independent-Samples T Test” design.

Measures

   Subjects were required to fill out a sleep log that consisted of one sleep variable; amount of sleep, as well as a questionnaire recording their gender, their level of fatigue and the amount of depression felt over a one week’s period. Each participant filled out the Zung Self-Rating Depression Scale, the Fatigue Severity Scale questionnaire, and recorded the amount of time slept, for example, 8 hours, 30 minutes, 10 seconds, in their sleep log for thirty consecutive days.

Procedures

   The study consisted of three procedures: The first procedure involved subject’s filling out questionnaires recording their gender and their levels of depression and fatigue felt for seven days. Depression was recorded using the Zung Self-Rating Depression Scale, where subjects read several statements and decided how much of the time the statement described how they have been feeling over a week’s period. Subjects measured whether the statement represented their feelings by checking one of the following categories: “a little of the time”, “some of the time”, “good part of the time”, or “most of the time” which represented the numbers one (lowest) to four (highest) respectively. Subjects then scored their results by adding together the number that was representative of each category checked for each statement.

   Fatigue was recorded using the Fatigue Severity Scale, where subjects read several statements and circled a number from one (lowest) to seven (highest), depending on how appropriate they felt the statement applied to them over a week’s period. A low value indicates that the statement is not very appropriate, and a high value indicates agreement with the statement. Participants scored their results by adding together the number circled for each statement to get their total score.

   The second procedure involved subjects keeping track of their total amount of sleep by filling out a sleep log each day for thirty consecutive days. The sleep variable was measured using standard time units (hours: minutes: seconds) and was recorded for each day in the following manner: Data for Sunday was recorded on Monday, Monday’s data was recorded on Tuesday, Tuesday’s data was recorded on Wednesday, and so forth, until thirty days worth of data was accounted for. Participants then averaged their one month’s; thirty days, of sleep time.

   The third procedure involved investigators pooling participant’s data in order to form one complete data sheet to conduct appropriate analysis.

Results

   It was hypothesized that gender differences contributes to the level of depression and fatigue experienced by individuals, which in turn affects individuals total amount of seep time. The data from the study was analyzed using a “Bivariate Correlations” design and an “Independent-Samples T Test” design. The results were as follows:

   A Bivariate Correlation was computed to assess the relationship between gender and the level of depression and fatigue experienced. There was a weak positive correlation between gender and depression, r = .268, n = 22, p > .05 (Table 1), which indicates that gender differences does not accurately predict the level of depression experienced by participants. Analysis using an Independent-Samples T Test design showed that there was no difference (t (20) = - 1.24, p > .05), in the level of depression for genders: Males; (M = 30.78 [S.D. = 8.62]), and Females: (M = 34.85 [S.D. = 6.76]) (Table 2). The level of depression experience by participants for a one week’s period was approximately the same for both men and women.

   There was however, a moderate positive correlation between gender and fatigue level, r = .412, n = 22, p > .05 (Table 3). Thus, gender differences moderately predict whether participants fatigue rate will increase. However, Analysis using an Independent-Samples T Test design showed that there was no difference (t (20) = - 2.02, p > .05), in fatigue severity for genders: Males; (M = 18.67 [S.D. = 5.10]), and Females: (M = 23.54 [S.D. = 5.84]) (Table 4). Fatigue severity can be, to some extent, predicted by gender differences, however the prediction showed to be minimal since both men and women in the study experienced approximately the same level of fatigue.

   A Bivariate Correlation was computed to assess the relationship between subject’s average total amount of sleep time for thirty days and the level of depression and fatigue experienced. There was a moderate negative correlation between the participant’s average thirty day total sleep time and the level of fatigue felt for seven days, r = - .306, n = 22, p > .05 (Table 5). Increases in the amount of sleep were moderately correlated with decreases in the level of fatigue (Graph 1).

   There was a moderate negative correlation between the participant’s average thirty day sleep and the level of depression felt for seven days, r = - .395, n = 22, p > .05 (Table 6). Therefore, increases in the amount of sleep were moderately correlated with decreases in the level of depression (Graph 2).

Discussion

   The current study has shown that the level of depression and fatigue experienced by subjects is not significantly affected by gender difference. During the seven day time period, men and women experienced the same level of fatigue and feelings of depression. The study also showed that when participants sleep more during the nights, their level of fatigue and feelings of depression moderately decreases. These findings suggest that the severity of depression and fatigue does not affect men and women differently, and also both conditions can be decreased if the amount of time spent sleeping is increased.

   The findings of this study were particular interesting for two reasons: First it was not supported by previous literature and second, it gives way for the development of new theories in future research. Earlier findings in research suggest that women are more likely than men to experience depression and fatigue. Song, Jason, Taylor, Torres-Harding, Helgerson, and Witter (2002) conducted a study on the relationship between fatigue, age, and gender in an urban sample. Using 3,692 subjects, they investigated the impact of age and gender on fatigue severity and found that African American women had significantly higher rates of fatigue when compared to African American men (Song, et al. 2002).

   Also, study done by Nolen-Hoeksema (2001) reported that women are twice as likely as men to develop depression. In this study, Nolen-Hoeksema indicted several reasons for why women are more prone to depression. These included but were not limited to; due to women possessing less power and status than men, women are more prone to experiencing certain trauma such as sexual abuse, because of women’s negative self concepts, and their coping styles such as their inability to take action to relieve their distress (Nolen-Hoeksema, 2001).

   In addition, earlier findings in research also suggest that individuals who are depressed feels more fatigued and sleeps longer, which does not alienate or decrease the level of fatigue and depression, but instead serves as a symptom. All About Depression (2010) notes hypersomnia (over sleeping) as a possible symptom that occurs in individuals who are feeling depressed and fatigued. All About Depression (2010) & KidsHealth (Unknown) also notes that feelings of fatigue and depression does not get better with bed rest, but may cause one to feel tired and sluggish.

   The findings in this study can be use to possibly conduct a more in-depth research in the area of sleep and how it may affect individuals feelings of depression and fatigue. Most findings suggest that fatigue and depression can be caused by a lack of sleep; as noted by WebMD (Unknown); “lack of sleep caused by another medical illness or by personal problems can make depression worse”, but there are however little research done on hypersomnia (over sleeping) and its effects on depression and fatigue.

   The results of the current study show that there may be other factors that may impact individual’s feelings of depression and fatigue, and their amount of time spent sleeping. Two of those factors are substance use and behavioral activities. Participants in this study may have attended social events, or have an early work and/or school schedule which will in turn affect their amount of sleep time and even lead to one feeling fatigue and depressed due to the amount of activity being done. In addition, substance use may have also accounted for the feelings of depression and fatigue, and their amount of time spent sleeping. Participants may have hindered their sleep pattern and feelings of depression and fatigue by taking substances such as caffeine, sleeping medication and alcohol.

Baton Rouge: 3 Police officers, gunman dead in shooting. President Obama calls it "the work of cowards"
https://www.yahoo.com/news/baton-rouge-police-shooting-live-000000633.html?.tsrc=fp_liveblog

7 Food For Stress Relief

http://www.eatingwell.com/nutrition_health/mind_body_spirit/7_foods_for_stress_relief

"Buss"

https://soundcloud.com/vitchous/buss

Reggae music

                       My life is filled with joy to create the sound of my art "Music"

Luck of the Irish! http://www.travelpirates.com/flights/luck-of-the-irish-cheap-flights-from-multiple-us-cities-to-dublin-from-dollar-294_4092

Netflix Password:
https://www.yahoo.com/news/won-t-jail-sharing-netflix-130133733.html?nhp=1

Turkey rounds up thousands of military personnel: http://www.nytimes.com/2016/07/17/world/europe/turkey-attempted-coup-erdogan.html?_r=0

The new eco trend: Clothing made from mushrooms.
https://www.facebook.com/playgroundenglish/videos/304170569916280/

Tivoli, Jamaica; http://jamaica-gleaner.com/article/news/20160715/tivoli-gardens-police-post-attacked-residents-protest-teens-killing-cops

Turkey Quashes Coup;
http://www.cnn.com/2016/07/15/asia/turkey-military-action/

Let's go to the beach for cheap...

http://www.travelpirates.com/vacationpackages/hold-on-to-your-panama-hat-7-night-panama-beach-escape-just-dollar-382-pp-incl-flights-beachfront-condo-car_4065

Nice, France Truck Attack: Senseless loss of life.

http://www.cbsnews.com/news/deaths-reported-after-truck-plows-into-crowd-in-nice-france/#

Twitter nominates Dallas Police Chief David Brown for president: https://www.yahoo.com/news/dallas-police-chief-david-brown-000000570.html?nhp=1

Elections

It amazes me how much candidates belittle each other. Are we suppose to dismiss what they told us? that the other will ruin this country? See link "'Far and away the best': Sanders finally endorses Clinton" https://www.yahoo.com/news/clinton-sanders-set-appear-together-hampshire-072947495--election.html

Change

The tensions between black citizens and police has risen over the past week, between police shootings of African-American men in Minnesota and Louisiana and the gunning down of five white police officers by a black suspect in Dallas in apparent vengeance. We need change. When will this ever stop?