As many of you know the BANS sites have some what of a footprint.

“Powered by Build A Niche Store”

If you search for that term in your favorite search engine you will see thousands of BANS powered sites.

Finding a niche that no other BANS user has discovered isn’t going to be easy with the popularity of BANS.

You can however increase your chances of not duplicating another BANS user if you are looking to be truly unique.

Just put your niche in the search query along with “Powered by Build A Niche Store” in quotes. This will turn up any website that has the powered by logo turned on and related to the niche you are searching for.

Remember, this isn’t foolproof because some BANS users choose not to display the powered by logo for this simple reason, they don’t want to be discovered easily by their competitors.

I’ll give you an example …

Do a search for - go kart parts

Now do a search for - go kart parts “Powered by Build A Niche Store” and you will see how many BANS sites have targeted the go kart parts niche.

Happy NICHE hunting…

The premise is that there is lots of cool stuff for sale on E-Bay. Also, direct links to a site helps google find the site and wordpress has more respect in Google’s eyes than a BANS site.

So I am thinking of having the BANS site and a wordpress blog. Every day I will highlight 1 specific auction in a post. Should take a very short time to do so, copy the pic and add some copy. 5 minutes at the most.

But the money question is, how do I link to a single item through my BANs account or CJ PID?

Even if I have to the individual item I can put boiler plate that sends people to the BANS site. ie If you like this item, please visit our Used Widget Store to find hundreds like it.

So any suggestions would be welcome on how to make this idea work. I truly think the combination of wordpress and BANs is a winning combination from an SEO and synergistic perspective.

I would like to know how to intergrate bans into joomla myself rather that be a component + module or a mambot.

The downfall I see with bans for the most part is it isn’t setup like a blog like joomla. Joomla when you make a update to your site. It automatically send out a ping for the search engine spiders to come visist your site again.

Been using joomla for years now and know it inside and out.

One thing with Joomla! though is that isn’t really a blog, it is a content management system. Wordpress, TypePad, those are blogs. Yes Joomla can be used as a blog but talk about overkill! Same goes for Drupal.

Maybe I’m the minority here, but I’m not sure of the point of integrating BANS into something complex like Joomla. Wordpress maybe, but even then every example I’ve seen the store is a secondary part of the site and I wonder how much traffic that actually gets. To me, I want a store so I use something like BANS. I want my traffic to come because it is a store, thereby increasing the possibility of a sale. A blog is meant for a different audience, a different user. Sure you can still have a store attached, but there are easier ways of integrating ebay feeds into a blog or other site. That isn’t to say you shouldn’t have any content on your store, as you probably should to get the casual searcher, help with SEO, etc.

Besides, there are far easier ways to make money from a blog than attaching a store to it. Just my opinion anyway.

BANS JOOMLA INTEGRATION

I like the easy to use menu structure of the BANS site which allows users to easily find what they want and the search function which allows them to search ebay auctions for what they want.

In Wordpress I like the way a post can easily be set up to add more content to you site and the wealth of Wordpress plug-ins that do a varietly of amazing and helpful things.

When the BANS-Wordpress integration was announce I eagerly installed it but was disappointed in the fact that rather than combining the best of both you were really coring out the innards of a Wordpress site and filling it with BANS so you basically had BANS in a Wordpress shell that no longer had any of the Wordpress benefits.

Has integration gone any further? I notices some people on the forum are marketing an integrated product. Does it combine the power of both platforms? Thanks in advance for your help

I got home today and received an email from my hosting company stating that my hosting service and 6 of my domains had all been suspended and disabled. They stated this was due to a violation of their terms and conditions. They included a technical support ticket number for me to reference. ?

Their support system was the only thing I could access. All of my domains stated that my web service had been terminated. My email servers were not allowing me to authenticate, and I couldn’t access my FTP servers.

I accessed the tech support system, and the ticket stated that my services were disabled because Lacsote had sent them a letter to shut me down. They stated that I was selling counterfeit Lacoste products on my website.

The website in question was a Big and Tall Men’s fashion store. I had the BANS software pulling big and tall men’s fashions into several categories, one of which was Lacoste.

Build a niche store - BANS

I contacted my hosting co’s support, and when I gave them the ticket number, they had me hold because a manager wanted to handle the issue. I had to explain the eBAY affiliate program to them, and that I did not own, possess, actually sell, or ship any of these products. I explained that I was referring business to eBAY in exchange for referral commission.

They stated that they could give me Lacoste’s phone number and I could discuss it with them, otherwise I would need to respond to the support ticket stating that I would comply with their request to remove all of their products from my website. Once I did that they would re-enable my site, and I would have 24 hours to bring the site into compliance.

Build a niche store - BANS

If Lacoste had a problem with any of the products that showed up in my BANS store, I wish they could have gone to the source (i.e. the actual eBAY seller that possessed the product) instead of whacking my hosting. That pisses me off, but tells me that they didn’t understand what they were looking at. I’m not interested in any drama, and don’t have the nerves or energy to put up a fight with a big company like Lacoste. So I agreed to pull any references to their products down. I was able to access my site, and replaced the index.php with a temp page.

So that’s about where I’m at. I was pulling down quite a few first page google listings with this site, and was doing well with it. I really just wanted to post this to vent a bit. But also to let anyone else that might be running any clothing stores and have any Lacoste products showing up on their page to watch out. Lacoste is on the war path.

Build a niche store - BANS

Now I need to determine if there is a way for me to ensure that their products don’t appear on my site anymore. I’m afraid that by using a generic term like ‘polo shirt’ , that the BANS software might bring back a result like ‘lacoste polo shirt’.

Anyone know if it is possible to use a negative keyword or something?

Any recommendations appreciated.

Thanks

BANS

Francois al hajj was the target, and he has since passed away.

Rumors are that General Francois al hajj was supposed to take over from Sleiman in case he was elected president

فرنسوا الحاج

Language within Relationships

Language plays a huge role in every society.

It defines personalities, shapes thoughts, and effects human relationships. In the play Translations, by Brian Friel, the Irish language is notionally represented by the English language. Although Irish is no longer spoken by the majority in Ireland, the language is very much alive in its sense of wonder, curiosity, and wittiness.

The Irish characters in the play are supposedly speaking Irish throughout most of scenes although on some instances Latin and Greek are used in script. Through the characters’ dialogue and actions, ordinary relationships, like the relationship between father and son, are exposed in their raw form and can be analyzed for the distinction they express due to the use of language.

One can say that all the characters starring in this play are important but for the purpose of this analysis of language and the gestures that accompany it, only certain characters will be focused on.

Manus is the first character introduced in the beginning of the play. Hence, due to his strong and reoccurring presence in the play it is essential to focus on several of his relationships with other prominent characters like Hugh, Maire, and Owen. On the other hand, Yolland brings great insight into the play because of his role as the English military man. His relationship with Maire is especially interesting because it illustrates how two people of different tongues can communicate. Doalty and Bridget bring to light the relationship of peers who communicate only in one language, their native tongue of Irish. Their relationship is that of lighthearted friends who through the notionally Irish language, make many a funny scene together.

All these characters contribute to the representation of the Irish language in this play. Through their conversation and written gestures they illuminate the implication of the function of language in their relationships.

Manus deals with all the prominent characters of this play. His relationship with Maire is that of girlfriend and boyfriend. But their words to each other are not soft like the words of two people deeply in love. Rather, they are short and impatient almost exuding frustration. Manus is tense in his dealings with Marie: for example after he hands Maire a bowl of milk he says, “I’m sorry I couldn’t get up last night.” These words are cautious and slow.

Upon reading one would imagine him saying them quietly as to not cause an explosion with loudness. To respond, Maire dismissingly says “doesn’t matter” (9). Their dialogue is always very brief, using short, fast phrases; as seen in perhaps the longest of their conversations when they discuss the future of the hedge-school (16).

With Manus, Maire always takes on an epigrammatic demeanor. This irritates Manus as shown Act One when he says to Maire, “What the hell are you so crabbed about?!” (10).

His arrangement and choice of words shows that he is “crabbed” as well. Maire and Manus do not exchange happy, charming words with one another like couples often do. Even when Manus had the good news of his new employment kind words were not passed between them. Also, Owen was the one who actually broke the good news to Maire, showing that Manus and Maire’s exchange of words lack real communication and connection (59).

In contrast to her tense relationship with Manus, Maire had a special bond with Yolland. They were able communicate despite their lack of a common language. Unlike her dialogue with Manus, Maire’s discourse with Yolland was done in a patient manner. Maire did not mind repeating what she said more than once. As in their conversation about the waving to each other across the fields (59) and about the dance (60); reiteration was the theme. Also, with Yolland, Maire is soft, gentle, and kind in her words. She compliments Yolland saying, “I love the sound of your speech” (63) and that he has “soft hands; a gentleman’s hands” (66). Maire even tries to speak in Latin to communicate with Yolland (63, 64). A sign that she is willing to leave a language she is comfortable with in order to strengthen her relationship with Yolland. But, through their use of several languages it is apparent that Maire and Yolland communicated more through intuition about language than through an actual verbal language. Maire also uses gestures to get Yolland to understand, such as when she picks up a handful of dirt and says, “Earth” (64). It took greater effort on Maire and Yolland’s part for them to communicate but they did despite their different native tongues.

As for dialogue and interaction between Manus and Hugh it is that of mutual understanding. Hugh enters the play and immediately hands his hat and coat to Manus “as if to a footman” (21). Manus and Hugh exchange no greeting words.

In fact, they exchange very few words throughout the whole play. Mostly, Hugh orders Manus around and Manus obliges. In that way their words to one another are very few in number but from these words a lot is understood. Manus is extremely loyal to Hugh and in return Hugh trusts and relies on Manus. Hugh’s reliance on Manus is apparent whenever he addresses Manus. He only ever talks to Manus when he is asking him for something, such as when he asks for “a bowl of tea…” (23) or “ …a slice of soda bread” (85). Hugh does not ask for anything from anyone, except Manus.

Being brothers, one would think that Manus and Owen have many things in common. In fact, throughout the majority of the play, they do not. Through language and gesture, they are shown as very different characters with many dissimilar traits. But their relationship evolves through development of the play. By their early verbal exchange it is apparent that Manus and Owen do not have high opinions of one another. The first thing Manus says to his brother is, “You’re welcome, Owen,” (27).

It is as if Manus is already sick of Owen even upon his arrival. The disapproval Manus has for Owen is apparent in their conversation with Manus scolding Owen for mistranslation. Manus exclaims: “You weren’t saying what Lancey was saying!” (36). In this conversation Manus’s words are questioning and critical, while Owen’s comebacks are slick and unconcerned, showing that the brothers’ relationship is not playful and lighthearted, rather it is critical and serious. Near the end of the play, their relationship is transformed when Manus decides to leave.

Their dialogue is no longer conveying disapproval of one another. It becomes that of two brothers who care about one another. Owen says, “You’re being damned stupid, Manus,” (69). This statement stands as advice and concern when coming from Owen, a worried brother. The last interactions between Manus and Owen convey the new status of their relationship, shown in large part by the language used by Manus. He talks the most in this interaction than he has throughout the whole play, using passionate, detailed statements, showing his newfound trust in Owen.

Exchanges between Doalty and Bridget bring comedic relief to the play.

They use witty statements appropriate for use among friends who are comfortable with one another. Bridget enters Act One saying Doalty is “full as a pig” (10). Banter between Bridget and Doalty comes in playful teasing phrases. Bridget jokes with Doalty saying, “you dirty brute” (12) and, “That’s the point, you donkey you,” (13). As only a friend can, Doalty asks Bridget, “Are you stupid?” (18) and, “Who told you that yarn?” (19). At one point Doalty reacts physically to their exchange grabbing Bridget around the waist (12). The pair is flamboyant with their language, interacting with humor and pleasantry. Their relationship with each other is like their relationship with the Irish language: quick and smart.

Language contributes to every relationship as seen in the play. Through choice of words, arrangement of words, and execution of words one can easily make certain judgments about the status of any relationship. Language is the gateway to communication in every country and with every people. Hence, it must be used wisely.

Work Cited
Friel, Brian. Translations. London: Faber, 2000.

The Role of Gender in Depression

Brooke Shields, Jim Carrey, Princess Diana, and Van Gogh, all had something in common. Besides being famous, they all suffered from depression.

Depression affects 18.8 million people a year. A medical working definition states that “depression is a psychological disorder characterized by long bouts of severe mood disturbance or excessive elation” (Downing-Orr 26). Depression interferes with an individual’s ability to function. It disturbs both the mind and the body, sufferers’ thoughts change, their mood shifts, and even the way they feel about themselves distorts.

A depressive disorder is not the same as a passing blue mood. People with depression with feel extremely unhappy in such a way that there is no comfort or relief available to alleviate their sadness. However, with the “blues” one can find happiness and pleasure through time, within periods and moments.

With depression, there is no happiness or relief from the extreme sadness (Downing-Orr 30). Symptoms include anxiety, feelings of hopelessness or pessimism; lose of interest in hobbies, decreased sex drive, and fatigue. Depressives often have trouble sleeping and they experience changes in their weight and appetite, either gaining or losing weight. If depression goes untreated, symptoms can last for weeks, months, or even years.

Doctor JM Ussher states, “Surveys, hospital admissions, and statistics…all concur: adult women report more mental health problems than men, and are more likely to be diagnosed and treated for madness” (Caplan 127). His assertion has been reinforced all over the globe. More and more studies, rates, and research show that depression is twice as likely to occur in women then in men. In children, depression occurs in mostly the same rate between genders until the age of twelve, and if anything boys show more depressive symptoms than girls at that age (Mazure 10). However after the age of twelve, depression becomes twice more prevalent in females than in males.

This two-to-one ratio exists regardless of race, ethnicity, or economic status. The same ratio has been reported in eleven other countries all over the globe (Franklin). So why are women more susceptible to depression than men? What role does gender play in the onset and experience of depression? How does depression differ across gender? There are several components within the answer to these questions. The causes of depression, the way it appears, and the way it is dealt with all factor into why more women suffer from depressive disorders than men.

First, there are three primary types of depression: major depression, dysthymia, and manic depression (Behrman). Major depression is the most common type of depression (Blehar). It is more intense than dysthymia which is where sufferers walk around feeling simply sad.

They are not even aware of their disorder; they assume their state is a normal state of mind. The most powerful form of depression is manic depression, also called bipolar disorder. It is not as common as major depression or dysthymia but it is the most severe. A sufferer of manic depression experiences quick and sudden changes of intense mood, ranging from extreme sadness to euphoria. A greater number of women experience manic depression than men. Generally, they have more depressive episodes than manic ones. Differences in the type of depression more common among particular genders are generally due to the severity of the causes that induced the disorder.

The causes of depression in women are much more biologically intense than in men. There are always genetic factors involved which apply to both men and women, however biochemical bodily changes apply for women only. Each woman must go through processes which disrupt the secretion of hormones, chemicals which regulate mood (Downing-Orr 35). These processes include menstruation, childbirth, postpartum, menopause, etc. They also affect neurotransmitters, brain chemicals which help balance moods, to be deregulated (Belhar). Therefore, depression becomes a highly likely disorder after these aspects come into play. Obviously, many of the biological factors causing women’s depression are nonexistent for men simply because of gender.

A huge cause of depression in both men and women is the stress of social and gender roles. It appears that negative thinking patterns typically develop in childhood or adolescence (Mazure 12). Therefore research suggests that the traditional upbringing of girls might foster traits of negative thinking which help result in higher rates of depression for women. Females grow up with the pressures of self-image, self-esteem, and beauty being pushed upon them. Sometimes girls are told they are not good enough, not pretty enough, or simply not worth it. These issues contribute to their negative thinking patterns, causing pessimism which helps with the onset of depressive thoughts then depressive disorders. Therefore, after the age of twelve, after puberty, when gender roles become more defined, depression rates in women increase significantly.

Due to all the roles women must juggle and sort, many women often feel as though they have little control over life events. These feelings along with the traditional, stereotypical upbringings of women as limited to their sex role expectations increase the stressors which lead to depression. These stresses include major responsibilities at home and at work, parenthood, caring for children and aging parents. In many families, even though both the male and the female working, the woman often has the greater responsibility in the child care and in the household. Therefore, many women must juggle the roles of wife, mother and career women all at once. This often causes role conflict which increases any stressors that are already existent, helping with the onset of depression.

Men must also deal with their gender roles appropriately. Typically they have to be the provider for the family and the protector. Cultural factors and status factors state that they must always be strong. However, for men, the major cause of depression is work stress. A work stress study was done using the Job Strain Model which attempts to show that high job strain leads to mental health problems. This study did not plan to distinguish between men and women; however in analyzing the results, it was necessary to do so in order to accurately present the data, showing that the difference between depressive disorders in men and women is clear and crucial. Results showed that women tended to have higher job strain then men (Work). They were often placed in more active jobs with lower job control, causing a high amount of job strain which led to depressive disorders. As for men, their jobs had high job control and mostly low job strain. Men with high grade jobs and non-manual jobs had more job strain and more depressive systems then men in other types of jobs.

These results led to an important finding. Men deal with their depression differently then women. Men in non-manual jobs had more depressive disorders than men in manual jobs because men tend to actively deal with their depression. Therefore, with a manual job, a man can release his frustration and decrease his stress.

As mentioned, women’s depression rates become twice that of men’s after age of twelve, but also after that age, males began to show much more violent tendencies then before, showing that depression may often go undetected in males because of the way they deal with it. They are less likely to think about and mull over their depressed feelings, instead they outwardly channel their emotions.

Men often use drugs and alcohol to deal with their depression. Unlike women, they do not easily acknowledge or admit to their disorder. Instead they drink to get numb, exercise, watch TV, and engage in more violent activities (Davis). Women, on the other hand, want to think things over, talk, express their feelings, etc. Many depressives deal with their depression by attempting suicide.

Women attempt it more then men, but men succeed four times more then women (Caplan 27). Because of these differences in dealing methods, it is harder to detect depression in men than in women. Therefore one must ask the question: are women really more depressed than men or are the rates skewed just because it is harder to diagnose depression in men due to the way they deal with their symptoms?
It is clear that gender plays a significant role in the onset and experience of depression. Men have less physical and biological factors leading to depression which give them a higher tolerance to the disorder.

Their depression is mostly brought on by work stress while women’s is induced by biological factors and sex role intensities. Women tend to inwardly direct their depressive symptoms, while males tend to deal with the disorder outwardly and actively. Since, depression can be fatal it should be taken seriously and treated appropriately.

Even treating depression across genders differs. Some drugs have been found to work on women and not on men.

In a comparison anti-depressive agents of sertraline and imipramine, it was found that women responded to sertraline more then men and vice versa (Mazure 47). There are often sex-specific processes that affect the way treatments work.

Brain function or structure may relate to the different responses in men and women. Also, some medications are distributed and metabolized differently in men than in women. Many times hormone receptors interact with the drug-related receptors causing a variation in treatment success across genders.

Hence, in treating depression, gender must be taken into consideration.
The role that gender plays in depression cannot be ignored. Social factors, gender roles, and coping skills increase the divide between men and women in depression.

However, is the divide as deep as it appears? Depression is harder to detect in men because of the way men deal with their symptoms. Therefore, there should be a greater effort to find out how many men are really suffering from depression because for depression to be treated, it must first be detected.

The Role of Gender in Depression

I. Introduction: Depression

• Depressive disorders affect approximately 18.8 million American adults or about 9.5% of the U.S. population age 18 and older in a given year.

• 15% of depressed people will commit suicide.

• 30% of women are depressed. Men’s figures were previously thought to be half that of women, but new estimates are higher
• Even famous people suffer from depression, Brooke Shields, Jim Carrey, Princess Diana, Van Gogh.

What is depression?

• “Depression is a psychological disorder characterized by long bouts of severe mood disturbance or excessive elation” (Downing-Orr 26).

• An illness that involves the body, mood, and thoughts, that affects the way a person eats and sleeps, the way one feels about oneself, and the way one thinks about things.

• There should be a distinction between the “blues” and depression. Most obviously depression is severe episodes of unhappiness during which people re not able to find relief or comfort (Downing-Orr 30).

Types of Depressions

• Major Depression: most common forms
• Dysthymia: Many people just walk around seeming depressed - - simply sad, a condition that people are not even aware of but just live with daily. They go through life feeling unimportant, dissatisfied, frightened.
• Manic Depression: changing mood very quickly. Heavy form of depression People who suffer from manic depression have an extremely high rate of suicide.

“Surveys, hospital admissions, and statistics…all concur: adult women report more mental health problems than men, and are more likey to be diagnosed and treatef for madness.” JM Ussher. (Caplan 127).

Women vs. Men in Depression

In children depression is mostly the same until the age of 12. if the difference were to be noted it would show pre-pubertal boys as more depressed than pre- pubertal girls. However after the age of 12, females are twice as likely to be depressed then males. (Mazure 10)

Why are women more susceptible to depression?
What does gender have to do with depression?

Causes
Symptoms
Effects
Treatments

II. Causes

Reasons for the onset of Depression in women: (Belhar, NIMH)

• Genetic factors

• Biochemical factors brain biochemistry deregulation of certain brain chemicals, called neurotransmitters. hormones have mood-altering properties.

Women often develop depression based on event that effected their biological state, like after menstruation, after childbirth, at menopause (Downing-Orr 35).

• Social factors, gender roles a sense of having little control over life events, and a tendency to worry excessively Upbringing or sex role expectations … It appears that negative thinking patterns typically develop in childhood or adolescence Some experts have suggested that the traditional upbringing of girls might foster these traits and may be a factor in women’s higher rate of depression. That would be why at 12, puberty… roles get heavy.. depression rates go up in women.

• Roles of mother

Reasons for the onset of Depression in men:

• Gender roles: not being able to provide for the family
• Work stress
• Status factors
• Cultural factors
• Less physical and biological factors that make them have higher tolerance to depression.

III. Work effecting stress

Work Study, Job Strain Model

High job strain leads to mental health problems.

Study showed that women tended to have higher job strain then men. Placed in active jobs with low job control. Whereas men had high job control and low job strain. Men with high grade jobs non manual jobs, had more job strain and depressive symptoms then men in other types of jobs.

IV. Symptoms of Depression

Symptoms:

• Persistent sad, anxious, or “empty” mood.
• Feelings of hopelessness or pessimism.
• Feelings of guilt, worthlessness, or helplessness.
• Loss of interest or pleasure in hobbies and activities, including sex.
• Decreased energy, fatigue; feeling “slowed down.”
• Difficulty concentrating, remembering, or making decisions.
• Trouble sleeping, early morning awakening, or oversleeping.
• Changes in appetite and/or weight.
• Thoughts of death or suicide, or suicide attempts.
• Restlessness or irritability.
• Persistent physical symptoms, such as headaches, digestive disorders, and chronic pain that do not respond to routine treatment.

Symptoms are the same in men and women however they deal with it differently.

The symptoms of depression are similar for both men and women, but they tend to be expressed differently.

The most common symptoms of depression include low self-esteem; suicidal thoughts; loss of interest in usually pleasurable activities; fatigue; changes in appetite; sleep disturbances; apathy; and sexual problems, including reduced sex drive.

Dealing with Depression:

Men are less to admit to depression.

Men are more likely to drink, be more active, get involved in something to relieve
stress, watch TV, get numb, violence, (after 12 boys got much more violent.. )

Women more likely to want to think things over, talk, express their feelings, etc.
Women try suicide more then men but men succeed more then women.

Therefore, that brings us to the question of whether or not women are generally more depressed then men or do men just not show or report their depression as often as women. ?

V. Treatment

In treating men and women for depression one must take into account biological gendered differences. Some drugs have been found to work on women and not on men. Gender differences in antidepressive agents. In a comparison antidepressive agents of sertraline (SSRI) and imipramine, it was found that women responded to SSRI more then men. And men vice versa. (Mazure 47).

VII. Conclusion

There are obvious differences between men and women in regards to depression.

Therefore several factors must be taken into consideration when dealing with depression in both men and women. Factors like genetics, social roles, gender roles, coping skills, etc. Depression can be fatal. It should be taken seriously and treated appropriately.

There seems to be no set solution for depression, not for men or women.

Therefore, the role of gender in depression should be taken into consideration when dealing with the disorder in a man or a woman.

Summary of Article: “Work Stress, Mental Health and Antidepressant Medication Finding from the Health 200 Study”

During recent years, there has been increasing concern about the effects of work stress on mental health.

There is speculation that work with high job demands and low job control, leads to depression and anxiety disorders.

Several theories have come to light attempting to detail the effects of work stress on individuals.

One such theory is the Job Strain Model, also called the Demand-Control Model. This theory endorses the idea that high job demand and low job control, i.e., high job strain, leads to mental health problems.

In 2000, an epidemiologic study sought to test the Demand-Control Model using 8,000 participants consisting of both men and women.

The study was to determine whether or not degree of job strain had an effect mental health.

Two methods were used to determine such conclusions. One was a standardized psychiatric interview of the participant. Another was the meansure of the use antidepressant medication determine possible existence of a depressive and or anxiety disorder.

During the study participants were asked to participate in interviews, questionnaires, and health examinations. Medical health was assessed based on the Composite International Diagnostic Interview (CIDI).

This interview is a common tool for measure of mental disorders. The questionnaires given the participants implemented the use of the Demand-Control Model, utilizing a scale of job demands and job control to measure the intensity of work stress.

Individuals would use a five point scale to measure their perceived intensity of job demand and job control. Using statistical analysis methods, the data was collected and then analyzed.

Since results showed a significant relation between sex and job control associated with mental disorder, men and women’s results were separated to show degree of correlation. Also, during analysis of the study data was adjusted for leading factors such as age, martial status, income, etc.

Such factors were highly influential in the outcome measures. Household income was eliminated from the analysis because it showed no related to antidepressant use. While the results of antidepressant use were taken into consideration during the study, they were controlled for those who had a history of lifetime mental disorders.

Results of the study showed that women reported lifetime mental disorders much more often then men. They tended to be placed in active jobs with high job strain unlike men who had high job control and low job strain. In men, occupational grade highly impacted job strain which lead to mental disorder. Men placed in jobs that were of higher-grade and non-manually oriented showed greater job strain and depressive or anxiety disorders than men in other types of jobs.

In regard to antidepressant medication, women medicated two times as much as men. Working married women tended to implement the use of antidepressants more often then their non-married counterparts. However, there was no solid relation found between women’s use of antidepressants with work characteristics. In men, antidepressant use was highly related to job strain.

Therefore, the use of antidepressants only in men was due to high job strain and pointed to mental disorders.

Although there was a difference between results for men and women, overall the results of the study showed that in both sexes high job demand and low job control resulted in a prevalence of mental disorders. Hence, the study has further enforced the Demand-Control Model, showing that high job strain leads to mental disorders in both men and women.

Article:

Research report

Work stress, mental health and antidepressant medication findings from the Health 2000 Study

Marianna Virtanena, Teija Honkonena, Mika Kivimäkia, Kirsi Aholaa, Jussi Vahteraa, Arpo Aromaac and Jouko Lönnqvistd

aFinnish Institute of Occupational Health, Topeliuksenkatu 41 aA, FIN-00250 Helsinki, Finland
bUniversity of Helsinki, Department of Psychology, P. O. Box 9, FI-00014 University of Helsinki, Finland

cNational Public Health Institute, Department of Health and Functional Capacity, Mannerheimintie 166, FI-00300, Helsinki, Finland

dNational Public Health Institute, Department of Mental Health and Alcohol Research, Mannerheimintie 166, FI-00300 Helsinki, Finland, and University of Helsinki, Department of Psychiatry, P.O. Box 320, FI-00029 Helsinki University Central Hospital (HUCH), Helsinki, Finland

Received 3 March 2006; revised 30 May 2006; accepted 31 May 2006. Available online 19 December 2006.

Abstract

Background

Population-based studies on the association between work stress and mental disorders are scarce, and it is not known whether work stress predicts mental disorders requiring treatment.

Aims

To examine the associations of work stress with DSM-IV mental disorders and subsequent antidepressant medication.

Methods

3366 participants from a representative sample of the Finnish working population responded to a survey (The Health 2000 Study). 12-month prevalence of depressive or anxiety disorders was examined with the Composite International Diagnostic Interview. Data on antidepressant prescriptions with a 3-year follow-up period were collected from a nationwide register of Social Insurance Institution.

Results

In men and women, high job demands, low job control and high job strain were associated with 12-month prevalence of depressive or anxiety disorders. After adjustment for lifetime and baseline mental disorders, men with high job demands and high job strain had increased risk of future antidepressant medication.

Conclusions

Work stress is associated with mental disorders among both sexes and among men it is a risk factor for mental disorders treated with antidepressant medication.

Keywords: Antidepressants; CIDI; Demand–Control model; Mental disorders; Work stress

Article Outline

1. Introduction
2. Materials and methods
2.1. Study sample
2.2. Measurements
2.3. Statistical analyses
3. Results
4. Discussion
5. Conclusion
References

1. Introduction

Studies from several countries have reported an increase in work stress (Schaufeli and Enzmann, 1998), and that mental disorders, especially depression, are growing reasons for work disability and early retirement (Kruijshaar et al., 2003, Stewart et al., 2003 and Gould and Nyman, 2004). Along with such evidence, concern is growing about the adverse effects that work stress may have on mental health. The Job Strain Model (Karasek, 1979, Karasek and Theorell, 1990, Van der Doef and Maes, 1999, De Lange et al., 2003 and Theorell, 2003), also known as the Demand–Control Model, has been one of the most influential theories in research on psychosocial work characteristics and health.

The model posits that a combination of high job demands and low job control, referred to as job strain, is a risk factor for health problems. Although most previous research has focused on the relationship between work strain and cardiovascular diseases, there is some evidence that high job strain, high demands and low control are also associated with mental health problems (Karasek, 1979, Bromet et al., 1988, Karasek and Theorell, 1990, Stansfeld et al., 1997, Stansfeld et al., 1999, Cropley et al., 1999, Van der Doef and Maes, 1999, Mausner-Dorsch and Eaton, 2000, Paterniti et al., 2002, Stansfeld, 2002, De Lange et al., 2003, Theorell, 2003 and Wang, 2005) and self-reported use of psychopharmacological medication (Karasek, 1979 and Moisan et al., 1999).

However, most research has been cross-sectional and few published longitudinal studies have used symptoms or self-certified psychiatric sickness absences as an outcome measure. Some of these studies have reported null findings (Van der Doef and Maes, 1999 and Ylipaavalniemi et al., 2005). Two used a clinical or standardised interview and reported that high job demands and high work stress were associated with new affective disorder (Bromet et al., 1988), and new major depressive episode (Wang, 2005). However, these studies involved a selected vocational group of men (Bromet et al., 1988), or did not report results based on the original classification of the Job Strain Model (Bromet et al., 1988 and Wang, 2005). A major limitation in earlier research is related to common method variance, i.e. both work stress and mental health have been based on subjective assessments.

Register data on antidepressant medication offers an opportunity to avoid such a bias since prescriptions are based on physicians’ diagnoses. Antidepressant medication can also be considered as an indicator of mental disorders requiring pharmacological treatment. According to clinical practice guidelines on managing depression, in depressive disorders with significant disability, treatment with antidepressant medication is recommended (Finnish Psychiatric Association, 2004 and National Institute for Clinical Excellence, 2004). Prospective evidence on the relationship between work stress and antidepressant use would therefore be important in terms of prevention of disabling mental disorders. Thus far, it is not known whether work stress predicts antidepressant use.

In sum, limitations in previous studies include lack of structured psychiatric interviews in the assessment of mental disorders and bias due to common-method variance, recall problems and non-generalisability to the general population. In this population-based study, we examined whether high job demands, low job control and high job strain are associated with prevalence of depressive or anxiety disorders assessed by a standardised psychiatric interview. We also examined whether these stress indicators predict clinically significant depressive or anxiety disorders as measured by register-based antidepressant medication.

2. Materials and methods

2.1. Study sample

A multidisciplinary epidemiologic health survey, the Health 2000 Study, was carried out in the years 2000–2001 in Finland.

The two-stage stratified cluster sample was representative of the Finnish population (0.24% sample) and included 8028 subjects aged 30 years or over (Aromaa and Koskinen, 2004). Stratification and sampling were conducted as follows: The strata were the five university hospital districts, each serving about 1 million inhabitants and differing in several features related to geography, economic structure, health services and the socio-demographic characteristics of the population. First, the 15 largest cities were included with a probability of one.

Next, within each of the five districts all 65 other areas were sampled applying the probability proportional to population size (PPS) method. Finally, from each of these 80 areas a random sample of individuals was drawn from the National Population Register.

The detailed methodology of the project has been published (Aromaa and Koskinen, 2004).

The data collection phase started in August 2000 and was completed in March 2001, during which a total of 7419 subjects (93% of the 7977 subjects alive on the day the first phase of the survey began) attended at least one phase of the study. The subjects were interviewed at home, where they were given a questionnaire to be returned at the clinical health examination.

During the interview the respondents received an information leaflet and their written informed consent was obtained. Approval of the Ethics Committee of Epidemiology and Public Health in the Hospital District of Helsinki and Uusimaa was obtained for this study.

Of the total sample, 5871 persons were of working age (30 to 64 years). Of this base population, 5152 persons were interviewed (87.8%), 4935 persons returned the questionnaire (84.1%), and 4886 (83.2%) participated in the health examination, including the structured mental health interview (CIDI). The final cohort of the present study comprised the 3366 participants (1662 men, 1704 women) who were employed at the time of the interview.

2.2. Measurements

We used self-assessment scales to measure the components of the Demand–Control Model of job strain (Karasek, 1979, Karasek and Theorell, 1990 and Theorell, 2003). The scale of job demands comprises five items (α = 0.79) (e.g. “My job requires working very fast”).

The scale of job control comprises nine items (α = 0.85) (e.g. “My job allows me to make a lot of decisions on my own”; “My job requires a high level of skills”).

Responses are given on a 5-point scale ranging from 1 (strongly disagree) to 5 (strongly agree).

In job-strain literature, many methods for testing interactions between job demand and job control are widely used and accepted (Landsbergis et al., 1994, Schnall et al., 1994 and Hintsanen et al., 2005). Mean scores of job demands and job control were standardised and treated as continuous variables.

A continuous quotient term of job strain was calculated by dividing job demands score by job control score and then standardised (Landsbergis et al., 1994). An alternative job strain formulation, a quadrant term, was calculated for comparison. As presented in the original work of Karasek (1979), we dichotomised the job demand and job control scales at their median and formulated the following four subgroups: low-strain (low demands and high control), active (high demands and high control), passive (low demands and low control), and high-strain (high demands and low control).

Lifetime mental disorders were assessed by a single-item question asking whether a doctor had ever confirmed a diagnosis of mental disorder (yes/no).

Mental health status at baseline was based on a computerized version of the WHO Composite International Diagnostic Interview (M-CIDI) as a part of a comprehensive health examination. The standardized CIDI interview has been shown to be a valid assessment measure of common mental non-psychotic disorders (Jordanova et al., 2004).

The program uses operationalized criteria for DSM-IV diagnoses and allows the estimation of DSM-IV diagnoses for major mental disorders.

The 21 interviewers were mostly non-psychiatric health care professionals. They were trained for the CIDI interview for 3–4 days by psychiatrists and physicians who had been trained by a WHO authorised trainer. Mental disorders were assessed using DSM-IV definitions and criteria.

The participant was identified as a case if he/she fulfilled the criteria for a depressive or anxiety disorder. Depressive disorder meant a diagnosis during the previous 12 months of major depressive disorder or dysthymia, while anxiety disorders included diagnoses of panic disorder (with or without agoraphobia), generalized anxiety disorder, social phobia, phobia NOS and agoraphobia (without panic disorder).

Data on antidepressant medication were obtained from the National Prescription Register, managed by the Social Insurance Institution of Finland.

The national sickness insurance scheme covers the entire population and reimburses the costs of prescribed medication for virtually all patients. Information on drug prescriptions was linked to the data by means of each participant’s personal identification number (a unique number that all Finns receive at birth and that is used for all contacts with the social welfare and health care systems).

The prescription register of the Social Insurance Institution contains outpatient prescription data based on the WHO’s Anatomical Therapeutic Chemical (ATC) classification code (WHO Collaborating Centre for Drug Statistics Methodology, 2004). We extracted all the prescriptions coded as N06A, which is the ATC code for antidepressants, from January 1st, 2001 to December 31, 2003.

Information on demographic factors was collected in the home interview: sex, age, marital status, occupational grade, type of business, household income (range from 1 = less than 2500 FIM (420 €) per month to 13 = more than 50 000 FIM (8409 €) per month, and employment status (employed, unemployed or economically inactive).

Marital status was divided into two groups: those who were married or cohabiting and those who were divorced, widowed or single. Occupational grade was formed based on occupation and type of business: upper grade non-manual, lower grade non-manual, manual workers and self-employed (Statistics Finland, 1999).

2.3. Statistical analyses

Binary logistic regression models were used to calculate adjusted odds ratios and their 95% confidence intervals for having 12-month mental disorders, and at least one antidepressant prescription during the 3-year follow-up. We found a significant interaction between sex and job control associated with mental disorder (p = 0.024). We therefore present the results separately for men and women.

Analyses were adjusted for potential confounding factors: age, marital status, occupational grade and household income, which all showed some association with the outcome measures. Because household income was not related to antidepressant use it was excluded from that part of the analyses. To evaluate the association between work stress and antidepressant medication, lifetime and baseline mental disorders were additionally controlled for.

In addition to the main effects, the cross-product terms (Cohen and Cohen, 1983) of work stress indicator with each demographic factor were entered in the models to assess whether the association of work stress with mental disorders or antidepressant use was modified by any demographic factor.

Test of curvilinearity was performed by entering the cross-product term of the work stress variable itself after the main effect, e.g. ‘job demands × job demands’. In statistical analyses, the data were weighted to take into account the sampling design and to reduce the bias due to non-response. We used the SAS/Sudaan 9.0.1 statistical program package to perform the analyses.

3. Results

Table 1 presents the characteristics of the study participants for men and women. Men were younger, had higher household income, were more often in manual occupations or self-employed, and were more likely to be married or co-habiting than women. Men also reported lifetime mental disorders less often and had a lower prevalence of 12-month mental disorders than women. Men had higher job control and were more often in low-strain and active jobs whereas women were more often in passive and high-strain jobs.

a P-value for difference between men and women in ANOVA and χ2 tests.
b Self-reported information on doctor-diagnosed mental disorder.
c Diagnosis based on the CIDI interview.
d Job demands/Job control.

The findings regarding the association of work characteristics with 12-month mental disorders appear in Table 2.

In both sexes, high job demands (Model I) and high job strain (Model IV) were related to a higher prevalence and high job control (Model II) was associated with lower prevalence of 12-month mental disorder.

When job demands and job control were entered simultaneously in the model (Model III), the associations of both variables with mental disorders remained statistically significant. We found that among men and women, the association between job demands and mental disorder was curvilinear (p = 0.04 and 0.01, respectively).

This association is adjusted in Models I and III. We split the job demands score into tertiles and found that among men, the association between job demands and mental disorder was U-shaped (odds ratio for intermediate job demands = 0.58, 95% CI = 0.35–0.99 and for high job demands = 1.44, 95% CI = 0.89–2.33 when compared with low job demands; data not shown). Among women, only high job demands but not intermediate job demands was associated with mental disorder (OR = 1.74, 95% CI = 1.24–2.44 and OR = 1.02, 95% CI = 0.70–1.48, respectively).

Among men, we also found a significant interaction effect between occupational grade and job strain associated with mental disorder (p = 0.04). A separate analysis revealed that among higher-grade non-manual workers, the association between job strain and mental disorder was 4.10 (95% CI = 1.78–9.43).

Corresponding odds ratios among lower grade non-manual, manual and self-employed men were 1.31 (95% CI = 0.76–2.26), 1.60 (95% CI = 1.26–2.04), and 0.77 (95% CI = 0.39–1.54).

a Adjusted for age, marital status, household income and occupational grade.
b OR refers to change in probability of depressive or anxiety disorder per standard deviation increase in job demands, job control and job strain.
c Indicates curvilinear effect of job demands.

During the follow-up period, 96 (6%) men and 199 (12%) women had antidepressant medication. Findings regarding the association between work stress indicators and antidepressant medication are shown in Table 3.

No curvilinearity was found with regard to the association between work characteristics and antidepressant use. High job demands were associated with a greater risk of receiving antidepressant medication among men (Model I).

Job control was not significantly related to antidepressant use (Model II). After adjustment for job control, odds ratio for high job demands was 1.30 (95% CI = 1.04–1.62) among men (Model III). Also in men, high job strain was related to an odds ratio of 1.30 (95% CI = 1.08–1.57) with antidepressant use (Model IV).

Among women, work characteristics were not significantly associated with antidepressant use. However, we found a significant interaction between marital status and job demands predicting antidepressant use among women (p = 0.03).

In a stratified analysis, job demands were associated with an odds ratio of 1.19 (95% CI = 0.98–1.45) for antidepressant use among married women. Among non-married women, the corresponding odds ratio was 0.79 (95% CI = 0.59–1.07).

a Adjusted for age, marital status, occupational grade, lifetime mental disorder and baseline DSM-IV depressive or anxiety disorder.

b OR refers to change in probability of depressive or anxiety disorder per standard deviation increase in job demands, job control and job strain.

As shown in Table 4, test of interaction between job demands and job control associated with DSM-IV depressive or anxiety disorders and antidepressant use resulted in no statistically significant effects. We also tested the interaction using job demands and job control as categorical variables (tertiles) and found no statistically significant interactions.

a Adjusted for age, marital status, household income, occupational grade and the main effects of work characteristics.

b Adjusted for age, marital status, occupational grade, baseline depressive or anxiety disorders and lifetime mental disorders, and the main effects of work characteristics.
c Indicates curvilinear effect of job demands.

In a four-category model of job strain, high job strain was related to odds ratio of 2.54 for mental disorder compared with low job strain among men and 1.68 among women (Table 5). High job strain was associated with higher probability of antidepressant use among men (OR = 1.95) but not among women (OR = 1.16). A subgroup analysis of 1442 healthy men (with no lifetime or 12-month mental disorder) revealed a similar although statistically non-significant association between job strain and antidepressant medication (OR = 1.20, 95% CI = 0.90–1.58 for linear job strain and OR = 2.09, 95% CI = 0.80–5.50 for quadrant job strain, results not shown in the table).

a Adjusted for age, marital status, occupational grade and household income.

b Adjusted for age, marital status, occupational grade, and DSM-IV depressive or anxiety disorders and lifetime mental disorder at baseline.

4. Discussion

This population-based study of 3366 men and women showed that high work stress, as indicated in the Job Strain Model, was associated with DSM-IV diagnoses of depressive or anxiety disorders.

In men, high job demands and high job strain were also associated with increased risk of antidepressant medication at follow-up. Because we adjusted the analyses for lifetime mental disorders and 12-month depressive and anxiety disorders, we were largely able to control for their possible confounding effects on the perception of work stress. Since DSM-IV diagnoses also included dysthymia, we could substantially control for confounding by participant’s milder depression at baseline.

Job strain was associated with the 12-month prevalence of depressive or anxiety disorders in men and women.

This accords with earlier findings of an association between work stress and mental health problems (Karasek, 1979, Bromet et al., 1988, Karasek and Theorell, 1990, Stansfeld et al., 1997, Cropley et al., 1999, Stansfeld et al., 1999, Van der Doef and Maes, 1999, Mausner-Dorsch and Eaton, 2000, Paterniti et al., 2002, Stansfeld, 2002, De Lange et al., 2003, Theorell, 2003 and Wang, 2005).

However, only in two previous studies (Cropley et al., 1999 and Mausner-Dorsch and Eaton, 2000) was the Job Strain Model tested using a standardised psychiatric interview to define mental disorder.

In the former, the outcome measure was the prevalence of neurotic disorder, and in the latter, job strain was calculated as high demands and low control versus the other three combinations.

In the present study, we used the continuous job strain score as well as all items of the quadrant term (low-strain, active, passive and high-strain) as defined in the original model of Karasek (1979).

Our findings suggest that job control, i.e. having influence over one’s job is strongly associated with DSM-IV diagnosis of depressive or anxiety disorders, particularly among men. Among men and women, the association between job demands and these disorders was curvilinear.

Among men, high and low job demands were associated with higher probability of mental disorders than intermediate job demands. Because this part of the study was cross-sectional it is possible that this finding reflects reversed causality, i.e. men with mental disorders have changed to less demanding jobs. However, it is also likely that an adequate level of job demands is a prerequisite for well-being of men. Among women, only very high job demands were related to mental disorders, indicating a threshold effect.

In our study, the association between work stress and depressive or anxiety disorders was stronger for men than women and the association with future antidepressant use was evident only among men. In some earlier longitudinal studies, high job demands have predicted subsequent psychological symptoms in both sexes (Stansfeld et al., 1997, Stansfeld et al., 1999 and Paterniti et al., 2002).

In the Whitehall II study of white-collar civil servants, high job demands and low job control were also associated with sickness absence, especially among men (North et al., 1996). A study on female-dominated hospital personnel produced no support for the job strain model as a predictor of depression (Ylipaavalniemi et al., 2005).

Considering the present findings and earlier evidence, the effects of work strain on health may be weaker in women than men (Kessler, 2003 and Theorell, 2003).

One possible explanation for this is that the etiology of mental disorders may be related to different psychosocial factors in men and women. Work may be a dominant factor for men, whereas for women the psychosocial etiological factors may be distributed across several spheres, including domestic factors and social relations.

In fact, we found that high job demands were associated with an odds ratio of 1.2 for future antidepressant use among married women whereas the corresponding odds ratio among non-married women was 0.8. This finding may be related to accumulation of total burden among married women (Denton et al., 2004).

In men, the association between job strain and depressive or anxiety disorders was stronger among higher-grade non-manual men (OR = 4.1) than among men in other occupational groups.

In manual occupations, work stress seemed not to be among the factors that strongly contribute to mental health.

One potential explanation for this is higher work and career orientation and thus higher emotional commitment to work among non-manual men. However, the reasons for socioeconomic as well as sex differences in the relationship between psychosocial work environment and health are poorly understood and require further investigation.

The association between work stress and future antidepressant use was evident in men after the adjustment for baseline mental health status.

Antidepressant medication can be considered, first, as a proxy measure for clinically significant depressive or anxiety disorders. Onset of new mental disorder may have been more likely among men with high work stress. However, it is also possible that those men did not have a mental disorder but, on the contrary, their disturbing work stress symptoms may have been misinterpreted as depressive or anxiety disorder and treated with antidepressants (see Heath, 1999 and Kessler et al., 1999). Whichever is the case, the present evidence on the relationship between work stress and antidepressant use is important in terms of promotion of mental health at workplaces.

As in the majority of previous studies (Stansfeld et al., 1997, Cropley et al., 1999, Stansfeld et al., 1999, Van der Doef and Maes, 1999, Mausner-Dorsch and Eaton, 2000, Paterniti et al., 2002, De Lange et al., 2003 and Wang, 2005; discussion, see Warr, 1990), no evidence of multiplicative interaction between job demands and job control was found in this study, suggesting an additive rather than a synergistic effect. Also in his original paper Karasek (1979, p. 293) points out that “there is only moderate evidence for an interaction effect, understood as a departure from a linear additive model”.

The main limitation of this study was a cross-sectional analysis of work stress and DSM-IV mental disorders. In this design, the association between mental disorder and perceived work stress may actually reflect the association between a disorder and its symptoms.

The standardized CIDI interview is a valid measure of DSM-IV non-psychotic disorders (Jordanova et al., 2004). The validity of the measure of lifetime mental disorder used in our study is, however, unknown.

Corresponding with earlier research (Young et al., 1990), our results showed that women were more likely than men to have a history of lifetime mental disorders.

The reported lifetime mental disorder 9.7%, however, was lower than that reported by e.g. in the National Comorbidity Study (19% for affective disorders, 25% for anxiety disorders, Kessler et al., 1994). Our measurement of past doctor-diagnosed mental disorders is likely to exclude individuals who had not sought help for their mental health problems from a physician.

Data on antidepressant prescriptions covered a 3-year follow-up period and the adjustments were made for baseline DSM-IV mental disorders and mental health history. Register data on prescriptions are based on a visit to the physician and cover virtually all prescriptions for the cohort. Uneven treatment practice between physicians may affect the prescriptions but such variability is likely to be random in relation to work stress. Using antidepressant medication as an indicator of clinically significant depressive and anxiety disorders is likely to have resulted in an underestimate rather than overestimate of these disorders, because this measure did not cover persons with unrecognized or under-treated disorders or those treated with non-pharmacological methods.

5. Conclusion

Psychosocial work stress is associated with DSM-IV depressive or anxiety disorders among both sexes and among men it is a risk factor for mental disorders treated with antidepressant medication.

As mental disorders account for a considerable proportion of the disease burden and are a major cause of work disability, psychosocial factors at work should be regarded as a target worthy of priority in the promotion of mental health at workplaces.

Journal of Affective Disorders

Volume 98, Issue 3, March 2007, Pages 189-197

Article Title:Work stress, mental health and antidepressant medication findings from the Health 2000 Study Source:JOURNAL OF AFFECTIVE DISORDERS (0165-0327); Volume: 98; Issue: 3; Date: 2007