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State Psychological Reactance to Depression Public Service Announcements Among People With Varying Levels of Depressive Symptomatology a

a

Brianna A. Lienemann & Jason T. Siegel a

Department of Behavioral and Organizational Sciences School of Social Science, Policy & Evaluation, Claremont Graduate University Published online: 18 Jun 2015.

Click for updates To cite this article: Brianna A. Lienemann & Jason T. Siegel (2015): State Psychological Reactance to Depression Public Service Announcements Among People With Varying Levels of Depressive Symptomatology, Health Communication, DOI: 10.1080/10410236.2014.940668 To link to this article: http://dx.doi.org/10.1080/10410236.2014.940668

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Health Communication, 00: 1–15, 2015 Copyright © Taylor & Francis Group, LLC ISSN: 1041-0236 print / 1532-7027 online DOI: 10.1080/10410236.2014.940668

State Psychological Reactance to Depression Public Service Announcements Among People With Varying Levels of Depressive Symptomatology Downloaded by [Florida Atlantic University] at 13:45 05 September 2015

Brianna A. Lienemann and Jason T. Siegel Department of Behavioral and Organizational Sciences School of Social Science, Policy & Evaluation Claremont Graduate University

Campaigns seeking to help people with depression can be effective, but they can also backfire. Psychological reactance is proposed as a partial explanation. Two experimental studies examined the effect of two depression messages (i.e., autonomy-supportive language, controlling language) for participants (n = 2027, n = 777) with varying levels of depressive symptomatology. For Study 1, two versions of a print public service announcement about seeking help for depression served as the experimental stimulus. Study 2 used an existing video public service announcement about seeking help for depression, but the text was altered to create the two conditions. In both studies, increased depressive symptomatology was associated with reduced help-seeking attitudes and intentions, as well as greater state reactance to a public service announcement about depression. Increased state reactance mediated the relationship between increased depressive symptomology and unfavorable help-seeking outcomes. Further, across the two studies, participants with high levels of depressive symptomatology who were exposed to the autonomy-supportive language ad reported either as much, or more, state reactance than participants with high levels of depressive symptomatology who were in the control condition. These results warn that language perceived as autonomy-supportive by people without depression might be perceived as controlling among people with depression.

Depression affects 350 million people worldwide (World Health Organization [WHO], 2012). Each year, approximately 850,000 people commit suicide as a result of the illness (WHO, 2012). Fewer than 25% of people with depression receive treatment (WHO, 2012), and 50% of people who commit suicide do not tell a single person prior to the act (Kisely, Campbell, Cartwright, Bowes, & Jackson, 2011). The current study aims to add to a line of research seeking to increase the amount of help received by people with elevated depressive symptomatology (e.g., Demyan & Anderson, 2012; Lienemann, Siegel, & Crano, 2013; Siegel et al., 2012). The goal of the current study is to investigate whether the relationship between elevated depressive symptomatology and state reactance is partially responsible Correspondence should be addressed to Brianna A. Lienemann, School of Social Science, Policy & Evaluation, Claremont Graduate University, 150 E. 8th St., Claremont, CA 91711. E-mail: brianna.alyssa@gmail. com

for the challenge sometimes faced when trying to increase help seeking among this population. The current studies also test the hypothesis that autonomy-supportive language will not minimize state reactance among people with elevated depressive symptomatology, much as it has among the general population. DEPRESSION AND CAMPAIGNS TO INCREASE HELP SEEKING Depression is treatable, but unlike many illnesses where help seeking increases as the illness worsens, help seeking becomes less likely as a person becomes more depressed (Siegel, Lienemann, & Tan, 2014). This occurs, in part, because the negative bias that is part of the symptomology of depression negatively biases views of help seeking and the likelihood that help seeking can lead to favorable outcomes (Lienemann et al., 2013). As chronicled by Keeler,

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Siegel, and Alvaro (2013), increased levels of depressive symptomatology are associated with reduced agreement that family members could offer assistance for depression and reduced comfort with asking family members to do so. H1: Higher levels of depressive symptomatology will be associated with less favorable attitudes and intentions regarding help seeking for depression.

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BOOMERANG EFFECTS Coined by Hovland, Janis, and Kelley (1953), the term boomerang effect refers to any communication that influences a receiver to behave in a direction opposed to the one advocated by the message. Across numerous health domains, well-intended attempts to change behavior have resulted in an increase, rather than a decrease, in the behavior the campaign sought to curtail (for a review see Byrne & Hart, 2009). Specific to the current research endeavor, campaigns seeking to increase help seeking among people with depression have succeeded, but boomerang effects have been reported as well (e.g., Christensen, Leach, Barney, Mackinnon, & Griffiths, 2006). One campaign was successful at increasing help seeking though a television campaign; however, the print component of the campaign led to negative outcomes (Klimes-Dougan & Lee, 2010). While there are numerous reasons as to why boomerang effects are particularly likely to occur when seeking to influence people with depression to seek help (e.g., absolutistic dichotomous thinking; Beck, 1976), the current study investigates one specific cause, namely, state psychological reactance.

PSYCHOLOGICAL REACTANCE THEORY Brehm’s (1966) theory of psychological reactance proffers that when a person’s cognitive or behavioral freedom is threatened, psychological reactance, a motivational state, can be aroused. Reactance triggers arousal that is directed against any further loss of freedom and toward reestablishing previously lost freedom (Brehm, 1972). Means of reestablishing freedom include engaging in the restricted behavior (Brehm, 1966), exercising a different freedom (Wicklund, 1974), rejection of the advocated position (Worchel & Brehm, 1971), and negative cognitions and anger (Dillard & Shen, 2005).

DEPRESSION AND STATE REACTANCE Even though it was initially described as a state (Brehm, 1966), Brehm and Brehm (1981) noted that there were trait aspects of psychological reactance as well. Most scholarship investigating the relationship between depression

and reactance has focused on trait reactance (e.g., Dowd & Seibel, 1990). The current study returns to the initial operationalization and focuses on state reactance— the temporary motivational state that occurs when one’s freedom is restricted—that occurs over and above the personality aspects of reactance. Specifically, state psychological reactance is proposed as a partial explanation for the boomerang effects that have occurred in response to messages targeting people with elevated depressive symptomatology. There are numerous reasons as to why people with elevated depressive symptomatology might be at an increased likelihood to experience state reactance in response to an ad encouraging help seeking. For example, state reactance is most likely to be elicited when individuals believe they have the freedom to engage in the behavior (Brehm, 1972). Many people with depression likely believe they have the right to seek help, or more likely not seek help, should that be their choice. Further, as the decision whether to seek help can be life-changing, people with elevated depressive symptomatology likely perceive this as an important behavior, thus increasing state reactance if the message is seen as controlling. Beck’s (1976) cognitive theory of depression (CTD) offers additional reason to expect people with elevated depressive symptomatology to exhibit heightened state reactance when presented with a depression public service announcement (D-PSA) encouraging help seeking. The CTD theorizes that individuals with depression experience a depressogenic schema. A depressogenic schema is faulty thinking such that cognitions are skewed toward a negative bias, while positive information is relatively ignored. As such, it is likely that positive aspects of a D-PSA encouraging help seeking will be ignored while the negative aspects, such as the threats to freedom, will be amplified. A second component of depressive symptomology described by the CTD is the negative cognitive triad. The negative cognitive triad consists of negative views of oneself, one’s experiences, and one’s future. If people with depression are confident that their future is bleak, a D-PSA focusing on the benefits of help seeking could be seen as threatening to people’s freedom to believe how they choose. The third component described by the CTD focuses on cognitive errors made by people with depression. Beck (1976) proffers six cognitive errors that affect cognitions: absolutistic dichotomous thinking (i.e., placing all information in one of two extreme categories); minimization and magnification (i.e., minimizing one’s abilities or the positive aspects of an event and magnifying negative aspects of a situation); selective abstraction (i.e., focusing on one detail while ignoring other potentially more relevant details); arbitrary inference (i.e., reaching a conclusion when the situation suggests either no evidence to support that conclusion or evidence in contradiction to the conclusion); overgeneralization (i.e., taking a few incidents and applying them across

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situations, related and unrelated); and personalization (i.e., relating external events to oneself when there is no apparent connection). Any one of these cognitive errors could result in increased state reactance in response to a D-PSA advocating help seeking. For example, even if the threat to freedom is minimal, selective abstraction can lead a person with depression to perceive a threat to freedom when one does not exist, or the threat as being far greater than intended. Likewise, arbitrary inference can lead a statement noting how professional help can be useful to be perceived as a statement insisting that professional help be sought. Absolutistic, dichotomous thinking can cause a suggestion on how to behave on one issue (e.g., help seeking) to be seen as a suggestion for how to live one’s entire life. H2: Higher levels of depressive symptomatology will be associated with the higher levels of state reactance toward a D-PSA. The theory of psychological reactance proffers that reactance can mediate the persuasive impact of messages (Brehm, 1966). Simply, the relationship between a persuasive message and a boomerang effect can be explained by the message causing reactance, and reactance causing a boomerang effect. Accordingly, reactance is often provided as an explanation for resistance to persuasion (e.g., Ringold, 2002). In line with this reasoning, Bensley and Wu (1991) report that a high-threat message was perceived more negatively than a neutral message, which then led to increased intentions to drink alcohol. H3: State reactance toward a D-PSA will result in reduced compliance with the message. H4: State reactance toward a D-PSA will mediate the relationship between levels of depressive symptomatology and help-seeking attitudes and intentions.

AUTONOMY-SUPPORTIVE LANGUAGE AND PEOPLE WITH ELEVATED DEPRESSIVE SYMPTOMATOLOGY One means of reducing reactance to a persuasive message is the use of autonomy-supportive language, also referred to as indirect, nondirective, or implicit language. As described by Miller, Lane, Deatrick, Young, and Potts (2007), autonomy-supportive language uses terms such as “perhaps,” “possibly,” and “maybe.” Implicit messages, in contrast to messages that are forceful with their assertion and recommendations, are posited to be successful by avoiding the impression of trying to control behavior. In accord, adolescents rated the source of an antitobacco ad more favorably when implicit language was used; further, 10th graders exposed to an implicit antitobacco message reported significantly less inclination to try smoking in the future than 10th graders exposed to an explicit antitobacco message (Grandpre, Alvaro, Burgoon, Miller, & Hall, 2003).

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Even though autonomy-supportive messages have been successful at reducing reactance among numerous populations, Beck’s (1976) CTD provides reasons to be skeptical as to whether autonomy-supportive messages will be an equally effective tool for reducing state reactance among people with elevated depressive symptomatology. The cognitive errors that are hypothesized to increase state reactance in response to D-PSAs encouraging help seeking (e.g., arbitrary inference), could also cause autonomy-supportive message to be perceived as equally threatening as more explicit persuasive attempts. For example, minimization and magnification could lead to the minimization of the autonomy-supportive language and the magnification of an attempt to restrict one’s freedoms concerning how to approach one’s depression treatment. Absolutistic dichotomous thinking could lead people with elevated depressive symptomatology to perceive a message as either controlling or noncontrolling, rather than on a continuum. As even the most autonomy-supportive message is still offering a suggestion for how to behave, this may lead to an autonomy-supportive message and a controlling message to be perceived as equally threatening. Simply, the use of autonomy-supportive messages, a commonly used means of minimizing reactance (Brehm, 1966; Quick, Shen, & Dillard, 2012), will arguably be obsolete when communicating with people fighting depression. Supporting this prediction, Seibel and Dowd (1999) note that even the most low-pressure recommendations can elicit reactance in therapeutic settings. H5: In comparison to a D-PSA that includes controlling language, autonomy-supportive messages that encourage help seeking for depression will lead to less state reactance and more favorable help-seeking outcomes among people with the lowest levels of depressive symptomatology; however, autonomy-supportive messages will not lead to reduced state reactance and more favorable help-seeking outcomes among people experiencing elevated depressive symptomatology.

THE CURRENT STUDIES Five hypotheses are tested in the current set of studies to explore the relationship between depressive symptomatology, the level of controlling language in depression messages, state reactance, and help-seeking outcomes. The first study randomly assigned participants to view one of two print D-PSAs advocating help seeking for people with depression or a control ad (CA). The two D-PSAs differed in regard to the language used (i.e., controlling or autonomy-supportive). The second study sought to replicate Study 1 and reduce rival hypotheses. An existing D-PSA (WHO) was altered to have either controlling or autonomy-supportive language to ensure the specific message execution was not responsible for any

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effect revealed. Further, a video manipulation was used to test the robustness of the Study 1 results. An additional adjustment is that rather than assessing the outcome of help seeking across a variety of targets, due to the focus of the selected ad on help seeking from a romantic partner and mental health professionals, these targets became the outcomes of interest. The final change was the extra care given to ensure that the control ad had no hint of controlling language. METHOD

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Participants and Procedure Participants (S1: N = 2027; S2: N = 777) were Englishspeaking U.S. residents with access to the Internet. They were on average 34 years old (S1: M = 33.95; S2: M = 34.32), female (S1: n = 1315, 65.9%; S2: n = 435, 56.0%), White (S1: n = 1632, 80.7%; S2: n = 578, 74.4%), and in Study 1 had completed some college (n = 686, 33.9%) while in Study 2 they had a bachelor’s degree (n = 267, 34.4%). Participants typically did not have a current (S1: n = 1636, 81.0%; S2: n = 664, 85.5%) or lifetime diagnosis of depression (S1: n = 1255, 62.7%; S2: n = 534, 68.7%), believed to have had depression but did not seek treatment (S1: n = 1178, 58.6%; S2: n = 423, 54.4%), and have known someone with depression (S1: n = 1711, 84.6%; S2: n = 567, 73.0%). Furthermore, in Study 2 participants typically had not sought help for depression from a loved one (n = 486, 62.5%) or a professional (n = 498, 64.1%). Participants were recruited through the online system Mechanical Turk (MTurk) through Amazon (Buhrmester, Kwang, & Gosling, 2011). A recruitment script with a link to the survey was posted from July 12, 2011, to January 31, 2012, for Study 1 and from July 16, 2013, to July 23, 2013, for Study 2. The recruitment script indicated that the study involved viewing a print D-PSA and responding to items regarding the D-PSA, depression, and help seeking. Participants were compensated $0.30 for Study 1 and $0.60 for Study 2. Following provision of consent, participants responded to items assessing trait reactance, depression history, and depressive symptomatology. Participants were randomly assigned to view a control ad (CA), a D-PSA with autonomy-supportive language, or a D-PSA with controlling language. Participants then rated the ad’s relevancy and help seeking outcomes. Afterward, participants viewed (S1) or read the script for (S2) the ad again and responded to the reactance and demographic items. Depression Public Service Announcements and Control Ad Study 1 Three print ads were created for Study 1. The CA was a travel ad for Colorado. The CA and D-PSAs have similar format and color scheme, and are attributed to an organization

with a website. The D-PSAs are identical besides the use of autonomy-supportive versus controlling language. The autonomy-supportive language ad (ASLA) emphasized choice with phrases such as “may” and “you can” (Miller et al., 2007). The text for the ASLA was the following: Depression. You may know that depression is a debilitating illness that can be fatal. Depression is treatable, so you may want to think about seeking help. Some options include taking to your loved ones, attending support groups or seeking professional help. If you desire you can change your life. You can choose to take action. Depression and Bipolar Support Alliance. Visit us at: www.dbsalliance.org/

The controlling language ad (CLA) utilized commands such as “must” and “should” (Miller et al., 2007). The text for the CLA was the following: Depression. You should know that depression is a debilitating illness that can be fatal. Depression is treatable, so you must seek help. You need to talk to your loved ones, attend support groups, and seek professional help. You must change your life now. You must take action. Depression and Bipolar Support Alliance. Visit us at: www.dbsalliance.org/

Ad type was dummy coded to create two dummy variables (i.e., ASLA and CLA) for regression analysis. The control group was used as the reference group. Study 2 The two video D-PSAs for Study 2 were adapted from the WHO’s black dog of depression D-PSA. The text was altered to change the language to be controlling or autonomysupportive. In contrast, the ASLA consisted of the following text: If the black dog of depression makes you feel like the saddest soul on earth, you may know that you are not alone. Around 350 million people share this debilitating but treatable condition. If you are feeling depressed, consider asking for help. Seeking help is a choice. Think about if it is right for you. There is no shame in doing so. You have the freedom to decide your next step. You can choose to get help. It’s up to you. Depression. Get help. Be helped. World Health Organization. www.who.int.

In contrast, the CLA utilized the following text: If the black dog of depression makes you feel like the saddest soul on earth, you must know that you are not alone. Around 350 million people share this debilitating but treatable condition. If you are feeling depressed, you have to ask for help. Seeking help is not a choice. It is something you must do. There is no shame in doing so. Seeking help has to be your next step. You must get treatment. Depression. Get help. Be helped. World Health Organization. www.who.int.

The CA was an ad for an LG air conditioning system. The CA was selected due to its focus on the provision of information without an affective component. The ads did not include sound, so text displayed the message. The two D-PSAs were

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55 seconds in duration, while the CA was 31 seconds. Ad type was dummy coded to create two dummy variables (i.e., ASLA and CLA) for regression analysis with the CA as the reference group. Measures

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Manipulation Check The language of the ad was assessed with a 5-item Likert scale modeled after Miller and colleagues’ (2007) concreteness scale. Participants were provided with a definition of controlling language. Response options ranged from 1 (strongly disagree) to 7 (strongly agree), with an example being “The language of the message was controlling” (S1: α = .95, M = 3.36, SD = 1.65; S2: α = .96, M = 3.25, SD = 1.67). Predictor and Control Variables Depressive symptomatology was the predictor variable; trait reactance, ad relevance, current diagnosis of depression, gender, and age were control variables. As noted earlier, Brehm originally conceptualized reactance as situational but more recently has found evidence for reactance to also be a trait (Brehm & Brehm, 1981). As such, trait reactance was used as a control variable to isolate the situational reactance created by the D-PSAs. Personal relevance is also included as a covariate, as it is an essential component in the elaboration likelihood model (Petty & Cacioppo, 1979), with greater relevance increasing argument scrutiny and resulting in more complex information-processing strategies (Showers & Cantor, 1985). Furthermore, the CTD and reactance theory suggest that the processing of personally relevant information will be most affected for people with elevated depressive symptomatology (Beck, 1976). Gender was utilized as a control variable because men seek treatment for depression less often (Addis & Mahalik, 2003) and are significantly more reactant than women (Dowd, Wallbrown, Sanders, & Yesenosky, 1994). Age was included as a control variable because resistance to persuasive appeals perceived as attempting to control or restrict one’s freedoms is often strongest during transitional stages such as adolescence or late in life (Grandpre et al., 2003). A current diagnosis of depression indicates that those participants have recently been treated for depression. Considering that this study is primarily interested in the impact of D-PSAs to encourage help seeking, a current diagnosis was used as a control. Depressive symptomatology. The Beck Depression Inventory–II (BDI-II; Beck, Steer, & Brown, 1996) assessed depressive symptomatology. The BDI-II consists of 21 items with item scores ranging from 0 to 3. Participants select the one statement in each group of statements that best describes their feelings in the past 2 weeks. For example, the item “Sadness” had the responses: “I do not feel sad” (0), “I feel

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sad much of the time” (1), “I am sad all the time” (2), and “I am so sad or unhappy that I can’t stand it” (3). Scores are summed for a range from 0 to 63 with higher scores reflecting greater depressive symptomatology (S1: α = .95, M = 13.89, SD = 12.25, Min = 0, Max = 61; S2: α = .94, M = 11.35, SD = 10.60, Min = 0, Max = 55). Although scores were kept continuous for the current study, Beck et al. (1996) provide a categorization scheme of 0–13 to denote minimal depression, 14–19 to indicate mild depression, 20–28 to characterize moderate depression, and 29–63 to denote severe depression. If participants were to be categorized in the current studies, they would be divided as the following: nondepressed (S1: n = 1168; S2: n = 509), mild (S1: n = 282; S2: n = 112), moderate (S1: n = 298; S2: n = 92), and severe (S1: n = 279; n = 64). If categorized depression level by ad type would be the following: CA (nondepressed, S1: n = 376, S2: n = 147; mild, S1: n = 107, S2: n = 30; moderate, S1: n = 110, S2: n = 24; severe, S1: n = 83, S2: n = 21), ASLA (nondepressed, S1: n = 391, S2: n = 181; mild, S1: n = 94, S2: n = 39; moderate, S1: n = 88, S2: n = 41; severe, S1: n = 94, S2: n = 21), and CLA (nondepressed, S1: n = 401, S2: n = 181; mild, S1: n = 81, S2: n = 43; moderate, S1: n = 100, S2: n = 27; severe, S1: n = 102, S2: n = 22). Trait reactance. For Study 1, trait reactance was assessed with the Therapeutic Reactance Scale (TRS; Dowd, Milne, & Wise, 1991). The scale consists of 28 Likert items with response options from 1 (strongly disagree) to 7 (strongly agree), with an example being “I have a strong desire to maintain my personal freedoms.” Higher scores indicate greater levels of trait reactance (α = .80, M = 4.01, SD = 0.59). The TRS has been shown to a be a measure superior to the Resistance Potential (Beutler et al., 1991) scale with a depressed sample, as it showed evidence of convergent, divergent, and construct validity (Baker, Sullivan, & Marszalek, 2003). Although “therapeutic” is in the title, none of the items specifically assess reactance to therapy. The scale was developed to assess psychological reactance as an individual difference variable that could potentially be useful to therapists to help explain the relationship between therapeutic process and outcome (Dowd et al., 1991, p. 542). However, to alleviate any concern that the TRS might be better suited in a therapeutic context, the Hong Psychological Reactance Scale (HPRS; Hong & Faedda, 1996) was substituted for Study 2. The HPRS is an 11-item Likert scale anchored by 1 (strongly disagree) and 7 (strongly agree). An example of an item is “I refuse attempts of others to influence me.” Higher scores reflect greater trait psychological reactance (α = .89, M = 3.93, SD = 1.05). Relevance. For Study 1, relevance was assessed with a single Likert item with response options ranging from 1 (extremely irrelevant) to 7 (extremely relevant) (M = 3.51, SD = 1.82). The item was “How relevant is this advertisement to you?” To create a two-item measure for Study 2,

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the item “How important is this advertisement’s message to you?” was added. The “importance” item was on a 7-point Likert scale with the anchors 1 (extremely unimportant) to 7 (extremely important) (α = .74, r = .58, p < .001, M = 3.97, SD = 1.55). Demographic variables. Gender was assessed with a single dichotomous item (male/female). Age was continuous. Current diagnosis of depression was assessed with a single dichotomous item (yes/no).

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Mediating Variable: State Reactance State reactance to the message was a composite measure consisting of anger and negative cognitions. Z-scores were computed for each subscale. A relationship was established between state reactance and perceived threat to freedom (S1: r = .50, p < .001; S2: r = .43, p < .001), as was suggested by Quick and Stephenson’s (2007) two-step process for establishing a measure of state reactance. Descriptive statistics for state reactance were the following (S1: M = 0.00, SD = 0.84; S2: M = 0.00, SD = 0.85). Anger. Anger toward the ad was assessed with a 4-item Likert scale with response options ranging from 1 (none of this feeling) to 7 (a great deal of this feeling). Examples of items included “irritated” and “angry” (Dillard & Shen, 2005). Higher scores are reflective of greater anger toward the ad (S1: α = .95, M = 2.39, SD = 0.96; S2: α = .94, M = 2.02, SD = 1.46). Negative cognitions. Participants listed their thoughts about the ad and then ranked each thought as negative, neutral, or positive. Participants were instructed that we were interested in everything that went through their minds about the ad. Negative cognitions consisted of the total number of negative cognitions (S1: M = 1.66, SD = 1.91; S2: M = 1.36, SD = 1.70). Perceived threat to freedom. The Perceived Threat to Freedom scale (PTF; Dillard & Shen, 2005) consists of four Likert items with response options ranging from 1 (strongly disagree) to 7 (strongly agree). An example is “The message threatened my freedom to choose.” Higher scores specify greater perceived threat (S1: α = .90, M = 2.93, SD = 1.61; S2: α = .90, M = 2.72, SD = 1.55). Dependent Variables The dependent variables consisted of self-stigma of seeking help, attitudes toward seeking help, and help-seeking intentions. These variables are commonly assessed evaluation outcomes for depression mass media campaigns. Furthermore, stigma (Office of the Surgeon General, 2001) and negative attitudes toward treatment (Jorm, 2000) are barriers toward seeking help for depression that D-PSAs

can affect. Moreover, attitudes and intentions are theorized (theory of planned behavior, Ajzen & Fishbein, 1980) and empirically shown (Sheeran, 2002) to be predictive of behavior. Self-stigma of seeking help. The Self-Stigma of Seeking Help scale (SSOSH; Vogel, Wade, & Haake, 2006) consists of 10 Likert items with response items ranging from 1 (strongly disagree) to 7 (strongly agree). An example is “I would feel inadequate if I went to a therapist for psychological help.” Higher scores indicate greater SSOSH (S1: α = .89, M = 3.63, SD = 1.18; S2: α = .91, M = 3.21, SD = 1.24). Attitudes toward seeking help. In Study 1, attitudes were assessed with the Attitudes Toward Seeking Professional Psychological Help: A Shortened Form (ATSPPH-SF; Fischer & Farina, 1995). The ATSPPH-SF has 10 Likert items with response options ranging from 1 (strongly disagree) to 7 (strongly agree). An example is “I might want to have psychological counseling in the future.” Higher scores are reflective of more positive attitudes (α = .87, M = 4.36, SD = 1.10). There was concern that the ATSPPH-SF (Fischer & Farina, 1995) contained both attitude and intention items, so semantic differentials were used in Study 2 to assess attitudes toward seeking help (ASH). Five semantic differentials were used for each scale: unhelpful/helpful, bad/good, negative/positive, worthless/valuable, and foolish/wise. The semantic differentials were randomized for each target. Higher scores reflect more positive ASH: romantic partner (RP), α = .97, M = 5.58, SD = 1.51; mental health professional (MHP), α = .97, M = 5.99, SD = 1.37. In Study 2, the corresponding ASH and help-seeking intentions (HSI) items were shown together. For example, participants responded to ASH-RP and then HSI-RP before moving onto another target. Targets were randomized to prevent order effects. Help-seeking intentions. HSI were assessed with an abridged version of the General Help Seeking Questionnaire (GHSQ; Wilson, Deane, Ciarrochi, & Rickwood, 2005). The GHSQ was found reliable and valid for personal-emotional problems and suicidal ideation (Wilson et al., 2005). The GHSQ was developed to be modifiable to fit different study requirements by changing problem type and help sources. Participants were given the question “If you were depressed, how likely is it that you would seek help from the following people?” The scale was comprised of five Likert items for Study 1 and two Likert items for Study 2, with response options ranging from 1 (extremely unlikely) to 7 (extremely likely). Higher scores reflect greater intentions to seek help for depressive symptoms (friend [Fr], S1: M = 5.22, SD = 1.70; parent [P], S2: M = 4.34, SD = 2.19; family [Fm], S1: M = 3.96, SD = 2.01; RP, S1: M = 5.52, SD = 1.81, S2: M = 5.31, SD = 1.67; and MHP, S1: M = 4.78, SD = 1.83, S2: M = 5.23, SD = 1.67).

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STUDY 1 RESULTS Twenty-five multivariate outliers were removed based on Mahalanobis distance (from N = 2052 to N = 2027). Gender, age, current diagnosis of depression, trait reactance, and ad relevance were used as covariates. Analysis of covariance (ANCOVA) was used for the manipulation check. To test the hypotheses H1–H3, correlational analysis was conducted, while to test H4 and H5, moderated mediation analysis (Figure 1) was conducted using PROCESS (Hayes, 2012; bootstrap samples = 1000); 95% confidence intervals (CIs) are reported for direct effects, and 95% bias-corrected and accelerated (BCa) CIs are reported for indirect effects. To test the moderating role of ad type on the relationship between depressive symptomatology and state reactance, PROCESS Model 2 was conducted. BDI-II scores were entered as the independent variable (X), state reactance was entered as the outcome variable (Y), and the two dummy coded ad types (i.e., autonomy-supportive language ad vs. others and controlling language ad vs. others) were entered as the moderators (M and W). To test the full model, PROCESS Model 10 was conducted with BDI-II scores as the independent variable (X), help seeking outcome(s) as the outcome variable(s) (Y), the ad type dummy codes as the moderators (W and Z), and state reactance as the mediator (M). To test moderation effects between two ad types, PROCESS Model 1 was used. Only those participants who had been randomly assigned to those two conditions were selected. For example, when comparing the control ad to the autonomy-supportive language ad, only participants in those two conditions were selected. BDI-II was entered as the independent variable (X), the help-seeking outcomes as the outcome variable(s) (Y), and ad type as the moderating variable (M). PROCESS uses ordinary least squares (OLS) regression to estimate model coefficients along with bootstrap methods (bootstrap samples = 1000) to estimate CIs and indirect effects in moderated mediation. This allows for similar results to linear regression, while maintaining accurate estimation with nonnormal distributions. Interactions were probed using yˆ estimates for each combination of ad type (i.e., control, autonomy-supportive, controlling) and three BDI-II scores (mean and ±1 standard deviation [SD]).

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One SD below the mean denotes no to minimal depression (1.64), mean BDI-II scores denote mild depression (13.89), and one SD above the mean represents moderate depression (26.14). Thus, to examine the effects of ad type on the dependent variables (DVs) at each level of BDI-II, analyses were also conducted with ad type as the independent variable (X) and BDI-II as the moderator (W). Manipulation Check To check that the CLA was perceived as having the most controlling language, an ANCOVA was conducted with the covariates and BDI-II. There were mean differences for level of ad types, F(2, 2011) = 306.14, p < .001, ηp 2 = .23. The CLA (M = 4.46) was rated as having significantly more controlling language than the ASLA (M = 2.93, Mdiff = 1.52, SE = 0.08, p < .001) and the CA (M = 2.66, Mdiff = 1.80, SE = 0.08, p < .001). However, the ASLA was also rated as having more controlling language than the CA (Mdiff = 0.27, SE = 0.08, p = .001).1 Correlational Analysis In support of H1, for participants who viewed a control message (n = 676), depressive symptomatology was positively associated with SSOSH (r = .08, p = .03) and negatively associated with HSI-RP (r = −.17, p < .001), HSI-Fr (r = −.15, p < .001), HSI-P (r = −.19, p < .001), and HSI-Fm (r = −.19, p < .001). However, depressive symptomatology was not significantly associated with attitudes toward seeking professional help (r = −.05, p = .19) or HSI-MHP (r = −.07, p = .10). H2 and H3 only considered the participants who viewed a D-PSA (n = 1351). Supporting H2, depressive symptomatology was significantly positively associated with state reactance toward a D-PSA (r = .19, p < .001). Supporting H3 state reactance toward a D-PSA was positively associated with SSOSH (r = .18, p < .001) and negatively associated with attitudes toward seeking professional help (r = −.22, p < .001), HSIRP (r = −.08, p = .004), HSI-Fr (r = −.09, p = .001), HSI-P (r = −.08, p = .005), HSI-Fm (r = −.13, p < .001), and HSI-MHP (r = −.17, p < 001). Moderated Mediation Analysis

Ad Type Control, AutonomySupportive Language, Controlling Language

It was expected that ad type moderates the relationship between depressive symptomatology and (a) state reactance and (b) the help-seeking DVs. It was also hypothesized that state reactance would mediate the relationship between depressive symptomatology and the help-seeking

State Reactance

Help Seeking DVs Depressive Symptomatology

Self-Stigma, Attitudes toward Professional Help seeking, Help Seeking Intentions

FIGURE 1 Moderated mediation model.

1 Although the ASLA was rated as more controlling than the CA, the correlation between the ASLA and controlling language was negative, r = −.18, p < .001, while the correlation between the CLA and controlling language was positive, r = .48, p < .001.

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DVs (Figure 1). For moderated mediation, two relationships will be reported: conditional indirect effects (ab) of the independent variable on the dependent variable through the mediator at each level of the moderator, and the conditional direct effects (c’) of the independent variable on the dependent variable at each level of the moderator. The null hypothesis of no conditional indirect effect can be rejected if the CIs do not contain zero.

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State Reactance The model with the covariates explained 13.60% of the variance in state reactance, F(10, 2009) = 35.56, p < .001, d = .29, 95% CI [.20, .39]. There were significant main effects for depressive symptomatology (B = .02, SEB = .002, t(2009) = 8.99, p < .001, 95% CI [.01, .02]), the ASLA (B = .13, SEB = .04, t(2009) = 3.22, p = .001, 95% CI [.05, .21]), and the CLA (B = .37, SEB = .04, t(2009) = 8.65, p < .001, 95% CI [.29, .46]). Supporting H2, greater depressive symptomatology was associated with greater state reactance over and above the influence of trait reactance. Additionally, viewing a D-PSA was associated with increased state reactance over and above the effect of trait reactance. The main effects were qualified by a significant BDI × ASLA interaction (B = .01, SEB = .004, t(2009) = 2.65, p = .008, 95% CI [.003, .02]); however, the BDI × CLA interaction was nonsignificant (Figure 2). The conditional effect (i.e., simple slopes; θX→Y ) of depressive symptomatology on state reactance at each level of ad type was significant (CA: θX→Y = .01, SE = .003, t(2009) = 4.30, p < .001, 95% CI [.01, .02]; ASLA: θX→Y = .02, SE = .003, t(2009) = 7.88, p < .001, 95%

CI [.02, .03]; CLA: θX→Y = .01, SE = .003, t(2009) = 4.45, p < .001, 95% CI [.01, .02]). In support of H2, the greater the depressive symptomatology reported, the greater was the state reactance for all ads. In comparison to the CA, the ASLA was associated with significantly more state reactance for participants with mean (θX→Y = .13, SE = .04, t(1329) = 3.25, p = .001, 95% CI [.05, .21]), and high (θX→Y = .27, SE = .07, t(1329) = 3.86, p < .001, 95% CI [.13, .41]) depressive symptomatology. The CLA was associated with significantly greater state reactance than the CA regardless of depression level (low: θX→Y = .17, SE = .03, t(1348) = 5.49, p < .001, 95% CI [.11, .23]; mean: θX→Y = .19, SE = .02, t(1348) = 8.65, p < .001, 95% CI [.14, .23]; high: θX→Y = .20, SE = .04, t(1348) = 5.63, p < .001, 95% CI [.13, .27]). Supporting H5, the CLA was associated with significantly greater state reactance than the ASLA for individuals with low (θX→Y = .35, SE = .06, t(1336) = 5.81, p < .001, 95% CI [.23, .47]) and mean (θX→Y = .25, SE = .04, t(1336) = 5.52, p < .001, 95% CI [.16, .33]), depressive symptomatology, but not high depressive symptomatology (θX→Y = .14, SE = .07, t(1336) = 1.95, p = .05, 95% CI [−.001, .28]). SSOSH. The model with the covariates explained 10.90% of the variance in SSOSH, F(11, 2007) = 21.35, p < .001, d = .21, 95% CI [.12, .30]. Supporting H1, there was a main effect of depressive symptomatology, suggesting that as depressive symptomatology increased, SSOSH increased (B = .02, SEB = .003, t(2007) = 7.51, p < .001, 95% CI [.02, .03]). However, neither interaction was significant. Supporting H3, state reactance was positively associated with SSOSH (B = .12, SEB = .03, t(2007) = 3.81, p < .001, 95% CI [.06, .19]). Supporting H4 for all ads, state reactance explained the relationship between depressive symptomatology and SSOSH (CA: c’ = .02, SEc’ = .004, t(2007) = 3.86, p < .001, 95% CI [.01, .02], ab = .002, boot SEab = .001, 95% boot CI [.001, .003]; ASLA: c’ = .02, SEc’ = .004, t(2007) = 4.93, p < .001, 95% CI [.01, .03], ab = .003, boot SEab = .001, 95% boot CI [.001, .005]; CLA: c’ = .02, SEc’ = .004, t(2007) = 5.61, p < .001, 95% CI [.02, .03], ab = .002, boot SEab = .001, 95% boot CI [.001, .003]). Attitudes Toward Seeking Professional Help

FIGURE 2 Ad type moderating the relationship between depressive symptomatology and state reactance. The state reactance scale uses z-scores. BDI is a continuous variable that was centered for analyses. Low BDI is 1 SD below the mean, while high BDI is 1 SD above the mean. Prior to centering the mean BDI score was 13.89, 1 SD below the mean was 1.64, and 1 SD above the mean was 26.14.

The model with the covariates explained 14.38% of the variance in attitudes toward seeking professional help, F(11, 2008) = 28.02, p < .001, d = −.15, 95% CI [−.25, −.06]. There was a main effect of depressive symptomatology (B = −.02, SEB = .002, t(2008) = −6.73, p < .001, 95% CI [−.02, −.01]). In support of H1, as depressive symptomatology increased, attitudes decreased. The BDI × ASLA was not significant; however, the BDI × CLA interaction was significant (B = −.01, SEB = .005, t(2008) = −1.98, p = .048, 95% CI [−.02, −.0001]),

Attitudes toward Seeking Professional Help

REACTANCE TO DEPRESSION PSA

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4.64 4.59 4.57

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CA ASLA CLA

2.00 1.00 Low BDI

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4.40 4.39

Mean BDI

High BDI

FIGURE 3 Ad type moderating the relationship between depressive symptomatology and attitudes toward seeking professional help. BDI is a continuous variable that was centered for analyses. Low BDI is 1 SD below the mean, while high BDI is 1 SD above the mean. Prior to centering, the mean BDI score was 13.89, 1 SD below the mean was 1.64, and 1 SD above the mean was 26.14.

suggesting that ad type moderated the relationship between depressive symptomatology and attitudes toward seeking professional help (Figure 3). Comparing the CA to the ASLA, the conditional effect of ad type on attitudes toward seeking professional help was not significant for individuals at any level of depressive symptomatology. Comparing the CA to the CLA, the conditional effect of ad type on attitudes was not significant for individuals with low depressive symptomatology or mean depressive symptomatology (θX→Y = −.05, SE = .03, t(1348) = −1.93, p = .05, 95% CI [−.11, .001]), but it was significant for individuals with high depressive symptomatology (θX→Y = −.11, SE = .04, t(1348) = −2.49, p = .01, 95% CI [−.20, −.02]). Individuals with high depressive symptomatology who viewed the CLA reported significantly more negative attitudes toward seeking professional help than the CA. Partially supporting H5, comparing the ASLA to the CLA showed that the conditional effect of ad type on attitudes was not significant for any level of depressive symptomatology. Supporting H3, state reactance was negatively associated with attitudes toward seeking professional help (B = −.17, SEB = .03, t(2008) = −5.53, p < .001, 95% CI [−.24, −.11]). Supporting H4, state reactance explains the relationship between depressive symptomatology and attitudes for all ads (CA: c’ = −.01, SEc’ = .004, t(2008) = −2.99, p = .003, 95% CI [−.02, −.004], ab = −.002, boot SEab = .001, 95% boot CI [−.004, −.001]; ASLA: c’ = −.02, SEc’ = .004, t(2008) = −4.17, p < .001, 95% CI [−.02, −.01], ab = −.004, boot SEab = .001, 95% boot CI [−.006, −.002]; CLA: c’ = −.02, SEc’ = .004, t(2008) = −5.61, p < 001, 95% CI [−.03, −.01], ab = −.003, boot SEab = .001, 95% boot CI [−.004, −.001]).

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HSI-RP. The model with the covariates explained 7.76% of the variance in HSI-RP, F(11, 1911) = 11.57, p < .001, d = −.12, 95% CI [−.21, −.02]. Supporting H1, there was a significant main effect of depressive symptomatology, suggesting that as depressive symptomatology increased, HSI-RP decreased (B = −.03, SEB = .005, t(1911) = −7.43, p < .001, 95% CI [−.04, −.03]). However, neither interaction was significant. Failing to support H3, state reactance was not associated with HSI-RP. Failing to support H4, the relationship between depressive symptomatology and HSI-RP was not explained by state reactance for any ad. HSI-Fr. The model with the covariates explained 5.09% of the variance in HSI-Fr, F(11, 1976) = 8.35, p < .001, d = −.18, 95% CI [−.27, −.08]. In support of H1, there was a significant main effect for depressive symptomatology such that as depressive symptomatology increased, HSIF decreased (B = −.03, SEB = .004, t(1976) = −6.78, p < .001, 95% CI [−.04, −.02]). However, neither interaction was significant, though the BDI × ASLA interaction was nonsignificant at the p = .06 level (B = −.02, SEB = .009, t(1976) = −1.91, p = .06, 95% CI [−.03, .0004]). Failing to support H3, state reactance was not associated with HSI-Fr. Failing to support H4, the relationship between depressive symptomatology and HSI-Fr was not explained by state reactance. HSI-P. The model with the covariates explained 7.30% of the variance in HSI-P, F(11, 1930) = 13.90, p < .001, d = −.22, 95% CI [−.32, −.13]. Supporting H1, there was a significant main effect of depressive symptomatology such that as depressive symptomatology increased, HSIP decreased (B = −.04, SEB = .005, t(1930) = −7.21, p < .001, 95% CI [−.05, −.03]). However, neither interaction was significant. Supporting H3, state reactance was negatively associated with HSI-P (B = −.13, SEB = .06, t(1930) = −2.12, p = .03, 95% CI [−.26, −.01]). Supporting H4 for all ads, the relationship between depressive symptomatology and HSI-P was explained by state reactance (CA: c’ = −.04, SEc’ = .008, t(1930) = −4.54, p < .001, 95% CI [−.05, −.02], ab = −.002, boot SEab = .001, 95% boot CI [−.004, −.0002]; ASLA: c’ = −.03, SEc’ = .008, t(1930) = −3.79, p < .001, 95% CI [−.05, −.01], ab = −.003, boot SEab = .002, 95% boot CI [−.006, −.0002]; CLA: c’ = −.04, SEc’ = .008, t(1930) = −5.45, p < .001, 95% CI [−.06, −.03], ab = −.002, boot SEab = .001, 95% boot CI [−.005, −.0003]). HSI-Fm. The model with the covariates explained 5.24% of the variance in HSI-Fm, F(11, 1970) = 9.45, p < .001, d = .12, 95% CI [.02, .21]. Supporting H1, there was a main effect of depressive symptomatology, suggesting that as depressive symptomatology increased, HSI-Fm decreased (B = −.03, SEB = .005, t(1970) = −5.65,

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p < .001, 95% CI [−.03, −.02]). However, neither interaction was significant. Supporting H3, state reactance was negatively associated with HSI-Fm (B = −.16, SEB = .06, t(1970) = −2.80, p = .005, 95% CI [−.28, −.05). Supporting H4 for all ads, the relationship between depressive symptomatology and HSI-Fm was explained by state reactance (CA: c’ = −.03, SEc’ = .007, t(1970) = −3.85, p < .001, 95% CI [−.04, −.01], ab = −.002, boot SEab = .001, 95% boot CI [−.004, −.001]; ASLA: c’ = −.02, SEc’ = .007, t(1970) = −3.16, p = .002, 95% CI [−.04, −.01], ab = −.004, boot SEab = .001, 95% boot CI [−.007, −.001]; CLA: c’ = −.03, SEc’ = .007, t(1970) = −3.75, p < .001, 95% CI [−.04, −.01], ab = −.002, boot SEab = .001, 95% boot CI [−.005, −.001]). HSI-MHP. The model with the covariates explained 8.72% of the variance in HSI-HSI-MHP, F(11, 1962) = 16.81, p < .001, d = −.04, 95% CI [−.13, .05]. There was a main effect for depressive symptomatology (B = −.02, SEB = .004, t(1962) = −6.03, p < .001, 95% CI [−.03, −02]). In support of H1, the greater the depressive symptomatology reported, the less HSI-MHP. However, both interactions were nonsignificant. Supporting H3, state reactance was negatively associated with HSIMHP (B = −.22, SEB = .05, t(1962) = −4.18, p < .001, 95% CI [−.32, −.11]). Supporting H4 for all ads, the relationship between depressive symptomatology and HSI-MHP was explained by state reactance (CA: c’ = −.02, SEc’ = .006, t(1962) = −3.40, p < .001, 95% CI [−.03, −.01], ab = −.003, boot SEab = .001, 95% boot CI [−.005, −.001]; ASLA: c’ = −.03, SEc’ = .007, t(1962) = −4.18, p < .001, 95% CI [−.04, −.01], ab = −.005, boot SEab = .001, 95% boot CI [−.008, −.003]; CLA: c’ = −.03, SEc’ = .007, t(1962) = −4.01, p < .001, 95% CI [−.04, −.01], ab = −.003, boot SEab = .001, 95% boot CI [−.005, −.001]). STUDY 1 DISCUSSION Hypotheses 1, 2, and 4 received complete support, and hypotheses 3 and 5 received partial support, but all are indicative of the challenge faced by people attempting to influence people with depression to seek help. Increased levels of depressive symptomatology were associated with increased self-stigma, less favorable attitudes toward help seeking, and reduced intentions to seek help. Increased levels of depressive symptomatology were also associated with increased reactance toward messages encouraging help seeking; further, state reactance toward the D-PSAs was associated with reduced help-seeking inclinations across several, but not all, of the help-seeking measures. For all helpseeking measures that were associated with state reactance, state reactance toward the D-PSAs mediated the relationship between increased levels of depressive symptomatology and

reduced help-seeking inclinations. The results of the moderated mediation did not fully support H5, but the analyses indicate the influence of autonomy-supportive messages on people with low levels of depressive symptomatology is not necessarily akin to the responses of people with higher levels of depressive symptomatology. Findings were not revealed for all outcome measures, but among people with the highest levels of depressive symptomatology, the controlling language D-PSA and the autonomy-supportive D-PSA never performed better than the control, but there was occasion where each one provided evidence of a boomerang effect.

STUDY 2 RESULTS Similar to Study 1, seven multivariate outliers were removed based on Mahalanobis distance (from N = 784 to N = 777). Gender, age, current diagnosis of depression, trait reactance, and relevance of ad were used as covariates. ANCOVA was used for the manipulation check, while hypotheses were tested with correlational analysis (H1–H3) and the same bootstrap moderated mediation models used in Study 1 (H3–H5; PROCESS, Hayes, 2012). One standard deviation below the mean (0.75) and the mean (11.35) represent no to minimal depressive symptomatology, while one standard deviation above the mean (21.95) denotes moderate depressive symptomatology. Manipulation Check The ANCOVA demonstrated mean differences on controlling language for the different ad types, F(2, 771) = 140.48, p < .001, ηp 2 = .27. The CLA (M = 4.41) was rated as having significantly more controlling language than the ASLA (M = 2.69, Mdiff = 1.72, SE = 0.12, p < .001) and the CA (M = 2.51, Mdiff = 1.90, SE = 0.13, p < .001). Correlational Analysis In partial support of H1, among those who viewed a control ad (n = 222), depressive symptomatology was negatively associated with ASH-RP (r = −.21, p = .002), and HSI-RP (r = −.14, p = .04). However, depressive symptomatology was not associated with SSOSH (r = .12, p = .07), ASH-MHP (r = −.08, p = .25), or HSI-MHP (r = −.06, p = .38). H2 and H3 considered only those participants who viewed a D-PSA (n = 555). Supporting H2, depressive symptomatology was positively associated with state reactance (r = .10, p = .02). In support of H3, state reactance was positively associated with SSOSH (r = .16, p < .001) and negatively associated with ASH-RP (r = −.17, p < .001), ASH-MHP (r = −.21, p < .001), HSI-RP (r = −.14, p = .001), and HSI-MHP (r = −.17, p < .001).

REACTANCE TO DEPRESSION PSA

The model with the covariates explained 8.42% of the variance in state reactance, F(10, 766) = 6.32, p < .001, d = .12, 95% CI [−.04, .27]. There were significant main effects for depressive symptomatology (B = .01, SEB = .003, t(766) = 3.01, p = .003, 95% CI [.003, .02]) and the CLA (B = .18, SEB = .08, t(766) = 2.39, p = .02, 95% CI [.03, .33]). Supporting H2, greater depressive symptomatology and the CLA were associated with greater state reactance. These main effects were qualified by significant BDI × ASLA (B = .01, SEB = .006, t(766) = 2.20, p = .03, 95% CI [.002, .03]) and BDI × CLA interactions (B = .02, SEB = .007, t(766) = 2.13, p = .03, 95% CI [.001, .03], Figure 4). Ad type was a significant moderator of the relationship between depressive symptomatology and state reactance. The conditional effect of depressive symptomatology on state reactance was significant for individuals who viewed the ASLA (θX→Y = .01, SE = .004, t(766) = 2.92, p = .004, 95% CI [.004, .02]) and the CLA (θX→Y = .01, SE = .006, t(766) = 2.54, p = .01, 95% CI [.003, .03]). Comparing the CA to the ASLA showed no significant conditional effect of ad type on state reactance for individuals at any level of depressive symptomatology; however, the conditional effect for individuals at high levels of depressive symptomatology was nonsignificant at the p = .05 level (θX→Y = .18, SE = .09, t(495) = 1.94, p = .05, 95% CI [−.002, .37]), suggesting a nonsignificant trend that the ASLA was associated with greater state reactance than the CA for individuals with high levels of depressive symptomatology. Comparing the CA to the CLA showed significant conditional effects of ad type for individuals with mean (θX→Y = .09, SE = .04, t(486) = 2.43, p = .02, 95% CI [.02, .17]) and high levels

of depressive symptomatology (θX→Y = .18, SE = .05, t(486) = 3.28, p = .001, 95% CI [.07, .28]). For individuals with mean and high levels of depressive symptomatology, the CLA was associated with greater state reactance than the CA. Partially supporting H5, comparing the ASLA to the CLA, the conditional effect of ad type was not significant for participants with low or high levels of depressive symptomatology, but it was significant for participants at mean levels of depressive symptomatology (θX→Y = .15, SE = .07, t(546) = 2.09, p = .04, 95% CI [.009, .29]). For individuals with mean levels of depressive symptomatology, the CLA produced greater state reactance than the ASLA. SSOSH. The model with the covariates explained 14.06% of the variance in SSOSH, F(11, 765) = 12.30, p < .001, d = −.39, 95% CI [−.55, −.24]. Supporting H1, there was a significant main effect of depressive symptomatology (B = .03, SEB = .005, t(765) = 5.47, p < .001, 95% CI [.02, .04]), suggesting that as depressive symptomatology increased, SSOSH increased. There was a significant BDI × ASLA interaction (B = .02, SEB = .01, t(765) = 2.16, p = .03, 95% CI [.002, .04]); however, the BDI × CLA interaction was not significant (Figure 5). Comparing the CA to the ASLA, the conditional effect of ad type on SSOSH was not significant for people at any level of depressive symptomatology. Comparing the CA to the CLA showed a significant conditional effect of ad type for people with low depressive symptomatology (θX→Y = −.15, SE = .07, t(486) = −2.04, p = .04, 95% CI [−.29, −.005]), but it was nonsignificant for mean

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SSOSH

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Moderated Mediation Analysis: State Reactance

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1 Low BDI

Mean BDI

High BDI

FIGURE 4 Ad type moderating the relationship between depressive symptomatology and state reactance. The state reactance scale uses z-scores. BDI is a continuous variable that was centered for analyses. Low BDI is 1 SD below the mean, while high BDI is 1 SD above the mean. Prior to centering the mean BDI score was 11.35, 1 SD below the mean was 0.75, and 1 SD above the mean was 21.95.

Low BDI

Mean BDI

High BDI

FIGURE 5 Ad type moderating the relationship between depressive symptomatology and self-stigma of seeking help. BDI is a continuous variable that was centered for analyses. Low BDI is 1 SD below the mean, while high BDI is 1 SD above the mean. Prior to centering the mean BDI score was 11.35, 1 SD below the mean was 0.75, and 1 SD above the mean was 21.95.

LIENEMANN AND SIEGEL

and high depressive symptomatology. For individuals with low levels of depressive symptomatology, the CLA was associated with less SSOSH than the CA. Partially supporting H5, comparing the ASLA to the CLA demonstrated nonsignificant conditional effects for people with any level of depressive symptomatology. Supporting H3, state reactance was positively associated with SSOSH (B = .14, SEB = .06, t(765) = 2.38, p = .02, 95% CI [.02, .25]). Supporting H4 for the D-PSAs, the relationship between depressive symptomatology and SSOSH was explained by state reactance (ASLA: c’ = .04, SEc’ = .007, t(765) = 5.10, p < .001, 95% CI [.02, .05], ab = .002, boot SEab = .001, 95% boot CI [.0003, .004]; CLA: c’ = .03, SEc’ = .008, t(765) = 3.88, p < .001, 95% CI [.01, .04], ab = .002, boot SEab = .001, 95% boot CI [.0003, .005]). ASH-RP. The model with the covariates explained 13.81% of the variance in ASH-RP, F(11, 765) = 8.56, p < .001, d = .33, 95% CI [.17, .48]. Supporting H1, there was a significant main effect of depressive symptomatology suggesting that the greater the depressive symptomatology reported the more negative ASH-RP (B = −04, SEB = .007, t(765) = −5.33, p < .001, 95% CI [−.05, −.02]). There was also a significant main effect of the CLA suggesting that the CLA was associated with positive ASH-RP (B = .27, SEB = .14, t(765) = 1.97, p = .0495, 95% CI [.001, .54]). However, neither interaction was significant. Supporting H3, state reactance was negatively associated with ASHRP (B = −.19, SEB = .08, t(765) = −2.57, p = .01, 95% CI [−.34, −.05]). Supporting H4 for the D-PSAs, the relationship between depressive symptomatology and ASHRP was explained by state reactance (ASLA: c’ = −.04, SEc’ = .01, t(765) = −4.11, p < .001, 95% CI [−.06, −.02], ab = −.003, boot SEab = .001, 95% boot CI [−.007, −.0005]; CLA: c’ = −.04, SEc’ = .01, t(765) = −3.88, p < .001, 95% CI [−.06, −.02], ab = −.003, boot SEab = .002, 95% boot CI [−.007, −.0005]). ASH-MHP. The model with the covariates explained 7.42% of the variance in ASH-MHP, F(11, 765) = 5.33, p < .001, d = .24, 95% CI [.09, .40]. Supporting H1, there was a significant main effect of depressive symptomatology suggesting that higher depressive symptomatology led to more negative ASH-MHP (B = −.02, SEB = .006, t(765) = −3.75, p < .001, 95% CI [−.03, −.01]). Neither interaction was significant. Supporting H3, state reactance was negatively associated with ASH-MHP (B = −.21, SEB = .07, t(765) = −2.86, p = .004, 95% CI [−.35, −.07]). Supporting H4 for the D-PSAs, the relationship between depressive symptomatology and ASH-MHP was explained by state reactance (ASLA: c’ = −.03, SEc’ = .008, t(765) = −3.55, p < .001, 95% CI [−.04, −.01], ab = −.003, boot SEab = .001, 95% boot CI [−.007, −.0007]; CLA: c’ = −.03, SEc’ = .01, t(765) = −2.90, p = .004, 95% CI [−.05, −.01], ab = −.003, boot SEab = .002, 95% boot CI [−.007, −.0007]).

HSI-RP. The model with the covariates explained 12.08% of the variance in HSI-RP, F(11, 763) = 7.64, p < .001, d = .21, 95% [.06, .37]. Supporting H1, there was a significant main effect of depressive symptomatology such that as depressive symptomatology increased, HSIRP decreased (B = −.04, SEB = .008, t(763) = −4.65, p < .001, 95% CI [−.05, −.02]). Neither interaction was significant, though the BDI × ASLA and BDI × CLA interactions were at the p = .06 and .07 levels, respectively. Supporting H3, state reactance was negatively associated with HSI,RP (B = −.18, SEB = .08, t(763) = −2.19, p = .03, 95% CI [−.34, −.02]). Supporting H4 for the DPSAs, state reactance explained the relationship between depressive symptomatology and HSI,RP (ASLA: c’ = −.04, SEc’ = .01, t(763) = −3.82, p < .001, 95% CI [−.07, −.02], ab = −.002, boot SEab = .001, 95% boot CI [−.006, −.0004]; CLA: c’ = −.04, SEc’ = .01, t(763) = −3.77, p < .001, 95% CI [−.07, −.02], ab = −.003, boot SEab = .002, 95% boot CI [−.007, −.0005]). HSI-MHP. The model with the covariates explained 9.90% of the variance in HSI-MHP, F(11, 765) = 8.32, p < .001, d = .32, 95% CI [.17, .48]. Supporting H1, there was a significant main effect of depressive symptomatology such that as depressive symptomatology increased, HSIMHP decreased (B = −.03, SEB = .007, t(765) = −4.69, p < .001, 95% CI [−.05, −.02]). This main effect was qualified by a significant BDI × ASLA interaction (B = −.03, SEB = .01, t(765) = −1.98, p = .049, 95% CI [−.06, −.0002]), suggesting ad type was a significant moderator (Figure 6). However, the BDI × CLA interaction was not significant. 7 6 5 HSI-MHP

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5.72 5.70 5.29

5.29 5.23 5.15

5.01 4.86 4.76 Control Ad ASLA CLA

4 3 2 1 Low BDI

Mean BDI

High BDI

FIGURE 6 Ad type moderating the relationship between depressive symptomatology and help seeking intentions from a mental health professional. BDI is a continuous variable that was centered for analyses. Low BDI is 1 SD below the mean, while high BDI is 1 SD above the mean. Prior to centering the mean BDI score was 11.35, 1 SD below the mean was 0.75, and 1 SD above the mean was 21.95.

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REACTANCE TO DEPRESSION PSA

Comparing the CA to the ASLA showed that the conditional effect of ad type was not significant at any level of depressive symptomatology. Comparing the CA to the CLA suggested that the conditional effect of ad type was significant for people at low levels of depressive symptomatology (θX→Y = .22, SE = .11, t(486) = 2.01, p = .045, 95% CI [.005, .43]). However, it was not significant for people with mean or high levels of depressive symptomatology. The results suggest that for people with low levels of depressive symptomatology the CLA was associated with greater HSI-MHP than the CA. In partial support of H5, comparing the ASLA to the CLA showed no significant conditional effects of ad type on intentions. Supporting H3, state reactance was negatively associated with HSIMHP (B = −.18, SEB = .08, t(765) = −2.41, p = .02, 95% CI [−.33, −.03]). Supporting H4 for the D-PSAs, the relationship between depressive symptomatology and HSIMHP was explained by state reactance (ASLA: c’ = −.04, SEc’ = .01, t(765) = −4.25, p < .001, 95% CI [−.06, −.02], ab = −.002, boot SEab = .001, 95% boot CI [−.006, −.0003]; CLA: c’ = −.04, SEc’ = .01, t(765) = −3.38, p < .001, 95% CI [−.06, −.02], ab = −.003, boot SEab = .002, 95% boot CI [−.007, −.0005]).

STUDY 2 DISCUSSION Complementing the results from Study 1, the first hypothesis was supported. Increased depressive symptomatology was significantly associated with increased self-stigma of seeking professional help, reduced attitudes toward seeking help from a romantic partner or from a mental health professional, and less intentions to seek help from a romantic partner or a mental health professional. Also mimicking the results of Study 1, level of depressive symptomatology was positively associated with state reactance toward the D-PSAs. The third hypothesis also received support. Combining the responses to both D-PSAs, there was a positive relationship between state reactance toward the D-PSA and selfstigma of seeking help. There was a negative relationship between state reactance toward the D-PSAs and help-seeking attitudes (romantic partner, medical professional) and intentions (romantic partner, medical professional). The next hypothesis (H4) predicted that the relationship between increased depressive symptomatology and help-seeking outcomes among those exposed to either D-PSA would be mediated by state reactance. The proposed mediation was supported for all outcomes. The fifth hypothesis proposed moderated mediation such that the interaction between level of depressive symptomatology and D-PSA language intensity was posited to predict state reactance, which would then mediate the relationship between the interaction of level of depressive symptomatology and D-PSA language intensity and helpseeking outcomes. Among people with the lowest levels

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of depressive symptomatology, there were no significant differences in state reactance between people who received the control ad and people who received the controlling language D-PSA; however, significant differences between these two groups emerged among people with mean and highest levels such that the controlling language ad produced greater state reactance. Further, and somewhat unexpectedly, there were no differences in state reactance when comparing the autonomy-supportive D-PSA and the controlling D-PSA for those with the lowest and highest levels of depressive symptomatology. However, for participants with mean levels of depressive symptomatology the controlling D-PSA resulted in more state reactance than the autonomy-supportive D-PSA. We next assessed the relationship between exposure to the different ads and help-seeking outcomes. For selfstigma of seeking professional help, there was no difference between those exposed to the control ad and those exposed to the autonomy-supportive ad, nor was there a difference between those exposed to the autonomy-supportive ad versus the controlling language ad. However, there was a difference between the controlling language ad and the control ad for the people with the lowest levels of depressive symptomatology, but this was not the case for those with the highest levels of depressive symptomatology. The three ads had no differential impact on attitudes toward help seeking (romantic partner, mental health professional) or help-seeking intentions (romantic partner). Turning to help seeking intentions (mental health professional), the controlling ad resulted in significantly greater help seeking intentions than the control ad for people with the lowest levels of depressive symptomatology, but this effect was not revealed among those with the highest levels.

GENERAL DISCUSSION The current set of studies highlights the challenge in increasing help seeking among people with elevated depressive symptomatology through the use of D-PSAs. For the majority of help-seeking outcomes assessed in both studies, increased levels of depressive symptomatology were associated with more negative help-seeking attitudes and intentions. Highlighting the role played by state reactance, there was a positive relationship between depressive symptomatology and state reactance toward D-PSAs; this occurred in both studies, indicating that the effect is unlikely to be the result of the specific ads utilized. Additionally, among those exposed to a D-PSA, state reactance was associated with reduced help-seeking attitudes and intentions, and state reactance mediated the relationship between level of depressive symptomatology and helpseeking outcomes. Further highlighting the challenge faced by attempts to persuade people with elevated depressive symptomatology to seek help, and replicating the boomerang

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effects that have previously been revealed, results from Study 1 indicate an occasion where the controlling language DPSA led to more negative help-seeking attitudes than the control. There were no occasions where either D-PSA led to more favorable help-seeking responses than the control. In Study 2, among people with the highest levels of depression, the autonomy-supportive language D-PSA never led to more negative outcomes than the control ad, but it also never led to more favorable outcomes. These analyses indicate that autonomy-supportive messages may not serve to reduce reactance or to improve the persuasive strength of a message when the target is people with heightened levels of depressive symptomatology. Limitations and Strengths Limitations include the self-selection of participants into a depression study. Additionally, the study could have benefited from a greater proportion of participants with elevated depressive symptomatology. However, in both studies the proportion of participants with a current diagnosis of depression and a lifetime diagnosis of depression is higher than national 12-month and lifetime prevalence rates of major depressive disorder (MDD). National 12-month prevalence rates of MDD are 6.7% (Kessler, Chiu, Demler, & Walters, 2005), while lifetime prevalence rates are 16.6% (Kessler et al., 2005). Study 1 current and lifetime diagnoses of depression rates were 19.0% and 36.8%, respectively, while Study 2 current and lifetime diagnoses of depression rates were 14.5% and 31.3%, respectively. A theoretical limitation is that while this current study was guided by psychological reactance theory, that is not the only theoretical framework that can be used to describe boomerang effects (e.g., Ringold, 2002). Implications The current studies indicate that persuading people with elevated depressive symptomatology using D-PSAs can be challenging. Results indicate that autonomy-supportive messages might not be a path through which success will be uncovered. However, results also indicate the importance of trying to reach this population. Additional means of circumventing state reactance are needed. The success of mistargeting (e.g., “do you know someone who is fighting depression”) in a recent series of studies indicated that DPSAs can successfully influence help-seeking attitudes and intentions (Siegel et al., 2014); however, there is a critical need for additional approaches.

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State Psychological Reactance to Depression Public Service Announcements Among People With Varying Levels of Depressive Symptomatology.

Campaigns seeking to help people with depression can be effective, but they can also backfire. Psychological reactance is proposed as a partial explan...
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