Cancer-related fatigue in a couples’ context
Müller, Fabiola
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Müller, F. (2018). Cancer-related fatigue in a couples’ context: The role of daily cognitions and partner behaviors. University of Groningen.
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The role of daily cognitions and partner behaviors
PhD thesis by Fabiola Müller
ISBN: 978-94-034-0885-9 (printed version) ISBN: 978-94-034-0884-2 (electronic version) Cover design: Fabiola Müller
Lay-out: Thomas van der Vlis, Persoonlijk proefschrift Printed by: Ipskamp printing, www.ipskampprinting.nl
The research reported in this thesis was funded by the Dutch Cancer Society (RUG 2013-5928) and conducted within the Research Institute SHARE of the University Medical Center Groningen and the University of Groningen, The Netherlands. The printing of this thesis was financially supported by SHARE, the faculty of Medical Sciences at the University Medical Center Groningen, and the University of Groningen.
Copyright © 2018, F. Müller, Groningen, The Netherlands
All rights reserved. No parts of this thesis may be reproduced or transmitted in any form or by any means without prior written permission of the author.
The role of daily cognitions and partner behaviors
PhD thesis
to obtain the degree of PhD at the University of Groningen
on the authority of the Rector Magnificus Prof. E. Sterken
and in accordance with the decision by the College of Deans. This thesis will be defended in public on Tuesday 11 September 2018 at 11:00 hours
by
Fabiola Müller
born on 26 December 1987 in Steinfurt, Germany
Co-supervisor
Dr. M.A. Tuinman
Assessment committee
Prof. U. Bültmann Prof. L. Goubert Prof. E.M.A. Smets
Hjelmstad, L. T. (1993). Fine Black Lines. Reflections on Facing Cancer, Fear and Loneliness. Engle-wood, Colorado: Mulberry Hill Press.
At first I was energized The diagnosis shocked me into action
The clutching fear galvanized me The details demanded attention The family’s tears called for comfort
The decisions were made
The adrenaline flowed and I was energized But one day all the energy was gone –
Physical, psychic, emotional – The days turned into weeks And the weeks into months
Now I search Each cell of my body Each corner of my mind
For one tiny spark
Berscheid, E. (1999). The Greening of Relationship Science. American Psychologist, 54(4), 260–266. http://doi.org/10.4324/9780203311851
of the human condition: We are born into relationships, we live our lives in relationships with others,
and when we die, the effects of our relationships survive in the lives of the living […].
Relationships thus are the context in which most human behavior occurs, and so understanding and predicting that behavior
is difficult, if not impossible, if that context is ignored.
Chapter 1 General introduction 11
Chapter 2 Clinically distinct trajectories of fatigue and their
longitu-dinal relationship with the disturbance of personal goals following a cancer diagnosis
British Journal of Health Psychology, 2017, 22(3), 627-643
29
Chapter 3 Chronic multimorbidity impairs role functioning in
mid-dle-aged and older individuals mostly when non-partnered or living alone
PLoS ONE, 2017, 12(2), e0170525
59
Chapter 4 The reciprocal relationship between daily fatigue and
cata-strophizing following cancer treatment: Affect and physical activity as potential mediators
Psycho-Oncology, 2018, 27(3), 831-837
85
Chapter 5 Associations of daily partner responses with fatigue
inter-ference and relationship satisfaction in colorectal cancer patients
Health Psychology, in press
105
Chapter 6 Daily co-rumination mediates the maladaptive effect of
spouse catastrophizing on cancer patient’s fatigue
133
Chapter 7 General discussion 161
Appendix Supporting information
Summary in English Summary in Dutch About the author Acknowledgements
List of previous SHARE dissertations
189 202 208 217 218 222
Chapter 1
Cancer-related fatigue: The scale of the problem
A growing group of individuals is affected by cancer and its long-term adverse outcomes. Due to the aging population, widely available screening programs, and advanced treatment options, an increasing number of individuals is expected to be diagnosed with and to live past their cancer diagnosis (Siegel et al., 2012). In the Netherlands, the 5-year cancer survival rate has improved from 41% to 54% for men and from 57% to 63% for women between 1989 and 2007 and is predicted to increase further in the upcoming years. It is expected that 660.000 individuals will be living with a cancer diagnosis in 2020, a substantial increase compared to the prevalence rate of 419.293 documented in 2009 (KWF Kankerbestrijding, 2011). Similar trends are expected in the United States where the number of individuals living with a past cancer diagnosis is estimated to rise from 13.7 million in 2012 to almost 18 million in 2022 (Siegel et al., 2012). Colorectal cancer is among the most prevalent cancer types in both men and women (KWF Kankerbestrijding, 2011; Siegel et al., 2012). In the Netherlands, more than half of the patients with colorectal cancer can expect to be alive 5 years after receiving their diagnosis (i.e., 5-year relative survival rate of 59% for men and women; KWF Kankerbestrijding, 2011). Due to the high prevalence and relatively high survival rate, colorectal cancer patients can be expected to form a substantial proportion of the individuals living past a cancer diagnosis.
The expected increase of individuals living with a history of cancer stresses the pressing need to address the patients’ long-term adverse outcomes. One of the most common and interfering symptoms cancer survivors (see Box 1) experi-ence is cancer-related fatigue (Arndt, Stegmaier, Ziegler, & Brenner, 2006; Jones et al., 2016; Thong et al., 2013). The National Comprehensive Cancer Network [NCCN] defines cancer-related fatigue as “distressing, persistent, subjective sense of physical, emotional, and/or cognitive tiredness or exhaustion related to cancer or cancer treatment that is not proportional to recent activity and interferes with usual functioning” (NCCN, 2016). This definition stresses the multidimensional character of cancer-related fatigue that is experienced on a physical, emotional and cognitive level.
Box 1: Cancer survivor
In the current thesis, the term cancer survivor is used to broadly refer to cancer patients who have completed their cancer treatment or those who live beyond their cancer diagnosis without being treated with curative intent. The term survivor has been subject to debate as it might elicit associations of a cancer diagnosis with a battle. By no means is the use of this term intended to align with this association or offend people diagnosed with cancer and their close ones.
Cancer-related fatigue from an intrapersonal perspective
In order to understand the scope of the fatigue problem, it is necessary to in-vestigate the prevalence and development of fatigue as well as its adverse effects on patients’ daily life (i.e., fatigue interference, goal disturbance). Further, more research is needed that investigates factors that explain fatigue in patients after the completion of their cancer treatment. Insights into the development of fatigue and predictors of post-treatment fatigue are prerequisites to establish interventions aiming to relieve the fatigue burden in the growing group of patients living with a past cancer diagnosis.
Development and interfering effects of cancer-related fatigue
There is ample evidence that fatigue is experienced by the majority of cancer pa-tients during their cancer treatment (Prue, Rankin, Allen, Gracey, & Cramp, 2006; Servaes, Verhagen, & Bleijenberg, 2002a) and one quarter to one third of patients who have completed treatment (Jones et al., 2016; Servaes, Gielissen, Verhagen, & Bleijenberg, 2007). These findings stress that cancer-related fatigue is highly common during treatment and implies that some cancer patients recover from fatigue after treatment completion, while some remain fatigued. However, most studies on the prevalence of fatigue have either a cross-sectional design or a lon-gitudinal design reporting on average group-trends in the development of fatigue (e.g., Goedendorp, Gielissen, Verhagen, & Bleijenberg, 2013; Jones et al., 2016). Yet, whether and how fatigue develops differently for subgroups of patients from diagnosis, throughout treatment and until survivorship is still largely unknown. Further, as cross-sectional and longitudinal study designs assess fatigue retro-spectively over the course of weeks or months, we lack knowledge on how fatigue develops in shorter time intervals, that is, within several hours within the day.
The burden of fatigue is high. Cancer-related fatigue is associated with a substantial loss of quality of life (Schmidt et al., 2012) and interferences in many
domains ranging from daily and occupational functioning to patients’ social life and mental health (Curt et al., 2000; Donovan, McGinty, & Jacobsen, 2013; Dor-land et al., 2016; Meeske et al., 2007). Many patients report fatigue as one of their most interfering symptoms, even more so than pain or nausea (Arndt et al., 2006; Stone et al., 2003), which underlines the burden fatigue puts on the patients. Un-derstanding how fatigue develops over time and how it relates to interferences, both longitudinally and within days, is necessary to formulate recommendations about screening and treatment of patients most likely to be affected by long-term fatigue and its adverse effects.
A cognitive-behavioral model of cancer-related fatigue
Since the 1990s, evidence is accumulating that clinical variables, such as cancer diagnosis or treatment modalities, are unrelated to or insufficient to explain per-sistent long-term fatigue (e.g., Andrykowski, Curran, & Lightner, 1998; Servaes et al., 2002a; Smets et al., 1998). Instead, research suggests that psychosocial vari-ables such as cognitions and behaviors are related to fatigue in the long-term (e.g., Goedendorp et al., 2013; Servaes, Verhagen, & Bleijenberg, 2002b). These findings support a cognitive-behavioral model of fatigue (Donovan, Small, An-drykowski, Munster, & Jacobsen, 2007), which suggests a distinction between precipitating and perpetuating factors of cancer-related fatigue. That is, while clinical variables are assumed to initially precipitate fatigue, mostly cognitive and behavioral variables are expected to perpetuate fatigue after treatment has been completed. Most prominently, catastrophizing cognitions about fatigue (e.g., worrying that the fatigue will become worse) have been shown to predict long-term fatigue in cancer survivors (Goedendorp et al., 2013; Lukkahatai & Saligan, 2013). This finding demonstrated that intrapersonal cognitions might maintain fatigue after treatment completion. Indeed, cognitions appear to be potent targets for interventions aiming to relieve the fatigue burden in cancer survivors. That is, cognitive behavior therapy developed to target maladaptive cognitions (Blei-jenberg, Gielissen, Bazelmans, Berends, & Verhagen, 2004) has been shown to be effective in relieving patients’ fatigue burden (Gielissen, Verhagen, & Bleijenberg, 2007; Gielissen, Verhagen, Witjes, & Bleijenberg, 2006). However, much about the perpetuating effect of maladaptive cognitions remains unknown. For example, we currently lack knowledge about which affective (i.e., changes in mood) and
behavioral processes (i.e., changes in activity) explain how catastrophizing unfolds its maladaptive effect on fatigue in daily life. Behavioral perpetuating factors have received relatively little research attention, but negative social interactions and a perceived lack of social support have been shown to contribute to persistent fa-tigue after treatment completion (Goedendorp et al., 2013; Servaes et al., 2002b). In the cognitive-behavioral tradition, behaviors are mainly considered from the patient-perspective and not as a dynamic interpersonal process limiting our cur-rent understanding of which behaviors should be targeted in interventions aiming to relieve post-treatment fatigue.
Cancer-related fatigue from an interpersonal perspective
Another important development since the 1990s is the recognition that coping with a stressor is a dyadic interpersonal process, rather than an isolated intra-personal endeavor (Bodenmann, 1995, 1997; Coyne & Smith, 1991; DeLongis & O’Brien, 1990). That is, many patients do not cope alone, but experience a stressor such as cancer in the context of their relationship. The concept of dyadic coping emphasizes that both partners of the couple react to and cope with a stressor as an interrelated system (Bodenmann, 2005; Hagedoorn, Sanderman, Bolks, Tuinstra, & Coyne, 2008; Traa, De Vries, Bodenmann, & Den Oudsten, 2015). The coping strategies of cancer patients and their partners can take on various forms (e.g., empathic understanding, protective buffering) and as such can have both adaptive and maladaptive effects on individual and relationship outcomes (Bodenmann, 2005; Regan et al., 2015). Cancer-related fatigue can be conceptualized as a stressor the dyad copes with as an interrelated system. As such, considering the dyadic context can help us understand the interpersonal factors that might perpetuate fatigue, as well as the impact of dyadic coping efforts on the couples’ relationship. Two interpersonal models can be applied.
The operant model applied to cancer-related fatigue
The operant model in the field of pain (Fordyce, 1976) acknowledges that symptoms are not experienced in isolation but within a social context that might contribute to the patient’s symptom development. The model states that partner responses to-wards patients’ illness-behavior (e.g., resting) and well-behavior (e.g., being active) can either function as reinforcement or punishment. As such, partner responses
can either increase or reduce the frequency of illness-behaviors and hence impact other symptom outcomes, including symptom severity and symptom interferences (i.e., the degree to which patients’ symptoms interfere with their daily life such as work and social activities). Solicitous partner responses, such as taking over house-hold chores, are considered to be maladaptive as they reinforce illness-behavior. Punishing partner responses, such as responding with frustration, are considered to be adaptive as they discourage illness-behavior. Research on pain in the tradi-tion of the operant model provided ample evidence that partner responses have the potential to relieve or worsen patients’ symptom outcomes (e.g., Newton-John, 2002). These studies have been vital, as they demonstrated that symptoms are amenable to social contingencies and that their long-term developments cannot be fully understood without investigating partner behaviors. There is some evidence suggesting that also cancer-related fatigue might be amenable to social interactions (e.g., Goedendorp et al., 2013). However, contrary to the field of pain, we currently lack knowledge on how partner behaviors in couples coping with post-treatment fatigue might impact the patients’ fatigue experience.
The intimacy model applied to cancer-related fatigue
While the operant model acknowledges that symptoms are experienced within a social context, it is limited in mainly conceptualizing partners as exerting influ-ence upon the patients’ symptom experiinflu-ence. However, the dyadic context might not only shape symptom outcomes, but the context itself might get shaped by how couples cope. Put differently, partner behaviors might not only impact the pa-tient’s symptom outcomes, but also the couple’s relationship. Given that a healthy relationship is an important coping resource for both cancer patients and their partners (Drabe, Wittmann, Zwahlen, Büchi, & Jenewein, 2013; Manne & Badr, 2008; Yang & Schuler, 2009), it is crucial to look beyond symptom outcomes and also investigate which partner behaviors are a potential benefit or harm to the couples’ relationship.
The interpersonal process model of intimacy (Reis & Shaver, 1988) provides a framework to investigate partner behaviors’ influence on the couples’ relationship. The model states that the development of intimacy is a dynamic, dyadic process. If one partner’s self-disclosure is met with a response that communicates under-standing, validation and caring, intimacy develops. Partner responses that fail to
convey this responsiveness can create distance between partners and thus harm the couples’ relationship satisfaction. Evidence that partner support is associated with an increase in feelings of intimacy in patients diagnosed with cancer (Belcher et al., 2011) supports the rationale of this model. As such, the intimacy model allows conceptualizing partner behaviors as interpersonal processes that can either ben-efit or harm the couples’ relationship. However, only recently, researchers called attention to the impact of partner behaviors on the relationship in couples coping with pain (Cano & Williams, 2010; Prenevost & Reme, 2017). Hence, the impact of partner behaviors on relationship outcomes in couples coping with interfering and persistent symptoms, including fatigue, is not yet well understood.
Depending on the underlying research tradition, qualitatively different forms of partner behaviors are investigated. While research in the tradition of the operant model focuses on a variety of partner responses, research in the tradi-tion of the intimacy model focuses on partner communicatradi-tions. Other than the unilateral partner responses, partner communications entail mutual and dynamic partner behaviors to which both dyad members contribute. For example, commu-nications characterized by mutual self-disclosure have been associated with posi-tive relationship outcomes while hiding one’s concerns about cancer (i.e., protecposi-tive buffering) has consistently been associated with negative relationship outcomes (Regan et al., 2015). Currently, we lack insight into communications that are spe-cifically related to the adverse effects of cancer such as fatigue (e.g., co-rumination, couples’ communication extensively focusing on the negative aspects of fatigue) and how these conversations might not only influence the couples’ relationship but also patients’ symptom outcomes. Put differently, partner communications about fatigue might be another behavioral perpetuating factor of fatigue and, at the same time, influence the couples’ relationship. Integrating the operant model and intimacy model provides a valuable framework to investigate several partner behaviors (i.e., partner responses, couples’ communications) and their effects on both, individual patient outcomes as well as relationship outcomes.
A daily life perspective on cancer-related fatigue
Previous research provided important insights into the prevalence of cancer-relat-ed fatigue, its potential prcancer-relat-edictor variables and the relevance of intra- and interper-sonal processes in the adjustment to a chronic stressor. However, much research
shares the limitation that it conceptualizes and measures cognitions, behaviors, symptoms or relationship outcomes as rather static. That is, traditional research designs (e.g., cross-sectional studies) ask participants to provide a summarized report on their psychosocial states across the previous weeks or months. However, psychosocial states and symptoms are dynamic processes that unfold their effects in the context of daily life. Recent research supports this notion and demonstrated that catastrophizing cognitions (Burns et al., 2015; Holtzman & DeLongis, 2007), partner behaviors (Badr, Pasipanodya, & Laurenceau, 2013; Wilson, Martire, & Sli-winski, 2017), cancer-related fatigue (Kober et al., 2016; Timmerman, Dekker-van Weering, Tönis, Hermens, & Vollenbroek-Hutten, 2015) and relationship variables (Belcher et al., 2011; Debrot, Siegler, Klumb, & Schoebi, 2017) vary meaningfully on a daily level. In order to better understand which factors perpetuate fatigue and how dyadic coping impacts fatigue outcomes as well as the couples’ relationship, we need to investigate psychosocial concepts as dynamic processes that occur in the patients’ flow of everyday life.
The diary method (see Box 2)is well suited to investigate dynamic processes
as they unfold within individuals in their daily lives. Briefly, the repeated assess-ments of the diary method capture fluctuations of the concepts of interest and allow investigating their temporal relationships. Second, the (semi-)momentary measures reduce methodological problems of traditional designs (i.e., recall- bias). Third, diary data provide insight into the daily life of the participants as it natu-rally occurs and unfolds, fostering ecological validity and generalizability of the results obtained (Bolger, Davis, & Rafaeli, 2003; Heron & Smyth, 2010). By this, research questions can be addressed that are different from those investigated with traditional research designs. For example, traditional designs allow investigating whether patients experience more fatigue when they engage in higher levels of catastrophizing as compared with others (between-person differences) while the diary design allows investigating whether patients experience an increase in fa-tigue when they engage in higher levels of catastrophizing than typical for them (within-person process). As such, research acknowledging the dynamic nature of psychosocial processes and focusing on participants’ daily life has great theo-retical and clinical value as it provides insights into daily within-person processes (e.g., increases in catastrophizing) that can be targeted in interventions aiming to relieve fatigue.
Box 2: Diary method
In the current thesis, the term diary design/method is used to refer to studies employing an intensive longitudinal design. These designs are known under various names, e.g., ecological momentary assessment [EMA], experience sampling method [ESM], ambulatory assessment or diary study. All of these designs share the feature that time-varying constructs (e.g., cognitions, behaviors) get assessed repeatedly within individuals over time as they occur naturally in the individuals’ daily life (Bolger & Laurenceau, 2013; Schneider & Stone, 2016; Shiffman, Stone, & Hufford, 2008). A dyadic diary design refers to designs in which both members of a dyad, often intimate partners, report on their daily life experiences in the context of their relationship (Laurenceau & Bolger, 2005).
Cancer-related fatigue in a couples’ context: The role of daily cognitions and partner behaviors
The cognitive-behavioral model and the operant model pushed the field of chronic symptom development forward by acknowledging that distinct factors are re-sponsible for the initiation and perpetuation of symptoms and by demonstrating that symptoms are experienced within a social context that can contribute to their development. The intimacy model provides a complementary framework to understand how couples’ behaviors can influence the dyads’ adjustment to cancer and it directs attention explicitly to partner communications as another potential behavioral perpetuating factor of fatigue. Together, these models provide an in-trapersonal and interpersonal perspective to study perpetuating factors of fatigue.
The current thesis builds upon these models to investigate how intraper-sonal cognitions and interperintraper-sonal partner behaviors can impact the patient’s fatigue experience as well as the couple’s relationship satisfaction. In order to gain ecologically valid insights in cognitions and partner behaviors and to understand their fluctuations and within-person effects on daily fatigue and relationship out-comes, a daily perspective is applied. The insights of this thesis are hoped to inform the development and improvement of treatment modules aimed to relieve the symptom burden in couples coping with cancer-related fatigue while preserving the couples’ relationship satisfaction. Based on the outlined models and previous research, the following four questions guided the research presented in this thesis:
1. How do cancer-related fatigue and its interfering effects develop
longitudi-nally and in daily life?
2. Which intrapersonal cognitions can be targeted to benefit individual and relationship outcomes?
3. Which interpersonal partner behaviors can be targeted to benefit individual
and relationship outcomes?
4. What can we learn from the integration of an intrapersonal and
interper-sonal perspective to study cancer-related fatigue?
Outline of this thesis
By applying an intrapersonal as well as an interpersonal perspective, a dyadic diary design, and advanced statistical analyses, the following studies provide unique insights into perpetuating factors of cancer-related fatigue as well as adaptive and maladaptive dyadic coping processes and their impact on the couple’s relation-ship, see Table 1.
This thesis starts by demonstrating the relevance of the two central con-cepts of this thesis, cancer-related fatigue and adjustment to disease in a dyadic context, on a population level. That is, chapter 2 was dedicated to identify and describe subgroups of patients that differ in their longitudinal development of cancer-related fatigue and its associated goal disturbance. In chapter 3, the im-portant role of patients’ relationship status and living arrangement in mitigating the adverse effects of chronic disease has been studied. Together, the findings stress the clinical relevance of the fatigue problem and imply that daily partner behaviors are an important context to study disease outcomes. These two chapters laid the groundwork for the next chapters, which systematically address daily perpetuating factors of patients’ fatigue outcomes and predictors of couples’ rela-tionship satisfaction from an intrapersonal and interpersonal perspective. Based on the three guiding models, two classes of predictor and outcome variables are investigated, see Figure 1. Predictor variables include cognitions (i.e., patients’ and partners’ catastrophizing thoughts about fatigue) and partner behaviors (i.e., partner responses, patients’ and partners’ co-rumination) while the outcomes of interest are patients’ fatigue outcomes (i.e., fatigue severity, fatigue interference) and the couples’ relationship (i.e., patients’ and partners’ relationship satisfaction).
By applying a dyadic diary design,these chapters provide insights into how daily
cognitions and partner behaviors translate into changes in fatigue outcomes and relationship satisfaction in daily life.
Ta bl e 1 O ve rv ie w o f t he e m pi ric al c ha pt er s C hap te r Sa m pl e D es ig n Pe rs pe ct iv e A im St at ist ic al a na ly sis & so ftw are 2 C ol or ec ta l c an ce r pa tie nt s ( n = 1 83 ) Lo ng itud in al, fo llo w in g c anc er p a-tie nt s f ro m d ia gn os is t o 18 mo nt hs l at er Int ra pe rs on al Id en tif y s ub gr ou ps o f p at ie nt s d iff er in g in t he s ev er ity a nd d ev el op me nt o f t he ir fa tig ue a nd g oa l d ist ur ba nc e. G ro w th M ix tu re M od el in g: tr aj ec tor y an al ys es SP SS & L at en tG old 3 D ut ch g en er al po pu la tio n ( n = 25 214 ) Cr os s-se ct io na l, ba se lin e d at a o f t he L ife -Li ne s c ohor t s tu dy In ter per so na l St ud y t he m iti ga tin g e ffe ct o f r el at io n-sh ip s ta tu s a nd l iv in g a rr an ge me nt o n th e a dv er se e ffe ct s o f s in gl e a nd m ul tip le m or bid ity . A na ly se s o f c ov ar ia nc e: mo de ra tio n mo de l SP SS 4 C ol or ec ta l c an ce r su rv iv or s ( n = 1 01 ) D ai ly d ia ry s tu dy , re pe at ed me as ur eme nt s w ith in 1 4 d ay s Int ra pe rs on al In ve st ig at e t he p er pe tu at in g r ol e o f c at a-st ro ph iz in g i n d ai ly l ife a nd i ts a ffe ct iv e and b eh av io ra l m ed iat or s. M ul til ev el mo de lin g: me di at io n mo de l SP SS & R 5 C ol or ec ta l c an ce r su rv iv or s a nd t he ir pa rt ne rs ( n = 1 01 ) D ya di c d ai ly d ia ry st ud y, r ep ea te d me a-su re me nt s w ith in 1 4 day s In ter per so na l A na ly ze t he e ffe ct o f p ar tn er r es po ns es t o-w ar ds p at ie nt s’ f at ig ue - a nd w el l-b eh av io r on fat ig ue in te rf ere nc e a nd re lat io ns hi p sa tis fa ct io n a nd t he mo de ra tin g e ffe ct o f cu rre nt fat ig ue se ve rit y. M ul til ev el mo de lin g: mo de ra tio n mo de l R 6 C ol or ec ta l c an ce r su rv iv or s a nd t he ir pa rt ne rs ( n = 1 01 ) D ya di c d ai ly d ia ry st ud y, r ep ea te d me a-su re me nt s w ith in 1 4 day s Int ra - & Int er -pe rs on al In ve st ig at e t he e ffe ct s o f p at ie nt a nd s po us e ca ta st ro ph iz in g a nd t he d ya ds c o-ru m i-nat io n o n p at ie nt s’ f at ig ue a nd co up le s’ re lat io ns hi p s at isf ac tio n. M ul til ev el S tr uc tu ra l Equ at io n M od el in g: ac to a nd p ar tn er-eff ec t a na ly se s i nc or -po rat in g m ed iat io n (A PI M , A PI M eM ) M plu s
1
First, turning to cognitions that might perpetuate cancer-related fatigue after treatment completion, chapter 4 focuses on cancer survivors’ catastrophizing thoughts and their reciprocal relationship with fatigue as well as potential behav-ioral and affective mediators of this relationship. The last two chapters adopt an interpersonal perspective to increase our insight into dyadic processes that may either relieve or worsen symptom outcomes and might simultaneously impact the couples’ relationship. Chapter 5 aimed to identify daily partner responses towards patients’ fatigue- and well-behavior that might either foster or hamper the patients’ fatigue interference as well as relationship satisfaction. Further, it acknowledges that the severity of fatigue fluctuates within patients across days and as such might modify the impact of partner responses on fatigue and relationship outcomes. Lastly, chapter 6 links the study of cognitions and partner behaviors and assessed their effects on individual patient outcomes as well as both dyad members’ relationship outcomes. Applying a dyadic method of data analyses, it is investigated whether patients’ and partners’ catastrophizing translate via couples’ co-rumination into patients’ fatigue severity while also considering the effect of co-rumination on both partners’ relationship satisfaction.
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Clinically distinct trajectories of fatigue and their
longitudinal relationship with the disturbance of
personal goals following a cancer diagnosis
British Journal of Health Psychology, 2017, 22(3), 627-643 Fabiola Müller, Marrit A. Tuinman, Moniek Janse, Josué Almansa, Mirjam A. G. Sprangers, Ans Smink, Adelita V. Ranchor, Joke Fleer,
Abstract
Objectives: Most studies on fatigue in patients with cancer aggregate its prevalence
and severity on a group level, ignoring the possibility that subgroups of patients may differ widely in their development of fatigue. This study aimed to identify subgroups of patients with clinically distinct trajectories of fatigue from diagnosis to 18 months post-diagnosis. As fatigue might trigger goal disturbance, the study also identified trajectories of concrete and abstract goal disturbance, and longi-tudinally examined their co-occurrence with fatigue.
Design: Prospective design with quantitative and qualitative method of data collection. Methods: Patients with colorectal cancer (n = 183) reported on their levels of
fa-tigue and goal disturbance shortly after diagnosis (T1) and at 7 months (T2), and 18 months (T3) post-diagnosis. Growth mixture model analyses were performed to identify trajectories of fatigue and goal disturbance. Guidelines for the clinical relevance of fatigue were applied.
Results: Four clinically distinct trajectories of fatigue were identified as follows:
(1) persistent severe fatigue (25.4%), (2) moderate fatigue (56.1%), (3) no fatigue (13.8%), and (4) rapidly improving fatigue (4.7%). The majority of patients with cancer reported high disturbance of their concrete goals, while high disturbance of abstract goals was less evident. Fatigue and concrete goal disturbance co-occurred longitudinally.
Conclusions: The fatigue and goal disturbance experienced from diagnosis to 18
months post-diagnosis differ considerably for subgroups of patients with cancer. Fatigue and concrete goal disturbance are persistent burdens in the majority of patients. Investigating symptom burden beyond average trends can guide clini-cians to identify patients most in need for treatment. Targeting goal disturbance might benefit the psychological well-being in patients suffering from persistent symptoms.
Statement of Contribution
What is already known on this subject?
• Fatigue is a common and distressing symptom at all stages of the cancer experience. • Earlier studies suggest that many patients recover from fatigue after treat-ment completion. • Patients with cancer experience disturbance in their personal goals, which is related to poor psychological well-being.
What does this study add?
• Developments of fatigue and goal disturbance differ between subgroups of patients with cancer but co-occur within these subgroups. • About 30% of the patients experience severe fatigue after diagnosis, of which only few patients recover within 18 months post-diagnosis. • Targeting goal disturbance might benefit patients with severe and ongoing symptoms.
2
Introduction
Fatigue is a highly distressing symptom many patients with cancer experience at diagnosis and throughout their treatment (Goedendorp, Gielissen, Verhagen, Peters, & Bleijenberg, 2008; Prue, Rankin, Allen, Gracey, & Cramp, 2006). Al-though many patients seem to recover, approximately one quarter report fatigue after the completion of their cancer treatment (Goedendorp, Gielissen, Verhagen, & Bleijenberg, 2013; Servaes, Gielissen, Verhagen, & Bleijenberg, 2007). This long-term fatigue may persist for many years (Harrington, Hansen, Moskowitz, Todd, & Feuerstein, 2010; Minton & Stone, 2008) and is related to a substantial loss of quality of life (Donovan, McGinty, & Jacobsen, 2013; Kluthcovsky et al., 2012; Schmidt et al., 2012). As the population of patients treated for cancer is growing, there is a pressing need to identify specifically those patients most affected by fatigue. While most studies aggregate fatigue prevalence and severity at a group level, the primary aim of the current study was to identify and describe subgroups of patients with clinically relevant differences in the severity and development of their fatigue from diagnosis to survivorship. As fatigue might elicit the disturbance of personal goals, we also examined distinct trajectories of concrete and abstract goal disturbance and investigated their longitudinal associations with fatigue.
Empirical evidence suggests that fatigue in patients with cancer is most evident during active treatment and improves thereafter (e.g., Schmidt et al., 2015; Wang et al., 2014). This knowledge is derived mainly from cross-sectional stud-ies and longitudinal studstud-ies reporting on average developments of fatigue on the group level. These studies provided important insights into the extent of the fa-tigue problem and recognized that distinct (e.g., demographic and clinical) risk factors are responsible for the initiation and persistence of fatigue (Goedendorp et al., 2013; Schmidt et al., 2015; Servaes, Verhagen, & Bleijenberg, 2002). How-ever, research among other patient groups, most prominently pain (e.g., Axén & Leboeuf-Yde, 2013; Enthoven et al., 2016), demonstrated that studies aggregating symptom developments on a group level can disguise clinically and theoretically relevant differences between subgroups of patients. Similarly, the development of fatigue may relevantly differ for subgroups of patients from diagnosis to survivor-ship (Donovan, Small, Andrykowski, Munster, & Jacobsen, 2007).
Thus far, only a few studies have investigated distinct developments of fa-tigue in patients with cancer over time (Bødtcher et al., 2015; Donovan et al., 2007;
Schmidt et al., 2012; Servaes et al., 2007). These few studies, however, assessed developments of fatigue only after treatment completion, relied on retrospective reports on fatigue, or had a rather short follow-up period (i.e., 8 months after di-agnosis). For example, Schmidt et al. (2012) identified in their retrospective study a large group of patients without substantial fatigue from diagnosis to long-term survivorship, another subgroup with the commonly expected recovery after treat-ment completion and patients who had either a delayed recovery after treattreat-ment completion or remained fatigued even 6 years post-diagnosis. Another limitation of the above-mentioned studies is that they focused only on patients with breast cancer, which could be misleading, as women may be more likely to experience fa-tigue during and after cancer treatment than men (Husson et al., 2015; Oerlemans et al., 2013; Prue et al., 2006). Despite their limitations, these studies suggest that the development of fatigue can differ considerably for subgroups of patients, which calls for further investigation with prospective data.
Patients with cancer might not only differ in the development of their fa-tigue but also in the degree to which they are confronted with difficulties in achiev-ing their personal goals. Personal goals represent everythachiev-ing a person values and wants to achieve and as such provide meaning and structure to an individual’s life (Austin et al., 1996; Carver & Scheier, 2011; Wrosch, Scheier, Carver, & Schulz, 2003). Patients with cancer have been found to experience disturbances in achiev-ing their personal goals (Offerman, Schroevers, van der Velden, de Boer, & Pruyn, 2010; Stefanic, Caputi, & Iverson, 2014), which is related to impaired psychological well-being (Avis et al., 2012; Hullmann, Robb, & Rand, 2016). This is in line with the Illness Intrusiveness framework postulating that disturbances of one’s valued activities and interests is a key mechanism explaining how physical disease trans-lates into poor psychological outcomes such as depression and distress (Devins, 2010; Devins, Bezjak, Mah, Loblaw, & Gotowiec, 2006). Importantly, personal goals are assumed to differ in their level of abstraction (Austin et al., 1996; Carver & Scheier, 1998) and might thus be differently affected in patients with cancer. That is, goals can be differentiated into concrete short-term goals such as ‘accompany my partner to his doctor’s appointment tomorrow’ and related abstract goals such as ‘being a caring partner’. Abstract goals are assumed to be most important to a person as they are closely related to an individual’s core values and identity (Austin et al., 1996; Wrosch et al., 2003). Like fatigue, goal disturbance seems to improve
in patients with cancer over time (Janse, Ranchor, Smink, Sprangers, & Fleer, 2015; Janse, Sprangers, Ranchor, & Fleer, 2016; Pinquart, Fröhlich, & Silbereisen, 2008; Stefanic et al., 2014), but insights into its distinct developments, particularly the disturbance of concrete versus abstract goals, are lacking but needed to increase our knowledge of how patients’ goals are differently affected by cancer over time. Most notably, despite the evidence that both fatigue and goal disturbance are distressing and prevalent in patients with cancer and both show a comparable development over time, little research has considered whether fatigue and goal disturbance are related to each other. According to the theory of life-span devel-opment (Heckhausen, Wrosch, & Schulz, 2010), the attainability of goals depends on an individual’s resources to pursue them (e.g., time, cognitive, and physical abilities; Wrosch et al., 2003). Cancer-related fatigue represents a major limitation of such resources as it is typically characterized by impaired energy, cognition, and mood (Servaes et al., 2002). There is some preliminary evidence that high levels of fatigue (Sohl, Levine, Case, Danhauer, & Avis, 2014) or its indicators such as a lack of energy and concentration problems (Stefanic et al., 2014) are indeed positively associated with difficulties in achieving valued activities and important goals, respectively. Particularly concrete goals that are pursued on a daily basis and rely heavily on these resources (Carver & Scheier, 1998) might be disturbed by fatigue. The association of fatigue with the disturbance of abstract goals may be less pronounced, as abstract goals can be achieved via several pathways, that is, through the achievement of several related concrete goals (Wrosch et al., 2003). Investigating whether disease-related symptoms such as fatigue are longitudinally related to the disturbance of either concrete or abstract goals can help to reveal the mechanisms through which disease impacts psychological well-being.
In short, this prospective study among patients with colorectal cancer aimed to (1) identify and describe clinically distinct trajectories of fatigue from diagnosis to 18 months post-diagnosis, (2) identify trajectories of concrete and abstract goal disturbance, and (3) examine the associations of the trajectories of fatigue with the trajectories of concrete and abstract goal disturbance. Beyond the general trend of recovery from fatigue and goal disturbance, we expected to identify subgroups of patients with either no, persistent high, and high but improving trajectories. Fatigue and especially concrete goal disturbance were expected to develop concur-rently in a way that patients with high fatigue also report high goal disturbance.
Methods Participants
Available data were part of a larger study on goal adjustment in patients with cancer (Janse, van Faassen, et al., 2015; Janse, Fleer, Smink, Sprangers, & Ranchor, 2016; Janse, Ranchor, et al., 2015; Janse, Ranchor, Smink, Sprangers, & Fleer, 2016; Janse, Sprangers, et al., 2016). Newly diagnosed patients with colorectal cancer were recruited at four hospitals in the Netherlands. Patients younger than 18 years, those not able to understand Dutch and those with cognitive impairment, a psy-chiatric disorder, and drug or alcohol problems were excluded from participation. Of the 622 eligible patients, 497 were offered information, and 228 signed the informed consent form (response rate 45.9%). A detailed flow chart of the patient recruitment process is reported elsewhere (Janse, Fleer, et al., 2016). As this study aimed to investigate developments of fatigue and goal disturbance from diagnosis until early survivorship, we excluded patients who were lost to follow-up due to their health condition (n = 25; too ill/deceased). We also excluded patients who dropped out of the study (n = 8; mainly loss of interest) and those who finished the study but did not have complete data on the primary outcome measures (n = 3), resulting in a final sample of 183 patients with cancer. The Medical Ethical Committee of the University Medical Center Groningen approved the study (RUG 2009-4461).
Procedure
Patients with a confirmed colorectal cancer diagnosis were recruited between September 2011 and March 2013. A nurse or physician briefly introduced the study to eligible patients and handed them written information on the study, an informed consent form, and a prepaid envelope. In case patients did not respond within 2 weeks, they were called by the research assistant. After informed consent was given, patients were assigned to a trained interviewer. The interviews were scheduled approximately 1 month after cancer diagnosis (T1) and at 7 months (T2) and 18 months (T3) post-diagnosis. Interviews were conducted in person at a location convenient to the patient, most often their home.
Measures
Demographic and clinical variables. Age, gender, level of education, and relation-ship status were measured by means of self-reporting. Information regarding clini-cal variables was retrieved from the Netherlands Cancer Registry. The cancer site was dichotomized into (1) colon carcinoma and (2) a carcinoma located in the rectum, rectum sigmoid, or anus. Treatment was dichotomized into (1) surgery only and (2) surgery and additional treatment (chemo- and/or radiotherapy). Pa-tients with a permanent or temporary stoma were categorized as having a stoma (yes). Information on the cancer stage was dichotomized into (1) good prognosis (stage I, stage II) and (2) poor prognosis (stage III, stage IV).
Fatigue. Fatigue was assessed at all three measurement points with the fa-tigue symptom subscale of the cancer-specific EORTC QLQ-C30, version 3 (Aar-onson et al., 1993). Three questions measured fatigue during the past week (‘Did you need to rest?’, ‘Have you felt weak?’, ‘Were you tired?’). Responses were scored on a 4-point Likert scale ranging from (1) ‘not at all’, (2) ‘a little’, (3) ‘quite a bit’, to (4) ‘very much’. Following the scoring manual, scores were linearly transformed into a 0-100 scale with higher scores indicating higher levels of fatigue (Fayers et al., 2001). The internal consistency of the fatigue scale was good (range α = .85 - .86). Norm scores of the Dutch general population and established guidelines for relevant differences between groups and changes over time were applied to define the fatigue trajectories. A fatigue score of 15.5 is considered normal in Dutch aged 60-69 years, averaged for men and women (van de Poll-Franse et al., 2011). A deviation from this norm of at least 5 points is considered small-sized, of at least 13 points is considered medium-sized and of at least 19 points is considered large-sized (Cocks et al., 2011). Within trajectories, a deviation over time of at least 5 points (deterioration) and 4 points (improvement) is considered small-sized, of at least 10 points (deterioration) and 9 points (improvement) is considered medium-sized, and of at least 15 points (deterioration) is considered large-sized (Cocks et al., 2012). Although Cocks et al. (2012) could not estimate the size of a large improvement, we considered an improvement of at least 15 points as large-sized, similar to the estimate of a large-sized deterioration.
Goal disturbance. At each interview, patients were asked to name three to ten personal goals (i.e., plans, activities or projects) they were currently trying to achieve. For each stated goal, patients were asked to respond to one question: ‘To
which degree does your illness hinder you in achieving your goal?’ Responses could be given on a 10-point Likert scale ranging from (1) ‘not at all’ to (10) ‘very’. Two independent raters categorized the level of abstraction of each goal. This variable was dichotomized into (1) concrete short-term goals (e.g., gardening, spend time with my grandchildren) and (2) abstract goals (e.g., stay involved in the community, maintain good quality of life). The raters labelled 1,263 goals as concrete and 514 goals as abstract. A mean goal disturbance score was calculated for concrete and abstract goals at each measurement point (range 1-10), with a higher score indicating higher goal disturbance. Intraclass correlations [ICC] were calculated to estimate the internal consistency of the items measuring concrete goal disturbance (range ICC = .37 - .65) and abstract goal disturbance (range ICC = .34 - .58). As no norm scores or established guidelines for the measurement of goal disturbance exist, statistical testing was used to define goal disturbance trajectories.
Statistical analysis
A Wilcoxon signed rank test was conducted in IBM SPSS (Version 23) to test changes over time in fatigue and concrete and abstract goal disturbance on group level. Growth mixture model [GMM] analyses in LatentGold 4.5 (Vermunt & Magidson, 2005) were applied to identify subgroups of patients with different trajectories over time for fatigue and concrete and abstract goal disturbance (Ram & Grimm, 2009). Time was treated as a categorical variable; thus, no a priori as-sumptions about the shapes of the time trends were made. GMMs were estimated with an increasing number of trajectories. To handle missing data of patients who did not report concrete or abstract goals at all measurement points, GMMs were estimated using maximum likelihood on all available data. The following four criteria were applied to choose the best fitting models: First, the Bayesian infor-mation criterion [BIC] and the Akaike inforinfor-mation criteria [AIC and AIC3] were inspected, with lower values indicating better fit. Second, the best models were checked to assure that each trajectory had a substantial size (≥ 5%; Henselmans et al., 2010). Third, it was examined whether trajectories represented relevant dif-ferences in terms of their severity and development. Fourth, entropy-values were inspected, with values closer to one indicating good separation of trajectories and accurate classification of individuals within those trajectories (Ram & Grimm,
2009). See Figure S1 for graphs with alternative numbers of trajectories for the three outcome measures.
Demographic and clinical characteristics were analysed as descriptors of fatigue trajectories using mean values for continuous descriptors and frequen-cies for categorical descriptors, both weighted by the estimated individual tra-jectory membership probabilities. To assess the association between fatigue and goal disturbance, a model was fitted in which the trajectory membership of goal disturbance was predicted by the trajectory membership of fatigue. The trajectory parameters were fixed for both fatigue and goal disturbance based on the best model chosen, and only the effect of fatigue trajectory membership on goal dis-turbance trajectory membership was estimated. The associations with the highest probabilities are discussed.
Results
Sample characteristics
The 183 patients had an average age of 64.2 years (range 38-93) and were mostly male (60.7%). The majority had a partner (82.5%), and 45.4% had a medium edu-cational level. Approximately 60% of the patients were diagnosed with a colon carcinoma, and most (57.4%) had a good prognosis. The prognosis of nine patients was unknown. Thirty-five per cent of the patients had a permanent or temporary stoma, and more than half of the patients (54.6%) received additional treatment (chemo- and/or radiotherapy). The treatment of two patients was unknown.
Developments of fatigue
As expected, fatigue showed significant improvements over time on the group level but varied in its severity and development for subgroups of patients (see Table 1). The fatigue model with four trajectories showed the best fit according to the AIC and AIC3 (see Table 2). Although the smallest trajectory (4.7%) was just below the 5% criterion for trajectories of meaningful sizes, this trajectory was retained, as it was theoretically meaningful. As shown in Figure 1a, Trajectory 1, persis-tent severe fatigue (25.4%), showed large-sized deviations from population norms within 18 months post-diagnosis, a non-relevant deterioration between T1 and T2 (p = .47), and a small-sized improvement between T2 and T3 (p = .19). Trajectory 2, moderate fatigue (56.1%), showed medium-sized deviations from population
norms at T1 and steady yet non-significant (p = .38, p = .16) gradual improvements, resulting in fatigue scores approaching norm values at T3. Trajectory 3, no fatigue (13.8%), showed stable (p = .50, p = .68) fatigue scores below population norms. Trajectory 4, rapidly improving fatigue (4.7%), showed large-sized deviations from population norms at diagnosis, a large-sized improvement between T1 and T2 (p = .008), and a small-sized improvement between T2 and T3 (p = .27), resulting in fatigue scores below population norms at T3.
Table 3 shows demographic and clinical characteristics of the total sample and the four fatigue trajectories. On average, patients within the persistent severe fatigue trajectory were the youngest (61.9 years), more often highly educated (46.4%), and less often partnered (70.7%) compared to patients within the other trajectories. The gender distribution across the trajectories of fatigue appeared similar to that of the total sample with more men than women in each trajectory. The majority of patients within the no fatigue trajectory had a good prognosis and only received surgical treatment.
Developments of concrete goal disturbance
On the group level, concrete goal disturbance showed an improvement over time but differed for subgroups of patients (see Table 1). Based on the fit statistics (see Table 2) and relevant differences in the emerging trajectories, a concrete goal dis-turbance model with three trajectories was chosen (see Figure 1b). As shown in Table 1, Trajectory 1, high concrete goal disturbance (60.3%), showed high concrete goal disturbance with a significant improvement between T2 and T3 (p < .001). Trajectory 2, improving concrete goal disturbance (33.5%), showed high concrete goal disturbance within 1 month post-diagnosis (T1), a significant improvement between T1 and T2 (p < .001), resulting in low concrete goal disturbance at T2 and T3. Trajectory 3, low concrete goal disturbance (6.2%), showed stable (p = .81, p = .18) low concrete goal disturbance within 18 months post-diagnosis.
1 mo nt h p os t-7 mo nt hs p os t-18 mo nt hs p os t- di agn os is ( T1 ) di agn os is ( T2 ) di agn os is ( T3 ) T 1 - T 2 T 2 - T 3 T 1 - T 3 M ea n ( SE ) p Fa tig ue To ta l g ro up 34 .8 (2 .0 ) 29 .6 (1 .9) 25 .6 (1 .9) .0 17 .0 17 <. 001 D ist in ct tr aj ect or ie s Per sis ten t s ev er e ( 25 .4 % ) 56 .8 (5 .8 ) 60 .0 (5 .9) 52 .5 (6 .7 ) .47 .19 .54 M ode ra te (5 6. 1% ) 29 .3 (5 .2 ) 24 .2 (2 .5 ) 20 .9 (2 .7 ) .38 .16 .21 N o (1 3. 8% ) 2. 8 (1 .2 ) 1. 9 ( 1. 2) 2. 4 (1 .2 ) .50 .6 8 .78 Ra pi dl y i m pr ov in g ( 4. 7% ) 74 .7 (2 6. 8) 11 .7 (7. 2) 3. 4 (5 .6 ) .0 08 .27 .02 C onc re te g oa l d ist ur ba nc e To ta l g ro up 4. 9 ( 0. 2) 4.1 (0 .2 ) 2. 9 ( 0. 2) <. 001 <. 001 <. 001 D ist in ct tr aj ect or ie s H ig h ( 60 .3 %) 5. 6 ( 0. 3) 5. 6 ( 0. 4) 3. 8 ( 0. 3) .9 8 <. 001 <. 001 Impr ov in g ( 33. 5% ) 4. 2 ( 0. 5) 2. 0 ( 0. 3) 1. 5 (0 .1) <. 001 .02 <. 001 Lo w (6 .2 %) 1.1 (0 .1) 1.1 (0 .1) 1. 0 (0 .0) .81 .18 .23 Ta bl e 1 M ea n v al ue s, s ta nd ar d e rr or s a nd t es tin g o f d iff er en ce s o ve r t im e f or t he t ot al g ro up a nd f or t he d ist in ct t ra je ct or ie s o f f at ig ue , c on cr et e g oa l d ist ur ba nc e, an d a bs tra ct go al d ist ur ban ce
1 mo nt h p os t-7 mo nt hs p os t-18 mo nt hs p os t- di agn os is ( T1 ) di agn os is ( T2 ) di agn os is ( T3 ) T 1 - T 2 T 2 - T 3 T 1 - T 3 M ea n ( SE ) p A bs tr ac t g oa l d ist ur ba nc e To ta l g ro up 4.1 (0 .3 ) 4. 0 ( 0. 3) 3. 6 ( 0. 3) .67 .9 4 .50 D ist in ct tr aj ect or ie s Pe rs ist en t h ig h ( 21 % ) 6. 4 ( 0. 4) 7.6 (0 .4) 7.3 (0 .3 ) .01 9 .5 9 .0 39 La te im pr ov in g ( 13 .2 % ) 5. 7 ( 0. 2) 6.3 (0 .3 ) 1. 9 ( 0. 3) .15 <. 001 <. 001 Lo w (3 5. 9%) 1. 9 ( 0. 3) 1. 3 (0 .1) 1. 5 (0 .1) .0 82 .10 .38 Tr an sie nt (1 2% ) 7.4 (0 .8 ) 1. 5 ( 0. 3) 4. 0 (1 .5 ) <. 001 .13 .0 02 D el ay ed -o nset (8 .8 % ) 2. 0 ( 0. 5) 2.1 (0 .6 ) 7.7 (0 .7 ) .82 <. 001 <. 001 A cu te (9 .1% ) 1. 7 ( 0. 3) 8.1 (0 .6 ) 2. 0 ( 0. 4) <. 001 <. 001 .32 Ta bl e 1 (c on tin ue d)
