Initial Development of the Health Promoting Activities Scale to Measure the Leisure Participation of Mothers of Children With Disabilities

Abstract

OBJECTIVE. The Health Promoting Activities Scale (HPAS) measures the frequency with which mothers participate in self-selected leisure activities that promote health and well-being. We undertook an initial evaluation of the scale with mothers of school-age children with developmental disabilities (N = 152).

METHOD. We used a mixed methodology in the instrument design: a qualitative study to generate items and a quantitative study to evaluate the instrument. Our statistical analysis assessed the internal consistency, factor structure, and construct validity of the HPAS.

RESULTS. The HPAS showed good internal consistency (Cronbach’s α = .78). Construct validity was supported by moderate correlations with subjective maternal mental and general health (Short Form 36, Version 2) and by differentiation in leisure participation among groups of mothers reporting differences in mental health status.

CONCLUSION. Initial evaluation of the HPAS indicates that this brief tool is psychometrically sound. The HPAS allows professionals to evaluate clients’ participation in leisure occupations that promote health and well-being. Further development of the HPAS is warranted.

Keywords

disabled children health promotion leisure activities mothers psychometrics

Occupational therapists are concerned with people, the occupations in which they engage, and the relationships between occupation and health and well-being. Occupations are the everyday activities that structure time and meet performance requirements for life roles (American Occupational Therapy Association [AOTA], 2008). Many factors influence a person’s choice of activities, including health status, life roles, and individual interests and capabilities as well as what is available, meaningful, culturally relevant, and environmentally possible. People who have a health condition or disability may experience reduced capacity to participate in daily occupations in self-care, work or productivity, leisure, and social participation (AOTA, 2008; Law, 2002). Certain life situations, such as the role of family caregiver, may also prevent full participation in occupation, with consequences for health.

Mothers of children with developmental disabilities experience higher rates of stress and depression than other mothers (Singer, 2006). The well-being of children (both with and without disabilities) is inextricably tied to their parents’ health and capacity to meet the demands of the developing child (Schor, 2003). Although much occupational therapy research has examined the lived experience, goals, and time use of mothers of children with developmental disabilities, no research to date has investigated maternal participation in self-selected occupations that promote health and well-being. Mothers of children with disabilities have less free time (Crowe & Florez, 2006), may face barriers to participation in health-promoting occupations in the limited spare time they do have, and may experience health disparities as a consequence (Bourke-Taylor, Howie, & Law, 2010).

In this article, we describe a new scale that measures the frequency with which mothers participate in self-selected leisure activities that promote health and well-being. We review the role of occupational therapy in health promotion and leisure; the need for outcome measures to quantify participation in health-promoting occupations; and the link between caregiving and health for mothers of children with disabilities. We then describe the development and evaluation of the Health Promoting Activities Scale (HPAS).

Background

Occupational Therapy, Health Promotion, and Leisure

Occupational therapy has a unique, occupation-based approach that promotes and supports health in people and populations (AOTA, 2008; Scaffa, Van Slyke, & Brownson, 2008). Health promotion is a multipronged prevention strategy in which agencies at all levels—government, organization, and community—and individual health practitioners work to keep or create healthy environments and opportunities for or with people (World Health Organization, 2009). Occupational therapy practitioners may provide services at any of these levels within a health promotion capacity, although they are most likely to work at the individual health practitioner level (AOTA, 2008; Gupta, Chandler, & Toto, 2009; Scaffa et al., 2008). Health promotion strategies may incorporate any type of human occupation, including work, social participation, and leisure (Scaffa et al., 2008).

Previous research in occupational therapy has described how leisure occupations maintain health, rejuvenate the spirit, build skills and talents, and ultimately are personally validating, meaningful, enjoyable, and rewarding (Passmore, 2003; Passmore & French, 2003; Sandqvist, Akesson, & Eklund, 2005; Specht, King, Brown, & Foris, 2002). Leisure occupations are self-selected and thus meaningful, enjoyable, and important to the person participating. Research that connects health status and engagement in leisure occupations, however, is needed. Such research is fundamental to occupational therapy and a health promotion perspective.

Substantiation of the relationship between participation in leisure occupations and health status provides evidence to third-party payers and health care organizations that occupational therapy interventions maintain and promote health. Clients who experience a medical condition or disability may participate in leisure occupations infrequently, although participation is likely to be instrumental in achieving a state of good health. A review of 23 studies (most with cross-sectional designs) that investigated the relationship between health and occupation among samples of people with and without a disability found strong positive relationships between leisure occupations and health status in all populations (Law, Steinwender, & LeClair, 1998). Several of the studies reviewed examined both occupational engagement in everyday life and the addition of meaningful occupation to enhance daily life. The review also examined 10 studies that investigated the effects of a withdrawal of meaningful occupation in the lives of people with medical conditions and disabilities; this review suggested that the effects may be detrimental, although more research was recommended. The profession is committed to substantiating the relationship between occupation and health, a goal that is difficult to achieve without outcome measures (Gutman, 2008).

Outcome Measures to Quantify Participation in Health-Promoting Occupations

Creating outcome measures that quantify participation is challenging. As Coster (2008) eloquently described the issue, if occupational therapy research aims to examine participation, then as a profession

we should make sure that the content of the outcome measure examines . . . social relationships and engagement in family and community life, work, play, and leisure. A life of quality is so much more than buttoning a shirt or tying shoes. (Coster, 2008, p. 751)

Instruments that both measure participation and promote efficacy research have the added advantage of promoting occupationally based interventions (Coster, 2008). Coster (2006) emphasized the need for occupation-based outcome tools that explore the relationships between what people do and how they report their health and changes in this relationship over time; such tools would contribute to the theoretical foundations of the profession. Clients have reported that participation in leisure is a high priority compared with many other daily occupations (Specht et al., 2002).

Outcome tools must accurately measure a defined construct in a reliable and valid way and be sensitive to important changes within the construct being measured. They must be brief and easy to use, entail a low burden for participants, and be designed to collect data from the client about the client (DeVellis, 2003).

Caregiving and Health in Mothers of Children With Disabilities

The occupational therapy profession has engaged in service and advocacy on behalf of caregivers and recognizes their crucial role in the lives of people with disabilities (AOTA, 2007). As caregivers, mothers are responsible for numerous and constant tasks as the child grows (Bourke-Taylor, Howie, & Law, 2010). Mothers of children with disabilities spend a disproportionate amount of time in child and care occupations (Crowe & Florez, 2006), have less time to care for themselves and sleep (VanLeit & Crowe, 2002), have fewer opportunities to participate in paid work (Brehaut et al., 2004; Montes & Halterman, 2008; Powers, 2003), and consistently report poorer mental health and subjective well-being than other mothers (Brehaut et al., 2004; Montes & Halterman, 2007; Singer, 2006).

The link between caring and maternal health has often been assumed to be the result of grief (Green, 2007), social isolation (Davis et al., 2010; Feldman et al., 2007; Skok, Harvey, & Reddihough, 2006), constant pressure to navigate a largely unresponsive health care system on their child’s behalf (Green, 2007; Llewellyn, Thompson, & Whybrow, 2004), and social stigma related to raising a child with a disability (Green, 2003). No research has explored the relationship between maternal health and the occupations that a mother participates in outside of caregiving. It is not possible to fully explore such relationships without instruments that measure participation in self-selected occupations. Mothers themselves have described their wish for more time, opportunities, and support to pursue leisure activities for their own health, well-being, and development (Crowe & Florez, 2006; Davis et al., 2010; Donovan, VanLeit, Crowe, & Keefe, 2005; VanLeit & Crowe, 2002).

Development of the Health-Promoting Activities Scale

This article describes the initial development and psychometric evaluation of the HPAS. The construct measured by the HPAS is the frequency with which mothers participate in self-selected leisure occupations that promote or maintain health. We used a mixed-methodology instrument design model (Creswell, Fetters, & Ivankova, 2004) and framed two studies—an initial qualitative study to generate items and scoring criteria (Bourke-Taylor, Howie, & Law, 2010) and a quantitative study to examine the psychometric properties of the instrument. The aims of this research were as follows:

To create a brief scale to measure the frequency with which mothers caring for a school-age child with a disability participated in self-selected leisure occupations;

To determine the internal consistency of the scale using a sample of mothers;

To determine the construct validity of the scale through correlation with psychometrically sound instruments that measure subjective health status; and

To determine the extent to which the scale is able to differentiate between mothers grouped by differences in reported mental health and sleep habits.

In addition to the HPAS, we developed two other instruments after the qualitative study (Bourke-Taylor, Law, Howie, & Pallant, 2009, 2010).

HPAS Items and Response Format

As noted in the previous section, the construct measured by the HPAS is the frequency with which mothers participate in self-selected leisure occupations that promote health and well-being. Items for the HPAS were generated in the initial qualitative study; in that study, mothers identified many daily occupations outside their caregiver life role that were instrumental to their own health, enjoyable, social, and rejuvenating (Bourke-Taylor, Howie, & Law, 2010). After an examination of these mothers’ lived experience, researcher expertise on leisure occupations, and a review of existing instruments, we developed eight items for the HPAS (see Table 1).

Table 1.

Items in the Health Promoting Activities Scale and Examples of Mothers’ Activities

Item	Activities Described by Mothers	Other Activities
1. Personal health care tasks, such as planning and eating healthy food and drinks, following exercise program, and other tasks for your health	Purposefully planning time for healthy eating and exercise routines Going to the gym Consulting an expert about health	Reading health magazines and books Avoiding unhealthy foods and substances
2. A physically active recreational pursuit that you do alone	Walking Participating in a gym program Shopping for pleasure Gardening Swimming	Jogging Cycling Walking the dog
3. A physically active recreational pursuit that you do with other people	Tap dancing Playing squash Walking with another mother of a child with autism	Playing a team sport Camping Bush walking or hiking Playing golf
4. Spiritual or rejuvenating personal time	Praying Attending a bible groups Being with similar others to pray, worship, or reflect	Meditating Engaging in contemplation, meaning making, or worship
5. Social activities with people who are important and supportive toward you	Spending time with similar families Attending disability organization events	Attending social functions or extended family gatherings
6. Time out for yourself to spend as you wish	Getting a facial Shopping Doing nothing Listening to music Resting	Participating in musical activities or arts and crafts
7. A quiet, physically inactive leisure pursuit that you do alone	Reading Sewing Baking Using the computer	Listening to music or watching television
8. A quiet, physically inactive leisure pursuit that you do with others	Going to the movies Dining out Celebrating cultural occasions Meeting others	Playing cards Engaging in social networking via the computer

The scale items address the purpose and types of occupation, such as whether the occupation was active and was done with supportive people or alone; the specific details of each activity were not considered important to the construct of interest. The HPAS directions define leisure occupations as activities that provide access to and participation in social, emotional, physical, and spiritual experiences that are important and desirable to mothers. The directions instruct respondents to think about the sorts of activities they have participated in for health, social interaction, and leisure over the past year and to select the corresponding frequency response for each of the eight category items (full directions are available from Helen Bourke-Taylor). Some variation may exist in how a person categorizes the activity (e.g., she might categorize piano playing as an activity in Item 4, 6, or 7), but respondents are instructed to categorize the activity within only one item.

The 7-point Likert scale response format is 1 = never, 2 = 1–3 times per year, 3 = once a month, 4 = 2–3 times a month, 5 = once per week, 6 = 2–3 times per week, and 7 = once or more every day. The response format was configured at intervals similar to those in the scoring section of the Children’s Assessment of Participation and Enjoyment (King et al., 2004). The total HPAS score is calculated by adding the scores from the eight items. Lower scores indicate less frequent participation and higher scores more frequent participation.

Survey Research Design.

The research project was approved by the La Trobe University Health Science Faculty Ethics Committee. Data for the qualitative and quantitative studies were collected over a 2-year period (2006–2007). This article presents the evaluation of the HPAS resulting from the study.

Participants.

To be included in the research project, the mothers had to be the primary caregiver of a school-age child with a developmental disability; resident in the state of Victoria, Australia; and able to complete the survey in English. Disability was defined as any diagnosis accepted by the Australian government department that provided weekly subsidies to families of children with developmental disabilities. Table 2 describes the characteristics of the sample participating in the evaluation study (N = 152).

Table 2.

Characteristics of Participants (N = 152) and Their Children With a Disability

Characteristic	Mean	Standard Deviation	n	%
Mother’s age, yr	41.7	5.4
Family income, AUD	$59,104	$31,011
Mother’s education level
Primary			2	1
Secondary			65	43
Postsecondary or degree			54	36
Postgraduate			31	20
Mother’s relationship status
Married or living together			127	84
Separated, divorced, or widowed			15	10
Single			6	4
Mother’s work status
Full time			14	9
Part time			69	45
Mother’s reporting mental health condition (n = 78) a
Depression			57	38
Anxiety disorder			34	22
Posttraumatic stress disorder			4	3
Anorexia nervosa			2	1
Postnatal depression			8	5
Bipolar mood disorder			3	2
Mothers able to sleep through the night uninterrupted by needs of child with a disability			77	51
Mothers awoken by child at least 4 nights a week on average			74	49

Child’s age, yr	9.5	3.7
Child’s disability or condition b
Cerebral palsy			29	19
Developmental delay			26	17
Autism			69	45
Asperger syndrome			25	16
Intellectual disability			46	30
Language disorder			15	10
Epilepsy			20	13
Attention deficit hyperactivity disorder			19	13

Note. AUD = Australian dollars.

Mothers may have more than one mental health condition.

Children may have more than one diagnosis.

Participants were recruited through disability support networks. We posted a notice describing research “to investigate factors that affect the health of Victorian mothers of a child with a disability” on Web sites and printed the notice in the newsletters of 10 not-for-profit organizations. Interested mothers contacted Bourke-Taylor, who mailed a research packet to those who expressed willingness to participate.

Data Collection and Measures.

Data were collected for the evaluation study by means of a mailed questionnaire, and a follow-up phone call was made to verify all responses. The questionnaire consisted of a specifically designed booklet with demographic questions, five psychometrically sound previously published scales, and three original scales (including the HPAS) designed for this study. Other publications describe the other data collected and results (Bourke-Taylor, Howie, & Law, 2011; Bourke-Taylor, Howie, Law, & Pallant, 2011; Bourke-Taylor, Law, et al., 2009, 2010). Over a 10-month period, 180 mothers contacted Bourke-Taylor, and 152 completed surveys (84% response rate).

Demographic data collected included mother’s age, family income, child’s age, and mother’s education and work status (see Table 2). Mothers reported whether they had been diagnosed with a medical condition and how often they were awoken at night to attend to their child with a disability. We expected to use the responses to these questions to identify groups of mothers who would vary in their capacity to participate in leisure occupations.

The Short Form 36, Version 2 (SF–36v2; Ware, Kosinski, & Dewey, 2002) is a health-related quality of life (HRQOL) tool that measures how healthy a person feels and the influence of perceived health on what he or she is able to do in daily life. The SF–36v2 has been the primary tool used in thousands of research studies in the United States, where it was developed to evaluate HRQOL among people with various health and medical conditions (Ware, 2000, 2003). We included the SF–36v2 in the research packet to enable us to explore the relationship between subjective health status and the HPAS. The SF–36v2 was validated for use in Australia (Hawthorne, Osborne, Taylor, & Sansoni, 2007) and has eight dimension scores: physical functioning (PF), role–physical (RP), bodily pain (BP), general health (GH), vitality (VT), social functioning (SF), role–emotional (RE), and mental health (MH). Norm-based summary mental and physical health scores were determined using published norms. Use of the SF–36v2 in this research has been described elsewhere (Bourke-Taylor, Howie, & Law, 2011; Bourke-Taylor, Howie, Law, & Pallant, 2011).

Statistical Analysis

The SPSS–14 statistical package (SPSS, Inc., Chicago) was used for data entry and management. Descriptive statistics (means, standard deviations, and frequencies) were generated for all scale items. Exploratory factor analysis was performed after first confirming that the data were suitable for factor analysis. Principal components analysis (PCA) was used to extract the factors followed by oblique rotation of factors using oblimin rotation (δ = 0). The number of factors to be retained was guided by three decision rules: Kaiser’s criterion (eigenvalues >1), inspection of the scree plot, and use of Horn’s (1965) parallel analysis. Parallel analysis is among the most accurate approaches to estimating the number of components (Hubbard & Allen, 1987; Zwick & Velicer, 1986). The eigenvalues obtained from PCA are compared with those obtained from a randomly generated data set of the same size (Watkins, 2000). Only factors with eigenvalues exceeding the values obtained from the corresponding random data set were retained for further investigation. Cronbach’s α values were calculated to assess the internal reliability of the scale.

Construct validity was investigated by correlating the HPAS with the SF–36v2 dimensions and norm-based summary scores using conventional nonparametric investigations of correlation and known-groups validity (Tabachnick & Fidell, 2007). We expected that the HPAS and the SF–36v2 summary and dimension scores would correlate positively, indicating that the frequency of participation in leisure activities that involved social, physical, emotional, and spiritual fulfillment was associated with better subjective health. We did not expect the HPAS to correlate with mother’s age, child’s age, or family income.

Known-groups validity was tested by assessing the ability of the HPAS to discriminate between groups that were based on self-reported mental health condition and healthy sleep habits. We hypothesized that mothers with a mental health condition and poor sleep habits would report lower participation in leisure occupations (i.e., lower HPAS scores).

Results

Table 3 describes the frequency of responses to the eight HPAS items. The mean total score on the HPAS was 21.67 (standard deviation = 8.57, range = 8–51). Standard tests of normality indicated that the HPAS was not normally distributed. These tests revealed a skewed distribution (0.723) with kurtosis (0.408) and a significant Kolmogorov-Smirnov statistic (p = .001; Pallant, 2010), indicating violation of the assumption of normality.

Table 3.

Responses to Items in the Health Promoting Activities Scale (N = 152) and Component Loadings From Principal Components Analysis

	Never		1–3 Times Per Yr		Once a Month		2–3 Times a Month		Once a Week		2–3 Times Per Week		Once or More Every Day
Scale Item	n	%	n	%	n	%	n	%	n	%	n	%	n	%	Component 1
1. Personal health care tasks, such as planning and eating healthy food and drinks, following exercise program, and other tasks for your health	28	18	26	17	19	13	10	7	19	13	30	20	20	13	0.68
2. A physically active recreational pursuit that you do alone	85	56	21	14	12	8	10	7	12	8	11	7	1	1	0.64
3. A physically active recreational pursuit that you do with other people	82	54	19	13	11	7	8	5	13	9	16	11	3	2	0.63
4. Spiritual or rejuvenating personal time	65	43	43	28	12	8	8	5	12	8	9	6	3	2	0.65
5. Social activities with people who are important and supportive toward you	13	9	42	28	43	28	20	13	23	15	10	7	1	1	0.63
6. Time out for yourself to spend as you wish	34	22	52	34	31	20	11	7	14	9	10	7	0	0	0.67
7. A quiet, physically inactive leisure pursuit that you do alone	52	34	35	23	20	13	11	7	11	7	17	11	6	4	0.60
8. A quiet, physically inactive leisure pursuit that you do with others	56	37	51	34	25	16	8	5	10	7	2	1	0	0	0.56

Factor analysis of the HPAS followed standard protocols (Tabachnick & Fidell, 2007). To explore the underlying factor structure of the HPAS, the eight items were subjected to PCA. The suitability of the data for factor analysis was confirmed with a highly significant Bartlett’s test of sphericity (p < .001) and a high Kaiser–Meyer–Olkin (KMO) measure of sample adequacy value (KMO = 0.79; Pallant, 2010). PCA revealed two components with eigenvalues exceeding 1 (3.21 and 1.18) explaining 54.2% of the variance; however, all eight components loaded >0.56 on the first component (see Table 3). Oblimin rotation showed that the two components moderately correlated (−.39), thus indicating a single underlying dimension that accounted for 40.1% of the variance. The results of the scree test and parallel analysis also supported a single-factor solution. The single scale had good internal consistency (Cronbach’s α = .78). The total HPAS score was calculated by adding the scores from the eight items.

Correlations between the HPAS and the SF–36v2 dimensions and component summary scores revealed moderate positive correlations with overall mental health, GH, VT, SF, RE, and MH that support the construct validity of the scale (see Table 4). Between-groups analysis confirmed that mothers who reported that they did not have a mental health condition and those who had healthy sleep habits (i.e., whose sleep was not interrupted regularly) reported more frequent participation in health-promoting leisure activities (i.e., higher HPAS scores; see Table 5). These relationships confirmed that more frequent participation in activities reflected in the items in the HPAS was associated with better subjective overall general and mental health and more healthy sleep habits.

Table 4.

Nonparametric Correlations Between Health Promoting Activities Scale (HPAS) Scores and Short Form 36, Version 2 (SF–36v2) Scores

Item	Correlation With HPAS Score
Mother’s age (n = 151)	.16*
Family income (n = 130)	.05
Child’s age	.12
SF–36v2 score (n = 152)
Physical health component summary score	.23**
Mental health component summary score	.43**
Physical functioning	.24**
Role–physical	.20*
Bodily pain	.25**
General health	.45**
Vitality	.48**
Social functioning	.39**
Role–emotional	.37**
Mental health	.49**

p < .05. **p < .01.

Table 5.

Nonparametric Comparison of Health Promoting Activities Scale (HPAS) Scores Between Participants With and Without a Mental Health Condition and Healthy Sleep Habits

			Mann–Whitney U
Characteristic	n	Median HPAS Score	U	z	p	r
Reports a mental health condition
Yes	78	18
No	74	21	2,014.5	−3.216	.001	.261
Sleeps through every night
Yes	77	22
No	74	19	2,151.0	−2.601	.009	.211

Discussion

Psychometric Properties

The HPAS was developed to measure the frequency with which mothers of school-age children with developmental disabilities participate in self-selected leisure occupations that promote health and well-being. Initial evaluations presented in this study support the internal consistency, factor structure, and construct validity of the HPAS. Construct validity was supported in several ways. The HPAS correlated moderately with most health dimensions, indicating the association between participation in healthy leisure pursuits and well-being. The HPAS also discriminated between mothers with and without a diagnosed mental health condition and between those with healthy and unhealthy sleep habits.

Study Findings

Examination of the reported frequency with which mothers in this study participated in activities related to their subjective health status provides cause for reflection. More than half of the mothers did not participate in active recreational pursuits at all. In general, these mothers preferred inactive, quiet leisure pursuits, although more than one-third never participated in quiet leisure pursuits, either. About three-quarters of the mothers found time for themselves at least once per year and socialized with supportive others about once per month. The results of this study suggest that healthy sleep habits are somehow related to mothers’ leisure choices. Support programs for mothers with mental health conditions who are not making health-promoting decisions about their leisure time may be warranted. Findings from this research about the mental health status of mothers (Bourke-Taylor, Howie, Law, & Pallant, 2011) and participation in paid employment (Bourke-Taylor, Howie, & Law, 2011) have been described elsewhere.

The association between mothers’ physical health and participation in leisure pursuits was weak. Possible reasons may be that mothers in this sample were relatively young (mean age = 41 yr), 54% were working for pay, all were involved in busy family lives with many domestic duties, and all were involved in physical caregiver duties. Because mothers participated in many physically active occupations in their life roles, it seems reasonable to suggest that maternal physical health may be attributable to participation in occupations other than leisure (i.e., caregiving may necessitate moving equipment for child, lifting child, and assisting child in play and activities of daily living).

This study indicates that mothers’ participation in health-promoting leisure occupations is associated with their subjective health, particularly mental health. Applied to occupational therapy practice, these results suggest that mothers should be educated about this association so that lifestyle redesign that supports mental health and well-being may occur. The World Health Organization (WHO; 2009) described several strategies to promote health among populations. One is to address individual health:

Health promotion supports personal and social development through providing information, education for health, and enhancing life skills. By so doing, it increases the options available to people to exercise more control over their own health and over their environments, and to make choices conducive to health. (WHO, 2009, p. 4)

The HPAS may be used in educating mothers about ways to support better health and in enabling them to make choices conducive to better health. Occupational therapists can facilitate the improved participation and health of mothers by disseminating the findings of this study and contributing to future data collection. Recent research demonstrated the relationship between health-promoting behaviors and some aspects of health-related quality of life among mothers with multiple sclerosis; Tyszka and Farber (2010) used a lengthy tool (52 items) to measure health-promoting behaviors and demonstrated the need for occupational therapists to use health promotion strategies to support the life role participation of this group of mothers. The HPAS could be used similarly in future research and clinical work.

Limitations

Some limitations in this study may be addressed in future research. Different sampling methods that provide population-based data and additional verification of medical history are required. Future research might also investigate the relationships between satisfaction and both health status and participation in leisure occupations as measured by the HPAS. Future research should also investigate the relative contribution of participation in health-promoting occupations and other life factors to mothers’ mental health status. Evaluation of the sensitivity of the HPAS to detect changes in health-promoting behaviors and subjective health over time will indicate whether the HPAS is a valid outcome measure. Application to other types of occupational therapy clients requires further validation studies.

Implications for Occupational Therapy Practice

The HPAS provides practicing occupational therapists with a brief tool to

Address the mother’s capacity to participate in health-promoting leisure pursuits,

Educate mothers about their own health needs,

Assist mothers with healthy lifestyle redesign of leisure pursuits, and

Include client-centered goal setting in relation to HPAS items.

Use of the HPAS reminds occupational therapists that caregiver health and well-being are essential parts of family-centered practice in all work with children with disabilities.

Conclusion

The HPAS provides clinical occupational therapists and researchers with a tool that is brief, psychometrically sound, user friendly, and clinically relevant to measure the frequency with which mothers participate in self-selected leisure occupations that are associated with health. Initial evaluation of the scale presented in this article indicates that further research and development of the tool are warranted.

References

American Occupational Therapy Association. (2007). AOTA’s statement on family caregivers. American Journal of Occupational Therapy, 61, 710. doi: 10.5014/ajot.61.6.710

American Occupational Therapy Association. (2008). Occupational therapy practice framework: Domain and process (2nd ed.). American Journal of Occupational Therapy, 62, 625–683. doi: 10.5014/ajot.62.6.625

Bourke-Taylor

H. M.

Howie

, & Law

(2010). Impact of caring for a school-aged child with a disability: Understanding mothers’ perspectives. Australian Occupational Therapy Journal, 57, 127–136. doi: 10.1111/j.1440-1630.2009.00817.x

Bourke-Taylor

H. M.

Howie

, & Law

(2011). Barriers to maternal workforce participation and relationship between paid work and health. Journal of Intellectual Disability Research, 55, 511–520. doi: 10.1111/j.1365-2788.2011.01407.x

Bourke-Taylor

H. M.

Howie

Law

, & Pallant

J. F.

(2011). Self-reported mental health of mothers with a school-aged child with a disability in Victoria: A mixed method study. Journal of Paediatrics and Child Health. Advance online publication. doi: 10.1111/j.1440-1754.2011.02060.x

Bourke-Taylor

H. M.

Law

Howie

, & Pallant

J. F.

(2009). Development of the Assistance to Participate Scale (APS) for children’s play and leisure activities. Child: Care, Health and Development, 35, 738–745. doi: 10.1111/j.1365-2214.2009.00995.x

Bourke-Taylor

Law

Howie

, & Pallant

J. F.

(2010). Development of the Child’s Challenging Behaviour Scale (CCBS) for mothers of school-aged children with disabilities. Child: Care, Health and Development, 36, 491–498. doi: 10.1111/j.1365-2214.2009.01055.x

Brehaut

Kohen

Raina

Walter

Swindon

O’Donnell

, et al. (2004). The health of primary carers of children with cerebral palsy: How does it compare with that of other Canadian caregivers? Pediatrics, 114, e182–e191.

Coster

(2006). Guest editorial: The road forward for better measures for practice and research. OTJR: Occupation, Participation and Health, 26, 131.

10.

Coster

W. J.

(2008). Embracing ambiguity: Facing the challenge of measurement (Eleanor Clarke Slagle Lecture). American Journal of Occupational Therapy, 62, 743–752. doi: 10.5014/ajot.62.6.743

11.

Creswell

J. W.

Fetters

M. D.

, & Ivankova

N. V.

(2004). Designing a mixed methods study in primary care. Annals of Family Medicine, 2, 7–12. doi: 10.1370/afm.104

12.

Crowe

T. K.

, & Florez

S. I.

(2006). Time use of mothers with school-age children: A continuing impact of a child’s disability. American Journal of Occupational Therapy, 60, 194–203. doi: 10.5014/ajot.60.2.194

13.

Davis

Shelly

Waters

Boyd

Cook

Davern

, et al. (2010). The impact of caring for a child with cerebral palsy: Quality of life for mothers and fathers. Child: Care, Health and Development, 36, 63–73. doi: 10.1111/j.1365-2214.2009.00989.x

14.

DeVellis

R. F.

(2003). Scale development theory and application (2nd ed.). Thousand Oaks, CA: Sage.

15.

Donovan

J. M.

VanLeit

B. J.

Crowe

T. K.

, & Keefe

E. B.

(2005). Occupational goals of mothers of children with disabilities: Influence of temporal, social, and emotional contexts. American Journal of Occupational Therapy, 59, 249–261. doi: 10.5014/ajot.59.3.249

16.

Feldman

McDonald

Serbin

Stack

Secco

M. L.

, & Yu

C. T.

(2007). Predictors of depressive symptoms in primary caregivers of young children with or at risk for developmental delay. Journal of Intellectual Disability Research, 51, 606–619. doi: 10.1111/j.1365-2788.2006.00941.x

17.

Green

S. E.

(2003). What do you mean “What’s wrong with her?” Stigma in the lives of families of children with disabilities. Social Science and Medicine, 37, 1361–1374. doi: 10.1016/S0277-9536(02)00511-7

18.

Green

S. E.

(2007). “We’re tired, not sad”: Benefits and burdens of mothering a child with a disability. Social Science and Medicine, 64, 150–163. doi: 10.1016/j.socscimed.2006.08.025

19.

Gupta

Chandler

B. E.

, & Toto

(2009). Fact sheet: Occupational therapy’s role in health promotion. Bethesda, MD: American Occupational Therapy Association. Retrieved September 18, 2010, from www.aota.org/Practitioners/PracticeAreas/Work/FactSheets/Health-Promotions.aspx

20.

Gutman

S. A.

(2008). From the desk of the editor—Research priorities of the profession. American Journal of Occupational Therapy, 62, 499–501. doi: 10.5014/ajot.62.5.499

21.

Hawthorne

Osborne

R. H.

Taylor

, & Sansoni

(2007). The SF-36 Version 2: Critical analyses of population wieghts, scoring algorithms and population norms. Quality of Life Research, 16, 661–673.

22.

Horn

J. L.

(1965). A rationale and test for the number of factors in factor analysis. Psychometrika, 30, 179–185. doi: 10.1007/BF02289447

23.

Hubbard

, & Allen

(1987). An empirical comparison of alternative methods for principal component extraction. Journal of Business Research, 15, 173–190. doi: 10.1016/0148-2963(84)90047-X

24.

King

Law

King

Hurley

Hanna

Kertoy

, et al. (2004). Children’s Assessment of Participation and Enjoyment (CAPE) and Preferences for Activities for Children (PACS). San Antonio, TX: Harcourt Assessment.

25.

Law

(2002). Distinguished scholar lecture—Participation in the occupations of everyday life. American Journal of Occupational Therapy, 56, 640–649. doi: 10.5014/ajot.56.6.640

26.

Law

Steinwender

, & LeClair

(1998). Occupation, health and well being. Canadian Journal of Occupational Therapy, 65, 81–91.

27.

Llewellyn

Thompson

, & Whybrow

> (2004). Activism as a mothering occupation. In Esdaile

& Olson

(Eds.), Mothering occupations: Challenge, agency, and participation (pp. 282–305). Philadelphia: F. A. Davis.

28.

Montes

, & Halterman

(2007). Psychological functioning and coping among mothers of children with autism: A population-based study. Pediatrics, 119, e1040–e1046. doi: 10.1542/peds.2006-2819

29.

Montes

, & Halterman

(2008). Childcare problems and employment among families with preschool aged children with autism in the United States. Pediatrics, 122, e202–e208. doi: 10.1542/peds.2007-3037

30.

Pallant

J. F.

(2010). SPSS Survival manual (4th ed.). Sydney, New South Wales, Australia: Allen & Unwen Press.

31.

Passmore

(2003). The occupation of leisure: Three typologies and their influence on mental health in adolescence. OTJR: Occupation, Participation and Health, 23, 76–83.

32.

Passmore

, & French

(2003). The nature of leisure in adolescence: A focus group study. British Journal of Occupational Therapy, 66, 419–426.

33.

Powers

(2003). Children’s health and maternal work activity: Estimates under alternative disability definitions. Journal of Human Resources, 38, 522–556. doi: 10.2307/1558767

34.

Sandqvist

Akesson

, & Eklund

(2005). Daily occupations and well-being in women with limited cutaneous systemic sclerosis. American Journal of Occupational Therapy, 59, 390–397. doi: 10.5014/ajot.59.4.390

35.

Scaffa

M. E.

Van Slyke

, & Brownson

C. A.

; American Occupational Therapy Association Commission on Practice. (2008). Occupational therapy services in the promotion of health and the prevention of disease and disability. American Journal of Occupational Therapy, 62, 694–703. doi: 10.5014/ajot.62.6.694

36.

Schor

E. L.

; American Academy of Pediatrics Task Force on the Family. (2003). Family pediatrics: Report of the Task Force on the Family. Pediatrics, 111, 1541–1571.

37.

Singer

G. H.

(2006). Meta-analysis of comparative studies of depression in mothers of children with and without developmental disabilities. American Journal of Mental Retardation, 111, 155–169. doi: 10.1352/0895-8017(2006)111[155:MOCSOD]2.0.CO;2

38.

Skok

Harvey

, & Reddihough

(2006). Perceived stress, perceived social support, and wellbeing among mothers of school-aged children with cerebral palsy. Journal of Intellectual and Developmental Disability, 31, 53–57. doi: 10.1080/13668250600561929

39.

Specht

King

Brown

, & Foris

(2002). The importance of leisure in the lives of persons with congenital physical disabilities. American Journal of Occupational Therapy, 56, 436–445. doi: 10.5014/ajot.56.4.436

40.

Tabachnick

B. G.

, & Fidell

L. S.

(2007). Using multivariate statistics (5th ed.). Boston: Pearson Education.

41.

Tyszka

A. C.

, & Farber

R. S.

(2010). Exploring the relation of health-promoting behaviors to role participation and health-related quality of life in women with multiple sclerosis: A pilot study. American Journal of Occupational Therapy, 64, 650–659. doi: 10.5014/ajot.2010.07121

42.

VanLeit

, & Crowe

T. K.

(2002). Outcomes of an occupational therapy program for mothers of children with disabilities: Impact on satisfaction with time use and occupational performance. American Journal of Occupational Therapy, 56, 402–410. doi: 10.5014/ajot.56.4.402

43.

Ware

J. E.

Jr. (2000). SF–36 health survey update. Spine, 25, 3130–3139. doi: 10.1097/00007632-200012150-00008

44.

Ware

J. E.

Jr. (2003). Conceptualization and measurement of health-related quality of life: Comments on an evolving field. Archives of Physical Medicine and Rehabilitation, 84(Suppl. 2), S43–S51. doi: 10.1053/apmr.2003.50246

45.

Ware

J. E.

Kosinski

, & Dewey

J. E.

(2002). How to score version 2 of the SF–36 Health Survey (standard and acute forms). Lincoln, RI: Quality Metric.

46.

Watkins

(2000). Monte Carlo PCA for parallel analysis [Computer software]. State College, PA: Education & Psychological Associates.

47.

World Health Organization. (2009). Milestones in health promotion: Statements from global conferences. Geneva: Author.

48.

Zwick

, & Velicer

(1986). Comparison of five rules for determining the number of components to retain. Psychological Bulletin, 99, 432–442. doi: 10.1037/0033-2909.99.3.432