Annals of International Occupational Therapy

Original Research freeRelationship Between Sensory Processing and Perceptions of and Participation in Play and Leisure Activities Among Typically Developing Children: An Exploratory Study Esther E. Matthews, BOccTher(Hons), ; , BOccTher(Hons) Ted Brown, PhD, MSc, MPA, BScOT(Hons), GCHPE, OT(C), OTR, MRCOT, FOTARA, FAOTA, ; and , PhD, MSc, MPA, BScOT(Hons), GCHPE, OT(C), OTR, MRCOT, FOTARA, FAOTA Karen Stagnitti, PhD, BoccThy, GCHE, , PhD, BoccThy, GCHE Esther E. Matthews, BOccTher(Hons) , Ted Brown, PhD, MSc, MPA, BScOT(Hons), GCHPE, OT(C), OTR, MRCOT, FOTARA, FAOTA , and Karen Stagnitti, PhD, BoccThy, GCHE Published Online:May 10, 2020https://doi.org/10.3928/24761222-20200501-03PDFAbstract ToolsAdd to favoritesDownload CitationsTrack CitationsCopy LTI LinkHTMLAbstractPDF ShareShare onFacebookTwitterLinkedInRedditEmail SectionsMoreAbstractBackground:Occupational therapists often assess children's play, leisure interests, and sensory processing skills. This study explored relationships between parent-reported sensory processing factors in children 8 to 12 years old, children's self-reported perceptions of play, and children's participation in and choice of play and leisure activities.Methods:This cross-sectional quantitative study included children (n = 21) from regional Victoria, Australia, who were typically developing. The children indicated their participation in and choice of play and leisure activities using the Children's Leisure Assessment, and they indicated their views on their recreation using the Children's Perception of Their Play scale. The parents (n = 15) reported the children's sensory processing abilities measured by the Sensory Processing Measure. Data were analyzed with Spearman's rho correlations and linear regressions, and bootstrapping was applied to assess the accuracy of statistical results via resampling.Results:Significant positive correlations were found between vestibular skills and the variety, frequency, and preference of participation in games and sports. Sensory processing factors of social participation, vision, hearing, touch, proprioception, and praxis correlated negatively with children's value of choice within their play. Reduced proprioception was predictive of increased value of choice within play.Conclusion:The sensory processing factors of balance and proprioception were predictive of participation in play and perception. Further research is recommended. [Annals of International Occupational Therapy. 2021;4(2):85–92.]IntroductionPlay is an important occupation of childhood that promotes development, health, and well-being. Play is characterized by joyfulness, spontaneity, imagination, free choice, active engagement, intrinsic motivation, and inherent pleasure (Hurd & Anderson, 2011). A child's engagement in play and leisure activities is influenced by developmental stage, physical and psychological self, and cognitive abilities (Morrison et al., 1991). Leisure is viewed from three perspectives: leisure as an activity, leisure as a state of mind, and leisure as time (Hurd & Anderson, 2011). Leisure is defined as an activity that people engage in during uncommitted or free time. Leisure also relates to perceived freedom, perceived competence, and positive affect (Primeau, 2009). Finally, leisure refers to uncommitted or free time away from paid employment (Hurd & Anderson, 2011).According to Primeau (2009), "Play and leisure participation is defined as the client's engagement in play and leisure occupations that are typically expected of and available to a person of the same age and culture in home, school, work, and community settings" (p. 635). Participation in play and leisure is affected by environmental (including the physical, social, and political space) and personal factors (including age, gender, education level, cultural beliefs, and socioeconomic status) (Brown et al., 2011).Children and parents both recognize that play is different from physical activity (Curtis et al., 2012). Play is a highly social occupation and can support the child's social engagement and identity (Everley & Macfadyen, 2017). Play must be fun and include elements of choice (Curtis et al., 2012; Miller & Kuhaneck, 2008). Among this broad understanding of play, one quantitative measure was found that gave children the opportunity to voice their perceptions and views of their own play. Barnett's (2013) Children's Perception of Their Play (CPTP) scale provides researchers with an instrument to quantify the child's perspective and learn more about children's play. Sturgess et al. (2002) reviewed self-report questionnaires and concluded that there was growing awareness of the importance of including the child's voice. Rosenblum et al. (2010) developed the Children's Leisure Assessment Scale (CLASS) as a self-report measure of children's leisure participation. This instrument covers four dimensions of leisure participation: (a) frequency, (b) sociability, (c) preference, and (d) time spent.Sensory processing allows a person to use their body effectively by organizing sensations from the environment and their own body (Dunn, 2014). When children experience multiple sources of sensory input, sensory processing issues may affect their participation in play and leisure activities and their view of and priorities within their own play. Different types of play have been linked to sensory processing (Ismael et al., 2015; Watts et al., 2014), but surprisingly, no empirical studies have correlated the child's perceptions of play with sensory processing. Miller Kuhaneck and Britner (2013) established connections between social play and praxis in combination with sensory processing factors in children diagnosed with autism. When pretend play was studied among children 5 to 7 years, links were found between proprioception and object substitution and between social skills and the use of symbols (Roberts et al., 2018). Cosbey et al. (2012) focused on play behaviors and sensory processing skills and found a positive correlation between increased sensory processing skills and sociability of play. All children played socially; however, typically developing children did so more often and in larger groups.Although small to moderate relationships have been found between play and engagement in leisure activities and sensory processing, this emergent field of research requires further study to understand which aspects of sensory processing affect preferences and choices in the use of discretionary time. This area of study is relevant to occupational therapy because clinicians often assess children's play and leisure participation and sensory processing. The goal of this study was to investigate the way in which typically developing children, 8 to 12 years old, view, choose, and participate in their play and leisure activities as well as to identify associations between these observations and sensory processing factors, as reported by the parents. The study questions were: (1) What associations exist between a child's perception of their play and leisure activities and their sensory processing? and (2) What associations exist between a child's choice of play and leisure activities and their sensory processing?MethodsDesignA cross-sectional quantitative design was used to collect the quantitative data.ParticipantsChildren (n = 21) who were 8 to 12 years old and their parents (n = 15), from a regional city in Australia, were recruited through a flyer that was circulated on a social media platform and in person, with convenience and snowball sampling. The first author (E.E.M.) contacted interested parents and explained the project verbally. The parents were given an information packet containing plain language statements and consent forms for the parent and child as well as a demographic form that collected information to determine eligibility for inclusion. The inclusion and exclusion criteria ensured that all participants spoke and read English and that all children were typically developing. Children were excluded if a parent reported that they had a physical, developmental, or learning disability. Table 1 shows the demographic features of the children, including gender, age, school year, and number of siblings. Most of the participants were female (57.1% of children and 66.7% of parents).Table 1 Sample DemographicsCharacteristicn%M (SD)Gender Female1257.1 Male942.9Age, months 96–10729.6 108–119733.3 120–131314.2124.86 (13.89) 132–143733.3 144–15529.6Grade 214.8 3628.6 4419.0 5523.8 6523.8Siblings 029.5 1523.8 21152.4 314.8 429.5Note. n = 21; bootstrapped sample = 500.Power calculations were used to identify the number of child participants as 26, assuming .05 for the level of significance and 0.08 for statistical power (Taylor, 2017). However, because of resource and time limitations, only 21 children were recruited.MeasuresDemographic InformationA demographic form requested information on the child's gender, age, school grade, written and spoken language(s), number of siblings, and developmental history and on the parent's gender and written and spoken language(s).Sensory Processing MeasureThe Sensory Processing Measure (SPM) home form (Parham & Ecker, 2007) and manual (Parham et al., 2007) use a norm-referenced standardized system of eight scales (social participation, vision, hearing, touch, body awareness, balance and motion, planning and ideas, and total sensory systems) that assess responses to sensory stimuli. Suitable for children 5 to 12 years, the 75-item form is completed by the parent, who responds according to a 4-point Likert scale, where 1 = never, 2 = occasionally, 3 = frequently, and 4 = always. Raw scores are converted to standardized scores and interpreted as typical, some sensory problems, or definite dysfunction. The SPM was standardized with a sample of 1,051 children from the United States that found internal consistency (α) ranging from 0.77 to 0.95 and estimates of test-retest reliability ranging from 0.94 to 0.98 (Parham et al., 2007). Construct validity is shown within each scale, and the scales can be scored and interpreted separately. The SPM was developed from two scales, and the items for both scales had been subjected to multiple rounds of expert review.Children's Leisure Assessment ScaleThe CLASS (Rosenblum et al., 2010) is a 40-item self-report scale that is used to measure children's participation in play and leisure activities. Activities are rated across dimensions of participation; variety (range, 0–1), frequency (range, 0–4), sociability (range, 0–4), and preference (range, 0–10). The content and face validity of the scale were confirmed by an experienced panel. The internal consistency of the frequency domain of the instrument was rated as acceptable using the results of 249 participants from Israel who had a median age of 13.9 years, where α = 0.71 (Rosenblum et al., 2010).The internal reliability of the instrument was acceptable, with α ranging from 0.57 to 0.83 (Rosenblum et al., 2010). Factor analysis showed four subscales: (a) instrumental indoor activities, (b) outdoor activities, (c) self-enrichment activities, and (d) games and sports activities. Construct validity of the CLASS was investigated by comparing two age-matched groups of 114 girls and 114 boys selected from the original sample. Mean scores for all domains were calculated, and significant differences were found for variety, frequency, and preference, but not for sociability (Rosenblum et al., 2010). These findings differ from previous reports (Rosenblum et al., 2010). The CLASS can be used with children 8 to 18 years. With adult guidance, the instrument takes 15 to 30 minutes to complete.Children's Perception of Their PlayThe CPTP scale devised by Barnett (2013) is a quantitative method used to capture the child's voice in how they view and define play. The scale contains 25 items, and the child indicates their agreement with each item with a 4-point Likert scale, where 4 = definitely yes, 3 = probably yes, 2 = probably no, and 1 = no. Reverse scoring is used for eight of the items, which are phrased negatively. Factor analysis indicates six subscales: (a) child's choice (range, 6–24); (b) social play (range, 4–16); (c) planned activities (range, 5–20); (d) engagement (range, 4–16); (e) active play (range, 3–12); and (f) free time (range, 3–12). The internal reliability of the scale and the factor subscales was computed with coefficient ω from a sample of 689 U.S. participants who were 8 to 10 years. The results were ω = 0.88 for the whole scale and ranged from 0.79 to 0.91 for the subscales, indicating high internal consistency (Barnett, 2013). The form takes 10 minutes to complete.ProcedureEthical approval was obtained from the Human Ethics Advisory Group, Faculty of Health, Deakin University. All ethical requirements and guidelines were followed. Parents who responded to flyers that were distributed on a social media platform and in person were given both written and verbal explanations of the project and procedures. Parents provided written consent for their and their child's participation, and the child provided verbal assent if 9 years or younger and written assent if 10 years or older. After establishing consent, we arranged meeting times with the participants to complete the questionnaires. Some participants preferred to take the questionnaires home to complete. Appointments were held in a public space, such as a café or local library, were scheduled after school or on weekends, and took 1 to 2 hours. Participants could ask questions in person, by telephone, or by e-mail.We verbally explained the study and confirmed with each child their willingness to participate. Children who were 10 years or older also completed an assent form to indicate their willingness to participate. Children were asked to complete the CLASS and the CPTP on their own time, with either the parent or the researcher available for support. Parents were asked to complete the SPM for their children. Completed forms were returned in person, by e-mail, or by prepaid mail.Data AnalysisAll data underwent descriptive data analysis to yield frequency, percentage, mean, standard deviation, quartile, and range. The raw SPM data for each scale were reversed, so that a high score became indicative of greater skill, not greater challenge, and so that the scale ran in the same direction as the CLASS and the CPTP. These data and the reversed scores from the SPM were analyzed with the Statistical Package for Social Sciences, version 25, in accordance with the scoring protocol. All data were treated as ordinal.Correlations between the subscales of the SPM and the CLASS were calculated with Spearman's ρ. Where correlations were found, a general linear model was calculated to show predictive factors of the SPM on the factors of the CLASS. Correlations between the subscales of the SPM and the CPTP were calculated with Spearman's ρ. Where correlations were found, stepwise linear regression was calculated to show predictive factors of the SPM on the factors of the CPTP.Bootstrapping, in which a sample is used to estimate a population (Walker & Smith, 2017), was used to increase the rigor of all correlation calculations and regression models. Bootstrapping was performed according to the model indicated by the sample (n = 21) to infer results for a larger sample, by creating new iterations within the model by sampling from the data of the existing model. This process minimized the effect of the small sample size and improved the confidence interval (Preacher & Hayes, 2004). The specifications for the bootstrap procedure were a simple sampling method, a sample of 500, and a confidence interval of 95%. The confidence interval type was corrected for bias and accelerated.ResultsDescriptive statistics for the SPM, CLASS, and CPTP are shown in Table A, available in the online version of this article. Mean SPM subscale scores ranged from 22.48 to 30.14. The CLASS games and sports activities subscale had the highest mean scores for variety (M = 0.92), frequency (M = 2.63), sociability (M = 2.6), and preference (M = 7.35). On the CPTP, the child's choice subscale had the highest mean score (M = 16.43), whereas the active choice subscale had the lowest mean score (M = 8.67).Table A. Descriptive statistics for Sensory Processing Measure subscales and total score, Children's Leisure Assessment, and Children's Perceptions of Their Play (n = 21; bootstrapped sample = 500).MeasureStandardInterquartile rangesMeanDeviationMedianRangeQ1Q2Q3Sensory Processing Measure SOC25.436.092812 – 3021.52830 VIS30.144.853315 – 3329.53333 HEA22.482.482415 – 24212424 TOU29.715.313311 – 3326.53333 BOD28.292.393021 – 30273030 BAL31.712.353323 – 33313333 PLA24.524.032610 – 2723.52627 TOT155.917.3916494 – 168150164166Children's Leisure Assessment Total Variety.79.07.80.63 – .90.73.80.88 Frequency1.950.281.981.30 – 2.381.731.982.12 Sociability1.750.231.781.10 – 2.101.681.781.93 Preference6.060.976.083.83 – 7.905.616.086.64 Instrumental Indoor Activities Variety.86.15.88.38 – 1.00.75.881.00 Frequency2.440.492.501.38 – 3.502.192.502.75 Sociability1.610.401.500.75 – 2.381.381.501.94 Preference5.951.456.003.00 – 8.755.196.007.00 Outdoor Activities Variety.78.13.78.56 – 1.00.67.78.89 Frequency1.450.341.440.78 – 2.221.221.441.73 Sociability1.870.471.891.11 – 2.671.451.892.22 Preference6.131.356.114.11 – 8.225.066.117.39 Self-Enrichment Activities Variety.78.15.75.50 – 1.00.75.75.88 Frequency1.950.612.000.38 – 3.001.692.002.38 Sociability1.700.571.630.50 – 2.501.381.632.15 Preference5.661.875.631.00 – 9.004.515.636.82 Games and Sports Activities Variety.92.131.00.60 – 1.00.801.001.00 Frequency2.630.582.801.20 – 3.402.102.803.10 Sociability2.600.482.601.40 – 3.602.402.602.80 Preference7.341.447.603.60 – 9.406.607.608.20Children's Perceptions of Their Play Child's Choice16.432.251712 – 20151718 Social Play12.052.33128 – 16111213.5 Planned Activities11.712.17126 – 1510.51213 Engagement12.861.351311 – 15121314 Active Play8.672.0394 – 127.5910 Free Time9.951.77105 – 1291011Note: SOC = Social participation; VIS = Vision; HEA = Hearing; TOU = Touch; BOD = Body Awareness (proprioception); BAL = Balance and Motion (vestibular); PLA = Planning and Ideas (praxis); TOT = Total Sensory Systems.As seen in Table B, available in the online version of this article, significant positive correlations were found between the sensory processing factor of planning and ideas and the frequency of participation in self-enrichment activities (ρ = 0.435, p < .05) as well as between the subscale of balance and motion and the variety (ρ = 0.488, p < .05), frequency (ρ = 0.440, p < .05), and preference (ρ = 0.439, p < .05) domains of the subscale of games and sports activities.Table B. Correlation Coefficients of Sensory Processing Measure subscales and the Children's Leisure Assessment subscales (n = 21; bootstrapped sample = 500).CLASSSensory Processing Measure subscalesSOCVISHEATOUBODBALPLATOTTotal Score Variety.225.054−.037−.174.021.279−.067−.028 Frequency.067.191.151.131.057.053.178.122 Sociability.188.028−.11−.229−.149−.032.103−.135 Preference.27.15−.003.021.122.018.307.095Instrumental Indoor Activities Variety.01.073.007−.137−.293−.229.133−.249 Frequency−.045.028.002.018−.116−.374.251−.134 Sociability−.041.128.077.025−.192−.233.223−.08 Preference−.092−.023−.077−.191−.082−.341.276−.273Outdoor Activities Variety.116.053−.03−.211.073.165−.229.026 Frequency−.109.209.155−.111.225.34−.292.101 Sociability.152−.042−.139−.253.017.084−.23−.054 Preference.258.131−.076−.172.033.153.006.087Self-Enrichment Activities Variety.188−.025−.082−.033.106.221.239.039 Frequency.199.314.176.295.22.118.435*.393 Sociability.073−.025−.109−.282.023−.111.222−.134 Preference.126.281.179.265.422.009.305.315Games and Sports Activities Variety.174−.024.025−.125−.1.488*−.036.046 Frequency.145−.019.129.039−.072.440*.021.056 Sociability.301.083.02−.156−.195.131.323−.077 Preference.055−.255−.127−.107−.066.439*−.018−.086Note: CLASS=Children's Leisure Assessment. SOC = Social participation; VIS = Vision; HEA = Hearing; TOU = Touch; BOD = Body Awareness (proprioception); BAL = Balance and Motion (vestibular); PLA = Planning and Ideas (praxis); TOT = Total Sensory Systems.*=Correlation is significant at the 0.05 level (2-tailed).**=Correlation is significant at the 0.01 level (2-tailed).Bootstrap specifications: i) sampling method – simple; ii) number of samples – 500; iii) confidence interval (CI) level – 95%; and iv) CI type – bias-corrected and accelerated.A general linear model was calculated using these significant relationships, and a statistically significant effect was found where F(1, 5) = 3.198, p = .037, with the variety of games and sports activities accounting for 51.6% of the variance within the model. Therefore, the balance and motion factor was predictive of the variety of games and sports activities reported.Table C, available in the online version of this article, shows the results of correlation calculations between sensory processing factors and children's perceptions of play. Significant negative correlations were found between the social participation (ρ = −0.500, p < .05), vision (ρ = −0.583, p < .01), hearing (ρ = −0.515, p < .05), touch (ρ = −0.569, p < .01), planning and ideas (ρ = −0.539, p < .05), and total sensory systems (ρ = −0.558, p < .01) factors of the SPM and the CPTP child's choice factor. A significant negative correlation was found between the SPM body awareness factor (ρ = −0.691, p < .01) and the CPTP child's choice factor. No significant correlations were found between the SPM factors and any other CPTP factors.Table C. Correlation Coefficients between the Sensory Processing Measure subscales and the Children's Perceptions of Their Play subscales (n = 21; bootstrapped sample = 500).CPTP subscalesSensory Processing Measure subscalesSOCVISHEATOUBODBALPLATOTChild's Choice−.500*−.583**−.515*−.569**−.691**.073−.539*−.558**Social Play−.007.111.016.209.143−.088.033.158Planned Activities.063.105−.015−.031−.166−.173.128.012Engagement.016−.226−.214−.328−.136−.243.162−.372Active Play.233−.038−.203.064−.095−.210.275−.170Free Time.007.200.302.162.233.257.141.244Note: CPTP = Children's Perception of Their Play. SOC = Social participation; VIS = Vision; HEA = Hearing; TOU = Touch; BOD = Body Awareness (proprioception); BAL = Balance and Motion (vestibular); PLA = Planning and Ideas (praxis); TOT = Total Sensory Systems.*=Correlation is significant at the 0.05 level (2-tailed).**=Correlation is significant at the 0.01 level (2-tailed).Bootstrap specifications: i) sampling method – simple; ii) number of samples – 500; iii) confidence interval (CI) level – 95%; and iv) CI type – bias-corrected and accelerated.Significant results were entered into a multiple regression calculation. Because of the exploratory nature of this area of study, a stepwise method was used to enter the independent sensory processing variables. The regression results showed the following model: adjusted R2 = 0.293, F(1, 19) = 9.272, p = .007, 95% confidence interval [−0.168, −0.909]; β = −0.573. The SPM body awareness factor was the only independent variable that made a unique contribution to the model, accounting for 32.8% (p < .01) of variance. This finding indicated that the SPM body awareness factor was a significant predictor of the CPTP child's choice factor.DiscussionThe study findings show that sensory processing factors, as measured by the SPM, are partially related and predictive of participation in play and leisure activities, as measured by the CLASS, and of children's perceptions of their own play, as measured by the CPTP. Mean SPM subscale score values for the sample fell within the range that is seen in typically developing children.Emerging evidence indicates that there are relationships between children's sensory processing factors and their participation in and preference for play and leisure activities (Chien et al., 2016; Engel-Yeger, 2008; Roberts et al., 2018). This study is the first to examine relationships between sensory processing factors and play and leisure preferences and participation in typically developing Australian children who are 8 to 12 years old.Engel-Yeger (2008) explored sensory processing patterns and activity preferences among 6- to 11-year-old Israeli children with (n = 25) and without (n = 109) sensory processing challenges. Children with sensory processing challenges preferred activities that were more physically active. Those results differ from the current findings, which showed positive correlations between balance and motion and the variety, frequency, and preference domains of the games and sports factor. This finding suggests that children with robust sensory processing skills are more likely to participate in more types of games and sports activities, participate more often, and enjoy them more compared with children who have fewer sensory processing skills.Examining the relationship between play and children's sensory processing skills in typically developing children provides insights into different diagnostic groups. For example, children diagnosed with autism spectrum disorder are more likely than typically developing children to experience sensory processing challenges (Tomchek & Dunn, 2007), and they participate in play and leisure activities differently than their typically developing peers (Potvin et al., 2013). In a study by Potvin et al. (2013), all children who were diagnosed with autism (100%, n = 30) participated in playing computer or video games compared with 87.1% of their typically developing peers (n = 31). The CLASS games and sports factor includes playing computer games and playing board/card games (Rosenblum et al., 2010) as two of five items. Although there are correlations between the balance and motion factor of the SPM and three domains of the CLASS games and sports factor (variety, frequency, and preference), these items have less association with vestibular skills than the other constituent items of bicycle riding, playing outdoors, and team ball games (Rosenblum et al., 2010).Chien et al. (2016) investigated relationships between participation and sensory processing among a group of children (n = 36) with and without (n = 28) potential sensory impairments. Similar to the findings of the current study, they found that when children had lower energy ratings, they were less likely to participate in play and leisure activities. Children who were confident in their balance skills were more likely to adapt to and participate in a wider variety of physical activities. Although Chien et al. (2016) did not address the variety of sports participation, in a 3-year longitudinal study with children who were 6 to 9 years (n = 638) at intake, Vandorpe et al. (2012) found that motor coordination was predictive of continued participation in sports, which is congruent with the current findings. Motor coordination tests all involve elements of balance and movement, such as walking backward on a balance beam and jumping sideways over a set height for 15 seconds.Significant moderate to high negative correlations were found between the CPTP child's choice factor and the SPM vision, touch, hearing, body awareness, social participation, planning and ideas, and total sensory systems factors. The items within the CPTP child's choice subscale indicated a desire for control over the choice of activity, the time and content of play, and when to cease the activity (Barnett, 2013). Children who have fewer sensory processing skills showed a greater value for control over play activities. Free choice of activity has been theorized to be less important for children 9 to 11 years (Vitiello et al., 2012) and more important for children 5 to 6 years (Wing, 1995).Roberts et al. (2018) investigated sensory processing links with pretend play. The sensory processing factors of body awareness, balance and motion, and touch were related to children's ability to self-initiate elaborate play behaviors, choose how to play with the play materials, and direct the play. Body awareness also was related to initiating and choosing to play (Roberts et al., 2018), supporting the findings of this study. The current findings, which include vestibular and proprioceptive senses, were predictive of aspects of children's participation in play and their perspectives and values related to how they play. In the context of the findings of Miller Kuhaneck and Britner (2013) and Roberts et al. (2018), a growing body of evidence supports the connections between sensory processing factors and play and leisure.Implications for PracticeTypically developing children have a range of sensory processing skills that influence their participation and perceptions of play and leisure pursuits. Occupational therapists should consider that children with decreased sensory processing skills will be more likely to value the choice of activity as well as how and when the activity is performed and will be able to adapt interventions to support opportunities for increased choice. Occupational therapists can use the knowledge that children whose intrinsic physiology includes reduced vestibular capacity are less likely than their peers to participate in a wide variety of games and sports activities.Strengths and LimitationsThis study focused on the major occupations of childhood of play and leisure pursuits. Use of the CLASS and the CPTP to capture the voice of the child lends a client-centered focus to the research. Both the CLASS and the CPTP have established reliability and validity. This study was limited by the sample size and the specific geographical location, which may limit generalizability. However, bootstrapping was used to ensure that statistical analyses were robust. Respondent bias may be a limitation because participants may have adjusted their responses to be more socially desirable in cases where children asked for parental assistance in filling out the questionnaires. In addition, having the participants complete the questionnaires at home on their own or in the presence of the researcher may have led to bias.Correlating data derived from two different sets of informants (e.g., parents completing the SPM and children completing the CLASS and the CPTP) may have influenced the correlational analysis outcomes. However, no valid and reliable child report scale to measure sensory processing factors was available at the time. Because of the emergent nature of the topic, this research should be considered a pilot study.Future ResearchFuture research designs would include a mixed methods or qualitative approach to understand not only the values held by children about their own play but also the reasoning behind these perceptions, specifically at the intersection with sensory processing. This study could also be replicated to incorporate other factors, such as children with known clinical diagnoses, those from differing cultural backgrounds, or those living in different areas (e.g., rural vs. urban environment). Specific self-reported play activity preferences of children also could be correlated with sensory processing factors.ConclusionThis study examined the association between sensory processing and the child's voice in relation to participation in and preferences for play and leisure activities. Children's perception of play was significantly associated with body awareness and sensory processing. This finding informs occupational therapy practice, in particular, by emphasizing the importance of offering children a choice of play and leisure activities, particularly when their sense of body awareness and movement may not be well developed. Further research in this area is recommended.Barnett L. A. (2013). Children's perceptions of their play: Scale development and validation. Child Development Research, 2013, 1–18. 10.1155/2013/284741 CrossrefGoogle ScholarBrown T., O'Keefe S., & Stagnitti K. (2011). Activity preferences and participation of school-age children living in urban and rural environments. Occupational Therapy in Health Care, 25(4), 225–239. 10.3109/07380577.2011.589889 PMID:23899077 CrossrefGoogle ScholarBundy A. C., Shia S., Qi L., & Miller L. J. (2007). How does sensory processing dysfunction affect play? American Journal of Occupational Therapy, 61(2), 201–208. 10.5014/ajot.61.2.201 PMID:17436842 CrossrefGoogle ScholarChien C. W., Rodger S., Copley J., Branjerdporn G., & Taggart C. (2016). Sensory processing and its relationship with children's daily life participation. Physical & Occupational Therapy in Pediatrics, 36(1), 73–87. 10.3109/01942638.2015.1040573 PMID:26422598 CrossrefGoogle ScholarCosbey J., Johnston S. S., Dunn M. L., & Bauman M. (2012). Playground behaviors of children with and without sensory processing disorders. OTJR: Occupational, Participation and Health, 32(2), 39–47. 10.3928/15394492-20110930-01 CrossrefGoogle ScholarCurtis A., Hinckson E., & Water T. (2012). Physical activity is not play: Perceptions of children and parents from deprived areas. New Zealand Medical Journal, 125(1365). https://www.nzma.org.nz/journal/read-the-journal/all-issues/2010-2019/2012/vol-125-no-1365/article-curtis Google ScholarDunn W. (2014). Sensory Profile 2 user's manual. PsychCorp-Pearson. Google ScholarEngel-Yeger B. (2008). Sensory processing patterns and daily activity preferences of Israeli children. Canadian Journal of Occupational Therapy, 75(4), 220–229. 10.1177/000841741007700207 PMID:18975668 CrossrefGoogle ScholarEverley S., & Macfadyen T. (2015). "I like playing on my trampoline; it makes me feel alive." Valuing physical activity: Perceptions and meanings for children and implications for primary schools. Education 3–13: International Journal of Primary, Elementary and Early Years Education, 45(2), 151–175. 10.1080/03004279.2015.1069367 CrossrefGoogle ScholarHurd A., & Anderson D. (2011). The park and recreation professional's handbook. Human Kinetics. Google ScholarIsmael N. T., Lawson L. A., & Cox J. A. (2015). The relationship between children's sensory processing patterns and their leisure preferences and participation patterns. Canadian Journal of Occupational Therapy, 82(5), 316–324. 10.1177/0008417415577421 PMID:26590231 CrossrefGoogle ScholarMiller E., & Kuhaneck H. (2008). Children's perceptions of play experiences and play preferences: A qualitative study. American Journal of Occupational Therapy, 62(4), 407–415. 10.5014/ajot.62.4.407 PMID:18712003 CrossrefGoogle ScholarMiller Kuhaneck H., & Britner P. A. (2013). A preliminary investigation of the relationship between sensory processing and social play in autism spectrum disorder. OTJR: Occupational, Participation and Health, 33(3), 159167. 10.3928/15394492-20130614-04 PMID:24651901 CrossrefGoogle ScholarMorrison C. D., Bundy A. C., & Fisher A. G. (1991). The contribution of motor skills and playfulness to the play performance of preschoolers. American Journal of Occupational Therapy, 45(8), 687–694. 10.5014/ajot.45.8.687 PMID:1877636 CrossrefGoogle ScholarParham L. D., & Ecker C. (2007). Sensory Processing Measure (SPM): Home form. Western Psychological Services. Google ScholarParham L. D., Ecker C., Miller Kuhaneck H., Henry D. A., & Glennon T. J. (2007). Sensory Processing Measure (SPM): Manual. Western Psychological Services. Google ScholarPotvin M. C., Snider L., Prelock P., Kehayia E., & Wood-Dauphinee S. (2013). Recreational participation of children with high functioning autism. Journal of Autism and Developmental Disorders, 43(2), 445–457. 10.1007/s10803-012-1589-6 PMID:22752846 CrossrefGoogle ScholarPreacher K. J., & Hayes A. F. (2004). SPSS and SAS procedures for estimating indirect effects in simple mediation models. Behavior Research Methods, Instruments, & Computers, 36(4), 717–731. 10.3758/BF03206553 PMID:15641418 CrossrefGoogle ScholarPrimeau L. A. (2009). Play and leisure. In Crepeau E. B., Cohen E. S., & Boyt Schell B. A. (Eds.), Willard and Spackman's occupational therapy (11th ed., pp. 633–648). Wolters Kluwer/Lippincott Williams & Wilkins. Google ScholarRoberts T., Stagnitti K., Brown T., & Bhopti A. (2018). Relationship between sensory processing and pretend play in typically developing children. American Journal of Occupational Therapy, 72(1), 7201195050p1–7201195050p8. 10.5014/ajot.2018.027623 CrossrefGoogle ScholarRosenblum S., Sachs D., & Schreuer N. (2010). Reliability and validity of the Children's Leisure Assessment Scale. American Journal of Occupational Therapy, 64(4), 633–641. 10.5014/ajot.2010.08173 PMID:20825135 CrossrefGoogle ScholarSturgess J., Rodger S., & Ozanne A. (2002). A review of the use of self-report assessment with young children. British Journal of Occupational Therapy, 65(3), 108–116. 10.1177/030802260206500302 CrossrefGoogle ScholarTaylor R. R. (2017). Kielhofner's research in occupational therapy: Methods of inquiry for enhancing practice. F. A. Davis. Google ScholarTomchek S. D., & Dunn W. (2007). Sensory processing in children with and without autism: A comparative study using the short sensory profile. American Journal of Occupational Therapy, 61(2), 190–200. 10.5014/ajot.61.2.190 PMID:17436841 CrossrefGoogle ScholarVandorpe B., Vandendriessche J., Vaeyens R., Pion J., Matthys S., Lefevre J., Philippaerts R., & Lenoir M. (2012). Relationship between sports participation and the level of motor coordination in childhood: A longitudinal approach. Journal of Science and Medicine in Sport, 15(3), 220–225. 10.1016/j.jsams.2011.09.006 PMID:22047725 CrossrefGoogle ScholarVitiello V. E., Booren L. M., Downer J. T., & Williford A. (2012). Variation in children's classroom engagement throughout a day in preschool: Relations to classroom and child factors. Early Childhood Research Quarterly, 27(2), 210–220. 10.1016/j.ecresq.2011.08.005 PMID:25717218 CrossrefGoogle ScholarWalker D. A., & Smith T. J. (2017). Computing robust, bootstrap-adjusted fit indices for use with non-normal data. Measurement & Evaluation in Counseling & Development, 50(1–2), 131–137. 10.1080/07481756.2017.1326748 CrossrefGoogle ScholarWatts T., Stagnitti K., & Brown T. (2014). Relationship between play and sensory processing: A systematic review. American Journal of Occupational Therapy, 68(2), e37–e46. 10.5014/ajot.2014.009787 PMID:24581412 CrossrefGoogle ScholarWing L. A. (1995). Play is not the work of the child: Young children's perceptions of work and play. Early Childhood Research Quarterly, 10(2), 223–247. 10.1016/0885-2006(95)90005-5 CrossrefGoogle Scholar Previous article Next article FiguresReferencesRelatedDetails Request Permissions InformationCopyright 2021, SLACK IncorporatedPDF downloadAddress correspondence to Ted Brown, PhD, MSc, MPA, BScOT(Hons), GCHPE, OT(C), OTR, MRCOT, FOTARA, FAOTA, Associate Professor, Department of Occupational Therapy, School of Primary and Allied Health Care, Faculty of Medicine, Nursing and Health Sciences, Monash University–Peninsula Campus, Building G, 4th Floor, 47-49 Moorooduc Highway, Frankston, Victoria 3199, Australia; e-mail: ted.[email protected]edu.Ms. Matthews is an honours student, Occupational Science and Therapy Program, School of Health and Social Development, Faculty of Health, Deakin University–Waterfront Campus, Geelong, Victoria, Australia. Dr. Brown is Associate Professor and Undergraduate Course Coordinator, Department of Occupational Therapy, School of Primary and Allied Health Care, Faculty of Medicine, Nursing and Health Sciences, Monash University–Peninsula Campus, Frankston, Victoria, Australia. Dr. Stagnitti is Professor, Occupational Science and Therapy Program, School of Health and Social Development, Faculty of Health, Deakin University–Waterfront Campus, Geelong, Victoria, Australia.The authors have no relevant financial relationships to disclose. Received10/06/19Accepted3/09/20

Introduction:To address health disparities among underserved populations, occupational therapists can participate in community-engaged research and practice to improve access to preventive health services.Methods: This study used grounded theory and participant observation approaches to identify lessons learned from a community-engaged research project to improve cancer screening rates for Indigenous women with an intellectual and/or developmental disability (IDD).Audio recordings of meetings with a community advisory board (AB) were analyzed with an inductive coding approach, and results were member checked with AB members.The AB members (N = 8) were involved in statewide Indigenous health, cancer, and disability activities.Six of the eight AB members identified as Indigenous.Results: Key themes highlighted within the Indigenous research framework included reflection, relationship building, project planning, and project execution.Results of this phase of the research project highlight the importance of codesigning research projects with Indigenous communities. Conclusion:The findings have limited transferability to other research contexts.However, this study highlights the need for future research on best practices for occupational therapists to participate in community-engaged research projects to address health disparities in underserved populations, such as Indigenous women with IDD.

Every year, 795,000 Americans experience a stroke, the leading cause of serious long-term disability (Benjamin et al., 2019).Stroke is an acute neurological syndrome that is caused by disruption of the cerebral blood supply (Faralli et al., 2013).Motor impairments, including hemipa-resis, incoordination, and spasticity, are the most common deficits (Faralli et al., 2013).Approximately two thirds of stroke survivors continue to experience motor deficits of the arm and leg, resulting in disability and deterioration in quality of life (Radajewska et al., 2013).

Original Research freeFunctional Individualized Therapy for Teenagers With Executive Deficits: A Pilot Study Yael Fogel, PhD, OT, ; , PhD, OT Sara Rosenblum, PhD, OT, ; and , PhD, OT Naomi Josman, PhD, OT, , PhD, OT Yael Fogel, PhD, OT , Sara Rosenblum, PhD, OT , and Naomi Josman, PhD, OT Published Online:May 21, 2021https://doi.org/10.3928/24761222-20200923-01PDFAbstract ToolsAdd to favoritesDownload CitationsTrack CitationsCopy LTI LinkHTMLAbstractPDF ShareShare onFacebookTwitterLinkedInRedditEmail SectionsMoreAbstractObjective:Adolescents who have executive function deficit (EFD) profiles struggle to participate effectively in everyday life, creating a gap in age-expected functioning between them and their peers. This study evaluated the results of an 8-week program of Functional Individualized Therapy for Teenagers with EFDs (FITTED), a metacognitive occupation-based intervention to help adolescents to achieve everyday life goals.Methods:Phase 1 screened for the study group (41 adolescents with EFD profiles, 10–14 years old) with Behavior Rating Inventory of Executive Function (BRIEF) parent and self-reports and WebNeuro assessments. Phase 2 implemented the FITTED program in the study group with a cohort design. Participants rated their performance and satisfaction with everyday life goals preintervention, postintervention, and at 3-month follow-up.Results:Parent reports showed significant differences between pre- and postintervention findings on the BRIEF emotional control scale and between postintervention and follow-up findings on the initiation and plan-organize scales. Significant differences were noted from pre- to postintervention findings for self-reported performance and satisfaction (p < .001), but none were found between posttest and follow-up findings.Conclusion:The FITTED program improved performance and satisfaction with everyday life goals over time. It may be suitable for clinical use among adolescents with EFD profiles. Limitations included a small sample and the use of a single study group. Future studies could evaluate the effectiveness of this program relative to other interventions. [Annals of International Occupational Therapy. 2021;4(3):e126–e134.]IntroductionAdolescence is a period of transition from childhood to adulthood and a time of neural adjustment and learning. As adolescents mature, brain processes become more efficient and effective (Steinberg, 2008). Thus, this transition toward independent and responsible adulthood is considered a time of enormous change that entails adjustments in long-term personal goals and motivation and greater use of cognitive control skills (Crone & Dahl, 2012).Significant research has shown the contribution of the use of executive functions (EFs) as an underlying mechanism of adolescents' daily functioning (Josman & Rosenblum, 2018) and scholastic achievement (Jacob & Parkinson, 2015). The EFs are control functions that are used to implement or execute a task to face a new situation. These multidimensional cognitive constructs are necessary for many goal-directed and problem-solving behaviors (Otero et al., 2014). The EF skills help to shape adolescent behavior and promote socioemotional and educational competencies (Bierman et al., 2008; Riggs et al., 2006). Importantly, EFs in childhood and adolescence predict adult productivity and life outcomes (Diamond, 2013).Adolescents who have EF deficit (EFD) profiles often appear disorganized and forgetful and seem to lack initiative. They require frequent encouragement and cues when expected to do more than one thing at a time. In addition, because they have difficulty starting assignments, they may be described as lazy or procrastinating. They struggle to shift between activities, may perseverate on one task until it is completed, and have difficulty prioritizing important tasks, managing time, and meeting deadlines. Planning is challenging for them because they tend to focus only on the present (Otero et al., 2014). These difficulties limit their ability to perform and participate effectively in everyday life, creating a gap in functioning between them and their peers (Fogel et al., 2020; Josman & Rosenblum, 2018).Metacognitive and cognitive approaches are among the most promising approaches for occupational therapy intervention (Riccio & Gomes, 2013; Tamm et al., 2014). These approaches commonly involve teaching direct and indirect strategies for organizing, problem solving, evaluating, monitoring, and managing EFs in the context of everyday functional activities. Additionally, they allow practice to give the adolescent an opportunity to execute activities fluently and automatically (Galvin & Mandalis, 2009; Mahone & Slomine, 2007). Examples include the Cognitive Orientation to Daily Occupational Performance (CO-OP) for children and adolescents with developmental coordination disorders (Polatajko, 2017) and the Teen Cognitive-Functional (Cog-Fun) intervention for adolescents with attention deficit hyperactivity disorder (Levanon-Erez & Maeir, 2014). Both of these approaches are based on teaching cognitive strategies to improve daily functioning. Gilboa and Helmer (2020) published a self-management intervention for attention and EF in occupational therapy among children 6 to 14 years old.However, a broader, more dynamic evidence-based approach is needed to address a wider range of difficulties and allow individual adjustment of strategies to achieve therapeutic goals. This article describes an intervention program—the Functional Individualized Therapy for Teenagers with EFD (FITTED; Fogel et al., 2016)—that offers a unique lens on the treatment process for this population. This program targets a broad range of adolescents, with or without formal diagnoses, to develop self-awareness of their daily functioning, and its dynamic processes encourage self-generated individual strategies.We developed the FITTED program based on existing fundamental models and approaches. However, the FITTED program is unique in its integration of these models, which include the:World Health Organization (2007) International Classification of Functioning, Disability and Health: Children and Youth Version (ICF-CY)Person-Environment-Occupation-Performance model for identifying activities that present challenges in everyday life for adolescents (Baum et al., 2015)Dynamic Interactional Model of cognition (Toglia, 2018)Dynamic cognitive intervention (Hadas-Lidor et al., 2018) to direct each session and promote quality therapeutic interaction with adolescents (e.g., strategy creation and mediation processes)The FITTED model focuses on EFs, awareness, and strategies to improve occupational performance and increase participation. It helps adolescents to "see" their functioning and self-reflect (Buitelaar, 2017). The FITTED model has four unique essential characteristics: (1) It is a short, time-focused therapeutic framework of eight 1-hour weekly sessions that include evaluation before and after treatment. (2) It is targeted toward adolescents, with or without formal diagnoses, whose struggle to execute everyday life goals may result from EFD profiles. (3) It offers a structured protocol for each session to provide occupational therapists with a therapeutic framework. (4) It provides a protocol that requires parents' active involvement in the treatment sessions, based on the assumption that parents are the main supporters of their children's functioning.Each FITTED session follows three guiding principles. The first component, setting individual goals and treatment activities, is designed to enhance self-awareness and recognize difficulties. The adolescents gradually take a more active role in setting realistic goals and identifying activities that they want to perform more easily. The second component is raising awareness and identifying components of the activity that provide challenges in everyday life. This component facilitates recognition of successful (and unsuccessful) performance methods in terms of person, task, or environment through hierarchical mediation principles. This mediation includes a hierarchy of standard cues to use when the adolescent has difficulty. The cues increase, for example, from general cueing to structured cueing, up to simplifying the task or completing the task for the adolescent (Toglia, 1994). The third component is creating and practicing individual strategies for the adolescent to enable transfer and generalization to everyday life activities.The goal of this pilot study was to evaluate the effects of the FITTED program on everyday life goals among young adolescents with EFD profiles who struggle with significant areas of their lives. The main research questions were whether, after participation in the intervention, adolescents who were characterized as having EFD profiles showed improvement in EFs, as measured with the Behavior Rating Inventory of Executive Function (BRIEF), BRIEF self-report (BRIEF-SR), and WebNeuro, and in achieving everyday life goals, as measured with the Canadian Occupational Performance Measure (COPM; Law et al., 2005).MethodsResearch DesignThe study had two main phases. Phase 1 characterized the study (EFD profile) group compared with a control group of typically developing (TD) adolescents who were matched by age and gender. Phase 2 implemented the FITTED intervention with the study group only and evaluated the results at three time points: before the intervention, at the end of the 8-week intervention, and at follow-up 3 months after the intervention. The University of Haifa Ethics Committee approved this study.ParticipantsSample size was determined with the guidelines of G*Power software, considering the medium effect size of 0.25, power = 90, and alpha = 0.05 (Buchner et al., 2013). Given the complexity of the study design in terms of population variability and assessment and treatment processes, the study required a minimum of 40 participants in the study group (the group that received the intervention). Phase 1Study participants for Phase 1 were recruited through community advertisements aimed toward young adolescents (10–14 years old), both with and without difficulty with daily functioning. We excluded volunteers with known psychiatric, emotional, or autistic spectrum disorders; physical disabilities; or neurological diseases. Parents of participants who expressed willingness to participate in the study completed the BRIEF (Gioia et al., 2020) and a demographic questionnaire. Appropriate candidates were assigned to either the study group or the control group, according to BRIEF scores. Specifically, those included in the study (EFD profile) group scored at least 65 (outside normal range) on the metacognition (MI) or behavioral regulation (BRI) composite index of the parent-reported BRIEF. Those included in the age- and gender-matched control group had index scores in the normal range (< 65). All adolescent participants performed two subtests from the Wechsler Intelligence Scale for Children (WISC-R; Wechsler, 1998), and those with a score higher than 5 were included. Once accepted into the study, study group participants completed the BRIEF-SR (Guy et al., 2004) and WebNeuro (Silverstein et al., 2007) to characterize their EFD profiles compared with the control (TD) group.Of 133 participants who were initially screened for eligibility, 52 were excluded (22 were ineligible according to exclusion criteria and 30 did not return the final research forms). Of the remaining participants, 41 were assigned to the study group and 40 to the control group. Figure 1 shows the allocation of participants to the groups and the study procedures.Figure 1: Flow diagram of participant allocation to the study and study procedures. EFD = executive function deficit; TD = typically developing.Phase 2Only the 41 study group participants continued to Phase 2 and underwent the FITTED intervention. As part of the intervention, we used the COPM to determine each participant's intervention goals. However, we analyzed follow-up data for only 38 participants because 3 did not return the evaluation forms (1 did not return the form because of his mother's death and 2 did not respond to repeated requests).ProcedureTo address potential bias, one occupational therapist evaluated participant processes at the three time points. Another occupational therapist who had relevant theoretical knowledge and experience with adolescent interventions preformatted the intervention processes. To enhance and monitor the fidelity of the intervention, we developed protocol guidelines for uniform structure of the meetings, and we documented all meetings (Table A).Table A The FITTED Intervention ProtocolSessionSession goalMethod1Interview adolescent and parents. Define therapeutic contract. Select intervention goals.Personal contact with adolescent through daily log to identify strengths and weaknesses. Define three goals measured according to the Canadian Occupational Performance Measure (Law et al. 2005).2Learn about strategies and how to use them.Suggest activity for the adolescent to understand the need for a strategy to improve functioning.3, 5, 7Demonstrate analysis of activities and create individual strategies. Promote control and self-awareness, analysis of strengths and weaknesses.Analyze requirements of the selected goal. Identify components that allow or delay occupational functioning in the environment in which the adolescent operates and select elements for change to promote functioning. Practice strategies in the target activity or other relevant and meaningful activities. Find effective way to monitor strategy implementation.4, 6, 8Practice strategy in a variety of activities and contexts; transfer and include the strategy in other activities Provide opportunity to experiment with strategies in a variety of activities towards achieving the goalDisplay selected treatment activity. Before the activity, complete self-awareness page promoting self-control. During the activity, the therapist reflects strategies the adolescent uses. At activity end, complete self-awareness page for self-evaluation. Mediate.Pretest data were collected 1 week before the first intervention session, posttest data were collected 1 week after the last session, and follow-up data were obtained approximately 3 months after the intervention ended. The follow-up phase included only online questionnaires (BRIEF, BRIEF-SR, and COPM) that were sent to the participants without face-to-face meetings. Thus, the WebNeuro assessment, which requires specialized software and normally is conducted in person, could not be performed at follow-up.InstrumentsWe chose study instruments based on the recommendations in the literature to use both rating scales and performance-based measures. Because these tools assess different aspects of EFs, together, they indicate how well individuals respond to adverse conditions (Toplak et al., 2013). We selected assessment tools according to the ICF-CY framework (World Health Organization, 2007). The use of ICF-CY levels allowed us to obtain a broad functional picture of each adolescent's performance to determine the expected improvement after the FITTED program.Inclusion CriteriaDemographic Questionnaire. Parents completed the demographic questionnaire, which included information on the age and gender of the adolescent, the education of the mother and father, and the socioeconomic status of the family.WISC-R. Commonly used in evaluation studies of children 10 years or older who have complex neurodevelopmental disabilities, the WISC-R (Wechsler, 1998) assesses verbal and nonverbal capacity to evaluate intellectual functioning (Bental & Tirosh, 2007). We used its vocabulary and block design subtests to assess these capabilities, define participants' profiles, and exclude participants who had possible intellectual disabilities. For each subtest, the mean score was 10. Sattler (2008) reported that the two-subtest combination (vocabulary and block design) strongly correlated with the WISC-IV full scale IQ (r = .92) with adequate test–retest reliability (r = .87).BRIEF. The BRIEF (Gioia et al., 2020) includes 86 questions in five cognitive subscales (initiation, working memory, plan-organize, organization of materials, and monitoring) and three behavioral subscales (inhibit, shift, and emotional control). These eight subscales form the two composite indices—the metacognitive MI and the behavioral BRI—and a global executive composite (GEC) score. The results are expressed as t scores, where higher scores reflect more problematic behavior. A t score of 65 or higher is considered within the clinical range.The BRIEF parent version has good test–retest stability (range, .72–.84), high internal consistency in the general population (range, .78–.96; Smidts & Huizinga, 2009), and good convergent and divergent validity (Ferdinand & van der Ende, 1998; Verhulst et al., 1996).EFD Profile CharacterizationBrief-SR. The BRIEF-SR (Guy et al., 2004) is a reliable, valid self-report instrument that assesses EFs in 11- to 18-year-olds. It includes 80 statements in the same four MI and four BRI subdomains as the parent version. The MI and BRI scores are summed to obtain the overall GEC score. Reported t scores (M = 50, SD = 10) of greater than 65 are considered clinically significant. Test–retest reliability was .84 for the BRI and .87 for the MI. Internal reliability for the entire scale in the current study was alpha = 0.95; in the standardized sample, the BRIEF-SR yielded alpha = 0.80 to 0.98. Significant associations were found between the GEC and the Attention Deficit Hyperactivity Disorder Rating Scale-IV (inattention correlation = 0.63, p < .01; hyperactivity/impulsivity correlation = 0.60, p < .01) and the GEC and the Child Behavior Checklist (attention problems correlation = 0.72, p < .01; Gioia et al., 2020).WebNeuro. WebNeuro (Silverstein et al., 2007) is a computerized neuropsychological screening tool that measures cognitive function and its effects in different populations. The different versions allow measurement along time points, building a profile as the intervention progresses. WebNeuro assesses the sensorimotor, memory, executive, attention, and emotion perception (social cognition) domains of cognitive function. For most tests, automated software scores the responses. The validity coefficient between IntegNeuro and WebNeuro factors and overall performance scores ranged from .56 to .86. Validity coefficients between critical scores for each test ranged from .45 to .87. All participants completed the memory, attention, and executive domains of the WebNeuro.Everyday Life Goal Achievement: COPMThe COPM (Law et al., 2005) is an individualized outcome measure of daily activities. Each participant identified and prioritized three to five meaningful activities for which they perceived the greatest performance problems. They rated each activity for performance and satisfaction from 1 (not able to do at all) to 10 (able to do extremely well). During follow-up, the adolescents again rated their perceived performance and satisfaction for all activities identified at the baseline. Test–retest reliability for COPM performance was r = .84 (p < .001); for COPM satisfaction, it was r = .63 (p < .001). A change of at least 2 points was considered significant.Data AnalysisWe processed the resulting data with SPSS, version 21. For Phase 1, we used descriptive statistics for the main demographic data of the 81 participants, and we used t tests and multivariate analysis of variance to analyze between-group differences in inclusion criteria and characterize EFD profiles.Only 38 participants completed Phase 2 and received the follow-up questionnaires. We conducted repeated measures multivariate analysis of variance with Bonferroni correction pairwise comparisons (p < .5) to evaluate differences among pretest, posttest, and follow-up assessments. Partial eta-squared (ηp2) was reported as effect size, with ηp2 < .04 considered the minimum value to represent a clinically significant effect, .04 < ηp2 < .25 was considered a moderate effect, and ηp2 > .25 was considered a strong effect (Becker, 2000).ResultsPhase 1As shown in Table 1, the study (EFD profile) group (n = 41) included 29 (70.7%) boys and 12 (29.3%) girls, with mean age of 11.88 (SD = 1.08) years. The control (TD) group (n = 40) included 28 (70%) boys and 12 (30%) girls, with mean age of 12.19 (SD = 1.08) years.Table 1 Demographic CharacteristicsCharacteristicEFD group (n = 41)TD group (n = 40)Between-group differencepAge, mean ± SD (range), y11.88 ± 1.08 (10.08–14.05)12.19 ± 1.08 (10.00–14.75)−1.29a.2Gender, n Boys29 (70.7%)28 (70.0%)0.0b.94 Girls12 (29.3%)12 (30.0%)Mother's education, academic,cn34 (82.9%)37 (92.5%)1.71b.19Father's education, academic,cn30 (73.2%)27 (67.5%)0.31b.57Socioeconomic status,dn Low2 (4.9%) Average21 (51.2%)20 (50.0%)2.11b.34 High18 (43.9%)20 (50.0%)Note. EFD = executive function deficit; TD = typical development.at test.bChi-square test.cAcademic = higher education (> 2 years of schooling, including studies toward a degree or profession).dSocioeconomic status: low = monthly income of less than 7,000 Israeli shekel (ILS); average = monthly income of 7,000–14,000 ILS; high = monthly income of more than 14,000 ILS.Table B shows the scores for participant inclusion criteria and EFD profile characterization. For inclusion criteria, both groups were within the average range (10) of the two WISC subtests. However, significant differences were found between the groups, with a lower mean in the EFD profile study group, F(2,78) = 11.30, p < .001, ηp2 = .23. Significant differences were found between groups in the BRIEF index scores, with a lower mean in the study group, F(2,78) = 11.30, p < .001, ηp2 = .23; BRI, t(79) = 11.73, p < .001; MI, t(79) = 17.1, p < .001; and GEC, t(79) = 19.44, p < .001. For EFD profile characterization, significant differences were found for the study group between the BRIEF-SR overall GEC, t(79) = 6.14, p < .001; index scores (MI, t(79) = 7.08, and BRI, t(79) = 5.27, p < .001); and the WebNeuro assessment, F(6,74) = 11.84, p < .001, ηp2 = .49.Table B Participants' Inclusion Criteria and EFD-Profile CharacterizationMeasureEFD group (n= 41)TD group (n = 40)WISC-R95M (SD)M (SD)Fpηp2 Vocabulary9.63 (2.43)11.80 (2.69)14.43<.001.15 Block design11.20 (2.96)13.38 (2.09)14.56<.001.15M (SD)RangeM (SD)RangetpBRIEF-BRI67.70 (9.72)52–9446.32 (8.15)36–6611.73<.001BRIEF-MI66.65 (6.34)50–8142.95 (6.13)33–5917.10<.001BRIEF-GEC69.09 (5.26)58–8043.82 (6.36)33–5519.44<.001BRIEF subscalesM (SD)RangeM (SD)RangeFpηp2 Inhibition63.00 (12.13)40–10045.92 (6.70)40–6361.01<.001.43 Shift70.29 (11.04)48–9546.47 (6.86)38–59135.17<.001.63 Emotional control68.68 (12.15)45–9147.05 (9.05)36–6482.17<.001.51 Initiation62.21 (9.43)44–7942.47 (5.93)35–56126.35<.001.61 Working memory67.44 (8.51)49–8243.65 (5.43)36–57223.32<.001.73 Plan/Org67.41 (7.46)47–8243.77 (6.45)37–63231.87<.001.74 Organization of materials59.46 (7.83)40–7046.60 (9.16)34–6646.17<.001.36 Monitor63.65 (6.95)48–8242.87 (7.62)33–58164.36<.001.67M (SD)RangeM (SD)RangetpBRIEF-SR-BRI59.07 (12.18)37–8445.85 (10.36)18–685.26< .001BRIEF-SR-MI58.71 (10.83)31–8143.35 (8.59)22–637.07< .001BRIEF-SR-GEC59.39 (11.24)33–8445.10 (9.64)19–676.14< .001BRIEF-SR subscalesM (SD)RangeM (SD)RangeFpηp2 Inhibition55.70 (11.07)34–8646.52 (8.29)34–6617.77<.001.18 Shift58.60 (14.35)32–9145.85 (9.41)32–7822.25<.001.22 Emotional control61.17 (10.96)38–8349.35 (9.98)28–7125.71<.001.25 Monitor54.09 (10.10)36–7645.77 (8.51)31–6316.05<.001.17 Working memory56.04 (11.39)34–8643.50 (7.57)32–6133.92<.001.30 Plan/Org58.32 (10.89)31–7945.15 (10.49)18–7530.69<.001.28 Organization of materials55.22 (11.54)33–7645.07 (8.00)33–6421.01<.001.21 Task completion61.12 (11.00)35–8443.55 (8.08)26–6166.81<.001.46WebNeuro domainM (SD)M (SD)Fpηp2 Memory−0.59 (1.40).550 (.58)23.15<.001.22 Attention−1.09 (1.04).160 (.87)34.93<.001.30 Executive−0.57 (1.10).350 (.71)20.16<.001.20Note.EFD = group with executive function deficits; TD = group with typical development; M = mean; SD = standard deviation; WISC-95 = Wechsler Scale for Intelligence; BRIEF = Behavior Rating Inventory of Executive Function.Phase 2BRIEF and BRIEF-SR Comparisons Over TimeSignificant differences were found over time in the BRIEF MI and BRI scores, F(2,34) = 8.36, p < .001, ηp2 = .50. The post hoc Bonferroni test (p < .05) showed a significant difference in the BRI score from pre- to posttest (p = .003) and from pretest to follow-up (p < .001), but none from posttest to follow-up (p = .63). Further, the MI score showed no significant difference from pre- to post-test (p = .09), but found significant differences from pre-test to follow-up (p < .001) and from posttest to follow-up (p = .003).Additional significant differences were found over the three time points in the BRIEF GEC total score, F(2,36) = 16.03, p < .001, ηp2 = .47. The post hoc Bonferroni test (p < .05) showed a significant difference in the GEC score from pre- to posttest (p = .007), from pretest to follow-up (p < .001), and from posttest to follow-up (p = .02).Significant differences also were noted across time points in the BRIEF scales, F(8,16) = 3.52, p < .003, ηp2 = .72. Post hoc Bonferroni tests (p < .05) showed a significant difference in BRIEF scales from pre- to posttest (emotional control, p < .001), from pretest to follow-up (inhibit, p = .009; emotional control, p = .009; initiation, p = .001; plan-organize, p = .007; organization of materials, p = .01; monitoring, p = .009), and from posttest to follow-up (initiation, p = .02; plan-organize, p = .001).No significant differences at any time point were found in the BRIEF-SR GEC total score, F(2,30) = .89, p = .42, ηp2 = .06; BRIEF-SR BRI or MI score, F(4,28) = .97, p = .44, ηp2 = .12; or BRIEF-SR scales, F(8,16) = .58, p = .85, ηp2 = .37.COPM-Score Time ComparisonsAs shown in Table C, significant differences were found along the three time points in performance and satisfaction, respectively, F(2,36) = 52.59, p < .001, ηp2 = .74; F(2,36) = 35.72, p < .001, ηp2 = .66. The post hoc Bonferroni test (p < .05) identified a significant difference in performance and satisfaction from pre- to posttest (p < .001) and from pretest to follow-up (p < .001), but none from posttest to follow-up (p = ns).Table C Comparison of the Differences in All Outcome Measures, Pretest–Posttest–Follow-UpMeasureTime 1 BaselineTime 2 After treatmentTime 3 Follow-upF(2,74)ηp2pM (SD)M (SD)M (SD)BRIEF BRI67.34 (10.21)62.87 (8.93)61.47(8.92)12.69.25<.001 MI65.18 (7.06)63.45 (6.94)60.36 (7.32)16.28.31<.001 GEC67. 26(5.99)64. 34(5.84)61.74 (6.59)17.96.33<.001BRIEF subscale Inhibition61.02 (12.49)59.58 (10.66)57.02(10.88)5.42.13.006 Shift68.60 (11.24)64.63 (9.50)64.45 (9.25)4.12.10.020 Emotional control66.60 (12.72)60.13 (11.29)60.07 (9.99)9.48.20.001 Initiation62.29 (10.20)60.89 (9.37)55.58 (9.03)9.43.20<.001 Working memory66.05 (9.48)63.82 (7.64)63.24 (8.28)2.91.07.061 Plan/Org65.92 (9.00)65.21 (8.21)61.13 (8.14)9.42.20<.001 Organization of materials58.10 (8.66)56.58 (7.58)54.84 (9.16)4.36.10.016 Monitor61.26 (8.25)60.29(7.25)57.23 (7.55)4.67.11.012COPM Performance4.28 (1.54)6.60 (1.85)7.00 (1.35)52.00.58<.001 Satisfaction3.90 (2.04)6.99 (2.03)6.88 (1.50)39.33.51<.001DiscussionThis article described a pilot study to evaluate the effect of the FITTED intervention for adolescents with EFD profiles. The results show improved achievement of everyday life goals between pre- and postintervention. Participants maintained their achievements 3 months after the intervention, as evidenced by the finding of no significant differences between postintervention and follow-up scores. The BRIEF emotional control subscale showed significant postintervention improvements, and improvements at follow-up were seen in the MI plan-organize and initiation scales. Previous studies reported similar results, including improved EF components, even after the intervention, according to the BRIEF parent report (Gilboa & Helmer, 2020; Hahn-Markowitz et al., 2017).Chavez-Arana et al. (2018) suggested that the effect of challenging behavior on parents may explain why 50% of interventions for EFs target behavior regulation by teaching parents positive behavior supports. These techniques apply educational methods to broaden the behavioral repertoire and redesign the context (Carr & Sidener, 2002). Similarly, the FITTED program targets regulation by teaching these supports to parents through their presence and involvement during and after the intervention, which may explain our findings.The self-reported BRIEF scores showed no improvements in EF components between pre- and postintervention or follow-up. These results align with other studies that used adolescent self-reports. For example, the only significant changes reported by Dahlgren et al. (2014) after their Cognitive Remediation Therapy for young female adolescents with anorexia nervosa represented the shift subscale. Verbeken et al. (2018) found no significant interaction effect for the BRIEF-SR inhibit subscale after computer attention and inhibit training of children with obesity. Positive illusion bias may have influenced the lack of self-reported improvement after the FITTED program. Specifically, self-perceptions may be more biased than external evaluation criteria. Adolescents may embed this bias into their daily coping strategies as a self-defense mechanism against awareness of the pain that results from their difficulties (Hoza et al. 2012). Applied in our study, this explanation reinforces the need for interventions focused on achieving functional goals. Improved self-awareness of their abilities could decrease the need for adolescents to maintain defensive behavior that could lead to depression or low self-esteem. Partic

Review freeScoping Review of the Role of Occupational Therapy in the Treatment of Women With Postpartum Depression Skye P. Barbic, PhD, OT, ; , PhD, OT Kayla MacKirdy, MOT, ; , MOT Randi Weiss, MOT, ; , MOT Alyssa Barrie, MRSc, BScOT, ; , MRSc, BScOT Vanessa Kitchin, MLIS, ; and , MLIS Susan Lepin, EA, , EA Skye P. Barbic, PhD, OT , Kayla MacKirdy, MOT , Randi Weiss, MOT , Alyssa Barrie, MRSc, BScOT , Vanessa Kitchin, MLIS , and Susan Lepin, EA Published OnlineOctober 01, 2021https://doi.org/10.3928/24761222-20210921-02PDFAbstract ToolsAdd to favoritesDownload CitationsTrack CitationsCopy LTI LinkHTMLAbstractPDF ShareShare onFacebookTwitterLinkedInRedditEmail SectionsMoreAbstractBackground:Postpartum depression (PPD) can have a myriad of negative psychological and functional effects on mothers and their children. In Canada, most women who have PPD are either not diagnosed or not treated. Occupational therapists have the skill set to assess and treat women with PPD who experience psychosocial and functional challenges associated with motherhood.Goal:The goal of our study was to understand the current evidence supporting the role of occupational therapy to enhance the outcomes of women with PPD.Methods:We conducted a scoping review of the literature, searching the CINAHL, Ovid/MEDLINE, and PsycINFO databases from 1950 to March 2018 with a list of keywords identified by research, clinical, and context experts and an information librarian. We included all articles that specified occupational therapy intervention and/or occupation-focused interventions for women with PPD.Results:Our review identified 2,162 studies. After screening for inclusion and exclusion criteria, 14 studies were reviewed. Three themes concerning the role of occupational therapy for women with PPD were identified: (a) supporting occupational disruption and transitions, (b) managing the experience of motherhood in the context of depression, and (c) value added of occupational therapy to current PPD best practices.Conclusion:Considering the negative experiences and health risks associated with PPD, there is a need for client-centered assessments and interventions that focus on the needs and priorities of mothers. Given the broad challenges that can be associated with new motherhood, occupational therapists can have a clear role in developing an evidence base to support expansion of the profession into this field to optimize the well-being of new mothers. [Annals of International Occupational Therapy. 2021;4(4):e249–e259.]IntroductionPostpartum depression (PPD) is a nonpsychotic type of depression that occurs among mothers up to 1 year after childbirth (Stewart et al., 2003). The World Health Organization (WHO) reports that PPD and other mental illnesses experienced by women as a result of pregnancy and childbirth affect approximately 10% of women during pregnancy and 13% of women postpartum (WHO, 2017). It is estimated that 26% to 84% of women experience mild depressive symptoms after childbirth (Beck et al., 2006; O'Hara et al., 1991). This experience is popularly referred to as the "baby blues." The estimated prevalence has a wide range because no accepted set of criteria for the baby blues has been established (O'Hara & Wisner, 2014). The baby blues can evolve into PPD, with symptoms that may include feelings of anxiety and/or shame, a negative outlook on motherhood, and a lack of self-efficacy (Goodman, 2004; Lanes et al., 2011). Despite these symptoms, in Canada, PPD is commonly undiagnosed (Sharma & Sharma, 2012) and undertreated (Kennedy et al., 2002; Zauderer, 2009). The high number of undiagnosed women is problematic because PPD can be associated with harmful, long-term, and potentially devastating consequences for the mother, child, and family (Murray et al., 1996; O'Hara & McCabe, 2013; Sharma & Sharma, 2012; Stewart et al., 2003). Early identification of PPD and increased integration of coordinated mental health services are needed to support the full range of needs of women who are affected.Risk factors for PPD include mild depressive symptoms, antenatal depression and/or anxiety, limited social supports, low socioeconomic status, and former depressive episodes (Hannah et al., 1992; Henshaw et al., 2004; Kennedy et al., 2002; Lanes et al., 2011; Robertson et al., 2004; Sharma & Sharma, 2012; Stewart et al., 2003; Underwood et al., 2016). However, these factors explain only approximately 30% of the risk variance for PPD (Underwood et al., 2016). Other risk factors include premature birth, birth trauma (e.g., preeclampsia), the experience of infertility, teenage motherhood, recent immigration, and health challenges for the newborn (Falah-Hassani et al., 2015; Gold et al., 2013; Robertson et al., 2004; Seven & Akyuz, 2015; Silverman et al., 2017). The needs of this population are unique and have been shown to be common across cultures (Bloch et al., 2005; Dennis et al., 2004). Opportunity exists to work closely with this population to tailor accessible interventions that are responsive to the needs of women experiencing PPD. One profession that may have an important role is occupational therapy.Occupational therapy helps individuals to solve the problems that interfere with their ability to do the things that are important to them and to achieve health and well-being through participation (Canadian Association of Occupational Therapists [CAOT], 2016). Occupational therapists are trained to address difficulties associated with role transitions, including the transition to parenting a newborn (George, 2011). This training includes making adaptations during life transitions, identifying resources, and enhancing a sense of coherence, self-compassion, and resilience. Commonly reported experiences during this transition include significant disruptions to a mother's sense of self and occupational balance (Horne et al., 2005; Slootjes et al., 2016). For PPD, this imbalance has been shown to be associated with a decrease in well-being of the mother and her family (Ruble et al., 1990; Slootjes et al., 2016), including the quality of the relationship and support from a new mother's partner (Burke, 2003; Clout & Brown, 2016; Yim et al., 2015). Because PPD can affect the entire family and social unit, effective diagnostic methods and treatments are needed to ensure the health and well-being of all involved.Various options for the treatment of PPD are available, and the most common is pharmaceutical intervention (Leitch, 2002). Nonpharmaceutical interventions, such as nondirective counseling and cognitive behavioral therapy, are increasingly being used (Alderdice et al., 2013; Bowen et al., 2012; Dennis & Dowswell, 2013), with evidence showing that these interventions may help mothers to address and cope with the drastic life changes early in the postpartum period (Dennis & Hodnett, 2007; Grigoriadis & Ravitz, 2007; O'Hara, 2009; O'Hara et al., 2000). However, limited evidence is available on the explicit role of occupational therapists in delivering these types of interventions. We hypothesize that the concept of occupation may provide a therapeutic focus for the treatment of PPD. Occupational therapists are trained to consider numerous aspects of a person's functioning and can offer a depth of therapy to address the complexities of PPD. Therefore, increasing the evidence base for occupational therapy interventions for this population is crucial because occupational therapists may profoundly improve treatment outcomes for women and their circles of care (O'Hara, 2009; Slootjes et al., 2016). Our goal is to describe the literature on the role of occupational therapy in addressing the needs of mothers with PPD.MethodsWe selected a scoping review as the most appropriate approach to explore this broad topic. The approach was informed by Arksey and O'Malley's (2005) seminal methodological framework for scoping studies. This framework has five steps: (a) identifying the research question, (b) identifying relevant studies, (c) performing study selection, (d) charting the data, and (e) collating, summarizing, and reporting the results.We included an additional step: establishing trustworthiness of our findings to validate the results with experts—one occupational therapist who specializes in working with families in the perinatal period and two patient partners with lived experience of PPD.Identifying the Research QuestionWe began our pursuit of the role of occupational therapy with new mothers experiencing PPD. However, we recognize that this area is emerging, and there is a need to focus on the effect of PPD on the entire circle of care. After consultations with expert occupational therapists whose main focus is women's health, the primary question we used to direct this scoping review was the following: What is the role of occupational therapy as a health intervention to improve health and quality of life outcomes in women diagnosed with PPD?Identifying Relevant StudiesOur search was revised after undergoing a peer review with PRESS (Peer Review of Electronic Search Strategies). The search strategy was designed by a University of British Columbia research librarian whose subject specialty includes occupational therapy. We searched peer-reviewed journals published in any year from the following databases: CINAHL on EBSCO, Ovid/MEDLINE, and PsycINFO on EBSCO. The original and revised search strategy for each database is listed in Table A. Grey literature (i.e., thesis dissertations, reports, white papers) was accessed through Google Scholar, Grey Matters, desLibris, and ProQuest Dissertations and Theses. We also manually searched the reference lists of studies that met our criteria for inclusion and examined suggested related articles within the online journals. We used broad search terms to capture articles that fell within the lens of occupational therapy but did not directly specify occupational therapy. Because of the frequent comorbidity of depression, anxiety, and other mental health challenges, we included a variety of search terms related to these mental health issues to ensure that we captured all relevant articles. Search terms were created after consultation with practitioners who had experience caring for women with PPD and were included in the terms listed in Table A.Table A. Original search strategy and peer-reviewed search strategyOriginal search - resulting in 1,731 resultsRevised search - resulting in 431 novel resultsPPD OR postnatal depression OR maternal depression OR maternal mental health OR postpartum depression OR prenatal mental health OR perinatal mental health OR prenatal depression OR antenatal depression OR baby blues OR postpartum blues OR postpartum anxiety OR antenatal anxiety OR perinatal mood disorder OR perinatal anxiety disorder OR postpartum psychosis OR maternity blues OR PPA OR prenatal anxiety OR postpartum anxiety disorder AND occupational therapy OR occupational therap* OR OT OR occupation AND motivation OR values OR interests OR role OR routine OR social environment* OR cultural environment* OR political environment* OR institutional environment* OR physical environment* OR participation OR performance OR skill* OR identit* OR adapt* OR activit* OR participation OR self care OR communit* OR social OR recreation OR leisure OR spiritualit* OR support* OR relationship* OR ADL* OR activities of daily living OR rehabilitation.Postpartum Depression OR (postpartum or maternal or perinatal or prenatal or antenatal or postnatal or puerperal) adj3 depress*) OR (postpartum or maternal or perinatal or prenatal or antenatal or postnatal or puerperal) adj3 anxiety) OR (postpartum or maternal or perinatal or prenatal or antenatal or postnatal or puerperal) adj3 mental health OR (postpartum or maternal or perinatal or prenatal or antenatal or postnatal or puerperal) adj3 anxiety disorder*) OR (postpartum or maternal or perinatal or prenatal or antenatal or postnatal or puerperal) adj3 mood disorder*) OR (baby or postpartum or maternal) adj2 blues OR PPD OR PPA AND Occupational Therapy OR occupational therap* OR OT OR occupation* AND Self Care OR Rehabilitation OR (motivation or values or interest* or role* or routine*) OR (cultural or social or political or institutional or physical ad2 environment) OR (participation or performance or skill* or identit* or adapt*) OR "Activities of Daily Living" OR activities of daily living OR ADL OR (activit* or participation or self-care or self care or communit* or social or recreation or leisure or spirituality or support or relationship*)Study SelectionWe followed a two-stage process for study screening and selection with a piloted screening checklist. First, two research team members (K.M., R.W.) independently screened the titles and abstracts of the search results to determine whether each citation met the inclusion criteria. We included any article that discussed PPD, occupational therapy, occupational disruptions, and/or mental health and then reviewed electronic copies of article titles and abstracts and highlighted relevant titles.Next, these same research team members independently read full-text versions of potentially relevant citations with reference to predetermined criteria for inclusion and exclusion. The articles were divided into two categories: (1) articles that explicitly described occupational therapy interventions with women with PPD and (2) articles that explicitly discussed occupational disruption among women with PPD (with no specific mention of occupational therapy) and psychosocial rehabilitation interventions. Discrepancies between the two reviewers were resolved through consensus by discussion with the senior research team member (S.P.B.). We used the following inclusion criteria: peer-reviewed journals, books, or grey literature (e.g.., doctoral theses, technical reports, white papers) published in English and literature focused on research participants identified as birth mothers experiencing PPD and interventions (either occupational therapy or occupation related) focused on this target population. Our search included articles that involved occupational therapy and articles that included some indication that the content could reasonably fall within the scope of occupational therapy (e.g., discussion of functioning, groups, or self-care).Charting the DataWe recorded information from the full-text review in a data extraction table (Table B) that included the following study information: author(s), year, journal, country, study type, type of mental health challenge (e.g., antenatal, post-natal, both), recommendations, and explicit mention of occupational therapy. The review team identified the principal themes that emerged from the literature, summarized the themes, and used thematic analysis to collate the findings. Specifically, we familiarized ourselves with the literature; coded the included articles; generated, reviewed, and named themes; and presented the findings (Braun & Clarke, 2006).Table B. Data and recommendations extracted from scoping review (n=14)Study (author, year)JournalCountryStudy typeAnte/post/bothRecommendationsOccupational Therapy explicitly specifiedBarkin, et al., 2010Journal of Women's HealthUSAQualitativePostCreate new measure of maternal functioningNoBarkin & Wisner, 2013MidwiferyUSAQualitativePostDevelop new needs assessments and interventions for self-careNoByatt et al., 2012Journal of Reproductive & Infant PsychologyUSAQualitativePostBetter training and more resources provided to health care professionals to improve mental health care servicesNoCassar, 2005World Federation of Occupational Therapists BulletinMaltaQualitativeBothAssessments, home visits, activities of daily living schedules, relaxation techniquesYesFisher, Feekery, & Rowe, 2004Archive Women's Mental HealthAustraliaMixed-methods follow-upPostPsychoeducational groups and emphasis on social support to increase maternal moodNoGao, Xie, Yang, & Chan, 2015International Journal of Nursing StudiesChinaRCTPostIncorporate the principles of Interpersonal Psychotherapy into postnatal careNoHamilton-Dodd, Kawamoto, Clark, Burke, & Fanchiang, 1989American Journal of Occupational TherapyUSAQuasi-experimental pilot studyPostProvide education to mothers on physiological changes, management of activities of daily living, and infant developmentYesHorne, Corr & Earle, 2005Journal of Occupational ScienceUKSmall-scale exploratory studyPostRecognition that mothers may experience difficulty in the transition to becoming a mother due to changes in their occupationsYesMorris, 1987British Journal of Medical PsychologyUKQualitativePostProvision of group psychotherapy for treatment of women with PPDYesOlson, 2006Occupational Therapy in Mental HealthUSAQualitativePostUse CBT to build confidence, create coping skills, change expectations around interactions with the child. Do home visits. Encourage co-occupations between child and motherYesPitonyak, 2014American Journal of Occupational TherapyUSAExpert opinionPostOccupational therapists to assist clients in developing routines to support breastfeeding, address barriers to breastfeeding, provide education about breastfeeding, encouraging safe postures for breastfeedingYesSlootjes, McKinstry, Kenney, 2015Australian Journal of Occupational TherapyAustraliaExpert opinionPostAssessments, environmental adaptations, and assistive equipment prescriptions for ergonomic support. Assisting mothers to return to former occupations through: assessment of function, advocating for workplace accommodations, and adaptations.YesUgarriza & Schmidt, 2006Journal of Psychosocial Nursing Services and Mental Health ServicesUSAPilot study, pretest/posttest designPostCognitive behavioural therapy, relaxation strategies, and education about the illnessNoWalczak & Passmore, 2011Australian Journal of Occupational TherapyAustraliaQuasi-experimental pre-post followup designPostOccupational therapy-led group mindfulness trainingYesConsultationCanada's Strategy for Patient-Oriented Research (2016) and Levac et al. (2010) contend that consultation is a vital step in ensuring that scoping review research is both rigorous and useful. Expert occupational therapists who specialize in working with women with PPD were consulted to develop and refine our research question. After we extracted the data from the scoping review, we consulted with one peer partner (S.L.) to validate the findings and elaborate on gaps that were not identified in the search.ResultsAs shown in Figure 1, the search yielded 2,162 results. A total of 127 articles remained after initial review of the title or abstract. After full-text review, we identified 14 articles that met the inclusion criteria. The included studies were published between 1987 and 2016 and were completed in the United States (n = 7), Australia (n = 3), the United Kingdom (n = 2), Malta (n = 1), and China (n = 1).Figure 1. PRISMA diagram. RCT= randomized controlled trial.Scope of Occupational Therapy Interventions for Women With PPDOf the 14 articles reviewed, we found 8 articles that specifically mentioned occupational therapy interventions. Of these studies, five were qualitative and the other three had relatively low levels of evidence (e.g., pilot studies). Sample sizes ranged from 1 to 16. The following key themes emerged from these eight studies (Table B). Six articles focused on the population and interventions that were within the scope of occupational therapy. Three of the studies were qualitative, and the remaining three varied in levels of evidence, ranging from a randomized controlled trial to studies that used a pretest-posttest design without control groups. Sample sizes ranged from 20 to 180. Three themes emerged: (a) supporting occupational disruption and transitions, (b) managing the experience of motherhood in the context of depression, and (c) enhancing the value added of occupational therapy to existing treatment best practices.Theme 1: Supporting Occupational Disruption and TransitionsMost articles from our review discussed the occupational changes that new mothers often experience when transitioning into motherhood. All articles emphasized that occupational disruption was a normal experience for new mothers, but for mothers with PPD, symptoms of depression could significantly affect the ability to participate in meaningful roles and activities. All articles emphasized that all women are unique and require different treatment, depending on the context, type of PPD, severity of symptoms, goals for care, and resources. Eight articles specifically discussed the value of adding occupational therapy to support women's health, specifically, with therapeutic techniques that address the intersection of health impairment and occupational disruption (Cassar, 2005; Hamilton-Dodd et al., 1989; Horne et al., 2005; Morris, 1987; Olson, 2006; Pitonyak, 2014, Slootjes et al., 2016). Six other articles (Barkin et al., 2010; Barkin & Wisner, 2013; Byatt et al., 2012; Fisher et al., 2004; Gao et al., 2015) described a need to complement medical and pharmacological best practices with psychosocial interventions to support care in the context of what is important to the mother and her circle of care (i.e., other parent, support network, workplace).Cassar (2005) outlined the role of the occupational therapist in helping new mothers to balance the variety of occupations, occupational disruption, and transition into new roles expected through creating a schedule of their activities of daily living. In a qualitative descriptive study of an occupational therapy program from Malta, Cassar (2005) summarized the role of occupational therapists in assisting mothers with PPD through community support, assessment of function, and specific goals for time use and occupational balance. A qualitative study by Barkin and Wisner (2013) similarly detailed the role of psychosocial rehabilitation approaches to support challenges that new mothers (n = 31) had with finding time for self-care occupations (although many of the participants recognized the importance of these activities). Examples included finding time to eat, take a shower, or pursue leisure activities. A small-scale exploratory study (n = 6) by Horne et al. (2005) found that women with PPD reported that they struggled to reengage in occupations that they had previously valued, such as self-care (e.g., showering, sleeping), leisure (e.g., spending time with friends, going to a movie), and productivity (e.g., continuing to work at a paid position, volunteering, and/or attending school). Horne et al. (2005) identified a need for timely access to occupational therapy for women with PPD to support occupational balance, explore new occupations, and return to past occupations. Slootjes et al. (2016) also described a critical upstream role for occupational therapists to provide comprehensive assessments of functioning and risk, which are contextualized based on the needs of the mother and the resources, environment, and societal expectations.Slootjes et al. (2016) and others (Barkin et al., 2010; Cassar, 2005; Pitonyak, 2014) highlighted the need to create functional, clinically meaningful, and accessible assessments to address key components of maternal mental health for women with PPD. Barkin et al. (2010) completed qualitative research with three focus groups, "each comprised of 10 or 11 women" (p. 1494). Within each focus group, the lack of screening assessments for new mothers' functioning was emphasized. Legacy generalized measures (e.g., assessments for generalized depression) were seen as a barrier for some mothers with PPD. Later work by Barkin and Wisner (2013) described the need for an assessment to examine the mother's well-being over time to monitor changes in the progress or effectiveness of interventions in the context of dynamic roles and respect for culture and social determinants of health.Our review also found articles that emphasized the importance of home visits and assessment by occupational therapists (Cassar, 2005; Olson, 2006). For example, in a qualitative descriptive study by Cassar (2005), occupational therapists in Malta were allocated to a specific program to work with women with PPD in the community. The author reported "positive qualitative results" (p. 37) in terms of reduced reliance on pharmaceuticals and improved functioning among those who received an occupational therapy intervention. Interventions included home visits by an occupational therapist to assess the physical and social environment and determine barriers or stressors that could affect the mother's ability to perform her occupations in early motherhood. However, the only reported support for this finding was the narrative of one client's positive experience with the program. Another descriptive case study (n = 1) by Olson (2006) found that home visits are important for occupational engagement in this population. Olson (2006) argued that home visits are beneficial because the occupational therapist can ensure that the environment is both safe and optimized for the mother to manage her daily activities.Theme 2: Managing the Experience of Motherhood in the Context of DepressionAll articles in our review described productive (i.e., breastfeeding, structuring of routine, returning to work), emotional (e.g., reduced self-esteem, decreased confidence, limited mastery), and physical (e.g., pain) issues that occupational therapists address with this population.Subtheme: Breastfeeding as an OccupationOur review found two articles that described breast-feeding as within "the domain of occupational therapists" because of involvement of activities of daily living, feeding, and eating (Pitonyak, 2014). One expert opinion article specifically discussed the role that occupational therapists can play in addressing the challenges (e.g., role satisfaction, self-esteem) that many new mothers face with breastfeeding (e.g., low milk supply, workplace support). Breastfeeding was described as a meaningful co-occupation. Pitonyak (2014) argued that many mothers and babies need assistance to resolve difficulties with breast-feeding to reduce the risk of PPD and suggested roles for occupational therapists to enable new mothers to balance breastfeeding with other occupations (e.g., self-care, productivity, leisure) through developing routines, addressing social and/or physical environment barriers, and making breastfeeding ergonomically safe.Subtheme: Ergonomic Interventions to Support OccupationsOur review also showed a role for occupational therapists in preventing injury or pain and aiding recovery after childbirth through the use of ergonomics. One expert opinion article by Slootjes et al. (2016) noted that, without ergonomic supports, new mothers are at risk for "back pain, carpal tunnel syndrome, and repetitive strain injuries" (p. 132). Our review often cited research on associated pain and the severity of symptoms of PPD (Angelo et al., 2014). One article described the important role of occupational therapy expertise with ergonomics to minimize or prevent physical injury or assist in recovery (Slootjes et al., 2016). Slootjes et al. (2016) specifically recommended timely ergonomic assessment, early education, environmental adaptations, and prescriptions for assistive equipment to support mothers with PPD who also may experience pain. All studies emphasized early intervention and integration of occupational therapy with multidisciplinary community support services, such as primary care or nursing, if possible.Subtheme: Psychosocial Interventions to Support Occupational EngagementOur review also showed roles for occupational therapists in supporting occupational balance and emotional well-being through psychoeducation, psychotherapy, mindfulness, and relaxation (Hamilton-Dodd et al., 1989; Olson, 2006; Ugarriza & Schmidt, 2006).Hamilton-Dodd et al. (1989) completed a quasi-experimental pilot study (n = 16) that described a four-session "maternal preparation program" for women at risk for PPD that started 1 month before birth and lasted 2 to 3 weeks after birth. The intervention was led by three occupational therapists who focused on providing education about the physical changes that new mothers could expect, developing strategies for how to carry out activities of daily living associated with being a new mother (e.g., simplification, time management, energy conservation), and designing individualized exercise programs. Mothers who participated in the program reported high satisfaction, but limited information was provided about the immediate and long-term effects on participants.Several studies described the use of diverse psychotherapeutic frames of reference to guide interventions for psychosocial issues among this population (Morris, 1987; Ugarriza & Schmidt, 2006). Two studies (Olson, 2006; Ugarriza & Schmidt, 2006) described how occupational therapists can use cognitive behavioral techniques to support women with PPD to promote infant-parent engagement, improve participation in daily activities with the infant, develop coping skills, and support the reframing of expectations around interactions with the child. Through initiating co-occupations, such as play, Olson (2006) argued that occupational therapists can use cognitive behavioral techniques to assist the mother in changing her beliefs regarding her ability to interact with the child positively.Two studies focused on the positive effect of occupational therapy-led mindfulness training, guided by a cognitive behavioral frame of reference, to help women experiencing PPD and/or perinatal anxiety. Walczak and Passmore (2011) used a quasi-experimental pre-test-post-test follow-up design (n = 13) and found that occupational therapy-led group mindfulness training was an effective method to help women to regulate their thinking and emotions during their activities

Date Presented 04/04/19 Many symptoms of young adults with multiple sclerosis (MS) affect their age appropriate milestones, such as education, family, and vocational planning. This dissertation study shows how fine-motor skills of young adults with MS (YAwMS) play a role in their occupational performance as they attempt to achieve planned life goals. This mixed-method study addresses how the quantitative results of the study support the qualitative findings through cross-case comparison and merged findings. Primary Author and Speaker: Mary Squillace