Feasibility trial evaluation of a physical activity and screen-viewing course for parents of 6 to 8 year-old children: Teamplay
© Jago et al; licensee BioMed Central Ltd. 2013
Received: 22 October 2012
Accepted: 20 February 2013
Published: 4 March 2013
Many children spend too much time screen-viewing (watching TV, surfing the internet and playing video games) and do not meet physical activity (PA) guidelines. Parents are important influences on children’s PA and screen-viewing (SV). There is a shortage of parent-focused interventions to change children’s PA and SV.
Teamplay was a two arm individualized randomized controlled feasibility trial. Participants were parents of 6–8 year old children. Intervention participants were invited to attend an eight week parenting program with each session lasting 2 hours. Children and parents wore an accelerometer for seven days and minutes of moderate-to-vigorous intensity PA (MVPA) were derived. Parents were also asked to report the average number of hours per day that both they and the target child spent watching TV. Measures were assessed at baseline (time 0) at the end of the intervention (week 8) and 2 months after the intervention had ended (week 16).
There were 75 participants who provided consent and were randomized but 27 participants withdrew post-randomization. Children in the intervention group engaged in 2.6 fewer minutes of weekday MVPA at Time 1 but engaged in 11 more minutes of weekend MVPA. At Time 1 the intervention parents engaged in 9 more minutes of weekday MVPA and 13 more minutes of weekend MVPA. The proportion of children in the intervention group watching ≥ 2 hours per day of TV on weekend days decreased after the intervention (time 0 = 76%, time 1 = 39%, time 2 = 50%), while the control group proportion increased slightly (79%, 86% and 87%). Parental weekday TV watching decreased in both groups. In post-study interviews many mothers reported problems associated with wearing the accelerometers. In terms of a future full-scale trial, a sample of between 80 and 340 families would be needed to detect a mean difference of 10-minutes of weekend MVPA.
Teamplay is a promising parenting program in an under-researched area. The intervention was acceptable to parents, and all elements of the study protocol were successfully completed. Simple changes to the trial protocol could result in more complete data collection and study engagement.
Physical activity (PA) is associated with lower levels of many risk factors among children including lipid levels [1, 2], blood pressure [1, 2] and body mass [3, 4]. Screen-viewing (SV), (e.g., watching television, playing video games and surfing the internet), is associated with an increased risk of heart disease  and obesity . Many children exceed recommended hours of SV [6–8] and do not engage in sufficient amounts of PA [9, 10]. The early school years (6–8 years of age) are a key period when children’s PA and SV behaviors are established . A number of systematic reviews have indicated that currently there are only a limited number of effective interventions to change children’s physical activity  or prevent obesity via increased PA [12–15] highlighting a need for new, more effective approaches.
The majority of interventions that have attempted to increase children’s PA or reduce their SV have been delivered during curriculum time at school and have required manipulation of physical education provision, or involved educational components that are designed to increase children’s ability to change their behavior [11, 12]. However, a number of systematic reviews and meta-analyses have shown that PA / SV interventions delivered within the school setting have reported null, weak or inconsistent effects [11, 12]. Where interventions were successful, they tended to use several different intervention strategies . As such, non-school approaches that utilize multiple intervention strategies need to be investigated .
Parents provide key socializing influences on their children’s PA  with parental support for PA being strongest before children’s transition to adolescence . Parental PA facilitation (i.e., providing access, financial and transportation forms of PA support) is positively associated with objectively-assessed PA [18, 19] among children. In addition, parental restriction of SV is associated with lower child SV . Efforts to empower parents with the knowledge, skills, resources and support to facilitate active lifestyles among their children are warranted.
Although it has been argued that PA and SV are distinct behaviors  and that change in one behavior does not necessarily affect the other, it is important to recognize that reducing SV time can make more time in which it is possible to engage in PA. Reducing SV and increasing PA together also offers contextually compatible targets, which allow families to tailor behavior change interventions to their own requirements. Providing separate interventions for each would not be pragmatic in the public health context, whereas addressing both has the potential to increase effectiveness. There is, however, a shortage of research focusing on how parents can help their children engage in more PA and less SV. A systematic review of PA interventions found only four family-based studies that met the study inclusion criteria and as such there is insufficient evidence to draw conclusions on the utility of this approach . As all four studies were conducted in the US and three focused exclusively on children from minority ethnic groups, the extent to which their findings are applicable to other countries and population groups may be limited. Furthermore, a review of multiple-component interventions to increase PA also highlights the absence of parent engagement in current approaches . No study was found involving working directly with families, and parent engagement was restricted to newsletters home or the occasional parent evening. This lack of research is surprising as group-based parenting program interventions have been shown to be successful in engaging parents in providing support for behavior change in their children . For example, Golan and colleagues have shown that interventions involving parents have been successful in childhood obesity treatment [24–28]. To date, no study has developed a parenting intervention to increase PA and reduce SV for non-obese children.
Behavior change interventions that have been based on psychological theory tend to be more successful than those that have not . As well as improving impact, theory also supports evaluation design by assisting with the identification of key mediators of behavior change . From an intervention perspective, self-determination theory (SDT) focuses on fostering autonomous (voluntary) types of motivation and feelings of competence, autonomy and belonging . Previous research has found associations between these factors and self-reported exercise behavior and pedometer counts in children and adolescents [31, 32] and as such, SDT could provide a useful basis for intervention. As SDT [30, 33] addresses the role of social agents in fostering people’s motivation it may be particularly appropriate for working with parents to help their children feel more physically competent and build motivation in children for increased PA and reduced SV behaviors.
Develop an intervention, an intervention manual, and resources for a group parenting program to promote increased PA and decreased SV in children.
Assess the feasibility of recruiting and retaining parents of 6–8 year old children to a PA/SV parenting program.
Examine the feasibility of collecting accelerometer data from children of this age and their parents.
Examine the potential change in MVPA and SV as a result of participating in the intervention and the potential future effect size.
Conduct post-intervention qualitative work to identify any factors that affect the measurement processes.
Provide the necessary information to calculate the sample size for an adequately powered RCT evaluation of the Teamplay intervention.
A two arm individualized randomized controlled feasibility trial was used to evaluate the Teamplay intervention. Participants were parents with at least one child aged 6–8 years recruited from two neighboring wards in Bristol (UK). One ward was selected from the lowest and one from the middle tertiles of deprivation according to the index of multiple deprivation (IMD)  for the city of Bristol in order to sample approximate low and middle socioeconomic status areas of the city. The study was approved by a University of Bristol ethics committee. Participants were informed about the study in writing and in person, and written informed consent was obtained for all participants.
Participants were recruited via leaflets and advertisements that were distributed across the community in coffee shops, children’s centers, play groups, school playgrounds and community centers and face-to-face in schools and community centers. Based on our extensive formative research [35, 36], the recruitment materials promoted a ‘Free 8-week course for parents’ which had the tag line “less stress, more fun in family life”. These materials focused on the parenting aspects of the course which many of the participants mentioned to the intervention staff as a key reason for joining the course. Moreover, to ensure that the course appealed to all parents, and not only parents of overweight or obese children the intervention materials focused on focused on having fun through physical activity and did not mention obesity or other health-related conditions. Parents were invited to meet the study team at an informal coffee morning at their child’s school or local community venue or to contact the study team by telephone. At these meetings parents were provided with information about the interventions and study procedures (including data collection and the randomization procedure). Parents were also asked to indicate if they would like to attend either a morning course (with free childcare) or an evening course (no childcare provided). Participants who consented to take part were randomized, within their chosen course preference to the intervention or control arm by an independent statistician with no other involvement in the study, using computer-generated random sequences.
Description of intervention and control groups
Participants assigned to the intervention arm were invited to attend an eight week parenting program held in one of three local community centers. Parents attended without their children and each weekly session lasted two hours. The program was scheduled to coincide with school holiday periods with 4 weeks of content running before and after the primary school half term (a week long break in the middle of a school semester). To maximize opportunities for participants to attend, three programs were run, two during the day (for which a crèche was provided) and another during the evening. The control group received no additional input during the period of the intervention, but was provided with written materials summarizing the intervention content at the end of the study.
Intervention development and delivery
The intervention content was informed by conducting in depth interviews with parents who reflected the intended user group  and an advisory group consisting of local council and parent-group representatives to help gather expert input and real life experiences which could be utilized in the intervention. The intervention was developed by the project team. As the intervention was focused on using the principles of SDT, we also drew on the SDT and educational experience of KRF and SJS. SDT helped to influence the development of material appropriate for children aged 6–8 years and informed the content on using active play to build autonomous motivation, confidence, and competence for increasing PA and reducing SV. The parenting aspects of the intervention were developed by project staff in consultation with members of Family Links, a UK parenting charity that trains professionals to run a parenting program (the Nurturing Program). Parenting aspects were aligned with SDT to encourage parents to use autonomy-supportive rather than controlling parenting strategies . The content drew heavily on our formative research with parents which examined key issues that affected parental PA and SV behaviors, how these issues could be addressed and possible ways of structuring and delivering a group-based PA and SV parenting intervention [35, 37].
Intended learning outcomes and content for the eight intervention sessions
Intended learning outcomes
Introduction to Teamplay
• Introduce parents to the Teamplay course and create a safe, enjoyable and respectful environment
PA: What is it & why is it important?
• Help parents to identify/understand the benefits of PA
Physical activity recommendations
• Help parents to develop an understanding of what physical activity is.
• Introduce the value and importance of Active Play and support parents in identifying play ideas
• Introduce praise and facilitating the learning of effective use of praise
Praise and criticism
• Help parents to recognize feelings surrounding praise and criticism and the impact upon behavior
• Help parents look at SV in their household and identifying the pros and cons
• Introduce strategies and tools to help parents to reduce SV
Boundaries and consistency
• Introduce concepts of boundaries and consistency
Increasing ‘Inner motivation’
• Introduce parents to ‘Inner Motivation’, and top tips to encourage children’s inner motivation
• Support parents to implement a family agreement for behaviors such as reducing SV
• Help parents discover local activities that could contribute to their child’s PA
• Understand the impact of expectations on self-esteem and behavior
Helping children grow up
• Support parents in offering an empowering environment for their child
Supporting children’s PA
• Support parents to discover ways to promote a fun and enjoyable PA environment
• Introduce key movement skills for PA and provide practical ideas to support their development
• Help parents support their child to experience success in PA through adapting activities
• Help parents to use personal power to make healthy choices and support their child to do the same
• Help parents understand the relationship between personal power, choices and self-esteem
• Introduce the idea that PA can help improve self esteem
Choices and consequences
• Introduce choices and consequences as a useful tool to reduce conflict
• Provide tools for parents and children to help communicate feelings
Nurturing and downtime
• Create an understanding of the importance of looking after oneself
Problem solving and negotiating
• Introduce problem solving and negotiation to help improve communication and reduce conflict
Summing up: useful tools
• Recap parenting tools and useful ways that they can be used
Summing up: getting active
• Reaffirm the benefits and importance of PA and the ways in which it may be increased
Continuing your journey
• Establish a family PA goal and signpost parents to more information and further support
Baseline and follow-up measures
All measures were assessed at baseline (time 0) at the end of the intervention (time 1, week 8) and 2 months after the intervention had ended (time 2, week 16). The final assessment was designed to provide an indication of any long term effect of the intervention.
Parental employment status, parental ethnicity, parental gender and child age were assessed by parental report at baseline. Participant postcode was used to derive the Index of Multiple Deprivation (IMD) score for the home address. The IMD is an area level measure of deprivation that includes income, health, educational and employment status  with higher scores indicating higher levels of deprivation i.e. lower socioeconomic status (SES). Since the likely primary outcome of a full scale trial would be MVPA using accelerometer data, we assessed the feasibility of collecting accelerometer data (Aim 3) and the observed change in MVPA following participation in the intervention (Aim 4). All children and parents were asked to wear an Actigraph accelerometer (Model GT1M; ActiGraph LLC, FL, USA) for seven days at each time point. The Actigraphs were set to record data every 10 seconds. Periods of ≥60 minutes of zero values were defined as accelerometer “non-wear” time and discarded. Participants were included in the analysis if they provided ≥1 day of data with at least 480 minutes of data between 6 am and 11 pm. A cut-point of ≥2296 counts per minute  was used to identify mean minutes of weekday and weekend MVPA for the children. A cut-point of ≥2019 was used to categorize the parent activity data as MVPA .
Using a validated scale, parents were also asked to report the average number of hours per day that both they and the target child spent watching television. The assessment of TV viewing via a single question has been shown to correlate (r = 0.60) with 10 days of TV diaries among young children . Parent and child TV viewing on weekday and weekend days at all three time points was categorized as < 2 hours per day, or ≥ 2 hours per day, corresponding to thresholds suggested by the American Academy of Pediatrics (AAP) TV viewing guidelines for children of 2 hours per day [41, 42]. The UK does not have agreed SV thresholds .
Attendance and post-study qualitative work
Attendance was recorded at each session (Aim 2). Intervention and control group participants who had initially provided consent to take part in an interview were randomly selected to be telephoned to see if they were still willing to take part. Parents were telephoned and interviews carried out until saturation had been met for intervention and control groups. A total of 16 interviews were conducted with intervention participants while 10 interviews were conducted with control participants. Interviews with intervention participants were conducted by a researcher who was independent of Teamplay. The interviews focused on thoughts about the data collection process, particularly how it could be improved and any factors that affected the wearing of the accelerometers. All interviews were recorded and transcribed.
We used appropriate descriptive statistics (frequencies, percentages, means, standard deviations) to describe the recruitment and attendance data. Linear regression models were used to compare differences in means and 95% CI between the trial groups at follow up for the PA variables, adjusted for baseline PA. As the data are from a feasibility trial and we are not powered to detect a difference between groups, p-values are not reported. For descriptive purposes we also graphically presented the proportion of children and parents that met or exceeded the AAP TV viewing guidelines.
Sample size calculations to detect a 10 minute difference in child weekend day moderate-to-vigorous physical activity between intervention and control groups
N required per group
Total N required for analysis
Total N inflated for attrition
Total N rounded and based on 10 participants per course group
Number of intervention groups$
Number of control groups$
Analysis aimed at identifying factors that affected data completion rates, namely: 1) perceptions of the data collection process; 2) reasons for not wearing the accelerometers; and 3) strategies to improve data completion. Data were analyzed thematically to enable the exploration of accounts relating to these specific areas of interest. Transcripts were read and re-read by different members of the research team and a coding frame developed based on the themes identified. Using NVivo (Version 9, QSR, Southport, UK), meaningful content was coded and retrieved electronically, and then summarized to enable comparisons to be made within and across the interviews . Quotes that were deemed to best represent the nature of each theme were then extracted.
There were 75 participants who provided consent and were randomized (Additional file 1: Figure SA). Twenty-seven participants withdrew post randomization. Of these, 7 intervention and 6 control group participants failed to attend or respond to contact attempts for baseline data collection, 6 participants withdrew once they’d been assigned to the control group, and 8 intervention group participants could not attend the course because of logistical issues (e.g. having an unwell child or a new baby). As a result, 25 participants allocated to the intervention group and 23 allocated to the control group provided baseline data. Some data were provided by 23 intervention and 15 control group participants at first follow up, and by 22 intervention and 11 control group participants at the second follow-up. Three intervention and 12 control group participants dropped out of the study during follow-up stages; 9 because of lost contact, 3 because they no longer wanted to take part in the study, and 3 because of personal factors (i.e. new job, bereavement and personal problems).
Descriptive characteristics of participants at baseline (time 0)
Intervention (n = 25)
Control (n = 23)
Gender of study child
Parent relationship to child
Any other White
Any other Asian
Any other ethnic group
1st Quartile (lowest IMD)
4th Quartile (Highest IMD)
(n = 21)
(n = 19)
≥ 37 (hours/week)
<2 hours / day
≥2 hours / day
<2 hours / day
≥2 hours / day
<2 hours / day
≥2 hours / day
<2 hours / day
≥2 hours / day
Age of study child (n = 16)
Number of children
Mean IMD score
Parent physic al activity
Weekday MVPA (mins / day)
Weekend MVPA (mins / day)
Child physical activity
Weekday MVPA (mins / day)
Weekend MVPA (mins / day)
Weekly attendance ranged from 52% to 84% (Additional file 1: Figure SB). Two parents withdrew during the course of the intervention, but no parents who attended the course missed more than 4 sessions. The percentage of randomized participants who provided accelerometer data at Time 0, 1 and 2 is presented by trial arm in Additional file 1: Table SB. At Time 0, data were provided by 84% of intervention and 87% of control group children. At the first follow-up (Time 1) 56% of the intervention and 60% of the control children provided valid data with 68% of the intervention and control parents providing data. The number of valid days of accelerometer data per participant are presented by intervention arm and for the overall sample at each time point for children and adolescents in Additional file 1: Table SC. Overall there was a median of 4 days of valid data per child and 5 days per adult at each time point, but there was considerable variability between individuals.
Children’s physical activity data by trial arm and adjusted between group differences at time 1 (8 weeks) and 2 (16 weeks)
Adjusted difference in means (95 % CI) †
N in comparison of means
−2.64 (−16.50 to 11.22)
MVPA/weekend day (mins)
11.04 (−7.87 to 29.94)
CPM / weekday
−89.34 (−257.85 to 79.16)
CPM/ weekend day
184.83 (−265.53 to 635.18)
−3.23 (−22.35 to 15.86)
MVPA/weekend day (mins)
−19.65 (−56.57 to 17.27)
CPM / weekday
−32.56 (−177.59 to 122.47)
CPM/ weekend day
12.58 (−375.33 to 400.51)
Parents’ physical activity data by trial arm and adjusted between group differences at time 1 (8 weeks) and 2 (16 weeks)
Adjusted difference in means (95 % CI) †
N in comparison of means
9.06 (−7.54 to 25.66)
MVPA/weekend day (mins)
12.94 (−9.75 to 35.63)
CPM / weekday
25.57 (−66.64 to 117.79)
CPM/ weekend day
77.62 (−36.27 to 191.52)
−3.65 (−20.27 to 12.97)
MVPA/weekend day (mins)
−4.92 (−35.36 to 25.51)
CPM / weekday
−28.60 (−120.28 to 63.09)
CPM/ weekend day
16.06 (−178.50 to 210.62)
Sample size calculations are reported in Table 2 using a range of scenarios regarding the standard deviation of child PA, alpha and beta levels. In all cases the required sample size for a trial was inflated by 35% to account for attrition and missing accelerometer data at Time 2 as observed in this study. A sample of between 80 and 340 participants, would be needed to detect a mean difference of 10-minutes of weekend MVPA. It is important to note, however, that a sample size of 240 participants (i.e. 12 intervention groups) would provide the ability to detect at a 10-minute difference with 80% power and at an alpha of 0.05 assuming a standard deviation of 20 minutes and would provide ample power for all other scenarios.
Qualitative data summary
The mothers interviewed were happy with the principle that they and their child should wear the accelerometers. However, many mothers reported problems associated with wearing the accelerometers which deterred them from wearing them regularly or at all. Difficulty in remembering to wear the accelerometers was a common problem for both mothers and children.
“I found it difficult at the beginning to remember to put it on … I suppose if I’d been going to the course I would have been more aware of it.” (Mother, control group)
Some mothers for whom English was not their first language, reported that they did not understand the purpose of the accelerometer and did not realize that they had to wear it.
“I think at first, the last time you just, you explained to wear it but some people don’t understand it.” (Mother, intervention group)
“I couldn’t feel that I have to do it, it was like I just you can do it.” (Mother, intervention group)
Many mothers found wearing the accelerometers uncomfortable or annoying. This was particularly a problem when wearing clothing without belt loops to attach the accelerometer to, as the elastic belt holding the monitors was conspicuous and would ride up.
“You can’t wear it with a dress, well you look a bit daft and it kind of wriggles up a bit.” (Mother, control group)
Although some mothers reported that their child was happy or even proud and excited to wear an accelerometer, many mothers also reported that their child also disliked wearing them and some refused to wear them at all. Similar to parent views, children also found wearing the accelerometers uncomfortable, or felt self-conscious or susceptible to taunts from school peers, as they were usually the only child in their class wearing one.
“My son, yeah. He, he wore it and then he was complaining like it was too tight sometimes.” (Mother, intervention group)
“Yeah, and some children laughing at her…at school… sometimes children was pushing and say “what’s this?”… and they say “why you wearing this, what happened with you?”.” (Mother, intervention group)
Parent (N = 26) reported problems associated with wearing accelerometers, their own strategies for overcoming these problems, and their suggestions to improve compliance in future interventions
Parent reported problem
Successful strategies used by parents
Parents’ suggestions for future intervention
Difficulty in remembering to wear the accelerometers
• Keeping the accelerometers in a visible place when they are taken off at night
• Allowing parents to opt in/out of a text reminder service was seen as a positive way to remind parents to wear the accelerometers
• Making wearing the accelerometers a habit
Lack of understanding about the accelerometers
• Spend more time explaining why parents are asked to wear the accelerometers
• Having the information translated into parents’ native language
The accelerometers being uncomfortable or not practical to wear (for parents and children)
• Choosing to wear clothes with belt loops
Children feeling targeted at school due to being only child wearing the accelerometer
• Support from teachers and school staff
• Providing information on the project/physical activity for the whole class
• Wearing the accelerometer underneath the school uniform
• Asking the whole class to be involved in the project
Children refusing to wear the accelerometers
• Parents encouraging their child to wear the monitor
• Some children were naturally interested and proud to wear the accelerometer
Increasing motivation to wear the accelerometer for parents and children: Provision of data feedback
• Many parents and children were interested in seeing the results from the accelerometers
• Promoting to parents at the initial data collection that they will get feedback on their data
• Knowing if their child was getting enough PA compared to the recommendations, knowing if they’d increased PA over the 3 time points, and having a comparison of other people or the average were all of interest
The data presented in this study have shown that it is possible to recruit parents to a PA / SV parenting course but a relatively high number of participants withdrew from the study during the study process. As noted in the flow-chart, 7 intervention and 6 control group participants failed to attend or respond to contact attempts for baseline data collection and 6 participants withdrew once they'd been assigned to the control group. Although, the six participants (8% of overall sample) withdrawing after being assigned to the control group is regrettable, overall there was reasonable acceptance of being randomized to intervention or control arms. It is important to highlight that there was considerable variability in the demographic and ethnic profile of the participants suggesting that sample was diverse and that the program potentially has broad appeal.
The data presented in this study indicate that the Teamplay course attendance levels were high. Overall data provision rates were reasonable, but there were some participants who failed to provide three valid days of accelerometer data. The parental interviews suggested that reasons for non-wear included a lack of understanding of why the monitors needed to be worn, forgetting to wear the monitors and their visibility and inconvenience. The parents suggested that these issues could be mitigated by providing text reminders to wear the monitors, spending more time explaining the purpose of the accelerometers and providing information to the participating child’s school on PA and the purpose of the accelerometer. Additionally, finding ways to improve the appeal of the monitors to the children so that they did not feel “daft (self-conscious)” when wearing them would likely increase wear time.
The analyses of the quantitative data suggested that the intervention children increased their weekend MVPA by 11 minutes more than the control group at the first follow-up with no marked difference in terms of weekday MVPA. These effects were not maintained at the second follow-up, and indeed intervention children were active less than control children at this point. The descriptive analyses also showed that a smaller proportion of the intervention children watched 2 or more hours of TV at the weekend than the control group at the first follow-up with less marked differences for weekday TV. These differences were maintained at the second follow-up. Thus, the intervention appears to have yielded an immediate positive effect on weekend MVPA and TV viewing but additional strategies will be needed to maintain these effects. Such strategies might include an internet-based maintenance program or a less intense group intervention to maintain behavior change once the original 8 sessions have been completed. For example, a less intense component could involve meeting once a month to monitor/discuss progress. The positive effects on weekend PA and SV suggest that the intervention worked best at the weekend. This is logical, since this is when 6–8 year old children are likely to spend more time with their parents. The findings suggest that parent input led to this change in child behavior. As noted in the introduction to this paper, the bulk of research to increase children’s PA has focused on school-based approaches . These studies tend to focus on the development of PA on a weekday and largely ignore weekend and non-school day PA. The Teamplay intervention may therefore provide a solution for this neglected aspect of children’s PA and SV.
Parents in the intervention group engaged in 9 more minutes of weekday MVPA and 13 more minutes of weekend MVPA than the control group at the first follow-up but these effects were not maintained at the second follow-up. As with children, the intervention parents were also less likely to spend 2 or more hours per day watching TV than parents in the control group at both the first and second follow-up. Thus, the intervention appears to have had a beneficial effect on parent PA / SV behaviors. This finding is consistent with some of the early parent-focused obesity treatment work which suggested the parent-only interventions yielded positive effects on the adiposity and cardiovascular risk profile of both the target child and the parent .
This study suggests that achieving a mean difference of 10 minutes MVPA between intervention and control children following intervention is feasible. As the effect of increased PA on risk factors is likely to be curvilinear there is no agreed number of “extra minutes” that confer health benefits, but a mean increase of 10-minutes per day would likely have a beneficial effect on cardiometabolic risk factors. For example, analysis of the US National Health and Nutrition Examination Survey (NHANES) shows that young people with 14–33 mean minutes MVPA per day (the second quartile) were 35% less likely to be in the top quartile for waist circumference, 42% less likely to be in the top quartile for high non-HDL cholesterol and 50% less likely to be the top quartile for systolic blood pressure when compared to the participants with 0–13 mean minutes of MVPA (the lowest quartile).
The sample size calculations suggest that between 80 and 340 parent–child dyads would need to be recruited to conduct an adequately powered evaluation of the intervention. The considerable variability between these numbers is a function of differences in the variance (standard deviations) that have been reported for the MVPA of 6 to 8 year old children. Assuming 10 parents are recruited to each course, this equates to running between 4 and 17 eight-week interventions with ample allowance for attrition. However, as noted above, 240 participants (i.e. 12 courses) would provide the ability to detect at a 10-minute difference with 80% power and an alpha of 0.05, assuming a standard deviation of 20 minutes, and would provide ample power for all other scenarios. As such, a sample of 240 participants would appear to present a conservative sample size and such a sample of 12 courses could be conducted within a larger city if a rolling recruitment program were implemented.
Strengths and limitations
Statements about the effects of the intervention versus control group are tentative as this was a feasibility study and there was a lack of statistical power to detect group differences. However, the study design and analysis is consistent with the nature of feasibility studies and it is important that these preliminary studies are conducted and the findings disseminated prior to conducting larger trials [50, 51]. The sample for this study was small and it appears that on average, the children and parents recruited had PA levels at baseline that were already close to achieving the national guidelines. This suggests the sample was slightly biased towards parents who were relatively active and as such, there is a need to replicate in a larger sample with a wider distribution of PA levels. It is also important to note that although there was considerable variability in socioeconomic position and ethnicity we do not have any information about household income or adult composition of households and so cannot interpret if these factors affected participation in the study. It is also important to highlight that we only assessed TV viewing in this study and as such we were not able to assess the effect on other forms of SV including multi-SV where multiple devices are watched at one time . The second follow-up also occurred only 2 months after the intervention had ended and a longer-term follow-up might be required to assess potential impact beyond the intervention period. Only one father participated in the parenting program and as such the results reported here cannot be generalized to fathers. The interviews highlighted the difficulties parents had with wearing the accelerometers and strategies to address this issue should be addressed in future work.
The Teamplay intervention represents a promising parenting program in an under-researched field. The intervention was acceptable to parents, and all elements of the study protocol were successfully completed. This feasibility trial demonstrates that a trial with a sample size of 240 families would likely demonstrate effectiveness of this intervention, and that a trial would be appropriate. Qualitative data suggest simple changes to the trial protocol which could result in more complete data collection and study engagement. This feasibility trial demonstrates that a trial with a sample size of 240 families would be appropriate.
We thank Family Links who have assisted with this project, in particular to Sarah Darton for her time and valuable input. This project was funded by a project grant from the British Heart Foundation (PG/10/025/28302).
- Raitakari OT, Taimela S, Porkka KV, Telama R, Valimaki I, Akerblom HK, Viikari JS: Associations between physical activity and risk factors for coronary heart disease: the Cardiovascular risk in Young Finns Study. Med Sci Sports Exerc. 1997, 29: 1055-1061. 10.1097/00005768-199708000-00011.View ArticleGoogle Scholar
- Thomas NE, Baker JS, Davies B: Established and recently identified coronary heart disease risk factors in young people: the influence of physical activity and physical fitness. Sports Med. 2003, 33: 633-650. 10.2165/00007256-200333090-00001.View ArticleGoogle Scholar
- Jago R, Baranowski T, Baranowski JC, Thompson D, Greaves KA: BMI from 3–6 y of age is predicted by TV viewing and physical activity, not diet. Int J Obes Relat Metab Disord. 2005, 29: 557-564. 10.1038/sj.ijo.0802969.View ArticleGoogle Scholar
- Jago R, Baranowski T, Yoo S, Cullen KW, Zakeri I, Watson K, Himes JH, Pratt C, Sun W, Pruitt LA, Matheson DM: Relationship between physical activity and diet among African-American girls. Obes Res. 2004, 12 (Suppl): 55S-63S.View ArticleGoogle Scholar
- Burazeri G, Goda A, Kark JD: Television viewing, leisure-time exercise and acute coronary syndrome in transitional Albania. Prev Med. 2008, 47 (1): 112-115. 10.1016/j.ypmed.2008.01.020.View ArticleGoogle Scholar
- Biddle SJ, Gorely T, Marshall SJ, Cameron N: The prevalence of sedentary behavior and physical activity in leisure time: a study of Scottish adolescents using ecological momentary assessment. Prev Med. 2009, 48: 151-155. 10.1016/j.ypmed.2008.10.025.View ArticleGoogle Scholar
- Gorely T, Biddle SJ, Marshall SJ, Cameron N: The prevalence of leisure time sedentary behaviour and physical activity in adolescent boys: an ecological momentary assessment approach. Int J Pediatr Obes. 2009, 4 (4): 289-298. 10.3109/17477160902811181. 1-10View ArticleGoogle Scholar
- Mendoza JA, Zimmerman FJ, Christakis DA: Television viewing, computer use, obesity, and adiposity in US preschool children. Int J Behav Nutr Phys Act. 2007, 4: 44-10.1186/1479-5868-4-44.View ArticleGoogle Scholar
- Riddoch CJ, Mattocks C, Deere K, Saunders J, Kirkby J, Tilling K, Leary SD, Blair SN, Ness AR: Objective measurement of levels and patterns of physical activity. Arch Dis Child. 2007, 92: 963-969. 10.1136/adc.2006.112136.View ArticleGoogle Scholar
- Jago R, Anderson C, Baranowski T, Watson K: Adolescent patterns of physical activity: differences by gender, day and time of day. Am J Prev Med. 2005, 28: 447-452. 10.1016/j.amepre.2005.02.007.View ArticleGoogle Scholar
- van Sluijs EM, McMinn AM, Griffin SJ: Effectiveness of interventions to promote physical activity in children and adolescents: systematic review of controlled trials. BMJ. 2007, 335: 703-10.1136/bmj.39320.843947.BE.View ArticleGoogle Scholar
- Stice E, Shaw H, Marti CN: A meta-analytic review of obesity prevention programs for children and adolescents: the skinny on interventions that work. Psychol Bull. 2006, 132: 667-691.View ArticleGoogle Scholar
- Brown T, Summerbell C: Systematic review of school-based interventions that focus on changing dietary intake and physical activity levels to prevent childhood obesity: an update to the obesity guidance produced by the National Institute for Health and Clinical Excellence. Obes Rev. 2009, 10: 110-141. 10.1111/j.1467-789X.2008.00515.x.View ArticleGoogle Scholar
- Waters E, de Silva-Sanigorski A, Hall BJ, Brown T, Campbell KJ, Gao Y, Armstrong R, Prosser L, Summerbell CD: Interventions for preventing obesity in children. Cochrane Database Syst Rev. 2011, 20 (3): CD001871.Google Scholar
- Metcalf B, Henley W, Wilkin T: Effectiveness of intervention on physical activity of children: systematic review and meta-analysis of controlled trials with objectively measured outcomes (EarlyBird 54). BMJ. 2012, 345: e5888-10.1136/bmj.e5888.View ArticleGoogle Scholar
- Jago R, Baranowski T: Non-curricular approaches for increasing physical activity in youth: a review. Prev Med. 2004, 39: 157-163. 10.1016/j.ypmed.2004.01.014.View ArticleGoogle Scholar
- Brustad RJ: Who will go out and play? Parental and psychological influences on children's attraction to physical activity. Ped Exerc Sci. 1993, 5: 210-223.Google Scholar
- Davison KK, Jago R: Change in parent and peer support across ages 9 to 15 yr and adolescent girls' physical activity. Med Sci Sports Exerc. 2009, 41: 1816-1825. 10.1249/MSS.0b013e3181a278e2.View ArticleGoogle Scholar
- Jago R, Davison KK, Brockman R, Page AS, Thompson JL, Fox KR: Parenting styles, parenting practices, and physical activity in 10- to 11-year olds. Prev Med. 2011, 52: 44-47. 10.1016/j.ypmed.2010.11.001.View ArticleGoogle Scholar
- Jago R, Fox KR, Page AS, Brockman R, Thompson JL: Parent and child physical activity and sedentary time: do active parents foster active children?. BMC Public Health. 2010, 10: 194-10.1186/1471-2458-10-194.View ArticleGoogle Scholar
- Marshall SJ, Gorely T, Biddle SJ: A descriptive epidemiology of screen-based media use in youth: a review and critique. J Adolesc. 2006, 29: 333-349. 10.1016/j.adolescence.2005.08.016.View ArticleGoogle Scholar
- O'Connor TM, Jago R, Baranowski T: A systematic review of physical activity interventions for youth with family components. Am J Prev Med. In PressGoogle Scholar
- Parent-training/education programmes in the management of children with conduct disorders Technology appraisal (TA102). : , http://www.nice.org.uk/TA102.
- Golan M, Crow S: Targeting parents exclusively in the treatment of childhood obesity: long-term results. Obes Res. 2004, 12: 357-361. 10.1038/oby.2004.45.View ArticleGoogle Scholar
- Golan M, Crow S: Parents are key players in the prevention and treatment of weight-related problems. Nutr Rev. 2004, 62: 39-50. 10.1111/j.1753-4887.2004.tb00005.x.View ArticleGoogle Scholar
- Golan M, Weizman A: Familial Approach to the treatment of childhood obesity: Conceptual Model. JNE. 2001, 33 (2): 102-107. 10.1016/S1499-4046(06)60173-5.View ArticleGoogle Scholar
- Golan M, Weizman A, Apter A, Fainaru M: Parents as the exclusive agents of change in the treatment of childhood obesity. Am J Clin Nutr. 1998, 67: 1130-1135.Google Scholar
- Robertson W, Friede T, Blissett J, Rudolf MC, Wallis M, Stewart-Brown S: Pilot of "Families for Health": community-based family intervention for obesity. Arch Dis Child. 2008, 93: 921-926. 10.1136/adc.2008.139162.View ArticleGoogle Scholar
- Baranowski T, Jago R: Understanding mechanisms of change in children's physical activity programs. Exerc Sport Sci Rev. 2005, 33: 163-168. 10.1097/00003677-200510000-00003.View ArticleGoogle Scholar
- Ryan RM, Deci EL: Self-determination theory and the facilitation of intrinsic motivation, social development, and well-being. Am Psychol. 2000, 55: 68-78.View ArticleGoogle Scholar
- Standage M, Gillison F, Treasure DC: Self-determination and motivation in physical education. Self-determination theory in exercise and sport. Edited by: Hagger MS, Chatzisarantis NL. 2007, Champaign, Il: Human Kinetics, 71-85.Google Scholar
- Standage M, Gillison FB, Ntoumanis N, Treasure DC: Predicting student’s physical activity and health-related well-being: a prospective cross-domain investigation of motivation across school physical education and exercise settings. J Sport Exerc Psychol. 2012, 34: 37-60.Google Scholar
- Joussemet M, Landry R, Koestner R: A self-determination theory perspective on parenting. Can Psychol. 2008, 49: 194-200.View ArticleGoogle Scholar
- Noble M, McLennan D, Wilkinson K, Whitworth A, Barnes H, Dibben C: The English Indices of Deprivation. pp. 1–129. 2007, London: Communities and Local Government, 1-129.Google Scholar
- Jago R, Steeds JK, Bentley GF, Sebire SJ, Lucas PJ, Fox KR, Stewart-Brown S, Turner KM: Designing a physical activity parenting course: parental views on recruitment, content and delivery. BMC Public Health. 2012, 12: 356-10.1186/1471-2458-12-356.View ArticleGoogle Scholar
- Bentley GF, Goodred JK, Jago R, Sebire SJ, Lucas PJ, Fox KR, Stewart-Brown S, Turner KM: Parents' views on child physical activity and their implications for physical activity parenting interventions: a qualitative study. BMC Pediatr. 2012, 12: 180-10.1186/1471-2431-12-180.View ArticleGoogle Scholar
- Bentley GF, Goodred JK, Jago R, Sebire SJ, Fox KR, Stewart-Brown S, Turner KM: Parents’ views on child physical activity and their implications for physical activity parenting interventions: a qualitative study. BMC Pediatr. In ReviewGoogle Scholar
- Evenson KR, Catellier DJ, Gill K, Ondrak KS, McMurray RG: Calibration of two objective measures of physical activity for children. J Sports Sci. 2008, 26: 1557-1565. 10.1080/02640410802334196.View ArticleGoogle Scholar
- Troiano RP, Berrigan D, Dodd KW, Masse LC, Tilert T, McDowell M: Physical activity in the United States measured by accelerometer. Med Sci Sports Exerc. 2008, 40: 181-188.View ArticleGoogle Scholar
- Anderson DR, Field DE, Collins PA, Lorch EP, Nathan JG: Estimates of young children's time with television: a methodological comparison of parent reports with time-lapse video home observation. Child Dev. 1985, 56: 1345-1357. 10.2307/1130249.View ArticleGoogle Scholar
- American Academy of Pediatrics - Committee on Public Education: Children. Adolescents and television. Pediatrics. 2001, 107: 423-426.View ArticleGoogle Scholar
- Strasburger VC: Children, adolescents, obesity, and the media. Pediatrics. 2011, 128: 201-208.View ArticleGoogle Scholar
- Department of Health PA: Health Improvement and Protection,: Start Active. 2011, Stay Active: A report on physical activity from the four home countries’ Chief Medical Officers. LondonGoogle Scholar
- Basterfield L, Adamson AJ, Parkinson KN, Maute U, Li PX, Reilly JJ: Surveillance of physical activity in the UK is flawed: validation of the Health Survey for England physical activity questionnaire. Arch Dis Child. 2008, 93 (12): 1054-1058. 10.1136/adc.2007.135905.View ArticleGoogle Scholar
- Fairclough SJ, Butcher ZH, Stratton G: Whole-day and segmented-day physical activity variability of northwest England school children. Prev Med. 2007, 44: 421-425. 10.1016/j.ypmed.2007.01.002.View ArticleGoogle Scholar
- Ridgers ND, Timperio A, Crawford D, Salmon J: Five-year changes in school recess and lunchtime and the contribution to children's daily physical activity. Br J Sports Med. 2012, 46: 741-746. 10.1136/bjsm.2011.084921.View ArticleGoogle Scholar
- Thompson JL, Jago R, Brockman R, Cartwright K, Page AS, Fox KR: Physically active families - de-bunking the myth? A qualitative study of family participation in physical activity. Child Care Health Dev. 2009, 36: 265-274.View ArticleGoogle Scholar
- Golan M, Weizman A, Fainaru M: Impact of treatment for childhood obesity on parental risk factors for cardiovascular disease. Prev Med. 1999, 29: 519-526. 10.1006/pmed.1999.0584.View ArticleGoogle Scholar
- Holman RM, Carson V, Janssen I: Does the fractionalization of daily physical activity (sporadic vs. bouts) impact cardiometabolic risk factors in children and youth?. PLoS One. 2011, 6: e25733-10.1371/journal.pone.0025733.View ArticleGoogle Scholar
- Craig P, Dieppe P, Macintyre S, Michie S, Nazareth I, Petticrew M: Developing and evaluating complex interventions: the new Medical Research Council guidance. BMJ. 2008, 337: a1655-10.1136/bmj.a1655.View ArticleGoogle Scholar
- Jago R, Sebire SJ: Publishing pilot and feasibility evaluations of behavioural interventions: Implications for Preventive Medicine. Prev Med. 2012, 55 (6): 548-549. 10.1016/j.ypmed.2012.07.005.View ArticleGoogle Scholar
- Jago R, Sebire SJ, Gorely T, Cillero IH, Biddle SJ: "I'm on it 24/7 at the moment": a qualitative examination of multi-screen viewing behaviours among UK 10–11 year olds. Int J Behav Nutr Phys Act. 2011, 8: 85-10.1186/1479-5868-8-85.View ArticleGoogle Scholar
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