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Record W7047585011

Goal setting and skills achievements in children with disabilities

2015· dissertation· en· W7047585011 on OpenAlexaboutno aff

Bibliographic record

VenueOpen Archive (Karolinska Institutet) · 2015
Typedissertation
Languageen
FieldPhysics and Astronomy
TopicMagnetic confinement fusion research
Canadian institutionsnot available
Fundersnot available
KeywordsGoal settingIntervention (counseling)Process (computing)Goal orientationStrengths and weaknessesPsychological intervention
DOInot available

Abstract

fetched live from OpenAlex

The overall aim of this thesis was to increase knowledge about how children with different types of disabilities can identify performance issues and select goals for intervention. Furthermore, the objective was to study the effects of a goal-directed, task-oriented intervention based on children’s self-identified goals from both quantitative and qualitative perspectives.
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\nEstablishing intervention goals with families, to improve the ability of children with disabilities to perform tasks that they need, want, or are expected to do, to participate in their everyday lives is a central part of paediatric occupational therapy. Within this process children’s perspectives are of importance; to give greater consideration to children’s needs, the children need to be involved in the goal-setting process. As goal setting is an abstract process, it can be questioned whether children with disabilities can identify goals and whether their goals are functional and achievable. Further knowledge about how the child’s self-identified goals influence goal-directed intervention is sparse or even lacking. A specific interest was directed towards including the children in the goal setting, using the Perceived Efficacy and Goal Setting System (PEGS).
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\nThe PEGS is a picture-based self-report for children, developed in Canada. It uses children’s self-reported performance on everyday tasks to allow them to choose and prioritize goals for intervention. To be useful in a Swedish context, the PEGS needed to be translated and adapted. In study I, five items in the PEGS required adaptation, and one new item was added. Using the Swedish version of the PEGS, 44 child–parent dyads were able to identify individual strengths and weaknesses in the child’s performance of everyday tasks as well as to select goals for intervention.
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\nChildren’s self-identified goals in studies I–III included improvements in self-care, and leisure and school tasks. In study II, results from 18 children showed that their goals were relatively stable over time: 78% had an absolute agreement ranging from 50% to 100%. Moreover, in studies II and III goals identified by the children differed from those identified by their parents, and results from 31 child–parent dyads in study II, showed that 48% of the children had no goals identical to those chosen by their parents.
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\nIn studies III and IV, when goal-directed, task-oriented intervention was provided, children’s self-identified goals were achievable. There was evidence of an increase in mean goal attainment (mean T-scores) in both groups (child-goal (n=17): estimated mean difference [EMD] 27.84, 95% confidence interval [CI] 22.93 to 32.76; parent-goal (n=16): EMD 21.42, 95% CI 16.16 to 26.67). There was no evidence of a differences in mean T-scores post-intervention between the two groups (EMD 6.42, 95% CI -0.80 to 13.65), which indicates that children’s self-identified goals are achievable to the same extent as goals identified by parents. These results were sustained at the 5-month follow-up.
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\nFrom a parental perspective, working on children’s self-identified goals was overall a positive experience. The findings revealed three categories: Goals challenged the parents, The intervention demanded an intensive and flexible parental engagement, and The child’s personal goals gave more than anticipated. Even though the goal-directed intervention comprehensively relied on the parents’ engagement and sometimes was challenging, the parents observed that the children’s personal goals positively influenced the children’s self-esteem, increased the children’s motivation for practice, and helped their children develop more than they as parents had anticipated.

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How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.287
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0060.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.009
GPT teacher head0.296
Teacher spread0.287 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2015
Admission routes1
Has abstractyes

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